451
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Assessment of Epidemiological Determinants of COVID-19 Pandemic Related to Social and Economic Factors Globally. JOURNAL OF RISK AND FINANCIAL MANAGEMENT 2020. [DOI: 10.3390/jrfm13090194] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The COVID-19 pandemic has manifested more than a health crisis and has severely impacted on social, economic, and development crises in the world. The relationship of COVID-19 with countries’ economic and other demographic statuses is an important criterion with which to assess the impact of this current outbreak. Based on available data from the online platform, we tested the hypotheses of a country’s economic status, population density, the median age of the population, and urbanization pattern influence on the test, attack, case fatality, and recovery rates of COVID-19. We performed correlation and multivariate multinomial regression analysis with relative risk ratio (RRR) to test the hypotheses. The correlation analysis showed that population density and test rate had a significantly negative association (r = −0.2384, p = 0.00). In contrast, the median age had a significant positive correlation with recovery rate (r = 0.4654, p = 0.00) and case fatality rate (r = 0.2847, p = 0.00). The urban population rate had a positive significant correlation with recovery rate (r = 0.1610, p = 0.04). Lower-middle-income countries had a negative significant correlation with case fatality rate (r= −0.3310, p = 0.04). The multivariate multinomial logistic regression analysis revealed that low-income countries are more likely to have an increased risk of case fatality rate (RRR = 0.986, 95% Confidence Interval; CI = 0.97−1.00, p < 0.05) and recovery rate (RRR = 0.967, 95% CI = 0.95–0.98, p = 0.00). The lower-income countries are more likely to have a higher risk in case of attack rate (RRR = 0.981, 95% CI = 0.97–0.99, p = 0.00) and recovery rate (RRR = 0.971, 95% CI = 0.96–0.98, p = 0.00). Similarly, upper middle-income countries are more likely to have higher risk in case of attack rate (RRR = 0.988, 95% CI = 0.98–1.0, p = 0.01) and recovery rate (RRR = 0.978, 95% CI = 0.97–0.99, p = 0.00). The low- and lower-middle-income countries should invest more in health care services and implement adequate COVID-19 preventive measures to reduce the risk burden. We recommend a participatory, whole-of-government and whole-of-society approach for responding to the socio-economic challenges of COVID-19 and ensuring more resilient and robust health systems to safeguard against preventable deaths and poverty by improving public health outcomes.
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452
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Jayaweera M, Perera H, Gunawardana B, Manatunge J. Transmission of COVID-19 virus by droplets and aerosols: A critical review on the unresolved dichotomy. ENVIRONMENTAL RESEARCH 2020; 188:109819. [PMID: 32569870 PMCID: PMC7293495 DOI: 10.1016/j.envres.2020.109819] [Citation(s) in RCA: 649] [Impact Index Per Article: 129.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/01/2020] [Accepted: 06/10/2020] [Indexed: 05/07/2023]
Abstract
The practice of social distancing and wearing masks has been popular worldwide in combating the contraction of COVID-19. Undeniably, although such practices help control the COVID-19 pandemic to a greater extent, the complete control of virus-laden droplet and aerosol transmission by such practices is poorly understood. This review paper intends to outline the literature concerning the transmission of virus-laden droplets and aerosols in different environmental settings and demonstrates the behavior of droplets and aerosols resulted from a cough-jet of an infected person in various confined spaces. The case studies that have come out in different countries have, with prima facie evidence, manifested that the airborne transmission plays a profound role in contracting susceptible hosts. The infection propensities in confined spaces (airplane, passenger car, and healthcare center) by the transmission of droplets and aerosols under varying ventilation conditions were discussed. Interestingly, the nosocomial transmission by airborne SARS-CoV-2 virus-laden aerosols in healthcare facilities may be plausible. Hence, clearly defined, science-based administrative, clinical, and physical measures are of paramount importance to eradicate the COVID-19 pandemic from the world.
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Affiliation(s)
- Mahesh Jayaweera
- Department of Civil Engineering, University of Moratuwa, Sri Lanka.
| | - Hasini Perera
- Department of Forestry and Environmental Science, University of Sri Jayewardenepura, Sri Lanka
| | | | - Jagath Manatunge
- Department of Civil Engineering, University of Moratuwa, Sri Lanka
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453
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Sarmadi M, Marufi N, Kazemi Moghaddam V. Association of COVID-19 global distribution and environmental and demographic factors: An updated three-month study. ENVIRONMENTAL RESEARCH 2020; 188:109748. [PMID: 32516636 PMCID: PMC7258807 DOI: 10.1016/j.envres.2020.109748] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/18/2020] [Accepted: 05/26/2020] [Indexed: 05/05/2023]
Abstract
We investigated the association of some environmental and economic factors and the global distribution indicators of the COVID-19 pandemic. Since the number of cases and deaths is higher in high-income countries located in higher latitudes and colder climates, further studies are required to shed light on this matter.
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Affiliation(s)
- Mohammad Sarmadi
- Department of Environmental Health Engineering, School of Health, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran; Health Sciences Research Center, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
| | - Nilufar Marufi
- Students Research Committee, Neyshabur University of Medical Sciences, Neyshabur, Iran
| | - Vahid Kazemi Moghaddam
- Department of Environmental Health, Neyshabur University of Medical Sciences, Neyshabur, Iran.
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454
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Wei JT, Liu YX, Zhu YC, Qian J, Ye RZ, Li CY, Ji XK, Li HK, Qi C, Wang Y, Yang F, Zhou YH, Yan R, Cui XM, Liu YL, Jia N, Li SX, Li XJ, Xue FZ, Zhao L, Cao WC. Impacts of transportation and meteorological factors on the transmission of COVID-19. Int J Hyg Environ Health 2020; 230:113610. [PMID: 32896785 PMCID: PMC7448770 DOI: 10.1016/j.ijheh.2020.113610] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 08/03/2020] [Accepted: 08/21/2020] [Indexed: 12/20/2022]
Abstract
The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease.
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Affiliation(s)
- Jia-Te Wei
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Yun-Xia Liu
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Yu-Chen Zhu
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Jie Qian
- School of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Run-Ze Ye
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Chun-Yu Li
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Xiao-Kang Ji
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Hong-Kai Li
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Chang Qi
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Ying Wang
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Fan Yang
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Yu-Hao Zhou
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China
| | - Ran Yan
- Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Xiao-Ming Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China
| | - Yuan-Li Liu
- School of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Na Jia
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China
| | - Shi-Xue Li
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China; Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Xiu-Jun Li
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China; Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China
| | - Fu-Zhong Xue
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China; Institute for Medical Dataology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China.
| | - Lin Zhao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China.
| | - Wu-Chun Cao
- Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, PR China; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China.
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455
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Alkhowailed M, Shariq A, Alqossayir F, Alzahrani OA, Rasheed Z, Al Abdulmonem W. Impact of meteorological parameters on COVID-19 pandemic: A comprehensive study from Saudi Arabia. INFORMATICS IN MEDICINE UNLOCKED 2020; 20:100418. [PMID: 32875061 PMCID: PMC7453268 DOI: 10.1016/j.imu.2020.100418] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 08/21/2020] [Accepted: 08/24/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The Coronavirus disease 2019 (COVID-19) has now been declared a global public health disaster with no currently available vaccine. This study was undertaken to analyse the effect of meteorological parameters such as temperature, humidity, and wind speed on the spread of ongoing COVID-19 in Saudi Arabia. METHODS The COVID-19 dashboard for five major cities of Saudi Arabia - Riyadh, Makah, Jeddah, Medina and Dammam was used for data collection. The data on weather were collected from the Weather Underground Company (IBM business GA, USA, 2020). The data were analysed by Spearman's rank correlations using JASP statistical software in two main sections. In the first section the data on COVID-19 from cities were combined to analyse the overall picture of COVID-19 and in the second section, different meteorological parameters such as temperature, humidity and wind speed were analysed. RESULTS Novel data revealed interesting facts on the spreading of COVID-19 in Saudi Arabia, the data showed that the number of COVID-19 positive cases increases due to the decrease of temperature or humidity, whereas an average decrease in the wind speed was also found to be associated with an elevation of the number of positive cases. CONCLUSIONS This study determined the impact meteorological factors on the infectivity rate of COVID-19. An inverse association was found between the meteorological parameters with the spreading of COIVD-19. Therefore, this study directs the health authorities to implement specific measures against the spreading of this global pandemic based on weather patterns.
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Affiliation(s)
- Mohammad Alkhowailed
- Department of Dermatology, College of Medicine, Qassim University, Buraidah, Qassim, Saudi Arabia
| | - Ali Shariq
- Department of Microbiology, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Fuhaid Alqossayir
- Department of Family and Community Medicine, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | | | - Zafar Rasheed
- Department of Medical Biochemistry, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Waleed Al Abdulmonem
- Department of Pathology, College of Medicine, Qassim University, Buraidah, Saudi Arabia
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456
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Jamil T, Alam I, Gojobori T, Duarte CM. No Evidence for Temperature-Dependence of the COVID-19 Epidemic. Front Public Health 2020; 8:436. [PMID: 32984240 PMCID: PMC7479095 DOI: 10.3389/fpubh.2020.00436] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 07/16/2020] [Indexed: 12/24/2022] Open
Abstract
The pandemic of the COVID-19 extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. The hypothesis that COVID-19 spread is temperature-dependent was tested based on data derived from nations across the world and provinces in China. No evidence of a pattern between spread rates and ambient temperature was found, suggesting that the SARS-CoV-2 is unlikely to behave as a seasonal respiratory virus.
