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Coleman HJ, Schwartz DK, Kaar JL, Garcea RL, Randolph TW. Stabilization of an Infectious Enveloped Virus by Spray-Drying and Lyophilization. J Pharm Sci 2024:S0022-3549(24)00141-2. [PMID: 38643898 DOI: 10.1016/j.xphs.2024.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/11/2024] [Accepted: 04/11/2024] [Indexed: 04/23/2024]
Abstract
Enveloped viruses are attractive candidates for use as gene- and immunotherapeutic agents due to their efficacy at infecting host cells and delivering genetic information. They have also been used in vaccines as potent antigens to generate strong immune responses, often requiring fewer doses than other vaccine platforms as well as eliminating the need for adjuvants. However, virus instability in liquid formulations may limit their shelf life and require that these products be transported and stored under stringently controlled temperature conditions, contributing to high cost and limiting patient access. In this work, spray-drying and lyophilization were used to embed an infectious enveloped virus within dry, glassy polysaccharide matrices. No loss of viral titer was observed following either spray-drying (at multiple drying gas temperatures) or lyophilization. Furthermore, viruses embedded in the glassy formulations showed enhanced thermal stability, retaining infectivity after exposure to elevated temperatures as high as 85 °C for up to one hour, and for up to 10 weeks at temperatures as high as 30 °C. In comparison, viruses in liquid formulations lost infectivity within an hour at temperatures above 40 °C, or after incubation at 25 °C for longer periods of time.
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Affiliation(s)
- Holly J Coleman
- Department of Chemical and Biological Engineering, University of Colorado Boulder, CO 80303, USA
| | - Daniel K Schwartz
- Department of Chemical and Biological Engineering, University of Colorado Boulder, CO 80303, USA
| | - Joel L Kaar
- Department of Chemical and Biological Engineering, University of Colorado Boulder, CO 80303, USA
| | - Robert L Garcea
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, CO 80303, USA
| | - Theodore W Randolph
- Department of Chemical and Biological Engineering, University of Colorado Boulder, CO 80303, USA.
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2
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Grover EN, Buchwald AG, Ghosh D, Carlton EJ. Does behavior mediate the effect of weather on SARS-CoV-2 transmission? Evidence from cell-phone data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.26.24304854. [PMID: 38585859 PMCID: PMC10996765 DOI: 10.1101/2024.03.26.24304854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Background There is growing evidence that weather alters SARS-CoV-2 transmission, but it remains unclear what drives the phenomenon. One prevailing hypothesis is that people spend more time indoors in cooler weather, leading to increased spread of SARS-CoV-2 related to time spent in confined spaces and close contact with others. However, the evidence in support of that hypothesis is limited and, at times, conflicting. Objectives We aim to evaluate the extent to which weather impacts COVID-19 via time spent away-from-home in indoor spaces, as compared to a direct effect of weather on COVID-19 hospitalization, independent of mobility. Methods We use a mediation framework, and combine daily weather, COVID-19 hospital surveillance, cellphone-based mobility data and building footprints to estimate the relationship between daily indoor and outdoor weather conditions, mobility, and COVID-19 hospitalizations. We quantify the direct health impacts of weather on COVID-19 hospitalizations and the indirect effects of weather via time spent indoors away-from-home on COVID-19 hospitalizations within five Colorado counties between March 4th 2020 and January 31st 2021. Results We found evidence that changes in 12-day lagged hospital admissions were primarily via the direct effects of weather conditions, rather than via indirect effects by which weather changes time spent indoors away-from-home. Sensitivity analyses evaluating time at home as a mediator were consistent with these conclusions. Discussion Our findings do not support the hypothesis that weather impacted SARS-CoV-2 transmission via changes in mobility patterns during the first year of the pandemic. Rather, weather appears to have impacted SARS-CoV-2 transmission primarily via mechanisms other than human movement. We recommend further analysis of this phenomenon to determine whether these findings generalize to current SARS-CoV-2 transmission dynamics and other seasonal respiratory pathogens.
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Affiliation(s)
- Elise N. Grover
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
| | - Andrea G. Buchwald
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Debashis Ghosh
- Department of Biostatistics & Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
| | - Elizabeth J. Carlton
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
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3
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Yan ZL, Liu WH, Long YX, Ming BW, Yang Z, Qin PZ, Ou CQ, Li L. Effects of meteorological factors on influenza transmissibility by virus type/subtype. BMC Public Health 2024; 24:494. [PMID: 38365650 PMCID: PMC10870479 DOI: 10.1186/s12889-024-17961-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 02/02/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Quantitative evidence on the impact of meteorological factors on influenza transmissibility across different virus types/subtypes is scarce, and no previous studies have reported the effect of hourly temperature variability (HTV) on influenza transmissibility. Herein, we explored the associations between meteorological factors and influenza transmissibility according to the influenza type and subtype in Guangzhou, a subtropical city in China. METHODS We collected influenza surveillance and meteorological data of Guangzhou between October 2010 and December 2019. Influenza transmissibility was measured using the instantaneous effective reproductive number (Rt). A gamma regression with a log link combined with a distributed lag non-linear model was used to assess the associations of daily meteorological factors with Rt by influenza types/subtypes. RESULTS The exposure-response relationship between ambient temperature and Rt was non-linear, with elevated transmissibility at low and high temperatures. Influenza transmissibility increased as HTV increased when HTV < around 4.5 °C. A non-linear association was observed between absolute humidity and Rt, with increased transmissibility at low absolute humidity and at around 19 g/m3. Relative humidity had a U-shaped association with influenza transmissibility. The associations between meteorological factors and influenza transmissibility varied according to the influenza type and subtype: elevated transmissibility was observed at high ambient temperatures for influenza A(H3N2), but not for influenza A(H1N1)pdm09; transmissibility of influenza A(H1N1)pdm09 increased as HTV increased when HTV < around 4.5 °C, but the transmissibility decreased with HTV when HTV < 2.5 °C and 3.0 °C for influenza A(H3N2) and B, respectively; positive association of Rt with absolute humidity was witnessed for influenza A(H3N2) even when absolute humidity was larger than 19 g/m3, which was different from that for influenza A(H1N1)pdm09 and influenza B. CONCLUSIONS Temperature variability has an impact on influenza transmissibility. Ambient temperature, temperature variability, and humidity influence the transmissibility of different influenza types/subtypes discrepantly. Our findings have important implications for improving preparedness for influenza epidemics, especially under climate change conditions.
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Affiliation(s)
- Ze-Lin Yan
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Wen-Hui Liu
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yu-Xiang Long
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Bo-Wen Ming
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Peng-Zhe Qin
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.
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4
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Yan C, Hu YN, Gui ZC, Lai TN, Ali W, Wan NH, He SS, Liu S, Li X, Jin TX, Nasir ZA, Alcega SG, Coulon F. Quantitative SARS-CoV-2 exposure assessment for workers in wastewater treatment plants using Monte-Carlo simulation. WATER RESEARCH 2024; 248:120845. [PMID: 37976948 DOI: 10.1016/j.watres.2023.120845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 10/17/2023] [Accepted: 11/05/2023] [Indexed: 11/19/2023]
Abstract
Several studies on COVID-19 pandemic have shown that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originating from human stool are detected in raw sewage for several days, leading to potential health risks for workers due to the production of bioaerosols and droplets during wastewater treatment process. In this study, data of SARS-CoV-2 concentrations in wastewater were gathered from literatures, and a quantitative microbial risk assessment with Monte Carlo simulation was used to estimate the daily probability of infection risk through exposure to viable infectious viral airborne particles of the workers during four seasons and under six environmental conditions. Inhalation of bioaerosols and direct ingestion of wastewater droplets were selected as exposure pathways. Spearman rank correlation coefficients were used for sensitivity analysis to identify the variables with the greatest influence on the infection risk probability. It was found that the daily probability of infection risk decreased with temperature (T) and relative humidity (RH) increase. The probability of direct droplet ingestion exposure pathway was higher than that of the bioaerosol inhalation pathway. The sensitivity analysis indicated that the most sensitive variable for both exposure pathways was the concentration of SARS-CoV-2 in stool. So, appropriate aeration systems, covering facilities, and effective ventilation are suggested to implement in wastewater treatment plants (WWTPs) to reduce emission concentration. Further to this, the exposure time (t) had a larger variance contribution than T and RH for the bioaerosol inhalation pathway. Implementing measures such as adding more work shifts, mandating personal protective equipment for all workers, and implementing coverage for treatment processes can significantly reduce the risk of infection among workers at WWTPs. These measures are particularly effective during environmental conditions with low temperatures and humidity levels.
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Affiliation(s)
- Cheng Yan
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China; Hubei Key Laboratory of Environmental Water Science in the Yangtze River Basin, China University of Geosciences, Wuhan 430074, PR China.
| | - Yi-Ning Hu
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China
| | - Zi-Cheng Gui
- CCDI (Suzhou) exploration and design consultant Co., Ltd., Suzhou 215123, PR China
| | - Tian-Nuo Lai
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China
| | - Wajid Ali
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China
| | - Nian-Hong Wan
- Central & Southern China Municipal Engineering Design and Research Institute Co, Ltd., Wuhan 430010, PR China
| | - Shan-Shan He
- Central & Southern China Municipal Engineering Design and Research Institute Co, Ltd., Wuhan 430010, PR China
| | - Sai Liu
- CITIC Treated Water into River Engineering Investment Co., Ltd., Wuhan 430200, PR China
| | - Xiang Li
- Three Gorges Base Development Co., Ltd., Yichang 443002, PR China
| | - Ting-Xu Jin
- Department of Toxicology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou 215123, PR China; School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, PR China
| | - Zaheer Ahmad Nasir
- School of Water, Energy and Environment, Cranfield University, Cranfield MK43 0AL, UK
| | - Sonia Garcia Alcega
- School of Physical Sciences, The Open University, Walton Hall, Milton Keynes MK6 7AA, UK
| | - Frederic Coulon
- School of Water, Energy and Environment, Cranfield University, Cranfield MK43 0AL, UK
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Varela-Lasheras I, Perfeito L, Mesquita S, Gonçalves-Sá J. The effects of weather and mobility on respiratory viruses dynamics before and during the COVID-19 pandemic in the USA and Canada. PLOS DIGITAL HEALTH 2023; 2:e0000405. [PMID: 38127792 PMCID: PMC10734953 DOI: 10.1371/journal.pdig.0000405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023]
Abstract
The flu season is caused by a combination of different pathogens, including influenza viruses (IVS), that cause the flu, and non-influenza respiratory viruses (NIRVs), that cause common colds or influenza-like illness. These viruses exhibit similar dynamics and meteorological conditions have historically been regarded as a principal modulator of their epidemiology, with outbreaks in the winter and almost no circulation during the summer, in temperate regions. However, after the emergence of SARS-CoV2, in late 2019, the dynamics of these respiratory viruses were strongly perturbed worldwide: some infections displayed near-eradication, while others experienced temporal shifts or occurred "off-season". This disruption raised questions regarding the dominant role of weather while also providing an unique opportunity to investigate the roles of different determinants on the epidemiological dynamics of IVs and NIRVs. Here, we employ statistical analysis and modelling to test the effects of weather and mobility in viral dynamics, before and during the COVID-19 pandemic. Leveraging epidemiological surveillance data on several respiratory viruses, from Canada and the USA, from 2016 to 2023, we found that whereas in the pre-COVID-19 pandemic period, weather had a strong effect, in the pandemic period the effect of weather was strongly reduced and mobility played a more relevant role. These results, together with previous studies, indicate that behavioral changes resulting from the non-pharmacological interventions implemented to control SARS-CoV2, interfered with the dynamics of other respiratory viruses, and that the past dynamical equilibrium was disturbed, and perhaps permanently altered, by the COVID-19 pandemic.