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Affiliation(s)
- Tahira Jamil
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.,Red Sea Research Centre (RSRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Intikhab Alam
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Takashi Gojobori
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Carlos M Duarte
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.,Red Sea Research Centre (RSRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
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457
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Zhao ZY, Zhu YZ, Xu JW, Hu SX, Hu QQ, Lei Z, Rui J, Liu XC, Wang Y, Yang M, Luo L, Yu SS, Li J, Liu RY, Xie F, Su YY, Chiang YC, Zhao BH, Cui JA, Yin L, Su YH, Zhao QL, Gao LD, Chen TM. A five-compartment model of age-specific transmissibility of SARS-CoV-2. Infect Dis Poverty 2020; 9:117. [PMID: 32843094 PMCID: PMC7447599 DOI: 10.1186/s40249-020-00735-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 08/05/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. METHODS An epidemiological model with five compartments (susceptible-exposed-symptomatic-asymptomatic-recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. RESULTS The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: β43 = 7.71 × 10- 9; SAR43 = 3.86 × 10- 8), followed by group 3 to 4 (median: β34 = 3.07 × 10- 9; SAR34 = 1.53 × 10- 8), group 2 to 2 (median: β22 = 1.24 × 10- 9; SAR22 = 6.21 × 10- 9), and group 3 to 1 (median: β31 = 4.10 × 10- 10; SAR31 = 2.08 × 10- 9). The lowest transmissibility was from age group 3 to 3 (median: β33 = 1.64 × 10- 19; SAR33 = 8.19 × 10- 19), followed by group 4 to 4 (median: β44 = 3.66 × 10- 17; SAR44 = 1.83 × 10- 16), group 3 to 2 (median: β32 = 1.21 × 10- 16; SAR32 = 6.06 × 10- 16), and group 1 to 4 (median: β14 = 7.20 × 10- 14; SAR14 = 3.60 × 10- 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: β43 = 4.27 × 10- 8; SAR43 = 2.13 × 10- 7), followed by group 3 to 4 (median: β34 = 1.81 × 10- 8; SAR34 = 9.03 × 10- 8). CONCLUSIONS SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.
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Affiliation(s)
- Ze-Yu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Yuan-Zhao Zhu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Jing-Wen Xu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Shi-Xiong Hu
- Hunan Provincial Center for Disease Control and Prevention, 405 Furong Middle Road Section One, Kaifu District, Changsha City, 410001 Hunan Province People’s Republic of China
| | - Qing-Qing Hu
- Division of Public Health, School of Medicine, University of Utah, 201 Presidents Circle, Salt Lake City, UT 84112 USA
| | - Zhao Lei
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Xing-Chun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Yao Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Meng Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Li Luo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Shan-Shan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Jia Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Ruo-Yun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Fang Xie
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Ying-Ying Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Ben-Hua Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Jing-An Cui
- Department of Mathematics, School of Science, Beijing University of Civil Engineering and Architecture, Beijing, People’s Republic of China
| | - Ling Yin
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province People’s Republic of China
| | - Yan-Hua Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
| | - Qing-Long Zhao
- Jilin Provincial Center for Disease Control and Prevention, 3145 Jingyang Big Road, Lvyuan District, Changchun, 130062 Jilin Province People’s Republic of China
| | - Li-Dong Gao
- Hunan Provincial Center for Disease Control and Prevention, 405 Furong Middle Road Section One, Kaifu District, Changsha City, 410001 Hunan Province People’s Republic of China
| | - Tian-Mu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang’an Road, Xiang’an District, Xiamen City, 361102 Fujian Province People’s Republic of China
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458
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Association of Environmental Parameters with COVID-19 in Delhi, India. Indian J Clin Biochem 2020; 35:497-501. [PMID: 32837037 PMCID: PMC7436072 DOI: 10.1007/s12291-020-00921-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/11/2020] [Indexed: 12/24/2022]
Abstract
The present study explores the association between weather and COVID-19 pandemic in Delhi, India. The study used the data from daily newspaper releases from the Ministry of Health and Family Welfare, Government of India. Linear regression was run to understand the effect of the number of tests, temperature, and relative humidity on the number of COVID-19 cases in Delhi. The model was significantly able to predict number of COVID-19 cases, F (4,56) = 1213.61, p < 0.05, accounting for 99.4% of the variation in COVID-19 cases with adjusted R2 = 98.8%. Maximum Temperature, average temperature and average relative humidity did not show statistical significance. The only number of tests was significantly associated with COVID-19 cases.
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459
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Wu Y, Jing W, Liu J, Ma Q, Yuan J, Wang Y, Du M, Liu M. Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 729:139051. [PMID: 32361460 PMCID: PMC7187824 DOI: 10.1016/j.scitotenv.2020.139051] [Citation(s) in RCA: 366] [Impact Index Per Article: 73.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 04/25/2020] [Accepted: 04/26/2020] [Indexed: 04/13/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic is the defining global health crisis of our time and the greatest challenge facing the world. Meteorological parameters are reportedly crucial factors affecting respiratory infectious disease epidemics; however, the effect of meteorological parameters on COVID-19 remains controversial. This study investigated the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, which has useful implications for policymakers and the public. Daily data on meteorological conditions, new cases and new deaths of COVID-19 were collected for 166 countries (excluding China) as of March 27, 2020. Log-linear generalized additive model was used to analyze the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, with potential confounders controlled for, including wind speed, median age of the national population, Global Health Security Index, Human Development Index and population density. Our findings revealed that temperature and relative humidity were both negatively related to daily new cases and deaths. A 1 °C increase in temperature was associated with a 3.08% (95% CI: 1.53%, 4.63%) reduction in daily new cases and a 1.19% (95% CI: 0.44%, 1.95%) reduction in daily new deaths, whereas a 1% increase in relative humidity was associated with a 0.85% (95% CI: 0.51%, 1.19%) reduction in daily new cases and a 0.51% (95% CI: 0.34%, 0.67%) reduction in daily new deaths. The results remained robust when different lag structures and the sensitivity analysis were used. These findings provide preliminary evidence that the COVID-19 pandemic may be partially suppressed with temperature and humidity increases. However, active measures must be taken to control the source of infection, block transmission and prevent further spread of COVID-19.
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Affiliation(s)
- Yu Wu
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Wenzhan Jing
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Jue Liu
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Qiuyue Ma
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Jie Yuan
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Yaping Wang
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Min Du
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Min Liu
- Department of Epidemiology and Biostatics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China.
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460
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Auler AC, Cássaro FAM, da Silva VO, Pires LF. Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: A case study for the most affected Brazilian cities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 729:139090. [PMID: 32388137 PMCID: PMC7194794 DOI: 10.1016/j.scitotenv.2020.139090] [Citation(s) in RCA: 141] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 04/27/2020] [Accepted: 04/27/2020] [Indexed: 04/13/2023]
Abstract
This study aimed to analyze how meteorological conditions such as temperature, humidity and rainfall can affect the spread of COVID-19 in five Brazilian (São Paulo, Rio de Janeiro, Brasília, Manaus and Fortaleza) cities. The cities selected were those with the largest number of confirmed cases considering data of April 13. Variables such as number of cumulative cases, new daily cases and contamination rate were employed for this study. Our results showed that higher mean temperatures and average relative humidity favored the COVID-19 transmission, differently from reports from coldest countries or periods of time under cool temperatures. Thus, considering the results obtained, intersectoral policies and actions are necessary, mainly in cities where the contamination rate is increasing rapidly. Thus, prevention and protection measures should be adopted in these cities aiming to reduce transmission and the possible collapse of the health system.
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Affiliation(s)
- A C Auler
- Department of Soil Science and Rural Engineering, Federal University of Paraná, 80.035-050 Curitiba, PR, Brazil
| | - F A M Cássaro
- Laboratory of Physics Applied to Soils and Environmental Sciences, Department of Physics, State University of Ponta Grossa, 84.030-900 Ponta Grossa, PR, Brazil
| | - V O da Silva
- Chamber of Public Health, Federal University of Paraná, 83.260-000 Matinhos, PR, Brazil
| | - L F Pires
- Laboratory of Physics Applied to Soils and Environmental Sciences, Department of Physics, State University of Ponta Grossa, 84.030-900 Ponta Grossa, PR, Brazil.
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461
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Prata DN, Rodrigues W, Bermejo PH. Temperature significantly changes COVID-19 transmission in (sub)tropical cities of Brazil. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 729:138862. [PMID: 32361443 PMCID: PMC7182516 DOI: 10.1016/j.scitotenv.2020.138862] [Citation(s) in RCA: 256] [Impact Index Per Article: 51.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 04/18/2020] [Accepted: 04/19/2020] [Indexed: 04/13/2023]
Abstract
The coronavirus disease 2019 (COVID-19) outbreak has become a severe public health issue. The novelty of the virus prompts a search for understanding of how ecological factors affect the transmission and survival of the virus. Several studies have robustly identified a relationship between temperature and the number of cases. However, there is no specific study for a tropical climate such as Brazil. This work aims to determine the relationship of temperature to COVID-19 infection for the state capital cities of Brazil. Cumulative data with the daily number of confirmed cases was collected from February 27 to April 1, 2020, for all 27 state capital cities of Brazil affected by COVID-19. A generalized additive model (GAM) was applied to explore the linear and nonlinear relationship between annual average temperature compensation and confirmed cases. Also, a polynomial linear regression model was proposed to represent the behavior of the growth curve of COVID-19 in the capital cities of Brazil. The GAM dose-response curve suggested a negative linear relationship between temperatures and daily cumulative confirmed cases of COVID-19 in the range from 16.8 °C to 27.4 °C. Each 1 °C rise of temperature was associated with a -4.8951% (t = -2.29, p = 0.0226) decrease in the number of daily cumulative confirmed cases of COVID-19. A sensitivity analysis assessed the robustness of the results of the model. The predicted R-squared of the polynomial linear regression model was 0.81053. In this study, which features the tropical temperatures of Brazil, the variation in annual average temperatures ranged from 16.8 °C to 27.4 °C. Results indicated that temperatures had a negative linear relationship with the number of confirmed cases. The curve flattened at a threshold of 25.8 °C. There is no evidence supporting that the curve declined for temperatures above 25.8 °C. The study had the goal of supporting governance for healthcare policymakers.
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Affiliation(s)
- David N Prata
- Institute of Regional Development, Graduate Program of Computational Modelling, Federal Univeristy of Tocantins. Quadra 109 Norte, 77001-090 Palmas, TO, Brazil.
| | - Waldecy Rodrigues
- Institute of Regional Development, Graduate Program of Computational Modelling, Federal Univeristy of Tocantins. Quadra 109 Norte, 77001-090 Palmas, TO, Brazil
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462
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Iqbal N, Fareed Z, Shahzad F, He X, Shahzad U, Lina M. The nexus between COVID-19, temperature and exchange rate in Wuhan city: New findings from partial and multiple wavelet coherence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 729:138916. [PMID: 32388129 PMCID: PMC7194511 DOI: 10.1016/j.scitotenv.2020.138916] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 04/20/2020] [Accepted: 04/21/2020] [Indexed: 04/13/2023]
Abstract
This study attempts to document the nexus between weather, COVID-19 outbreak in Wuhan and the Chinese economy. We used daily average temperature (hourly data), daily new confirmed cases of COVID-19 in Wuhan, and RMB (Chinese currency) exchange rate to represent the weather, COVID-19 outbreak and the Chinese economy, respectively. The methodology of Wavelet Transform Coherence (WTC), Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) is employed to analyze the daily data collected from 21st January 2020 to 31st March 2020. The results have revealed a significant coherence between the series at different time-frequency combinations. The overall results suggest the insignificance of an increase in temperature to contain or slow down the new COVID-19 infections. The RMB exchange rate and the COVID-19 showed an out phase coherence at specific time-frequency spots suggesting a negative but limited impact of the COVID-19 outbreak in Wuhan on the Chinese export economy. Our results are contrary to many earlier studies which suggest a significant role of temperature in slowing down the COVID-19 spread. These results can have important policy implications for the containment of COVID-19 spread and macro-economic management with respect to changes in the weather.
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Affiliation(s)
- Najaf Iqbal
- College of Economics and Management, Hunan University of Arts and Science, Changde, China; Wuhan University of Technology, Wuhan, Hubei, China
| | - Zeeshan Fareed
- School of Business, Huzhou University, Huzhou, Zhejiang, China
| | - Farrukh Shahzad
- School of Economics and Management, Guangdong University of Petrochemical Technology, Guangdong, China.
| | - Xin He
- College of Economics and Management, Hunan University of Arts and Science, Changde, China
| | - Umer Shahzad
- Institute of Guangdong Economy & Social Development, Guangdong University of Finance and Economics (GDUFE), 510320, Guangzhou, P.R. China; School of Economics, Shandong University, Jinan, Shandong Province, China.
| | - Ma Lina
- Wuhan University of Technology, Wuhan, Hubei, China
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463
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Coccia M. Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 729:138474. [PMID: 32498152 PMCID: PMC7169901 DOI: 10.1016/j.scitotenv.2020.138474] [Citation(s) in RCA: 382] [Impact Index Per Article: 76.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 04/03/2020] [Indexed: 04/13/2023]
Abstract
This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats similar to COVID-19 having an accelerated viral infectivity in society. Using data on sample of N = 55 Italian province capitals, and data of infected individuals at as of April 7th, 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM10 (particulate matter 10 μm or less in diameter) or ozone. In particular, hinterland cities with average high number of days exceeding the limits set for PM10 (and also having a low wind speed) have a very high number of infected people on 7th April 2020 (arithmetic mean is about 2200 infected individuals, with average polluted days greater than 80 days per year), whereas coastal cities also having days exceeding the limits set for PM10 or ozone but with high wind speed have about 944.70 average infected individuals, with about 60 average polluted days per year; moreover, cities having more than 100 days of air pollution (exceeding the limits set for PM10), they have a very high average number of infected people (about 3350 infected individuals, 7th April 2020), whereas cities having less than 100 days of air pollution per year, they have a lower average number of infected people (about 1014 individuals). The findings here also suggest that to minimize the impact of future epidemics similar to COVID-19, the max number of days per year that Italian provincial capitals or similar industrialized cities can exceed the limits set for PM10 or for ozone, considering their meteorological conditions, is about 48 days. Moreover, results here reveal that the explanatory variable of air pollution in cities seems to be a more important predictor in the initial phase of diffusion of viral infectivity (on 17th March 2020, b1 = 1.27, p < 0.001) than interpersonal contacts (b2 = 0.31, p < 0.05). In the second phase of maturity of the transmission dynamics of COVID-19, air pollution reduces intensity (on 7th April 2020 with b'1 = 0.81, p < 0.001) also because of the indirect effect of lockdown, whereas regression coefficient of transmission based on interpersonal contacts has a stable level (b'2 = 0.31, p < 0.01). This result reveals that accelerated transmission dynamics of COVID-19 is due to mainly to the mechanism of "air pollution-to-human transmission" (airborne viral infectivity) rather than "human-to-human transmission". Overall, then, transmission dynamics of viral infectivity, such as COVID-19, is due to systemic causes: general factors that are the same for all regions (e.g., biological characteristics of virus, incubation period, etc.) and specific factors which are different for each region and/or city (e.g., complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity) and health level of individuals (habits, immune system, age, sex, etc.). Lessons learned for COVID-19 in the case study here suggest that a proactive strategy to cope with future epidemics is also to apply especially an environmental and sustainable policy based on reduction of levels of air pollution mainly in hinterland and polluting cities- (having low wind speed, high percentage of moisture and number of fog days) -that seem to have an environment that foster a fast transmission dynamics of viral infectivity in society. Hence, in the presence of polluting industrialization in regions that can trigger the mechanism of air pollution-to-human transmission dynamics of viral infectivity, this study must conclude that a comprehensive strategy to prevent future epidemics similar to COVID-19 has to be also designed in environmental and socioeconomic terms, that is also based on sustainability science and environmental science, and not only in terms of biology, medicine, healthcare and health sector.
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Affiliation(s)
- Mario Coccia
- CNR - National Research Council of Italy, Research Institute on Sustainable Economic Growth, Collegio Carlo Alberto, Via Real Collegio, 30-10024 Moncalieri, Torino, Italy; Yale School of Medicine, 310 Cedar Street, Lauder Hall, New Haven, CT 06510, USA.
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464
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Smit AJ, Fitchett JM, Engelbrecht FA, Scholes RJ, Dzhivhuho G, Sweijd NA. Winter Is Coming: A Southern Hemisphere Perspective of the Environmental Drivers of SARS-CoV-2 and the Potential Seasonality of COVID-19. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E5634. [PMID: 32764257 PMCID: PMC7459895 DOI: 10.3390/ijerph17165634] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 07/29/2020] [Accepted: 07/31/2020] [Indexed: 01/09/2023]
Abstract
SARS-CoV-2 virus infections in humans were first reported in December 2019, the boreal winter. The resulting COVID-19 pandemic was declared by the WHO in March 2020. By July 2020, COVID-19 was present in 213 countries and territories, with over 12 million confirmed cases and over half a million attributed deaths. Knowledge of other viral respiratory diseases suggests that the transmission of SARS-CoV-2 could be modulated by seasonally varying environmental factors such as temperature and humidity. Many studies on the environmental sensitivity of COVID-19 are appearing online, and some have been published in peer-reviewed journals. Initially, these studies raised the hypothesis that climatic conditions would subdue the viral transmission rate in places entering the boreal summer, and that southern hemisphere countries would experience enhanced disease spread. For the latter, the COVID-19 peak would coincide with the peak of the influenza season, increasing misdiagnosis and placing an additional burden on health systems. In this review, we assess the evidence that environmental drivers are a significant factor in the trajectory of the COVID-19 pandemic, globally and regionally. We critically assessed 42 peer-reviewed and 80 preprint publications that met qualifying criteria. Since the disease has been prevalent for only half a year in the northern, and one-quarter of a year in the southern hemisphere, datasets capturing a full seasonal cycle in one locality are not yet available. Analyses based on space-for-time substitutions, i.e., using data from climatically distinct locations as a surrogate for seasonal progression, have been inconclusive. The reported studies present a strong northern bias. Socio-economic conditions peculiar to the 'Global South' have been omitted as confounding variables, thereby weakening evidence of environmental signals. We explore why research to date has failed to show convincing evidence for environmental modulation of COVID-19, and discuss directions for future research. We conclude that the evidence thus far suggests a weak modulation effect, currently overwhelmed by the scale and rate of the spread of COVID-19. Seasonally modulated transmission, if it exists, will be more evident in 2021 and subsequent years.