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Affiliation(s)
- Irma Varela-Lasheras
- Nova School of Business and Economics, Universidade Nova de Lisboa, Carcavelos, Portugal
| | - Lilia Perfeito
- LIP, Laboratório de Instrumentação e Física Experimental de Partículas, Lisbon, Portugal
| | - Sara Mesquita
- LIP, Laboratório de Instrumentação e Física Experimental de Partículas, Lisbon, Portugal
- Nova Medical School, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Joana Gonçalves-Sá
- Nova School of Business and Economics, Universidade Nova de Lisboa, Carcavelos, Portugal
- LIP, Laboratório de Instrumentação e Física Experimental de Partículas, Lisbon, Portugal
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6
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Wagatsuma K, Koolhof IS, Saito R. Nonlinear and Multidelayed Effects of Meteorological Drivers on Human Respiratory Syncytial Virus Infection in Japan. Viruses 2023; 15:1914. [PMID: 37766320 PMCID: PMC10535838 DOI: 10.3390/v15091914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/07/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
In this study, we aimed to characterize the nonlinear and multidelayed effects of multiple meteorological drivers on human respiratory syncytial virus (HRSV) infection epidemics in Japan. The prefecture-specific weekly time-series of the number of newly confirmed HRSV infection cases and multiple meteorological variables were collected for 47 Japanese prefectures from 1 January 2014 to 31 December 2019. We combined standard time-series generalized linear models with distributed lag nonlinear models to determine the exposure-lag-response association between the incidence relative risks (IRRs) of HRSV infection and its meteorological drivers. Pooling the 2-week cumulative estimates showed that overall high ambient temperatures (22.7 °C at the 75th percentile compared to 16.3 °C) and high relative humidity (76.4% at the 75th percentile compared to 70.4%) were associated with higher HRSV infection incidence (IRR for ambient temperature 1.068, 95% confidence interval [CI], 1.056-1.079; IRR for relative humidity 1.045, 95% CI, 1.032-1.059). Precipitation revealed a positive association trend, and for wind speed, clear evidence of a negative association was found. Our findings provide a basic picture of the seasonality of HRSV transmission and its nonlinear association with multiple meteorological drivers in the pre-HRSV-vaccination and pre-coronavirus disease 2019 (COVID-19) era in Japan.
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Affiliation(s)
- Keita Wagatsuma
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8510, Japan;
- Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
| | - Iain S. Koolhof
- College of Health and Medicine, School of Medicine, University of Tasmania, Hobart 7000, Australia;
| | - Reiko Saito
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8510, Japan;
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7
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Yin Y, Lai M, Zhou S, Chen Z, Jiang X, Wang L, Li Z, Peng Z. Effects and interaction of temperature and relative humidity on the trend of influenza prevalence: A multi-central study based on 30 provinces in mainland China from 2013 to 2018. Infect Dis Model 2023; 8:822-831. [PMID: 37496828 PMCID: PMC10366480 DOI: 10.1016/j.idm.2023.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/23/2023] [Accepted: 07/08/2023] [Indexed: 07/28/2023] Open
Abstract
Background Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China. Methods We estimated the time-varying reproduction number (Rt) of influenza and explored the impact of temperature and relative humidity on Rt using generalized additive quasi-Poisson regression models combined with the distribution lag non-linear model (DLNM). The effect of temperature and humidity interaction on Rt of influenza was explored. The multiple random-meta analysis was used to evaluate region-specific association. The excess risk (ER) index was defined to investigate the correlation between Rt and each meteorological factor with the modification of seasonal and regional characteristics. Results Low temperature and low relative humidity contributed to influenza epidemics on the national level, while shapes of merged cumulative effect plots were different across regions. Compared to that of median temperature, the merged RR (95%CI) of low temperature in northern and southern regions were 1.40(1.24,1.45) and 1.20 (1.14,1.27), respectively, while those of high temperature were 1.10(1.03,1.17) and 1.00 (0.95,1.04), respectively. There were negative interactions between temperature and relative humidity on national (SI = 0.59, 95%CI: 0.57-0.61), southern (SI = 0.49, 95%CI: 0.17-0.80), and northern regions (SI = 0.59, 95%CI: 0.56,0.62). In general, with the increase of the change of the two meteorological factors, the ER of Rt also gradually increased. Conclusions Temperature and relative humidity have an effect on the influenza epidemics in China, and there is an interaction between the two meteorological factors, but the effect of each factor is heterogeneous among regions. Meteorological factors may be considered to predict the trend of influenza epidemic.
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Affiliation(s)
- Yi Yin
- School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Miao Lai
- School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Sijia Zhou
- School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Ziying Chen
- School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xin Jiang
- School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Liping Wang
- Division of Infectious Disease/Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhongjie Li
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhihang Peng
- School of Public Health, Nanjing Medical University, Nanjing, 211166, China
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8
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Hashim BM, Al-Naseri SK, Hamadi AM, Mahmood TA, Halder B, Shahid S, Yaseen ZM. Seasonal correlation of meteorological parameters and PM 2.5 with the COVID-19 confirmed cases and deaths in Baghdad, Iraq. INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION : IJDRR 2023; 94:103799. [PMID: 37360250 PMCID: PMC10277160 DOI: 10.1016/j.ijdrr.2023.103799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 06/09/2023] [Accepted: 06/10/2023] [Indexed: 06/28/2023]
Abstract
The COVID-19 pandemic was a serious global health emergency in 2020 and 2021. This study analyzed the seasonal association of weekly averages of meteorological parameters, such as wind speed, solar radiation, temperature, relative humidity, and air pollutant PM2.5, with confirmed COVID-19 cases and deaths in Baghdad, Iraq, a major megacity of the Middle East, for the period June 2020 to August 2021. Spearman and Kendall correlation coefficients were used to investigate the association. The results showed that wind speed, air temperature, and solar radiation have positive and strong correlations with the confirmed cases and deaths in the cold season (autumn and winter 2020-2021). The total COVID-19 cases negatively correlated with relative humidity but were not significant in all seasons. Besides, PM2.5 strongly correlated with COVID-19 confirmed cases for the summer of 2020. The death distribution by age group showed the highest deaths for those aged 60-69. The highest number of deaths was 41% in the summer of 2020. The study provided useful information about the COVID-19 health emergency and meteorological parameters, which can be used for future health disaster planning, adopting prevention strategies and providing healthcare procedures to protect against future infraction transmission.
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Affiliation(s)
- Bassim Mohammed Hashim
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Saadi K Al-Naseri
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Alaa M Hamadi
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Tahani Anwar Mahmood
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Bijay Halder
- Department of Remote Sensing and GIS, Vidyasagar University, Midnapore, 721102, India
- New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Nasiriyah, 64001, Iraq
| | - Shamsuddin Shahid
- Department of Water & Environmental Engineering, University of Teknologi Malaysia, 81310, Johor, Malaysia
| | - Zaher Mundher Yaseen
- Civil and Environmental Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
- Interdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
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9
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Zhu H, Chen S, Liang R, Feng Y, Joldosh A, Xie Z, Chen G, Li L, Chen K, Fang Y, Ou J. Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China. BMC Infect Dis 2023; 23:299. [PMID: 37147566 PMCID: PMC10161995 DOI: 10.1186/s12879-023-08184-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 03/20/2023] [Indexed: 05/07/2023] Open
Abstract
BACKGROUND This study adopted complete meteorological indicators, including eight items, to explore their impact on hand, foot, and mouth disease (HFMD) in Fuzhou, and predict the incidence of HFMD through the long short-term memory (LSTM) neural network algorithm of artificial intelligence. METHOD A distributed lag nonlinear model (DLNM) was used to analyse the influence of meteorological factors on HFMD in Fuzhou from 2010 to 2021. Then, the numbers of HFMD cases in 2019, 2020 and 2021 were predicted using the LSTM model through multifactor single-step and multistep rolling methods. The root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to evaluate the accuracy of the model predictions. RESULTS Overall, the effect of daily precipitation on HFMD was not significant. Low (4 hPa) and high (≥ 21 hPa) daily air pressure difference (PRSD) and low (< 7 °C) and high (> 12 °C) daily air temperature difference (TEMD) were risk factors for HFMD. The RMSE, MAE, MAPE and SMAPE of using the weekly multifactor data to predict the cases of HFMD on the following day, from 2019 to 2021, were lower than those of using the daily multifactor data to predict the cases of HFMD on the following day. In particular, the RMSE, MAE, MAPE and SMAPE of using weekly multifactor data to predict the following week's daily average cases of HFMD were much lower, and similar results were also found in urban and rural areas, which indicating that this approach was more accurate. CONCLUSION This study's LSTM models combined with meteorological factors (excluding PRE) can be used to accurately predict HFMD in Fuzhou, especially the method of predicting the daily average cases of HFMD in the following week using weekly multifactor data.
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Affiliation(s)
- Hansong Zhu
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, The Practice Base On the School of Public Health Fujian Medical University, Fuzhou, Fujian, 350012, China
| | - Si Chen
- Fujian Climate Center, Fuzhou, 350028, Fujian, China
| | - Rui Liang
- Department of Nutrition, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Yulin Feng
- School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Aynur Joldosh
- School of Public Health, Xiamen University, Xiamen, 361005, Fujian, China
| | - Zhonghang Xie
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, The Practice Base On the School of Public Health Fujian Medical University, Fuzhou, Fujian, 350012, China
| | - Guangmin Chen
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, The Practice Base On the School of Public Health Fujian Medical University, Fuzhou, Fujian, 350012, China
| | - Lingfang Li
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, The Practice Base On the School of Public Health Fujian Medical University, Fuzhou, Fujian, 350012, China
| | - Kaizhi Chen
- College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, Fujian, China.
| | - Yuanyuan Fang
- Department of Pediatric Surgery, Fujian Children's Hospital, Fuzhou, 350001, Fujian, China.
| | - Jianming Ou
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, The Practice Base On the School of Public Health Fujian Medical University, Fuzhou, Fujian, 350012, China.
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Zupanc M, Zevnik J, Filipić A, Gutierrez-Aguirre I, Ješelnik M, Košir T, Ortar J, Dular M, Petkovšek M. Inactivation of the enveloped virus phi6 with hydrodynamic cavitation. ULTRASONICS SONOCHEMISTRY 2023; 95:106400. [PMID: 37060711 PMCID: PMC10085970 DOI: 10.1016/j.ultsonch.2023.106400] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/23/2023] [Accepted: 04/05/2023] [Indexed: 06/19/2023]
Abstract
The COVID -19 pandemic reminded us that we need better contingency plans to prevent the spread of infectious agents and the occurrence of epidemics or pandemics. Although the transmissibility of SARS-CoV-2 in water has not been confirmed, there are studies that have reported on the presence of infectious coronaviruses in water and wastewater samples. Since standard water treatments are not designed to eliminate viruses, it is of utmost importance to explore advanced treatment processes that can improve water treatment and help inactivate viruses when needed. This is the first study to investigate the effects of hydrodynamic cavitation on the inactivation of bacteriophage phi6, an enveloped virus used as a SARS-CoV-2 surrogate in many studies. In two series of experiments with increasing and constant sample temperature, virus reduction of up to 6.3 logs was achieved. Inactivation of phi6 at temperatures of 10 and 20 °C occurs predominantly by the mechanical effect of cavitation and results in a reduction of up to 4.5 logs. At 30 °C, the reduction increases to up to 6 logs, where the temperature-induced increased susceptibility of the viral lipid envelope makes the virus more prone to inactivation. Furthermore, the control experiments without cavitation showed that the increased temperature alone is not sufficient to cause inactivation, but that additional mechanical stress is still required. The RNA degradation results confirmed that virus inactivation was due to the disrupted lipid bilayer and not to RNA damage. Hydrodynamic cavitation, therefore, has the potential to inactivate current and potentially emerging enveloped pathogenic viruses in water at lower, environmentally relevant temperatures.