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Affiliation(s)
- Albertus J. Smit
- Department of Biodiversity and Conservation Biology, University of the Western Cape, Cape Town 7535, South Africa
- Elwandle Coastal Node, South African Environmental Observation Network (SAEON), Port Elizabeth 6031, South Africa
| | - Jennifer M. Fitchett
- School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South Africa;
| | - Francois A. Engelbrecht
- Global Change Institute, University of the Witwatersrand, Johannesburg 2050, South Africa; (F.A.E.); (R.J.S.)
| | - Robert J. Scholes
- Global Change Institute, University of the Witwatersrand, Johannesburg 2050, South Africa; (F.A.E.); (R.J.S.)
| | - Godfrey Dzhivhuho
- Department of Microbiology, Immunology and Cancer Biology, Myles H. Thaler Center for AIDS and Human Retrovirus Research, University of Virginia, Charlottesville, VA 22903, USA;
| | - Neville A. Sweijd
- Alliance for Collaboration on Climate and Earth Systems Science (ACCESS), Council for Scientific and Industrial Research (CSIR), Pretoria 0001, South Africa;
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465
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Agapito G, Zucco C, Cannataro M. COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E5596. [PMID: 32756428 PMCID: PMC7432400 DOI: 10.3390/ijerph17155596] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/19/2020] [Accepted: 07/24/2020] [Indexed: 01/23/2023]
Abstract
The management of the COVID-19 pandemic presents several unprecedented challenges in different fields, from medicine to biology, from public health to social science, that may benefit from computing methods able to integrate the increasing available COVID-19 and related data (e.g., pollution, demographics, climate, etc.). With the aim to face the COVID-19 data collection, harmonization and integration problems, we present the design and development of COVID-WAREHOUSE, a data warehouse that models, integrates and stores the COVID-19 data made available daily by the Italian Protezione Civile Department and several pollution and climate data made available by the Italian Regions. After an automatic ETL (Extraction, Transformation and Loading) step, COVID-19 cases, pollution measures and climate data, are integrated and organized using the Dimensional Fact Model, using two main dimensions: time and geographical location. COVID-WAREHOUSE supports OLAP (On-Line Analytical Processing) analysis, provides a heatmap visualizer, and allows easy extraction of selected data for further analysis. The proposed tool can be used in the context of Public Health to underline how the pandemic is spreading, with respect to time and geographical location, and to correlate the pandemic to pollution and climate data in a specific region. Moreover, public decision-makers could use the tool to discover combinations of pollution and climate conditions correlated to an increase of the pandemic, and thus, they could act in a consequent manner. Case studies based on data cubes built on data from Lombardia and Puglia regions are discussed. Our preliminary findings indicate that COVID-19 pandemic is significantly spread in regions characterized by high concentration of particulate in the air and the absence of rain and wind, as even stated in other works available in literature.
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Affiliation(s)
- Giuseppe Agapito
- Department of Legal, Economic and Social Sciences, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy;
- Data Analytics Research Center, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy
| | - Chiara Zucco
- Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy;
| | - Mario Cannataro
- Data Analytics Research Center, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy
- Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy;
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466
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Barcelo D. An environmental and health perspective for COVID-19 outbreak: Meteorology and air quality influence, sewage epidemiology indicator, hospitals disinfection, drug therapies and recommendations. JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2020; 8:104006. [PMID: 32373461 PMCID: PMC7198433 DOI: 10.1016/j.jece.2020.104006] [Citation(s) in RCA: 126] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 04/27/2020] [Accepted: 04/29/2020] [Indexed: 05/17/2023]
Abstract
This Opinion Paper wishes to provide a summary of recent findings and solutions for a better understanding of the environmental and health problems associated with COVID-19. The list of topics covered is large: meteorology and air quality factors with correlation number of infections, sewage waters as a way to reveal the scale of COVID-19 outbreak, current hospital disinfection procedures and new eco-friendly technologies and list of drug therapies recommend waiting for the desired vaccine to come. During the last two months we did notice an increase in the scientific literature regarding COVID-19 with a partial vision of this problem. The current Opinion Paper is one of the first attempts, to my understanding, to summarize and integrate environmental and human health aspects related to the monitoring, fate and treatment solutions for COVID-19. That being said I believe that this Opinion Paper can serve as multipurpose document, not only for scientists of different disciplines but for social media and citizens in general.
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Affiliation(s)
- Damia Barcelo
- Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, C/Jordi Girona 18-26, 08034 Barcelona, Spain
- Catalan Institute for Water Research (ICRA), C/Emili Grahit 101, 17003 Girona, Spain
- College of Environmental and Resources Sciences, Zhejiang A&F University, Hangzhou 311300, China
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467
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Barcelo D. An environmental and health perspective for COVID-19 outbreak: Meteorology and air quality influence, sewage epidemiology indicator, hospitals disinfection, drug therapies and recommendations. JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2020; 8:104006. [PMID: 32373461 DOI: 10.1016/j/jece.2020.104006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 04/27/2020] [Accepted: 04/29/2020] [Indexed: 05/28/2023]
Abstract
This Opinion Paper wishes to provide a summary of recent findings and solutions for a better understanding of the environmental and health problems associated with COVID-19. The list of topics covered is large: meteorology and air quality factors with correlation number of infections, sewage waters as a way to reveal the scale of COVID-19 outbreak, current hospital disinfection procedures and new eco-friendly technologies and list of drug therapies recommend waiting for the desired vaccine to come. During the last two months we did notice an increase in the scientific literature regarding COVID-19 with a partial vision of this problem. The current Opinion Paper is one of the first attempts, to my understanding, to summarize and integrate environmental and human health aspects related to the monitoring, fate and treatment solutions for COVID-19. That being said I believe that this Opinion Paper can serve as multipurpose document, not only for scientists of different disciplines but for social media and citizens in general.
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Affiliation(s)
- Damia Barcelo
- Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, C/Jordi Girona 18-26, 08034 Barcelona, Spain
- Catalan Institute for Water Research (ICRA), C/Emili Grahit 101, 17003 Girona, Spain
- College of Environmental and Resources Sciences, Zhejiang A&F University, Hangzhou 311300, China
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468
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Jahangiri M, Jahangiri M, Najafgholipour M. The sensitivity and specificity analyses of ambient temperature and population size on the transmission rate of the novel coronavirus (COVID-19) in different provinces of Iran. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 728:138872. [PMID: 32335407 PMCID: PMC7194726 DOI: 10.1016/j.scitotenv.2020.138872] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 04/19/2020] [Accepted: 04/19/2020] [Indexed: 04/14/2023]
Abstract
On 10 April 2020, Iran reported 68,192 COVID-19 cumulative cases including 4232 death and 35,465 recovery cases. Numerous factors could influence the transmission rate and survival of coronavirus. On this basis and according to the latest epidemiological researches, both ambient temperature (AT) and population size (PS) can be considered as significant transmissibility factors for coronavirus. The analysis of receiver operating characteristics (ROC) allows measuring the performance of a classification model using the confusion matrix. This study intends to investigate the sensitivity of AT and PS on the transmission rate of the novel coronavirus in different provinces of Iran. For this purpose, the information of each province of Iran including the annual average of AT and the number of healthy and diseased cases are categorized. Subsequently, the sensitivity and specificity analyses of both AT and PS factors are performed. The obtained results confirm that AT and PS have low sensibility and high sensitivity, respectively. Thus, there is no scientific reason to confirm that the number of COVID-19 cases in warmer climates is less than that of moderate or cold climates. Therefore, it is recommended that the cities/provinces with a population of over 1.7 million people have stricter inspections and more precise controls as their management policy.
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Affiliation(s)
- Mehdi Jahangiri
- Department of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | - Milad Jahangiri
- Department of Civil and Environmental Engineering, Shiraz University of Technology, Shiraz, Iran..