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Affiliation(s)
- Mojca Zupanc
- Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Jure Zevnik
- Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Arijana Filipić
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Ion Gutierrez-Aguirre
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Meta Ješelnik
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Tamara Košir
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Jernej Ortar
- Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Matevž Dular
- Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Martin Petkovšek
- Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia.
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11
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Kinnun JJ, Scott HL, Bolmatov D, Collier CP, Charlton TR, Katsaras J. Biophysical studies of lipid nanodomains using different physical characterization techniques. Biophys J 2023; 122:931-949. [PMID: 36698312 PMCID: PMC10111277 DOI: 10.1016/j.bpj.2023.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/12/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
For the past 50 years, evidence for the existence of functional lipid domains has been steadily accumulating. Although the notion of functional lipid domains, also known as "lipid rafts," is now widely accepted, this was not always the case. This ambiguity surrounding lipid domains could be partly attributed to the fact that they are highly dynamic, nanoscopic structures. Since most commonly used techniques are sensitive to microscale structural features, it is therefore, not surprising that it took some time to reach a consensus regarding their existence. In this review article, we will discuss studies that have used techniques that are inherently sensitive to nanoscopic structural features (i.e., neutron scatting, nuclear magnetic resonance, and Förster resonance energy transfer). We will also mention techniques that may be of use in the future (i.e., cryoelectron microscopy, droplet interface bilayers, inelastic x-ray scattering, and neutron reflectometry), which can further our understanding of the different and unique physicochemical properties of nanoscopic lipid domains.
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Affiliation(s)
- Jacob J Kinnun
- Large Scale Structures Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
| | - Haden L Scott
- Large Scale Structures Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee
| | - Dima Bolmatov
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee
| | - C Patrick Collier
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee
| | - Timothy R Charlton
- Large Scale Structures Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee
| | - John Katsaras
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee; Labs and Soft Matter Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
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12
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Zimmerberg J, Soubias O, Pastor RW. Special issue for Klaus Gawrisch. Biophys J 2023; 122:E1-E8. [PMID: 36921597 PMCID: PMC10111273 DOI: 10.1016/j.bpj.2023.02.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 03/17/2023] Open
Affiliation(s)
- Joshua Zimmerberg
- Section on Integrative Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Olivier Soubias
- Macromolecular NMR Section, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Richard W Pastor
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
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13
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Wu Y, Liang M, Liang Q, Yang X, Sun Y. A distributed lag non-linear time-series study of ambient temperature and healthcare-associated infections in Hefei, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:258-267. [PMID: 34915779 DOI: 10.1080/09603123.2021.2017862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 12/08/2021] [Indexed: 06/14/2023]
Abstract
Little is known about the effects of temperature on healthcare-associated infections (HAIs). A distributed lag non-linear model was used to estimate the association between ambient temperature and HAIs in Hefei, China. In total, 9,592 HAIs were included. The effect of low temperature (-0.1°C, 2.5th percentile) was significant on the current day (RR = 1.108, 95%CI:1.003-1.222), and then appeared on the 4th day (RR = 1.045, 95%CI:1.007-1.084) and the 5th day (RR = 1.033, 95%CI:1.006-1.061). The cumulative lag effects of low temperature lasted from the 5th to 10th days (RR = 1.123-1.143), and a long-term cumulative lag effect was observed on the 14th day (RR = 1.157, 95%CI:1.001-1.338). The lag effect of high temperature (31.0°C, 97.5th percentile) was not statistically significant. However, the effects of temperatures on HAIs were not significant among gender or age subgroups. This study suggests that the low temperatures have acute and lag effects on HAIs in Hefei, China.
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Affiliation(s)
- Yile Wu
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Qiwei Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Department of Hospital infection Prevention and Control, Children's Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xiyao Yang
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Center for Evidence-Based Practice, Anhui Medical University, Hefei, Anhui, China
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14
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Comprehensive analysis of lipid metabolism in influenza virus infection. Microb Pathog 2023; 175:106002. [PMID: 36693511 DOI: 10.1016/j.micpath.2023.106002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/19/2023] [Accepted: 01/20/2023] [Indexed: 01/22/2023]
Abstract
Influenza A virus (IAV) exploits host metabolic pathways to support its replication. To improve the understanding of lipid metabolic changes that could occur upon IAV infection, a comprehensive analysis of lipid metabolites in A549 cells infected with the avian H9N2 virus at the different time points was performed. It was found that H9N2 infection could largely promote the level of lipid metabolites. Further, these metabolites were mainly included in glycerophospholipids (GPs), sphingolipids (SPs), glycerolipids (GLs), fatty acids (FAs), sterollipids (STs), triglycerides (TGs), and prenol lipids (PRs). Specifically, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these metabolites were mainly associated with the glycerphospholipid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, and autophagy. Furthermore, it is interesting to note that these metabolites, including FFA(19:1), PE(P-17:0_20:3), PE(P-18:1_20:2), LPC(14:0/0:0), PE(O-18:0_20:3), and MGDG(16:0_18:1), are upregulated and shared in the top 10 at 12 h, 24 h, 36 h, and 48 h after H9N2 infection, indicative of the possibility of acting as biomarkers for the diagnosis in the lung infected with influenza virus. These pathways and altered metabolites could provide new understandings about biological characteristics and pathogenicity of influenza virus and have the potential to serve as biomarkers for influenza.
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15
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Matsuki E, Kawamoto S, Morikawa Y, Yahagi N. The Impact of Cold Ambient Temperature in the Pattern of Influenza Virus Infection. Open Forum Infect Dis 2023; 10:ofad039. [PMID: 36789010 PMCID: PMC9915965 DOI: 10.1093/ofid/ofad039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 01/25/2023] [Indexed: 01/29/2023] Open
Abstract
Background Prior literature suggests that cold temperature strongly influences the immune function of animals and human behaviors, which may allow for the transmission of respiratory viral infections. However, information on the impact of cold stimuli, especially the impact of temporal change in the ambient temperature on influenza virus transmission, is limited. Methods A susceptible-infected-recovered-susceptible model was applied to evaluate the effect of temperature change on influenza virus transmission. Results The mean temperature of the prior week was positively associated with the number of newly diagnosed cases (0.107 [95% Bayesian credible interval {BCI}, .106-.109]), whereas the mean difference in the temperature of the prior week was negatively associated (-0.835 [95% BCI, -.840 to -.830]). The product of the mean temperature and mean difference in the temperature of the previous week were also negatively associated with the number of newly diagnosed cases (-0.192 [95% BCI, -.197 to -.187]). Conclusions The mean temperature and the mean difference in temperature affected the number of newly diagnosed influenza cases differently. Our data suggest that high ambient temperature and a drop in the temperature and their interaction increase the risk of infection. Therefore, the highest risk of infection is attributable to a steep fall in temperature in a relatively warm environment.
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Affiliation(s)
- Eri Matsuki
- Correspondence: Naohisa Yahagi, MD, PhD, Keio University, Graduate School of Media and Governance, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan (); Eri Matsuki, MD, PhD, MPH, Keio University School of Medicine, Clinical and Translational Research Center, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan ()
| | - Shota Kawamoto
- Graduate School of Media and Governance, Keio University, Kanagawa, Japan
| | - Yoshihiko Morikawa
- Graduate School of Media and Governance, Keio University, Kanagawa, Japan
| | - Naohisa Yahagi
- Correspondence: Naohisa Yahagi, MD, PhD, Keio University, Graduate School of Media and Governance, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan (); Eri Matsuki, MD, PhD, MPH, Keio University School of Medicine, Clinical and Translational Research Center, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan ()
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16
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Nottmeyer L, Armstrong B, Lowe R, Abbott S, Meakin S, O'Reilly KM, von Borries R, Schneider R, Royé D, Hashizume M, Pascal M, Tobias A, Vicedo-Cabrera AM, Lavigne E, Correa PM, Ortega NV, Kynčl J, Urban A, Orru H, Ryti N, Jaakkola J, Dallavalle M, Schneider A, Honda Y, Ng CFS, Alahmad B, Carrasco-Escobar G, Holobâc IH, Kim H, Lee W, Íñiguez C, Bell ML, Zanobetti A, Schwartz J, Scovronick N, Coélho MDSZS, Saldiva PHN, Diaz MH, Gasparrini A, Sera F. The association of COVID-19 incidence with temperature, humidity, and UV radiation - A global multi-city analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158636. [PMID: 36087670 PMCID: PMC9450475 DOI: 10.1016/j.scitotenv.2022.158636] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 09/05/2022] [Accepted: 09/05/2022] [Indexed: 05/05/2023]
Abstract
BACKGROUND AND AIM The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally. METHODS We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone. RESULTS We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries. CONCLUSION Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission.
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Affiliation(s)
- Luise Nottmeyer
- Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
| | - Ben Armstrong
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Rachel Lowe
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Sam Abbott
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Sophie Meakin
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Kathleen M O'Reilly
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Rochelle Schneider
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Φ-Lab, European Space Agency, Frascati, Italy; European Centre for Medium-Range Weather Forecast (ECMWF), Reading, UK
| | - Dominic Royé
- Department of Geography, University of Santiago de Compostela, CIBER of Epidemiology and Public Health (CIBERESP), Spain
| | - Masahiro Hashizume
- Department of Paediatric Infectious Disease, Institute of Tropical Medicine, Nagasaki University, Japan; School of Tropical Medicine and Global Health, Nagasaki University, Japan; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Mathilde Pascal
- Santé Publique France, Department of Environmental and Occupational Health, French National Public Health Agency, Saint Maurice, France
| | - Aurelio Tobias
- School of Tropical Medicine and Global Health, Nagasaki University, Japan; Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Eric Lavigne
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada; Air Health Science Division, Health Canada, Ottawa, Canada
| | | | | | - Jan Kynčl
- Department of Infectious Diseases Epidemiology, National Institute of Public Health, Prague, Czech Republic; Department of Epidemiology and Biostatistics, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Aleš Urban
- Institute of Atmospheric Physics of the Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Hans Orru
- Department of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Niilo Ryti
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jouni Jaakkola
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Marco Dallavalle
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany; Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Yasushi Honda
- School of Tropical Medicine and Global Health, Nagasaki University, Japan; Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan; Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Chris Fook Sheng Ng
- School of Tropical Medicine and Global Health, Nagasaki University, Japan; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Barrak Alahmad
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Gabriel Carrasco-Escobar
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Ho Kim
- Department of Public Health Science, Graduate School of Public Health & Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea
| | - Whanhee Lee
- School of Biomedical Convergence Engineering, College of Information and Biomedical Engineering, Pusan National University, Yangsan, South Korea
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, València, Spain
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA
| | | | | | - Magali Hurtado Diaz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Antonio Gasparrini
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy.
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Kondrashov OV, Akimov SA. A Mechanism of Double-Membrane Vesicle Formation from Liquid-Ordered/Liquid-Disordered Phase Separated Spherical Membrane. MEMBRANES 2022; 13:25. [PMID: 36676832 PMCID: PMC9862188 DOI: 10.3390/membranes13010025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/12/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
Genome replication of coronaviruses takes place in specific cellular compartments, in so-called double-membrane vesicles (DMVs), formed from the endoplasmic reticulum (ER). An intensive production of DMVs is induced by non-structural viral proteins. Here, we proposed a possible mechanism of the DMV formation from ER-derived spherical vesicles where liquid-ordered and liquid-disordered lipid phases coexist. These vesicles are supposed to divide into two homogeneous liquid-ordered and liquid-disordered vesicles. The formation of two spherical vesicles constituting DMV requires a mechanical work to be performed. We considered the excess energy of the boundary between the coexisting lipid phases as the main driving force behind the division of the initial vesicle. Explicitly accounting for the energy of elastic deformations and the interphase boundary energy, we analyzed a range of physical parameters where the DMV formation is possible. We concluded that this process can principally take place in a very narrow range of system parameters. The most probable diameter of DMVs formed according to the proposed mechanism appeared to be approximately 220 nm, in an agreement with the average diameter of DMVs observed in vivo. Our consideration predicts the DMV size to be strongly limited from above. The developed analysis can be utilized for the production of DMVs in model systems.
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18
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Zhang B, Chen T, Liang S, Shen W, Sun Q, Wang D, Wang G, Yang J, Yang L, Wang D, Shu Y, Du X. Subtypes specified environmental dependence of seasonal influenza virus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158525. [PMID: 36075410 DOI: 10.1016/j.scitotenv.2022.158525] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/21/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
Understanding the role of meteorological factors in the transmission dynamics of respiratory infectious diseases remains challenging. Our study was to comprehensively investigate the nonlinear effects of environmental factors on influenza transmission, based on multi-region surveillance data from mainland China. An approach related to time-varying reproduction number (Rt) was proposed, which extracts the environment-related components from Rt to estimate the relationship between environmental factors and influenza transmission based on a mixed-effects regression model. Nonlinear relationships for absolute humidity (the lowest transmission was observed at absolute humidity of 12 g/m3) and mean temperature (the lowest transmission was observed at the mean temperature of 18 °C) with influenza transmission were observed. Influenza transmission holds almost constant with the average precipitation below 1 mm or sunshine hour below 9 h/day, but increases for the precipitation and decreases for the sunshine hour afterward. The environmental dependence varies across subtypes: A(H3N2) maintains relatively higher transmission in high temperature and humidity conditions, compared with other influenza subtypes. Overall, the subtypes specified environmental dependence of influenza transmission could explain 23.1 %, 29.2 % and 27.1 % of the variations for A(H1N1)pdm09, A(H3N2) and B-lineage in China. The projected seasonal transmission rates based on our approach could be used as a valuable seasonal proxy to model the influenza dynamics under various meteorological spaces. Finally, our approach is also applicable to obtain novel insights into the impact of environmental factors on other respiratory infectious diseases.
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Affiliation(s)
- Bing Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou 510180, PR China
| | - Tao Chen
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Shiwen Liang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Tongan District Center for Disease Control and Prevention, Xiamen 361100, PR China
| | - Wei Shen
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Department of Rheumatology and Immunology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, PR China
| | - Qianru Sun
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China
| | - Daoze Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China
| | - Gang Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China
| | - Jing Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Lei Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Dayan Wang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China.
| | - Yuelong Shu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou 510030, PR China; Institute of Pathogen Biology of Chinese Academy of Medical Science (CAMS)/ Peking Union Medical College (PUMC), Beijing 100730, PR China.
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou 510030, PR China.
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Zhu H, Chen S, Lu W, Chen K, Feng Y, Xie Z, Zhang Z, Li L, Ou J, Chen G. Study on the influence of meteorological factors on influenza in different regions and predictions based on an LSTM algorithm. BMC Public Health 2022; 22:2335. [PMID: 36514013 PMCID: PMC9745690 DOI: 10.1186/s12889-022-14299-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 09/26/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Influenza epidemics pose a threat to human health. It has been reported that meteorological factors (MFs) are associated with influenza. This study aimed to explore the similarities and differences between the influences of more comprehensive MFs on influenza in cities with different economic, geographical and climatic characteristics in Fujian Province. Then, the information was used to predict the daily number of cases of influenza in various cities based on MFs to provide bases for early warning systems and outbreak prevention. METHOD Distributed lag nonlinear models (DLNMs) were used to analyse the influence of MFs on influenza in different regions of Fujian Province from 2010 to 2021. Long short-term memory (LSTM) was used to train and model daily cases of influenza in 2010-2018, 2010-2019, and 2010-2020 based on meteorological daily values. Daily cases of influenza in 2019, 2020 and 2021 were predicted. The root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to quantify the accuracy of model predictions. RESULTS The cumulative effect of low and high values of air pressure (PRS), air temperature (TEM), air temperature difference (TEMD) and sunshine duration (SSD) on the risk of influenza was obvious. Low (< 979 hPa), medium (983 to 987 hPa) and high (> 112 hPa) PRS were associated with a higher risk of influenza in women, children aged 0 to 12 years, and rural populations. Low (< 9 °C) and high (> 23 °C) TEM were risk factors for influenza in four cities. Wind speed (WIN) had a more significant effect on the risk of influenza in the ≥ 60-year-old group. Low (< 40%) and high (> 80%) relative humidity (RHU) in Fuzhou and Xiamen had a significant effect on influenza. When PRS was between 1005-1015 hPa, RHU > 60%, PRE was low, TEM was between 10-20 °C, and WIN was low, the interaction between different MFs and influenza was most obvious. The RMSE, MAE, MAPE, and SMAPE evaluation indices of the predictions in 2019, 2020 and 2021 were low, and the prediction accuracy was high. CONCLUSION All eight MFs studied had an impact on influenza in four cities, but there were similarities and differences. The LSTM model, combined with these eight MFs, was highly accurate in predicting the daily cases of influenza. These MFs and prediction models could be incorporated into the influenza early warning and prediction system of each city and used as a reference to formulate prevention strategies for relevant departments.
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Affiliation(s)
- Hansong Zhu
- Emergency Response and Epidemic Management Institute, Fujian Center for Disease Control and Prevention, Fuzhou, 350012 Fujian China ,Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, 350012 Fujian China ,grid.256112.30000 0004 1797 9307The practice base on the school of public health Fujian Medical University, Fuzhou, 350012 Fujian China
| | - Si Chen
- Climate Assessment Office of Fujian Climate Center, Fuzhou, 350007 Fujian China
| | - Wen Lu
- grid.415108.90000 0004 1757 9178Shengli Clinical Medical College of Fujian Medical University, Department of Health Management of Fujian Provincial Hospital, Fuzhou, 350001 Fujian China
| | - Kaizhi Chen
- grid.411604.60000 0001 0130 6528College of Computer and Data Science, Fuzhou University, Fuzhou, 350108 Fujian China
| | - Yulin Feng
- grid.256112.30000 0004 1797 9307School of Public Health, Fujian Medical University, Fujian 350108 Fuzhou, China
| | - Zhonghang Xie
- Emergency Response and Epidemic Management Institute, Fujian Center for Disease Control and Prevention, Fuzhou, 350012 Fujian China ,Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, 350012 Fujian China ,grid.256112.30000 0004 1797 9307The practice base on the school of public health Fujian Medical University, Fuzhou, 350012 Fujian China
| | - Zhifang Zhang
- Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, 350012 Fujian China ,Science and Technology Information and Management, Fujian Center for Disease Control and Prevention, Fuzhou, 350012 Fujian China
| | - Lingfang Li
- Emergency Response and Epidemic Management Institute, Fujian Center for Disease Control and Prevention, Fuzhou, 350012 Fujian China ,Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, 350012 Fujian China
| | - Jianming Ou
- Emergency Response and Epidemic Management Institute, Fujian Center for Disease Control and Prevention, Fuzhou, 350012 Fujian China ,Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, 350012 Fujian China ,grid.256112.30000 0004 1797 9307The practice base on the school of public health Fujian Medical University, Fuzhou, 350012 Fujian China
| | - Guangmin Chen
- Emergency Response and Epidemic Management Institute, Fujian Center for Disease Control and Prevention, Fuzhou, 350012 Fujian China ,Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, 350012 Fujian China ,grid.256112.30000 0004 1797 9307The practice base on the school of public health Fujian Medical University, Fuzhou, 350012 Fujian China
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20
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Ng H, Li Y, Zhang T, Lu Y, Wong C, Ni J, Zhao Q. Association between multiple meteorological variables and seasonal influenza A and B virus transmission in Macau. Heliyon 2022; 8:e11820. [DOI: 10.1016/j.heliyon.2022.e11820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/03/2022] [Accepted: 11/15/2022] [Indexed: 11/26/2022] Open
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Abstract
RNA viruses include respiratory viruses, such as coronaviruses and influenza viruses, as well as vector-borne viruses, like dengue and West Nile virus. RNA viruses like these encounter various environments when they copy themselves and spread from cell to cell or host to host. Ex vivo differences, such as geographical location and humidity, affect their stability and transmission, while in vivo differences, such as pH and host gene expression, impact viral receptor binding, viral replication, and the host immune response against the viral infection. A critical factor affecting RNA viruses both ex vivo and in vivo, and defining the outcome of viral infections and the direction of viral evolution, is temperature. In this minireview, we discuss the impact of temperature on viral replication, stability, transmission, and adaptation, as well as the host innate immune response. Improving our understanding of how RNA viruses function, survive, and spread at different temperatures will improve our models of viral replication and transmission risk analyses.
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Affiliation(s)
- Karishma Bisht
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
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22
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Zhang S, Sun Z, He J, Li Z, Han L, Shang J, Hao Y. The influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza activity in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 843:157024. [PMID: 35772553 DOI: 10.1016/j.scitotenv.2022.157024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 06/24/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
Previous research has extensively studied the seasonalities of human influenza infections and the effect of specific climatic factors in different regions. However, there is limited understanding of the influences of monsoons. This study applied generalized additive model with monthly surveillance data from mainland China to explore the influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza in China. The results suggested two influenza active periods in northern China and three active periods in southern China. The study found that the northerly advancement of East Asian Summer Monsoon (EASM) influences the summer influenza spatio-temporal patterns in both southern and northern China. At the interannual scale, the north-south converse effect of EASM on influenza activity is mainly due to the converse effect of EASM on humidity and precipitation. Within the annual scale, influenza activity in southern China gradually reaches its maximum during the summer exacerbated by the northerly advancement of EASM. Furthermore, the winter epidemic in China is related to the low temperature and humidity influenced by the East Asian Winter Monsoon (EAWM). Moreover, the active period in transition season is related partially to the large rapid temperature change influenced by the transition of EAWM and EASM. Despite the delayed onset and instability, the climatic condition influenced by the East Asian Monsoon is one of the potential key drivers of influenza activity.
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Affiliation(s)
- Shuwen Zhang
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China.
| | - Juan He
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China.
| | - Ziming Li
- Environmental Meteorology Forecast Center of Beijing-Tianjin-Hebei, China Meteorological Administration, Beijing 100089, China; Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Ling Han
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Jing Shang
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Yu Hao
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
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23
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Roy A, Byrne S, Sarangi NK, Murphy PV, Keyes TE. A cell free biomembrane platform for multimodal study of influenza virus hemagglutinin and for evaluation of entry-inhibitors against hemagglutinin. Front Mol Biosci 2022; 9:1017338. [DOI: 10.3389/fmolb.2022.1017338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
Seasonal periodic pandemics and epidemics caused by Influenza A viruses (IAVs) are associated with high morbidity and mortality worldwide. They are frequent and unpredictable in severity so there is a need for biophysical platforms that can be used to provide both mechanistic insights into influenza virulence and its potential treatment by anti-IAV agents. Host membrane viral association through the glycoprotein hemagglutinin (HA) of IAVs is one of the primary steps in infection. HA is thus a potential target for drug discovery and development against influenza. Deconvolution of the multivalent interactions of HA at the interfaces of the host cell membrane can help unravel therapeutic targets. In this contribution, we reported the effect of a multivalent HA glycoprotein association on various glycosphingolipid receptors (GD1a, GM3, GM1) doped asymmetrically into an artificial host membrane spanned across an aqueous filled microcavity array. The extent of HA association and its impact on membrane resistance, capacitance, and diffusivity was measured using highly sensitive electrochemical impedance spectroscopy (EIS) and fluorescence lifetime correlation spectroscopy (FLCS). Furthermore, we investigated the inhibition of the influenza HA glycoprotein association with the host mimetic surface by natural and synthetic sialic acid-based inhibitors (sialic acid, Siaα2,3-GalOMe, FB127, 3-sialyl lactose) using electrochemical impedance spectroscopy and observe that while all inhibit, they do not prevent host binding. Overall, the work demonstrates the platform provides a label-free screening platform for the biophysical evaluation of new inhibitors in the development of potential therapeutics for IAV infection prevention and treatment.