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469
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Şahin M. Impact of weather on COVID-19 pandemic in Turkey. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 728:138810. [PMID: 32334158 PMCID: PMC7169889 DOI: 10.1016/j.scitotenv.2020.138810] [Citation(s) in RCA: 209] [Impact Index Per Article: 41.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 04/16/2020] [Accepted: 04/17/2020] [Indexed: 04/14/2023]
Abstract
The coronavirus pandemic, which has numerous global implications, has led people to believe that nothing will be the same as before. The present day is dominated by studies on determining the factors that affect, taking preventive actions, and trying to find an effective treatment on top priority. Meteorological parameters are among the crucial factors affecting infectious diseases. The present study examines the correlation between weather and coronavirus disease 2019 (COVID-19) by considering nine cities in Turkey. In this regard, temperature (°C), dew point (°C), humidity (%), and wind speed (mph) are considered as parameters of weather. Research states that the incubation period of COVID-19 varies from 1 day to 14 days. Therefore, the effects of each parameter within 1, 3, 7, and 14 days are examined. In addition, the population is included as an effective parameter for evaluation. The analyses are conducted based on Spearman's correlation coefficients. The results showed that the highest correlations were observed for population, wind speed 14 days ago, and temperature on the day, respectively. The study results may guide authorities and decision-makers on taking specific measures for the cities.
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Affiliation(s)
- Mehmet Şahin
- Department of Industrial Engineering, Iskenderun Technical University, 31200 Iskenderun, Turkey.
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470
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Das A, Ghosh S, Das K, Dutta I, Basu T, Das M. Re:(In) visible impact of inadequate WaSH Provision on COVID-19 incidences can be not be ignored in large and megacities of India. Public Health 2020; 185:34-36. [PMID: 32521329 PMCID: PMC7253972 DOI: 10.1016/j.puhe.2020.05.035] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 05/18/2020] [Indexed: 12/20/2022]
Affiliation(s)
- A Das
- Department of Geography, University of Gour Banga, Malda, India.
| | - S Ghosh
- Department of Geography, Kazi Nazrul University, Asansol, India.
| | - K Das
- Department of Geography, University of Gour Banga, Malda, India.
| | - I Dutta
- Department of Geography, University of Gour Banga, Malda, India.
| | - T Basu
- Department of Geography, University of Gour Banga, Malda, India.
| | - M Das
- Department of Geography, University of Gour Banga, Malda, India.
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471
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Adekunle IA, Tella SA, Oyesiku KO, Oseni IO. Spatio-temporal analysis of meteorological factors in abating the spread of COVID-19 in Africa. Heliyon 2020; 6:e04749. [PMID: 32835123 PMCID: PMC7434429 DOI: 10.1016/j.heliyon.2020.e04749] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/17/2020] [Accepted: 08/14/2020] [Indexed: 12/23/2022] Open
Abstract
In Asia, Europe and South America, the role of atmospheric condition in aiding or abating the growth curve of COVID-19 has been analysed. However, no study to date has examined such climatic extensions for the growth or otherwise of the novel coronavirus in Africa. Africa, with a mostly relatively warmer temperature differs from other regions of the world and in addition, has recorded far fewer cases compared to Asian, Europeans and the Americans (North and South). It then becomes imperative to examine the influence of meteorological indices in the growth or otherwise of coronavirus diseases in Africa to establish whether findings on the climatic conditions-COVID-19 growth are regionally specific. In this study, we examined the influence of meteorological factors for aiding or abating the spread of the aerosolised pathogen of COVID-19 in Africa. We rely on the generalised additive model (GAM) and found wind speed to positively relate to COVID-19 growth while mean temperature and relative humidity to inversely relates to COVID-19 growth curve in Africa. We accounted for potential cofounders in the core GAM model and discuss policy implications.
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Affiliation(s)
| | | | - Kayode O. Oyesiku
- Department of Geography, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria
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472
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Briz-Redón Á, Serrano-Aroca Á. A spatio-temporal analysis for exploring the effect of temperature on COVID-19 early evolution in Spain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 728:138811. [PMID: 32361118 PMCID: PMC7194829 DOI: 10.1016/j.scitotenv.2020.138811] [Citation(s) in RCA: 177] [Impact Index Per Article: 35.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 04/16/2020] [Accepted: 04/17/2020] [Indexed: 04/13/2023]
Abstract
The new SARS-CoV-2 coronavirus, which causes the COVID-19 disease, was reported in Wuhan, China, in December 2019. This new pathogen has spread rapidly around more than 200 countries, in which Spain has one of the world's highest mortality rates so far. Previous studies have supported an epidemiological hypothesis that weather conditions may affect the survival and spread of droplet-mediated viral diseases. However, some contradictory studies have also been reported in the same research line. In addition, many of these studies have been performed considering only meteorological factors, which can limit the reliability of the results. Herein, we report a spatio-temporal analysis for exploring the effect of daily temperature (mean, minimum and maximum) on the accumulated number of COVID-19 cases in the provinces of Spain. Non-meteorological factors such as population density, population by age, number of travellers and number of companies have also been considered for the analysis. No evidence suggesting a reduction in COVID-19 cases at warmer mean, minimum and maximum temperatures has been found. Nevertheless, these results need to be interpreted cautiously given the existing uncertainty about COVID-19 data, and should not be extrapolated to temperature ranges other than those analysed here for the early evolution period.
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Affiliation(s)
| | - Ángel Serrano-Aroca
- Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia San Vicente Mártir, Spain.
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473
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Kodera S, Rashed EA, Hirata A. Correlation between COVID-19 Morbidity and Mortality Rates in Japan and Local Population Density, Temperature, and Absolute Humidity. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17155477. [PMID: 32751311 PMCID: PMC7432122 DOI: 10.3390/ijerph17155477] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 07/27/2020] [Accepted: 07/27/2020] [Indexed: 12/13/2022]
Abstract
This study analyzed the morbidity and mortality rates of the coronavirus disease (COVID-19) pandemic in different prefectures of Japan. Under the constraint that daily maximum confirmed deaths and daily maximum cases should exceed 4 and 10, respectively, 14 prefectures were included, and cofactors affecting the morbidity and mortality rates were evaluated. In particular, the number of confirmed deaths was assessed, excluding cases of nosocomial infections and nursing home patients. The correlations between the morbidity and mortality rates and population density were statistically significant (p-value < 0.05). In addition, the percentage of elderly population was also found to be non-negligible. Among weather parameters, the maximum temperature and absolute humidity averaged over the duration were found to be in modest correlation with the morbidity and mortality rates. Lower morbidity and mortality rates were observed for higher temperature and absolute humidity. Multivariate linear regression considering these factors showed that the adjusted determination coefficient for the confirmed cases was 0.693 in terms of population density, elderly percentage, and maximum absolute humidity (p-value < 0.01). These findings could be useful for intervention planning during future pandemics, including a potential second COVID-19 outbreak.
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Affiliation(s)
- Sachiko Kodera
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (S.K.); (E.A.R.)
| | - Essam A. Rashed
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (S.K.); (E.A.R.)
- Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt
| | - Akimasa Hirata
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (S.K.); (E.A.R.)
- Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Nagoya 466-8555, Japan
- Correspondence: ; Tel.: +81-52-735-7916
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474
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Pourghasemi HR, Pouyan S, Farajzadeh Z, Sadhasivam N, Heidari B, Babaei S, Tiefenbacher JP. Assessment of the outbreak risk, mapping and infection behavior of COVID-19: Application of the autoregressive integrated-moving average (ARIMA) and polynomial models. PLoS One 2020; 15:e0236238. [PMID: 32722716 PMCID: PMC7386644 DOI: 10.1371/journal.pone.0236238] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 07/01/2020] [Indexed: 12/17/2022] Open
Abstract
Infectious disease outbreaks pose a significant threat to human health worldwide. The outbreak of pandemic coronavirus disease 2019 (COVID-19) has caused a global health emergency. Thus, identification of regions with high risk for COVID-19 outbreak and analyzing the behaviour of the infection is a major priority of the governmental organizations and epidemiologists worldwide. The aims of the present study were to analyze the risk factors of coronavirus outbreak for identifying the areas having high risk of infection and to evaluate the behaviour of infection in Fars Province, Iran. A geographic information system (GIS)-based machine learning algorithm (MLA), support vector machine (SVM), was used for the assessment of the outbreak risk of COVID-19 in Fars Province, Iran whereas the daily observations of infected cases were tested in the-polynomial and the autoregressive integrated moving average (ARIMA) models to examine the patterns of virus infestation in the province and in Iran. The results of the disease outbreak in Iran were compared with the data for Iran and the world. Sixteen effective factors were selected for spatial modelling of outbreak risk. The validation outcome reveals that SVM achieved an AUC value of 0.786 (March 20), 0.799 (March 29), and 86.6 (April 10) that displays a good prediction of outbreak risk change detection. The results of the third-degree polynomial and ARIMA models in the province revealed an increasing trend with an evidence of turning, demonstrating extensive quarantines has been effective. The general trends of virus infestation in Iran and Fars Province were similar, although a more volatile growth of the infected cases is expected in the province. The results of this study might assist better programming COVID-19 disease prevention and control and gaining sorts of predictive capability would have wide-ranging benefits.