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24
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Lim DK, Kim JW, Kim JK. Effects of climatic factors on the prevalence of influenza virus infection in Cheonan, Korea. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:59052-59059. [PMID: 35381925 DOI: 10.1007/s11356-022-20070-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 03/30/2022] [Indexed: 06/14/2023]
Abstract
Big data can be used to correlate diseases and climatic factors. The prevalence of influenza (flu) virus, accounting for a large proportion of respiratory infections, suggests that the effect of climate variables according to seasonal dynamics of influenza virus infections should be investigated. Here, trends in flu virus detection were analyzed using data from 9,010 tests performed between January 2012 and December 2018 at Dankook University Hospital, Cheonan, Korea. We compared the detection of the flu virus in Cheonan area and its association with climate change. The flu virus detection rate was 9.9% (894/9,010), and the detection rate was higher for flu virus A (FLUAV; 6.9%) than for flu virus B (FLUBV; 3.0%). Both FLUAV and FLUBV infections are considered an epidemic each year. We identified 43.1% (n = 385) and 35.0% (n = 313) infections in children aged < 10 years and adults aged > 60 years, respectively. The combination of these age groups encompassed 78.1% (n = 698/894) of the total data. Flu virus infections correlated with air temperature, relative humidity, vapor pressure, atmospheric pressure, particulate matter, and wind chill temperature (P < 0.001). However, the daily temperature range did not significantly correlate with the flu detection results. This is the first study to identify the relationship between long-term flu virus infection with temperature in the temperate region of Cheonan.
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Affiliation(s)
- Dong Kyu Lim
- Department of Medical Laser, Dankook University Graduate School of Medicine, Chungnam, South Korea
| | - Jong Wan Kim
- Department of Laboratory Medicine, Dankook University College of Medicine, Chungnam, South Korea
| | - Jae Kyung Kim
- Department of Biomedical Laboratory Science, College of Health Sciences, Dankook University, 119 Dandae-ro, Dongnam-gu, Cheonan-si, Chungnam, 31116, South Korea.
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25
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Gavenčiak T, Monrad JT, Leech G, Sharma M, Mindermann S, Bhatt S, Brauner J, Kulveit J. Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions. PLoS Comput Biol 2022; 18:e1010435. [PMID: 36026483 DOI: 10.1101/2021.06.10.21258647] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 09/08/2022] [Accepted: 07/25/2022] [Indexed: 05/22/2023] Open
Abstract
Although seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. While there is a sizable and growing literature on environmental drivers of COVID-19 transmission, recent reviews have highlighted conflicting and inconclusive findings. This indeterminacy partly owes to the fact that seasonal variation relates to viral transmission by a complicated web of causal pathways, including many interacting biological and behavioural factors. Since analyses of specific factors cannot determine the aggregate strength of seasonal forcing, we sidestep the challenge of disentangling various possible causal paths in favor of a holistic approach. We model seasonality as a sinusoidal variation in transmission and infer a single Bayesian estimate of the overall seasonal effect. By extending two state-of-the-art models of non-pharmaceutical intervention (NPI) effects and their datasets covering 143 regions in temperate Europe, we are able to adjust our estimates for the role of both NPIs and mobility patterns in reducing transmission. We find strong seasonal patterns, consistent with a reduction in the time-varying reproduction number R(t) (the expected number of new infections generated by an infectious individual at time t) of 42.1% (95% CI: 24.7%-53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions.
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Affiliation(s)
- Tomáš Gavenčiak
- Centre for Theoretical Studies, Charles University, Prague, Czech Republic
| | - Joshua Teperowski Monrad
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Health Policy, London School of Economics and Political Science, London, United Kingdom
| | - Gavin Leech
- Department of Computer Science, University of Bristol, Bristol, United Kingdom
| | - Mrinank Sharma
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Sören Mindermann
- Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Samir Bhatt
- Faculty of Medicine, School of Public Health, Imperial College London, London, United Kingdom
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Jan Brauner
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Jan Kulveit
- Centre for Theoretical Studies, Charles University, Prague, Czech Republic
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
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26
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Tripathi V, Bundel R, Mandal CC. Effect of environmental factors on SARS-CoV-2 infectivity in northern hemisphere countries: a 2-year data analysis. Public Health 2022; 208:105-110. [PMID: 35753085 PMCID: PMC9068792 DOI: 10.1016/j.puhe.2022.04.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 04/12/2022] [Accepted: 04/27/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE The COVID-19 pandemic that emerged in December 2019 brought human life to a standstill. With over 2-year since the pandemic originated from Wuhan, SARS-CoV-2 has caused more than 6 million deaths worldwide. With the emergence of mutant strains and COVID-19 surge waves, it becomes critically important to conduct epidemiological studies that allow us to understand the role of various environmental factors on SARS-CoV-2 infectivity. Our earlier study reported a strong negative correlation between temperature and COVID-19 incidence. This research is an extension of our previous study with an attempt to understand the global analysis of COVID-19 in northern hemisphere countries. STUDY DESIGN This research aims at achieving a better understanding of the correlation of environmental factors such as temperature, sunlight, and humidity with new cases of COVID-19 in northern hemisphere from March 2020 to February 2022. METHODS To understand the relationship between the different environmental variants and COVID-19, a statistical approach was employed using Pearson, Spearman and Kendall analysis. RESULTS Month-wise univariate analysis indicated a strong negative correlation of temperature and sunlight with SARS-CoV-2 infectivity, whereas inconsistencies were observed in correlation analysis in the case of humidity in winter months. Moreover, a strong negative correlation between average temperature of winter months and COVID-19 cases exists as evidenced by Pearson, Spearman, and Kendall analyses. In addition, correlation pattern between monthly temperature and COVID-19 cases of a country mimics to that of sunlight of a country. CONCLUSION This pilot study proposes that low temperatures and low sunlight might be additional risk factors for SARS-CoV-2 infectivity, mostly in northern hemisphere countries.
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Affiliation(s)
- Vaishnavi Tripathi
- Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, Ajmer, Rajasthan, India
| | - Rashmi Bundel
- Department of Statistics, University of Rajasthan, Jaipur, Rajasthan, India
| | - Chandi C Mandal
- Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, Ajmer, Rajasthan, India.
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27
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Rath SL, Tripathy M, Mandal N. How Does Temperature Affect the Dynamics of SARS-CoV-2 M Proteins? Insights from Molecular Dynamics Simulations. J Membr Biol 2022; 255:341-356. [PMID: 35552785 PMCID: PMC9101995 DOI: 10.1007/s00232-022-00244-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 05/07/2022] [Indexed: 11/30/2022]
Abstract
Enveloped viruses, in general, have several transmembrane proteins and glycoproteins, which assist the virus in entry and attachment onto the host cells. These proteins also play a significant role in determining the shape and size of the newly formed virus particles. The lipid membrane and the embedded proteins affect each other in non-trivial ways during the course of the viral life cycle. Unraveling the nature of the protein-protein and protein-lipid interactions, under various environmental and physiological conditions, could therefore prove to be crucial in development of therapeutics. Here, we study the M protein of SARS-CoV-2 to understand the effect of temperature on the properties of the protein-membrane system. The membrane-embedded dimeric M proteins were studied using atomistic and coarse-grained molecular dynamics simulations at temperatures ranging between 10 and 50 °C. While temperature-induced fluctuations are expected to be monotonic, we observe a steady rise in the protein dynamics up to 40 °C, beyond which it surprisingly reverts back to the low-temperature behavior. Detailed investigation reveals disordering of the membrane lipids in the presence of the protein, which induces additional curvature around the transmembrane region. Coarse-grained simulations indicate temperature-dependent aggregation of M protein dimers. Our study clearly indicates that the dynamics of membrane lipids and integral M protein of SARS-CoV-2 enables it to better associate and aggregate only at a certain temperature range (i.e., ~ 30-40 °C). This can have important implications in the protein aggregation and subsequent viral budding/fission processes.
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Affiliation(s)
- Soumya Lipsa Rath
- Department of Biotechnology, National Institute of Technology Warangal (NITW), Telangana, 506004, India.
| | - Madhusmita Tripathy
- Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, 64287, Darmstadt, Germany.
| | - Nabanita Mandal
- Department of Biotechnology, National Institute of Technology Warangal (NITW), Telangana, 506004, India
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Inaida S, Paul RE, Matsuno S. Viral transmissibility of SARS-CoV-2 accelerates in the winter, similarly to influenza epidemics. Am J Infect Control 2022; 50:1070-1076. [PMID: 35605752 PMCID: PMC9121648 DOI: 10.1016/j.ajic.2022.05.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/09/2022] [Accepted: 05/13/2022] [Indexed: 02/06/2023]
Abstract
The transmissibility of SARS-CoV-2 is anticipated to increase in the winter because of increased viral survival in cold damp air and thus would exacerbate viral spread in community. Analysis to capture the seasonal trend is needed to be prepared for future epidemics. We compared regression models for the 5-week case prior to each epidemic peak week for both the COVID-19 and influenza epidemics in winter and summer. The weekly case increase ratio was compared, using non-paired t tests between seasons. In order to test the robustness of seasonal transmission patterns, the normalized weekly case numbers of COVID-19 and influenza case rates of all seasons were assessed in a combined quadratic regression analysis. In winter, the weekly case increase ratio accelerated before epidemic peaks, similarly, for both COVID-19 and influenza. The quadratic regression models of weekly cases were observed to be convex curves in the winter and concave curves in the spring/summer for both COVID-19 and influenza. A significant increase of case increase ratio (3.19 [95%CI:0.01-6.37, P = .049]) of the COVID-19 and influenza epidemics was observed in winter as compared to spring/summer before the epidemic peak. The epidemic of COVID-19 was found to mirror that of influenza, suggesting a strong underlying seasonal transmissibility. Influenza epidemics can potentially be a useful reference for the COVID-19 epidemics.
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29
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Fever as an evolutionary agent to select immune complexes interfaces. Immunogenetics 2022; 74:465-474. [PMID: 35545703 PMCID: PMC9094598 DOI: 10.1007/s00251-022-01263-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/08/2022] [Indexed: 11/10/2022]
Abstract
We herein analyzed all available protein–protein interfaces of the immune complexes from the Protein Data Bank whose antigens belong to pathogens or cancers that are modulated by fever in mammalian hosts. We also included, for comparison, protein interfaces from immune complexes that are not significantly modulated by the fever response. We highlight the distribution of amino acids at these viral, bacterial, protozoan and cancer epitopes, and at their corresponding paratopes that belong strictly to monoclonal antibodies. We identify the “hotspots”, i.e. residues that are highly connected at such interfaces, and assess the structural, kinetic and thermodynamic parameters responsible for complex formation. We argue for an evolutionary pressure for the types of residues at these protein interfaces that may explain the role of fever as a selective force for optimizing antibody binding to antigens.
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Wang J, Zhang L, Lei R, Li P, Li S. Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010-2019 in Lanzhou, China. Front Public Health 2022; 10:833710. [PMID: 35273941 PMCID: PMC8902077 DOI: 10.3389/fpubh.2022.833710] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background Influenza is a seasonal infectious disease, and meteorological parameters critically influence the incidence of influenza. However, the meteorological parameters linked to influenza occurrence in semi-arid areas are not studied in detail. This study aimed to clarify the impact of meteorological parameters on influenza incidence during 2010-2019 in Lanzhou. The results are expected to facilitate the optimization of influenza-related public health policies by the local healthcare departments. Methods Descriptive data related to influenza incidence and meteorology during 2010-2019 in Lanzhou were analyzed. The exposure-response relationship between the risk of influenza occurrence and meteorological parameters was explored according to the distributed lag no-linear model (DLNM) with Poisson distribution. The response surface model and stratified model were used to estimate the interactive effect between relative humidity (RH) and other meteorological parameters on influenza incidence. Results A total of 6701 cases of influenza were reported during 2010-2019. DLNM results showed that the risk of influenza would gradually increase as the weekly mean average ambient temperature (AT), RH, and absolute humidity (AH) decrease at lag 3 weeks when they were lower than 12.16°C, 51.38%, and 5.24 g/m3, respectively. The low Tem (at 5th percentile, P5) had the greatest effect on influenza incidence; the greatest estimated relative risk (RR) was 4.54 (95%CI: 3.19-6.46) at cumulative lag 2 weeks. The largest estimates of RRs for low RH (P5) and AH (P5) were 4.81 (95%CI: 3.82-6.05) and 4.17 (95%CI: 3.30-5.28) at cumulative lag 3 weeks, respectively. An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (-4.75% to -1.46%) decrease in the weekly influenza case counts in a low RH environment. In addition, RH showed significant interaction with AT and AP on influenza incidence but not with wind speed. Conclusion This study indicated that low AT, low humidity (RH and AH), and high air pressure (AP) increased the risk of influenza. Moreover, the interactive effect of low RH with low AT and high AP can aggravate the incidence of influenza.
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Affiliation(s)
- Jinyu Wang
- School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Ling Zhang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, China
| | - Ruoyi Lei
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, China
| | - Pu Li
- The Second People's Hospital of Baiyin, Baiyin, China
| | - Sheng Li
- The First People's Hospital of Lanzhou, Lanzhou, China
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31
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Ali ST, Cowling BJ, Wong JY, Chen D, Shan S, Lau EHY, He D, Tian L, Li Z, Wu P. Influenza seasonality and its environmental driving factors in mainland China and Hong Kong. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 818:151724. [PMID: 34800462 DOI: 10.1016/j.scitotenv.2021.151724] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/20/2021] [Accepted: 11/12/2021] [Indexed: 05/27/2023]
Abstract
BACKGROUND Influenza epidemics occur during winter in temperate zones, but have less regular seasonality in the subtropics and tropics. Here we quantified the role of environmental drivers of influenza seasonality in temperate and subtropical China. METHODS We used weekly surveillance data on influenza virus activity in mainland China and Hong Kong from 2005 through 2016. We estimated the transmissibility via the instantaneous reproduction number (Rt), a real-time measure of transmissibility, and examined its relationship with different climactic drivers and allowed for the timing of school holidays and the decline in susceptibility in the population as an epidemic progressed. We developed a multivariable regression model for Rt to quantify the contribution of various potential environmental drivers of transmission. FINDINGS We found that absolute humidity is a potential driver of influenza seasonality and had a U-shaped association with transmissibility and hence can predict the pattern of influenza virus transmission across different climate zones. Absolute humidity was able to explain up to 15% of the variance in Rt, and was a stronger predictor of Rt across the latitudes. Other climatic drivers including mean daily temperature explained up to 13% of variance in Rt and limited to the locations where the indoor measures of these factors have better indicators of outdoor measures. The non-climatic driver, holiday-related school closures could explain up to 7% of variance in Rt. INTERPRETATION A U-shaped association of absolute humidity with influenza transmissibility was able to predict seasonal patterns of influenza virus epidemics in temperate and subtropical locations.
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Affiliation(s)
- Sheikh Taslim Ali
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region.
| | - Jessica Y Wong
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Dongxuan Chen
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - Songwei Shan
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - Eric H Y Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong Special Administrative Region
| | - Linwei Tian
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Zhongjie Li
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
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32
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Zhao Z, Hossain MI, Jung S, Wang Z, Yeo D, Song M, Min A, Park S, Choi C. Survival of murine norovirus and hepatitis A virus in bottled drinking water, strawberries, and oysters. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108623] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Iriarte-Alonso MA, Bittner AM, Chiantia S. Influenza A virus hemagglutinin prevents extensive membrane damage upon dehydration. BBA ADVANCES 2022; 2:100048. [PMID: 37082591 PMCID: PMC10074934 DOI: 10.1016/j.bbadva.2022.100048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
While the molecular mechanisms of virus infectivity are rather well known, the detailed consequences of environmental factors on virus biophysical properties are poorly understood. Seasonal influenza outbreaks are usually connected to the low winter temperature, but also to the low relative air humidity. Indeed, transmission rates increase in cold regions during winter. While low temperature must slow degradation processes, the role of low humidity is not clear. We studied the effect of relative humidity on a model of Influenza A H1N1 virus envelope, a supported lipid bilayer containing the surface glycoprotein hemagglutinin (HA), which is present in the viral envelope in very high density. For complete cycles of hydration, dehydration and rehydration, we evaluate the membrane properties in terms of structure and dynamics, which we assess by combining confocal fluorescence microscopy, raster image correlation spectroscopy, line-scan fluorescence correlation spectroscopy and atomic force microscopy. Our findings indicate that the presence of HA prevents macroscopic membrane damage after dehydration. Without HA, fast membrane disruption is followed by irreversible loss of lipid and protein mobility. Although our model is principally limited by the membrane composition, the macroscopic effects of HA under dehydration stress reveal new insights on the stability of the virus at low relative humidity.
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Owen L, Shivkumar M, Cross RBM, Laird K. Porous surfaces: stability and recovery of coronaviruses. Interface Focus 2022; 12:20210039. [PMID: 34956608 PMCID: PMC8662390 DOI: 10.1098/rsfs.2021.0039] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 11/03/2021] [Indexed: 12/12/2022] Open
Abstract
The role of indirect contact in the transmission of SARS-CoV-2 is not clear. SARS-CoV-2 persists on dry surfaces for hours to days; published studies have largely focused on hard surfaces with less research being conducted on different porous surfaces, such as textiles. Understanding the potential risks of indirect transmission of COVID-19 is useful for settings where there is close contact with textiles, including healthcare, manufacturing and retail environments. This article aims to review current research on porous surfaces in relation to their potential as fomites of coronaviruses compared to non-porous surfaces. Current methodologies for assessing the stability and recovery of coronaviruses from surfaces are also explored. Coronaviruses are often less stable on porous surfaces than non-porous surfaces, for example, SARS-CoV-2 persists for 0.5 h-5 days on paper and 3-21 days on plastic; however, stability is dependent on the type of surface. In particular, the surface properties of textiles differ widely depending on their construction, leading to variation in the stability of coronaviruses, with longer persistence on more hydrophobic materials such as polyester (1-3 days) compared to highly absorbent cotton (2 h-4 days). These findings should be considered where there is close contact with potentially contaminated textiles.
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Affiliation(s)
- Lucy Owen
- Infectious Disease Research Group, The Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, UK
| | - Maitreyi Shivkumar
- Infectious Disease Research Group, The Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, UK
| | - Richard B. M. Cross
- Emerging Technologies Research Centre, School of Engineering and Sustainable Development, De Montfort University, Leicester LE1 9BH, UK
| | - Katie Laird
- Infectious Disease Research Group, The Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, UK
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Ma P, Tang X, Zhang L, Wang X, Wang W, Zhang X, Wang S, Zhou N. Influenza A and B outbreaks differed in their associations with climate conditions in Shenzhen, China. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2022; 66:163-173. [PMID: 34693474 PMCID: PMC8542503 DOI: 10.1007/s00484-021-02204-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 10/04/2021] [Accepted: 10/07/2021] [Indexed: 05/20/2023]
Abstract
Under the variant climate conditions in the transitional regions between tropics and subtropics, the impacts of climate factors on influenza subtypes have rarely been evaluated. With the available influenza A (Flu-A) and influenza B (Flu-B) outbreak data in Shenzhen, China, which is an excellent example of a transitional marine climate, the associations of multiple climate variables with these outbreaks were explored in this study. Daily laboratory-confirmed influenza virus and climate data were collected from 2009 to 2015. Potential impacts of daily mean/maximum/minimum temperatures (T/Tmax/Tmin), relative humidity (RH), wind velocity (V), and diurnal temperature range (DTR) were analyzed using the distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Under its local climate partitions, Flu-A mainly prevailed in summer months (May to June), and a second peak appeared in early winter (December to January). Flu-B outbreaks usually occurred in transitional seasons, especially in autumn. Although low temperature caused an instant increase in both Flu-A and Flu-B risks, its effect could persist for up to 10 days for Flu-B and peak at 17 C (relative risk (RR) = 14.16, 95% CI: 7.46-26.88). For both subtypes, moderate-high temperature (28 C) had a significant but delayed effect on influenza, especially for Flu-A (RR = 26.20, 95% CI: 13.22-51.20). The Flu-A virus was sensitive to RH higher than 76%, while higher Flu-B risks were observed at both low (< 65%) and high (> 83%) humidity. Flu-A was active for a short term after exposure to large DTR (e.g., DTR = 10 C, RR = 12.45, 95% CI: 6.50-23.87), whereas Flu-B mainly circulated under stable temperatures. Although the overall wind speed in Shenzhen was low, moderate wind (2-3 m/s) was found to favor the outbreaks of both subtypes. This study revealed the thresholds of various climatic variables promoting influenza outbreaks, as well as the distinctions between the flu subtypes. These data can be helpful in predicting seasonal influenza outbreaks and minimizing the impacts, based on integrated forecast systems coupled with short-term climate models.
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Affiliation(s)
- Pan Ma
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China.
| | - Xiaoxin Tang
- Shenzhen National Climate Observatory, Shenzhen Meteorological Bureau, Shenzhen, 518000, China
| | - Li Zhang
- Shenzhen National Climate Observatory, Shenzhen Meteorological Bureau, Shenzhen, 518000, China
| | - Xinzi Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China
| | - Weimin Wang
- Shangluo Meteorological Bureau, Shangluo, 726000, Shanxi, China
| | - Xiaoling Zhang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China
| | - Shigong Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China
| | - Ning Zhou
- The First Hospital of Lanzhou, Lanzhou, 730000, Gansu, China
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Sensitivity of airborne transmission of enveloped viruses to seasonal variation in indoor relative humidity. INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2022. [PMCID: PMC8659254 DOI: 10.1016/j.icheatmasstransfer.2021.105747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
In temperate climates, the peak in infection rates of enveloped viruses during the winter is likely heightened by seasonal variation in relative humidity within indoor spaces. While these seasonal trends are established in influenza and human coronaviruses, the mechanisms driving this seasonality remain poorly understood. Relative humidity impacts the evaporation rate and equilibrium size of airborne particles, which in turn may impact particle removal rates and virion viability. However, the relative importance of these two processes is not known. Here we use the Quadrature-based model of Respiratory Aerosol and Droplets to explore whether the seasonal variation in enveloped viruses is driven by differences in particle removal rates or by differences in virion inactivation rates. Through a large ensemble of simulations, we found that dry indoor conditions typical of winter lead to slower virion inactivation than humid indoor conditions typical of summer; in poorly ventilated spaces, this reduction in inactivation rates increases the airborne concentration of active virions, but this effect was important to virion exposure only when the susceptible person was farther than 2 m downwind of the infectious person. On the other hand, the impact of relative humidity on particle settling velocity did not significantly affect the removal or travel distance of virus-laden particles, suggesting that relative humidity is more likely to affect seasonal transmission via inactivation rates than via particle removal.