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Affiliation(s)
- Hamid Reza Pourghasemi
- Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
| | - Soheila Pouyan
- Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
| | - Zakariya Farajzadeh
- Department of Agricultural Economics, College of Agriculture, Shiraz University, Shiraz, Iran
| | - Nitheshnirmal Sadhasivam
- Department of Geography, School of Earth Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India
| | - Bahram Heidari
- Department of Plant Production and Genetics, School of Agriculture, Shiraz University, Shiraz, Iran
| | - Sedigheh Babaei
- Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
| | - John P. Tiefenbacher
- Department of Geography, Texas State University, San Marcos, Texas, United States of America
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475
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Bukhari Q, Massaro JM, D’Agostino RB, Khan S. Effects of Weather on Coronavirus Pandemic. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E5399. [PMID: 32727067 PMCID: PMC7432279 DOI: 10.3390/ijerph17155399] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 07/21/2020] [Accepted: 07/24/2020] [Indexed: 11/17/2022]
Abstract
The novel coronavirus (SARS-CoV-2) has spread globally and has been declared a pandemic by the World Health Organization. While influenza virus shows seasonality, it is unknown if COVID-19 has any weather-related affect. In this work, we analyze the patterns in local weather of all the regions affected by COVID-19 globally. Our results indicate that approximately 85% of the COVID-19 reported cases until 1 May 2020, making approximately 3 million reported cases (out of approximately 29 million tests performed) have occurred in regions with temperature between 3 and 17 °C and absolute humidity between 1 and 9 g/m3. Similarly, hot and humid regions outside these ranges have only reported around 15% or approximately 0.5 million cases (out of approximately 7 million tests performed). This suggests that weather might be playing a role in COVID-19 spread across the world. However, this role could be limited in US and European cities (above 45 N), as mean temperature and absolute humidity levels do not reach these ranges even during the peak summer months. For hot and humid countries, most of them have already been experiencing temperatures >35 °C and absolute humidity >9 g/m3 since the beginning of March, and therefore the effect of weather, however little it is, has already been accounted for in the COVID-19 spread in those regions, and they must take strict social distancing measures to stop the further spread of COVID-19. Our analysis showed that the effect of weather may have only resulted in comparatively slower spread of COVID-19, but not halted it. We found that cases in warm and humid countries have consistently increased, accounting for approximately 500,000 cases in regions with absolute humidity >9 g/m3, therefore effective public health interventions must be implemented to stop the spread of COVID-19. This also means that 'summer' would not alone stop the spread of COVID-19 in any part of the world.
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Affiliation(s)
- Qasim Bukhari
- McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA;
| | - Joseph M. Massaro
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02215, USA;
| | - Ralph B. D’Agostino
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA;
| | - Sheraz Khan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA;
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Massachusetts Institute of Technology, 149 13th Street, CNY-2275, Boston, MA 02129, USA
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476
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Rashed EA, Kodera S, Gomez-Tames J, Hirata A. Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17155354. [PMID: 32722294 PMCID: PMC7432865 DOI: 10.3390/ijerph17155354] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 07/15/2020] [Accepted: 07/23/2020] [Indexed: 12/23/2022]
Abstract
This study analyzed the spread and decay durations of the COVID-19 pandemic in different prefectures of Japan. During the pandemic, affordable healthcare was widely available in Japan and the medical system did not suffer a collapse, making accurate comparisons between prefectures possible. For the 16 prefectures included in this study that had daily maximum confirmed cases exceeding ten, the number of daily confirmed cases follow bell-shape or log-normal distribution in most prefectures. A good correlation was observed between the spread and decay durations. However, some exceptions were observed in areas where travelers returned from foreign countries, which were defined as the origins of infection clusters. Excluding these prefectures, the population density was shown to be a major factor, affecting the spread and decay patterns, with R2 = 0.39 (p < 0.05) and 0.42 (p < 0.05), respectively, approximately corresponding to social distancing. The maximum absolute humidity was found to affect the decay duration normalized by the population density (R2 > 0.36, p < 0.05). Our findings indicate that the estimated pandemic spread duration, based on the multivariate analysis of maximum absolute humidity, ambient temperature, and population density (adjusted R2 = 0.53, p-value < 0.05), could prove useful for intervention planning during potential future pandemics, including a second COVID-19 outbreak.
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Affiliation(s)
- Essam A. Rashed
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (E.A.R.); (S.K.); (J.G.-T.)
- Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt
| | - Sachiko Kodera
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (E.A.R.); (S.K.); (J.G.-T.)
| | - Jose Gomez-Tames
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (E.A.R.); (S.K.); (J.G.-T.)
- Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Nagoya 466-8555, Japan
| | - Akimasa Hirata
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan; (E.A.R.); (S.K.); (J.G.-T.)
- Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Nagoya 466-8555, Japan
- Correspondence: ; Tel.: +81-52-735-7916
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477
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Zhu Y, Xie J, Huang F, Cao L. Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 727:138704. [PMID: 32315904 PMCID: PMC7159846 DOI: 10.1016/j.scitotenv.2020.138704] [Citation(s) in RCA: 636] [Impact Index Per Article: 127.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 04/11/2020] [Accepted: 04/13/2020] [Indexed: 04/13/2023]
Abstract
The novel coronavirus pneumonia, namely COVID-19, has become a global public health problem. Previous studies have found that air pollution is a risk factor for respiratory infection by carrying microorganisms and affecting body's immunity. This study aimed to explore the relationship between ambient air pollutants and the infection caused by the novel coronavirus. Daily confirmed cases, air pollution concentration and meteorological variables in 120 cities were obtained from January 23, 2020 to February 29, 2020 in China. We applied a generalized additive model to investigate the associations of six air pollutants (PM2.5, PM10, SO2, CO, NO2 and O3) with COVID-19 confirmed cases. We observed significantly positive associations of PM2.5, PM10, NO2 and O3 in the last two weeks with newly COVID-19 confirmed cases. A 10-μg/m3 increase (lag0-14) in PM2.5, PM10, NO2, and O3 was associated with a 2.24% (95% CI: 1.02 to 3.46), 1.76% (95% CI: 0.89 to 2.63), 6.94% (95% CI: 2.38 to 11.51), and 4.76% (95% CI: 1.99 to 7.52) increase in the daily counts of confirmed cases, respectively. However, a 10-μg/m3 increase (lag0-14) in SO2 was associated with a 7.79% decrease (95% CI: -14.57 to -1.01) in COVID-19 confirmed cases. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which could partially explain the effect of national lockdown and provide implications for the control and prevention of this novel disease.
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Affiliation(s)
- Yongjian Zhu
- School of Management, University of Science and Technology of China, Hefei, China.
| | - Jingui Xie
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China; Brunel Business School, Brunel University London, Uxbridge, United Kingdom.
| | - Fengming Huang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
| | - Liqing Cao
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
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478
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Ching J, Kajino M. Rethinking Air Quality and Climate Change after COVID-19. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E5167. [PMID: 32708953 PMCID: PMC7400058 DOI: 10.3390/ijerph17145167] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 07/10/2020] [Accepted: 07/14/2020] [Indexed: 12/11/2022]
Abstract
The world is currently shadowed by the pandemic of COVID-19. Confirmed cases and the death toll has reached more than 12 million and more than 550,000 respectively as of 10 July 2020. In the unsettling pandemic of COVID-19, the whole Earth has been on an unprecedented lockdown. Social distancing among people, interrupted international and domestic air traffic and suspended industrial productions and economic activities have various far-reaching and undetermined implications on air quality and the climate system. Improvement in air quality has been reported in many cities during lockdown, while the death rate of COVID-19 has been found to be higher in more polluted cities. The relationship between the spread of the SARS-CoV-2 virus and air quality is under investigation. In addition, the battle against COVID-19 could bring short-lived and long-lasting and positive and negative impacts to the warming climate. The impacts on the climate system and the role of the climate in modulating the COVID-19 pandemic are the foci of scientific inquiry. The intertwined relationship among environment, climate change and public health is exemplified in the pandemic of COVID-19. Further investigation of the relationship is imperative in the Anthropocene, in particular, in enhancing disaster preparedness. This short article intends to give an up-to-date glimpse of the pandemic from air quality and climate perspectives and calls for a follow-up discussion.
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Affiliation(s)
- Joseph Ching
- Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan;
| | - Mizuo Kajino
- Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan;
- Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8572, Japan
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479
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Sultana F, Reza HM. Are SAARC countries prepared to combat COVID-19 to save young, working-age population? AIMS Public Health 2020; 7:440-449. [PMID: 32968669 PMCID: PMC7505794 DOI: 10.3934/publichealth.2020036] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/28/2020] [Indexed: 12/24/2022] Open
Abstract
The COVID-19 outbreak has expanded across the globe. Most of the countries are launching different measures to stop the transmission of this virus. However, the death toll is steadily rising. Strikingly the rate of coronavirus infection among the young-age population is the highest in SAARC countries as more than 80% population of the SAARC countries are young who constitute the working-age group. The disease transmission also occurs at a slower rate presumably due to diverse lifestyles of different ethnicities, immunity and genetic traits; but not because of the hot and humid weather despite previous assumptions. Since SAARC countries comprise 23.75% of the world population and the largest portion of these people is the young working-class, some immediate measures need to be implemented to save these valuable lives from COVID-19. Till now, there is no specific treatment or vaccine available; hence timely-taken preventive measures are the only hope that can save the people of this region. Here we have demonstrated an altered disease transmission pattern in people of SAARC countries, measures initiated by the governments, causes of failure and further actions to be taken to control disease transmission.
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Affiliation(s)
- Farhana Sultana
- Department of Political Science and Sociology, North South University, Bashundhara R/A, Dhaka 1229, Bangladesh
| | - Hasan Mahmud Reza
- Department of Pharmaceutical Sciences, North South University, Bashundhara R/A, Dhaka 1229, Bangladesh
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480
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Tantrakarnapa K, Bhopdhornangkul B, Nakhaapakorn K. Influencing factors of COVID-19 spreading: a case study of Thailand. ZEITSCHRIFT FUR GESUNDHEITSWISSENSCHAFTEN = JOURNAL OF PUBLIC HEALTH 2020; 30:621-627. [PMID: 32837844 PMCID: PMC7301627 DOI: 10.1007/s10389-020-01329-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 05/22/2020] [Indexed: 12/24/2022]
Abstract
Aim A novel corona virus disease 2019 (COVID-19) was declared as pandemic by WHO as global level and local levels in many countries. The movement of people might be one influencing factor, this paper aims to report the situation COVID-19 and spreading in Thailand, including influencing factors of spreading and control. Subject and method Infected, confirmed COVID-19 data were obtained from the official website of the Department of Disease Control, Ministry of Public Health. Tourist data was downloaded from Ministry of Tourism and Sports. Researchers analyzed the situation from the first found case in Thailand until 15 April 2020 with the timeline of important influencing factors. Correlation coefficients of tourist data and infected case was calculated by person correlation coefficient. Results The number of infected cases was significant associated (correlation coefficient > 0.7) with economic factor, namely; number of visitors, generated income from both Thai and foreigner tourist (p value <0.01). The influencing factors of slow increased rate were the enforcement and implementation of both central and local government regulation, the strength of the Thai health care system, the culture and social relation, the partnership among various governmental and private sectors. Conclusion We found that the number of tourist and their activities were significant associated with number of infected, confirmed COVID-19 cases. The public education and social supporting were the key roles for regulation enforcement and implementation.
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Affiliation(s)
- Kraichat Tantrakarnapa
- Department of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Ratchathewi, Bangkok, Thailand
| | - Bhophkrit Bhopdhornangkul
- Infectious of Disease Control and Entomology Section, Division of Health Promotion and Preventive Medicine, Royal Thai Army Medical Crops, Bangkok, Thailand
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481
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Cheval S, Mihai Adamescu C, Georgiadis T, Herrnegger M, Piticar A, Legates DR. Observed and Potential Impacts of the COVID-19 Pandemic on the Environment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E4140. [PMID: 32532012 PMCID: PMC7311982 DOI: 10.3390/ijerph17114140] [Citation(s) in RCA: 109] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 06/03/2020] [Accepted: 06/06/2020] [Indexed: 12/18/2022]
Abstract
Various environmental factors influence the outbreak and spread of epidemic or even pandemic events which, in turn, may cause feedbacks on the environment. The novel coronavirus disease (COVID-19) was declared a pandemic on 13 March 2020 and its rapid onset, spatial extent and complex consequences make it a once-in-a-century global disaster. Most countries responded by social distancing measures and severely diminished economic and other activities. Consequently, by the end of April 2020, the COVID-19 pandemic has led to numerous environmental impacts, both positive such as enhanced air and water quality in urban areas, and negative, such as shoreline pollution due to the disposal of sanitary consumables. This study presents an early overview of the observed and potential impacts of the COVID-19 on the environment. We argue that the effects of COVID-19 are determined mainly by anthropogenic factors which are becoming obvious as human activity diminishes across the planet, and the impacts on cities and public health will be continued in the coming years.
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Affiliation(s)
- Sorin Cheval
- “Henri Coandă” Air Force Academy, 500183 Brașov, Romania; (S.C.); (A.P.)
- National Meteorological Administration, 013686 Bucharest, Romania
| | - Cristian Mihai Adamescu
- Research Center for Systems Ecology and Sustainability, University of Bucharest, 050095 Bucharest, Romania
| | | | - Mathew Herrnegger
- Institute for Hydrology and Water Management, University of Natural Resources and Life Sciences (BOKU), 1190 Vienna, Austria;
| | - Adrian Piticar
- “Henri Coandă” Air Force Academy, 500183 Brașov, Romania; (S.C.); (A.P.)
| | - David R. Legates
- Department of Geography and Spatial Sciences, University of Delaware, Newark, DE 19716-2541, USA;
- Department of Applied Economics and Statistics, University of Delaware, Newark, DE 19716-2541, USA
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482
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Das A, Das M, Ghosh S. Impact of nutritional status and anemia on COVID-19: Is it a public health concern? Evidence from National Family Health Survey-4 (2015-2016), India. Public Health 2020; 185:93-94. [PMID: 32593053 PMCID: PMC7280132 DOI: 10.1016/j.puhe.2020.06.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 06/01/2020] [Indexed: 12/25/2022]
Affiliation(s)
- A Das
- Department of Geography, University of Gour Banga, Malda, West Bengal, India.
| | - M Das
- Department of Geography, University of Gour Banga, Malda, West Bengal, India.
| | - S Ghosh
- Department of Geography, Kazi Nazrul University, Asansol, West Bengal, India.
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483
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Fareed Z, Iqbal N, Shahzad F, Shah SGM, Zulfiqar B, Shahzad K, Hashmi SH, Shahzad U. Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence. AIR QUALITY, ATMOSPHERE, & HEALTH 2020; 13:673-682. [PMID: 32837610 PMCID: PMC7279636 DOI: 10.1007/s11869-020-00847-1] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 05/27/2020] [Indexed: 05/02/2023]
Abstract
The worldwide outbreak of COVID-19 disease has caused immense damage to our health and economic and social life. This research article helps to determine the impact of climate on the lethality of this disease. Air quality index and average humidity are selected from the family of climate variables, to determine its impact on the daily new cases of COVID-19-related deaths in Wuhan, China. We have used wavelet analysis (wavelet transform coherence (WTC), partial (PWC), and multiple wavelet coherence (MWC), due to its advantages over traditional time series methods, to study the co-movement nexus between our selected data series. Findings suggest a notable coherence between air quality index, humidity, and mortality in Wuhan during a recent outbreak. Humidity is negatively related to the COVID-19-related deaths, and bad air quality leads to an increase in this mortality. These findings are important for policymakers to save precious human lives by better understanding the interaction of the environment with the COVID-19 disease.
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Affiliation(s)
- Zeeshan Fareed
- School of Business, Huzhou University, Huzhou, Zhejiang China
| | - Najaf Iqbal
- College of Economics and Management, Hunan University of Arts and Science, Changde, China
- School of Management, Wuhan University of Technology, Wuhan, China
| | - Farrukh Shahzad
- School of Economics and Management, Guangdong University of Petrochemical Technology, Guangdong, China
| | - Syed Ghulam Meran Shah
- School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China
| | - Bushra Zulfiqar
- School of Economics, Southwestern University of Finance and Economics, Chengdu, China
| | - Khurram Shahzad
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an, People’s Republic of China
| | | | - Umar Shahzad
- School of Economics, Shandong University, Jinan, Shandong Province People’s Republic of China
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484
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Adhikari A, Yin J. Short-Term Effects of Ambient Ozone, PM 2.5, and Meteorological Factors on COVID-19 Confirmed Cases and Deaths in Queens, New York. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E4047. [PMID: 32517125 PMCID: PMC7312351 DOI: 10.3390/ijerph17114047] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 05/18/2020] [Accepted: 06/03/2020] [Indexed: 12/15/2022]
Abstract
The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, has been rapidly increasing in the United States. Boroughs of New York City, including Queens county, turn out to be the epicenters of this infection. According to the data provided by the New York State Department of Health, most of the cases of new COVID-19 infections in New York City have been found in the Queens county where 42,023 people have tested positive, and 3221 people have died as of 20 April 2020. Person-to-person transmission and travels were implicated in the initial spread of the outbreaks, but factors related to the late phase of rapidly spreading outbreaks in March and April are still uncertain. A few previous studies have explored the links between air pollution and COVID-19 infections, but more data is needed to understand the effects of short-term exposures of air pollutants and meteorological factors on the spread of COVID-19 infections, particularly in the U.S. disease epicenters. In this study, we have focused on ozone and PM2.5, two major air pollutants in New York City, which were previously found to be associated with respiratory viral infections. The aim of our regression modeling was to explore the associations among ozone, PM2.5, daily meteorological variables (wind speed, temperature, relative humidity, absolute humidity, cloud percentages, and precipitation levels), and COVID-19 confirmed new cases and new deaths in Queens county, New York during March and April 2020. The results from these analyses showed that daily average temperature, daily maximum eight-hour ozone concentration, average relative humidity, and cloud percentages were significantly and positively associated with new confirmed cases related to COVID-19; none of these variables showed significant associations with new deaths related to COVID-19. The findings indicate that short-term exposures to ozone and other meteorological factors can influence COVID-19 transmission and initiation of the disease, but disease aggravation and mortality depend on other factors.