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The impact of temperature on the transmissibility potential and virulence of COVID-19 in Tokyo, Japan. Sci Rep 2021; 11:24477. [PMID: 34966171 PMCID: PMC8716537 DOI: 10.1038/s41598-021-04242-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 12/17/2021] [Indexed: 11/22/2022] Open
Abstract
Assessing the impact of temperature on COVID-19 epidemiology is critical for implementing non-pharmaceutical interventions. However, few studies have accounted for the nature of contagious diseases, i.e., their dependent happenings. We aimed to quantify the impact of temperature on the transmissibility and virulence of COVID-19 in Tokyo, Japan, employing two epidemiological measurements of transmissibility and severity: the effective reproduction number (\documentclass[12pt]{minimal}
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\begin{document}$$R_{t}$$\end{document}Rt) and case fatality risk (CFR). We estimated the \documentclass[12pt]{minimal}
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\begin{document}$$R_{t}$$\end{document}Rt and time-delay adjusted CFR and to subsequently assess the nonlinear and delayed effect of temperature on \documentclass[12pt]{minimal}
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\begin{document}$$R_{t}$$\end{document}Rt and time-delay adjusted CFR. For \documentclass[12pt]{minimal}
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\begin{document}$$R_{t}$$\end{document}Rt at low temperatures, the cumulative relative risk (RR) at the first temperature percentile (3.3 °C) was 1.3 (95% confidence interval (CI): 1.1–1.7). As for the virulence to humans, moderate cold temperatures were associated with higher CFR, and CFR also increased as the temperature rose. The cumulative RR at the 10th and 99th percentiles of temperature (5.8 °C and 30.8 °C) for CFR were 3.5 (95% CI: 1.3–10.0) and 6.4 (95% CI: 4.1–10.1). Our results suggest the importance to take precautions to avoid infection in both cold and warm seasons to avoid severe cases of COVID-19. The results and our proposed approach will also help in assessing the possible seasonal course of COVID-19 in the future.
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Singh J, Pandit P, McArthur AG, Banerjee A, Mossman K. Evolutionary trajectory of SARS-CoV-2 and emerging variants. Virol J 2021; 18:166. [PMID: 34389034 PMCID: PMC8361246 DOI: 10.1186/s12985-021-01633-w] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/03/2021] [Indexed: 12/17/2022] Open
Abstract
The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more recently, the independent evolution of multiple SARS-CoV-2 variants has generated renewed interest in virus evolution and cross-species transmission. While all known human coronaviruses (HCoVs) are speculated to have originated in animals, very little is known about their evolutionary history and factors that enable some CoVs to co-exist with humans as low pathogenic and endemic infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1), while others, such as SARS-CoV, MERS-CoV and SARS-CoV-2 have evolved to cause severe disease. In this review, we highlight the origins of all known HCoVs and map positively selected for mutations within HCoV proteins to discuss the evolutionary trajectory of SARS-CoV-2. Furthermore, we discuss emerging mutations within SARS-CoV-2 and variants of concern (VOC), along with highlighting the demonstrated or speculated impact of these mutations on virus transmission, pathogenicity, and neutralization by natural or vaccine-mediated immunity.
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Affiliation(s)
- Jalen Singh
- School of Interdisciplinary Science, McMaster University, Hamilton, ON, Canada
| | - Pranav Pandit
- EpiCenter for Disease Dynamics, One Health Institute, School of Veterinary Medicine, University of California Davis, Davis, CA, USA
| | - Andrew G McArthur
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
| | - Arinjay Banerjee
- Vaccine and Infectious Disease Organization, University of Saskatchewan, Saskatoon, SK, Canada.
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
- Department of Biology, University of Waterloo, Waterloo, ON, Canada.
| | - Karen Mossman
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada.
- Department of Medicine, McMaster University, Hamilton, ON, Canada.
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada.
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Raines KS, Doniach S, Bhanot G. The transmission of SARS-CoV-2 is likely comodulated by temperature and by relative humidity. PLoS One 2021; 16:e0255212. [PMID: 34324570 PMCID: PMC8321224 DOI: 10.1371/journal.pone.0255212] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 07/12/2021] [Indexed: 01/08/2023] Open
Abstract
Inferring the impact of climate upon the transmission of SARS-CoV-2 has been confounded by variability in testing, unknown disease introduction rates, and changing weather. Here we present a data model that accounts for dynamic testing rates and variations in disease introduction rates. We apply this model to data from Colombia, whose varied and seasonless climate, central port of entry, and swift, centralized response to the COVID-19 pandemic present an opportune environment for assessing the impact of climate factors on the spread of COVID-19. We observe strong attenuation of transmission in climates with sustained daily temperatures above 30 degrees Celsius and simultaneous mean relative humidity below 78%, with outbreaks occurring at high humidity even where the temperature is high. We hypothesize that temperature and relative humidity comodulate the infectivity of SARS-CoV-2 within respiratory droplets.
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Affiliation(s)
| | - Sebastian Doniach
- Applied Physics, Stanford University, Stanford, CA, United States of America
| | - Gyan Bhanot
- Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ, United States of America
- Physics and Astronomy, Rutgers University, Piscataway, NJ, United States of America
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States of America
- School of Medicine, University of California San Diego, La Jolla, CA, United States of America
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Simon M, Veit M, Osterrieder K, Gradzielski M. Surfactants - Compounds for inactivation of SARS-CoV-2 and other enveloped viruses. Curr Opin Colloid Interface Sci 2021; 55:101479. [PMID: 34149296 PMCID: PMC8196227 DOI: 10.1016/j.cocis.2021.101479] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We provide here a general view on the interactions of surfactants with viruses, with a particular emphasis on how such interactions can be controlled and employed for inhibiting the infectivity of enveloped viruses, including coronaviruses. The aim is to provide to interested scientists from different fields, including chemistry, physics, biochemistry, and medicine, an overview of the basic properties of surfactants and (corona)viruses, which are relevant to understanding the interactions between the two. Various types of interactions between surfactant and virus are important, and they act on different components of a virus such as the lipid envelope, membrane (envelope) proteins and nucleocapsid proteins. Accordingly, this cannot be a detailed account of all relevant aspects but instead a summary that bridges between the different disciplines. We describe concepts and cover a selection of the relevant literature as an incentive for diving deeper into the relevant material. Our focus is on more recent developments around the COVID-19 pandemic caused by SARS-CoV-2, applications of surfactants against the virus, and on the potential future use of surfactants for pandemic relief. We also cover the most important aspects of the historical development of using surfactants in combatting virus infections. We conclude that surfactants are already playing very important roles in various directions of defence against viruses, either directly, as in disinfection, or as carrier components of drug delivery systems for prophylaxis or treatment. By designing tailor-made surfactants, and consequently, advanced formulations, one can expect more and more effective use of surfactants, either directly as antiviral compounds or as part of more complex formulations.
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Key Words
- AFM, atomic force microscopy
- BVDV, Bovine Viral Diarrhea Virus
- C12E8, dodecyloctaglycol
- CPyC, cetylpyridinium chloride
- DSPC, 1,2-distearoyl-sn-glycero-3-phosphocholine
- Disinfection
- Enveloped viruses
- Flu, influenza virus
- HIV, human immunodeficiency virus
- HSV, herpes simplex virus
- ITC, isothermal titration calorimetry
- Ld, liquid-disordered
- Lipid bilayers
- Lo, liquid-ordered
- PA, phosphatidic acid (anionic)
- PC, phosphatidylcholine (zwitterionic)
- PE, phosphatidylethanolamine (zwitterionic)
- PI, phosphatidylinositol (anionic)
- POPC, 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine
- PS, phosphatidylserine (anionic)
- QUAT, quaternary alkyl ammonium
- RNP, ribonucleoprotein particle
- SAXS, small-angle X-ray scattering
- SDS, sodium dodecyl sulphate
- Surfactant
- TBP, tri-n-butyl phosphate
- TEM, transmission electron microscopy
- Virus inactivation
- cac, critical aggregate concentration
- cmc, critical micelle concentration
- p, packing parameter
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Affiliation(s)
- Miriam Simon
- Dept. of Chemical Engineering and the Russell Berrie Nanotechnolgy Inst. (RBNI), Technion-Israel Institute of Technology, Haifa, IL 3200003, Israel
| | - Michael Veit
- Institut für Virologie, Fachbereich Veterinärmedizin, Freie Universität Berlin, Robert von Ostertag-Straße 7-13, 14163 Berlin, Germany
| | - Klaus Osterrieder
- Institut für Virologie, Fachbereich Veterinärmedizin, Freie Universität Berlin, Robert von Ostertag-Straße 7-13, 14163 Berlin, Germany.,Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong
| | - Michael Gradzielski
- Stranski-Laboratorium für Physikalische und Theoretische Chemie, Institut für Chemie, Straße des 17. Juni 124, Sekr. TC7, Technische Universität Berlin, D-10623 Berlin, Germany
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Lindner-Cendrowska K, Bröde P. Impact of biometeorological conditions and air pollution on influenza-like illnesses incidence in Warsaw. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2021; 65:929-944. [PMID: 33454853 PMCID: PMC8149351 DOI: 10.1007/s00484-021-02076-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 05/13/2023]
Abstract
In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.
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Affiliation(s)
- Katarzyna Lindner-Cendrowska
- Institute of Geography and Spatial Organization, Polish Academy of Sciences, Twarda 51/55, 00-818 Warsaw, Poland
| | - Peter Bröde
- Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), Dortmund, Germany
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Byun WS, Heo SW, Jo G, Kim JW, Kim S, Lee S, Park HE, Baek JH. Is coronavirus disease (COVID-19) seasonal? A critical analysis of empirical and epidemiological studies at global and local scales. ENVIRONMENTAL RESEARCH 2021; 196:110972. [PMID: 33705770 PMCID: PMC7941024 DOI: 10.1016/j.envres.2021.110972] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 02/18/2021] [Accepted: 03/01/2021] [Indexed: 05/03/2023]
Abstract
Coronavirus disease (COVID-19) has infected more than 50 million people and killed more than one million, worldwide, during less than a year course. COVID-19, which has already become the worst pandemic in the last 100 years, is still spreading worldwide. Since the beginning of the outbreak, it has been of particular interest to understand whether COVID-19 is seasonal; the finding might help for better planning and preparation for the fight against the disease. Over the past 12 months, numerous empirical and epidemiological studies have been performed to define the distinct diffusion patterns of COVID-19. Thereby, a wealth of data has accumulated on the relationship between various seasonal meteorological factors and COVID-19 transmissibility at global and local scales. In this review, we aimed to discuss whether COVID-19 exhibits any seasonal features in a global and local perspective by collecting and providing summaries of the findings from empirical and epidemiological studies on the COVID-19 pandemic during its first seasonal cycle.
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Affiliation(s)
- Woo Seok Byun
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Sin Woo Heo
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Gunhee Jo
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Jae Won Kim
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Sarang Kim
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Sujie Lee
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Hye Eun Park
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea
| | - Jea-Hyun Baek
- School of Life Science, Handong Global University, Pohang, Gyeongbuk, 37554, Republic of Korea.
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Abstract
Aerosol particles can spread respiratory infections, especially those caused by viruses; however, the perceived threat is small for many technical reasons, as identified in this article. Under controlled conditions, aerosol particles can travel up to a distance of 28 feet (or 8 m); however, such aerosol particles are less likely to have sufficient quantities of viable viruses to spread infection. Additionally, nearly all the experimental models examined the behavior of the aerosols only in confined spaces, not in open areas; these findings, therefore, cannot be considered generally applicable. In the absence of scientific information and education, only misconceptions, unfounded fears, and unsubstantiated myths will prevail. Given that an effective vaccine and drugs are still not available, prevention remains the only option of protection against SARS-CoV-2, the new coronavirus. Wearing a mask is not only necessary but also critical to reduce the probability of viral spread by contact (fomite), not aerosol, transmission.
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44
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Beggs CB, Avital EJ. A psychrometric model to assess the biological decay of the SARS-CoV-2 virus in aerosols. PeerJ 2021; 9:e11024. [PMID: 33717712 PMCID: PMC7934646 DOI: 10.7717/peerj.11024] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/08/2021] [Indexed: 12/21/2022] Open
Abstract
There is increasing evidence that the 2020 COVID-19 pandemic has been influenced by variations in air temperature and humidity. However, the impact that these environmental parameters have on survival of the SARS-CoV-2 virus has not been fully characterised. Therefore, an analytical study was undertaken using published data to develop a psychrometric model to assess the biological decay rate of the virus in aerosols. This revealed that it is possible to describe with reasonable accuracy (R 2 = 0.718, p < 0.001) the biological decay constant for the SARS-CoV-2 virus using a regression model with enthalpy, vapour pressure and specific volume as predictors. Applying this to historical meteorological data from London, Paris and Milan over the pandemic period, produced results which indicate that the average half-life of the virus in aerosols outdoors was in the region 13-22 times longer in March 2020, when the outbreak was accelerating, than it was in August 2020 when epidemic in Europe was at its nadir. However, indoors, this variation is likely to be much less. As such, this suggests that changes in virus survivability due the variations in the psychrometric qualities of the air might influence the transmission of SARS-CoV-2.
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Affiliation(s)
- Clive B. Beggs
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK
| | - Eldad J. Avital
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
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45
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Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand. Nat Commun 2021; 12:1001. [PMID: 33579926 PMCID: PMC7881137 DOI: 10.1038/s41467-021-21157-9] [Citation(s) in RCA: 211] [Impact Index Per Article: 70.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/13/2021] [Indexed: 02/08/2023] Open
Abstract
Stringent nonpharmaceutical interventions (NPIs) such as lockdowns and border closures are not currently recommended for pandemic influenza control. New Zealand used these NPIs to eliminate coronavirus disease 2019 during its first wave. Using multiple surveillance systems, we observed a parallel and unprecedented reduction of influenza and other respiratory viral infections in 2020. This finding supports the use of these NPIs for controlling pandemic influenza and other severe respiratory viral threats. New Zealand has been relatively successful in controlling COVID-19 due to implementation of strict non-pharmaceutical interventions. Here, the authors demonstrate a striking decline in reports of influenza and other non-influenza respiratory pathogens over winter months in which the interventions have been in place.
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46
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Dash SP, Dipankar P, Burange PS, Rouse BT, Sarangi PP. Climate change: how it impacts the emergence, transmission, resistance and consequences of viral infections in animals and plants. Crit Rev Microbiol 2021; 47:307-322. [PMID: 33570448 DOI: 10.1080/1040841x.2021.1879006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The ongoing COVID-19 pandemic has made us wonder what led to its occurrence and what can be done to avoid such events in the future. As we document, one changing circumstance that is resulting in the emergence and changing the expression of viral diseases in both plants and animals is climate change. Of note, the rapidly changing environment and weather conditions such as excessive flooding, droughts, and forest fires have raised concerns about the global ecosystem's security, sustainability, and balance. In this review, we discuss the main consequences of climate change and link these to how they impact the appearance of new viral pathogens, how they may facilitate transmission between usual and novel hosts, and how they may also affect the host's ability to manage the infection. We emphasize how changes in temperature and humidity and other events associated with climate change influence the reservoirs of viral infections, their transmission by insects and other intermediates, their survival outside the host as well the success of infection in plants and animals. We conclude that climate change has mainly detrimental consequences for the emergence, transmission, and outcome of viral infections and plead the case for halting and hopefully reversing this dangerous event.
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Affiliation(s)
- Shiba Prasad Dash
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
| | - Pankaj Dipankar
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
| | - Prasad S Burange
- Department of Entomology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Barry T Rouse
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Sciences, The University of Tennessee Knoxville, Knoxville, TN, USA
| | - Pranita P Sarangi
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
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47
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Yang XD, Li HL, Cao YE. Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:E484. [PMID: 33435301 PMCID: PMC7827058 DOI: 10.3390/ijerph18020484] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 12/29/2020] [Accepted: 12/30/2020] [Indexed: 12/23/2022]
Abstract
The purpose of this study is to investigate whether the relationship between meteorological factors (i.e., daily maximum temperature, minimum temperature, average temperature, temperature range, relative humidity, average wind speed and total precipitation) and COVID-19 transmission is affected by season and geographical location during the period of community-based pandemic prevention and control. COVID-19 infected case records and meteorological data in four cities (Wuhan, Beijing, Urumqi and Dalian) in China were collected. Then, the best-fitting model of COVID-19 infected cases was selected from four statistic models (Gaussian, logistic, lognormal distribution and allometric models), and the relationship between meteorological factors and COVID-19 infected cases was analyzed using multiple stepwise regression and Pearson correlation. The results showed that the lognormal distribution model was well adapted to describing the change of COVID-19 infected cases compared with other models (R2 > 0.78; p-values < 0.001). Under the condition of implementing community-based pandemic prevention and control, relationship between COVID-19 infected cases and meteorological factors differed among the four cities. Temperature and relative humidity were mainly the driving factors on COVID-19 transmission, but their relations obviously varied with season and geographical location. In summer, the increase in relative humidity and the decrease in maximum temperature facilitate COVID-19 transmission in arid inland cities, while at this point the decrease in relative humidity is good for the spread of COVID-19 in coastal cities. For the humid cities, the reduction of relative humidity and the lowest temperature in the winter promote COVID-19 transmission.
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Affiliation(s)
- Xiao-Dong Yang
- Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo 315211, China; (X.-D.Y.); (H.-L.L.)
- Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo 315211, China
| | - Hong-Li Li
- Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo 315211, China; (X.-D.Y.); (H.-L.L.)
- Institute of East China Sea, Ningbo University, Ningbo 315211, China
| | - Yue-E Cao
- School of Environmental and Geographical Science, Shanghai Normal University, Shanghai 200234, China
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48
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Raines KS, Doniach S, Bhanot G. The transmission of SARS-CoV-2 is likely comodulated by temperature and by relative humidity. PLoS One 2021. [PMID: 34324570 DOI: 10.1101/2020.05.23.20111278] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023] Open
Abstract
Inferring the impact of climate upon the transmission of SARS-CoV-2 has been confounded by variability in testing, unknown disease introduction rates, and changing weather. Here we present a data model that accounts for dynamic testing rates and variations in disease introduction rates. We apply this model to data from Colombia, whose varied and seasonless climate, central port of entry, and swift, centralized response to the COVID-19 pandemic present an opportune environment for assessing the impact of climate factors on the spread of COVID-19. We observe strong attenuation of transmission in climates with sustained daily temperatures above 30 degrees Celsius and simultaneous mean relative humidity below 78%, with outbreaks occurring at high humidity even where the temperature is high. We hypothesize that temperature and relative humidity comodulate the infectivity of SARS-CoV-2 within respiratory droplets.
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Affiliation(s)
| | - Sebastian Doniach
- Applied Physics, Stanford University, Stanford, CA, United States of America
| | - Gyan Bhanot
- Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ, United States of America
- Physics and Astronomy, Rutgers University, Piscataway, NJ, United States of America
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States of America
- School of Medicine, University of California San Diego, La Jolla, CA, United States of America
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49
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Slusky DJG, Zeckhauser RJ. Sunlight and Protection Against Influenza. ECONOMICS AND HUMAN BIOLOGY 2021; 40:100942. [PMID: 33340885 DOI: 10.1016/j.ehb.2020.100942] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 10/01/2020] [Accepted: 10/27/2020] [Indexed: 06/12/2023]
Abstract
Recent medical literature suggests that vitamin D supplementation protects against acute respiratory tract infection. Humans exposed to sunlight produce vitamin D directly. This paper investigates how differences in sunlight, as measured over several years across states and during the same calendar week, affect influenza incidence. We find that sunlight strongly protects against getting influenza. This relationship is driven almost entirely by the severe H1N1 epidemic in fall 2009. A 10% increase in relative sunlight decreases the influenza index in September or October by 1.1 points on a 10-point scale. A second, complementary study employs a separate data set to study flu incidence in counties in New York State. The results are strongly in accord.
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Affiliation(s)
- David J G Slusky
- Department of Economics, University of Kansas, 1460 Jayhawk Blvd., 415 Snow Hall, Lawrence, KS, 66045, United States.
| | - Richard J Zeckhauser
- Harvard Kennedy School, Harvard University, 79 JFK St, Cambridge, MA, 02138, United States.
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50
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Hochman A, Alpert P, Negev M, Abdeen Z, Abdeen AM, Pinto JG, Levine H. The relationship between cyclonic weather regimes and seasonal influenza over the Eastern Mediterranean. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 750:141686. [PMID: 32861075 PMCID: PMC7422794 DOI: 10.1016/j.scitotenv.2020.141686] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 07/30/2020] [Accepted: 08/11/2020] [Indexed: 05/21/2023]
Abstract
The prediction of the occurrence of infectious diseases is of crucial importance for public health, as clearly seen in the ongoing COVID-19 pandemic. Here, we analyze the relationship between the occurrence of a winter low-pressure weather regime - Cyprus Lows - and the seasonal Influenza in the Eastern Mediterranean. We find that the weekly occurrence of Cyprus Lows is significantly correlated with clinical seasonal Influenza in Israel in recent years (R = 0.91; p < .05). This result remains robust when considering a complementary analysis based on Google Trends data for Israel, the Palestinian Authority and Jordan. The weekly occurrence of Cyprus Lows precedes the onset and maximum of Influenza occurrence by about one to two weeks (R = 0.88; p < .05 for the maximum occurrence), and closely follows their timing in eight out of ten years (2008-2017). Since weather regimes such as Cyprus Lows are more robustly predicted in weather and climate models than individual climate variables, we conclude that the weather regime approach can be used to develop tools for estimating the compatibility of the transmission environment for Influenza occurrence in a warming world. Furthermore, this approach may be applied to other regions and climate sensitive diseases. This study is a new cross-border inter-disciplinary regional collaboration for appropriate adaptation to climate change in the Eastern Mediterranean.
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Affiliation(s)
- Assaf Hochman
- Department of Tropospheric Research, Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Eggenstein - Leopoldshafen 76344, Germany.
| | - Pinhas Alpert
- Department of Geophysics, Porter School of the Environment and Earth Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Maya Negev
- School of Public Health, University of Haifa, Mt. Carmel 3498838, Israel
| | - Ziad Abdeen
- Al-Quds Public Health Society and the Al-Quds Nutrition and Health Research Institute, Faculty of Medicine-Al-Quds University, Abu-Deis, Palestinian Authority
| | - Abdul Mohsen Abdeen
- Al-Quds Public Health Society and the Al-Quds Nutrition and Health Research Institute, Faculty of Medicine-Al-Quds University, Abu-Deis, Palestinian Authority
| | - Joaquim G Pinto
- Department of Tropospheric Research, Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Eggenstein - Leopoldshafen 76344, Germany
| | - Hagai Levine
- Braun School of Public Health and Community Medicine, Hadassah - Hebrew University, Jerusalem 9110202, Israel
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