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Affiliation(s)
- Atin Adhikari
- Department of Biostatistics, Epidemiology & Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
| | - Jingjing Yin
- Department of Biostatistics, Epidemiology & Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
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485
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Islam MS, Sobur MA, Akter M, Nazir KHMNH, Toniolo A, Rahman MT. Coronavirus Disease 2019 (COVID-19) pandemic, lessons to be learned! J Adv Vet Anim Res 2020; 7:260-280. [PMID: 32607358 PMCID: PMC7320801 DOI: 10.5455/javar.2020.g418] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 12/23/2022] Open
Abstract
Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported as a worldwide emergency. Due to the extensiveness of spread and death, it has been declared as a pandemic. This review focused on the current pandemic situation and understanding the prevention and control strategies of COVID-19. Data presented here was by April 3, 2020. A total of 1,016,399 cases of COVID-19 with 53,238 deaths was reported from 204 countries and territories including two international conveyances over the world. After China, most of the new cases were from Europe, particularly Italy acting as the source of importation to many of the other countries around the world. China has obtained success by ascribing control strategies against COVID-19. The implementation of China's strategy, as well as the development of a vaccine, may control the pandemic of COVID-19. Further robust studies are required for a clear understanding of transmission parameters, prevention, and control strategies of SARS-CoV-2. This review paper describes the nature of COVID-19 and the possible ways for the effective controlling of the COVID-19 or similar viral diseases that may come in the future.
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Affiliation(s)
- Md. Saiful Islam
- Department of Microbiology and Hygiene, Faculty of Veterinary Science, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh
| | - Md. Abdus Sobur
- Department of Microbiology and Hygiene, Faculty of Veterinary Science, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh
| | - Mily Akter
- Department of Microbiology and Hygiene, Faculty of Veterinary Science, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh
| | - K. H. M. Nazmul Hussain Nazir
- Department of Microbiology and Hygiene, Faculty of Veterinary Science, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh
| | | | - Md. Tanvir Rahman
- Department of Microbiology and Hygiene, Faculty of Veterinary Science, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh
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486
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Ward MP, Xiao S, Zhang Z. The role of climate during the COVID-19 epidemic in New South Wales, Australia. Transbound Emerg Dis 2020; 67:2313-2317. [PMID: 32438520 PMCID: PMC7280716 DOI: 10.1111/tbed.13631] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 05/09/2020] [Accepted: 05/12/2020] [Indexed: 12/19/2022]
Abstract
Previous research has identified a relationship between climate and occurrence of SARS-CoV and MERS-CoV cases, information that can be used to reduce the risk of infection. Using COVID-19 notification and postcode data from New South Wales, Australia during the exponential phase of the epidemic in 2020, we used time series analysis to investigate the relationship between 749 cases of locally acquired COVID-19 and daily rainfall, 9 a.m. and 3 p.m. temperature, and 9 a.m. and 3 p.m. relative humidity. Lower 9 a.m. relative humidity (but not rainfall or temperature) was associated with increased case occurrence; a reduction in relative humidity of 1% was predicted to be associated with an increase of COVID-19 cases by 6.11%. During periods of low relative humidity, the public health system should anticipate an increased number of COVID-19 cases.
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Affiliation(s)
- Michael P Ward
- Sydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia
| | - Shuang Xiao
- School of Public Health, Fudan University, Shanghai, China
| | - Zhijie Zhang
- School of Public Health, Fudan University, Shanghai, China
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487
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Yuan S, Jiang SC, Li ZL. Do Humidity and Temperature Impact the Spread of the Novel Coronavirus? Front Public Health 2020; 8:240. [PMID: 32574306 PMCID: PMC7266870 DOI: 10.3389/fpubh.2020.00240] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 05/18/2020] [Indexed: 12/23/2022] Open
Affiliation(s)
- Shu Yuan
- College of Resources, Sichuan Agricultural University, Chengdu, China
| | - Si-Cong Jiang
- Chengdu KangHong Pharmaceutical Group Comp. Ltd., Chengdu, China
| | - Zi-Lin Li
- Department of Cardiovascular Surgery, Xijing Hospital, Medical University of the Air Force, Xi'an, China
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488
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Abstract
The current global health emergency, COVID-19, is not the first time that coronaviruses have posed a threat to human world shrinking our numbers by thousands. Before this SARS-CoV in 2003 and MERS-CoV in 2013 have caused epidemics. Four months in existence, and it has already affected 1,995,983 people and taken over 131,037 lives worldwide, yet we do not have any specific treatment available with us and the management is purely empirical. Looking at the similarities between SARS-CoV and SARS-CoV-2 in origin, genomics, pathogenesis and epidemiology, we can bring the researches done for SARS-CoV in use which can be our guide in finding an effective management strategy against SARS-CoV-2. There are various researches and studies reporting the use and effect of various phytochemical compounds in SARS-CoV treatment. Already, the thought has been put into action and in-silico screening for various natural plant compounds have been done to find a potential candidate compound. One such example is of curcumin, a secondary metabolite of turmeric, which is found to be effective against COVID-19 protease by molecular docking analysis.
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489
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Su D, Chen Y, He K, Zhang T, Tan M, Zhang Y, Zhang X. Influence of socio-ecological factors on COVID-19 risk: a cross-sectional study based on 178 countries/regions worldwide. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.04.23.20077545. [PMID: 32511588 PMCID: PMC7276015 DOI: 10.1101/2020.04.23.20077545] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background The initial outbreak of COVID-19 caused by SARS-CoV-2 in China in 2019 has been severely tested in other countries worldwide. We aimed to describe the spatial distribution of the COVID-19 pandemic worldwide and assess the effects of various socio-ecological factors on COVID-19 risk. Methods We collected COVID-19 pandemic infection data and social-ecological data of 178 countries/regions worldwide from three database. We used spatial econometrics method to assess the global and local correlation of COVID-19 risk indicators for COVID-19. To estimate the adjusted incidence rate ratio (IRR), we modelled negative binomial regression analysis with spatial information and socio-ecological factors. Findings The study indicated that 37, 29 and 39 countries/regions were strongly opposite from the IR, CMR and DCI index "spatial autocorrelation hypothesis", respectively. The IRs were significantly positively associated with GDP per capita, the use of at least basic sanitation services and social insurance program coverage, and were significantly negatively associated with the proportion of the population spending more than 25% of household consumption or income on out-of-pocket health care expenses and the poverty headcount ratio at the national poverty lines. The CMR was significantly positively associated with urban populations, GDP per capita and current health expenditure, and was significantly negatively associated with the number of hospital beds, number of nurses and midwives, and poverty headcount ratio at the national poverty lines. The DCI was significantly positively associated with urban populations, population density and researchers in R&D, and was significantly negatively associated with the number of hospital beds, number of nurses and midwives and poverty headcount ratio at the national poverty lines. We also found that climatic factors were not significantly associated with COVID-19 risk. Conclusion Countries/regions should pay more attention to controlling population flow, improving diagnosis and treatment capacity, and improving public welfare policies.
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Affiliation(s)
- Dai Su
- Department of Health Management, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Research Center for Rural Health Services, Hubei Province Key Research Institute of Humanities and Social Sciences, Wuhan, China
| | - Yingchun Chen
- Department of Health Management, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Research Center for Rural Health Services, Hubei Province Key Research Institute of Humanities and Social Sciences, Wuhan, China
| | - Kevin He
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, United States
| | - Tao Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China fourth Hospital, Sichuan University, Sichuan, China
| | - Min Tan
- Department of Health Management, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Research Center for Rural Health Services, Hubei Province Key Research Institute of Humanities and Social Sciences, Wuhan, China
| | - Yunfan Zhang
- Department of Health Management, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Research Center for Rural Health Services, Hubei Province Key Research Institute of Humanities and Social Sciences, Wuhan, China
| | - Xingyu Zhang
- Department of Systems, Populations, and Leadership, University of Michigan School of Nursing, Ann Arbor, United States
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490
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Coccia M. Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics (Preprint).. [DOI: 10.2196/preprints.19331] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
BACKGROUND
Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death.
OBJECTIVE
This study has two goals. The first is to explain the main factors determining the diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats with of accelerated viral infectivity in society.
METHODS
Correlation and regression analyses on on data of N=55 Italian province capitals, and data of infected individuals at as of April 2020.
RESULTS
The main results are:
o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution.
o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average.
o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals.
o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission.
o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society.
CONCLUSIONS
Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19.
CLINICALTRIAL
not applicable
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491
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Coccia M. Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics.. [DOI: 10.1101/2020.04.06.20055657] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
AbstractWhat is COVID-19?Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death.What are the goals of this investigation?This study explains the geo-environmental determinants of the accelerated diffusion of COVID-19 in Italy that is generating a high level of deaths and suggests general lessons learned for a strategy to cope with future epidemics similar to COVID-19 to reduce viral infectivity and negative impacts in economic systems and society.What are the results of this study?The main results are:
The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution.Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average.Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals.The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission.The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society.What is a socioeconomic strategy to prevent future epidemics similar to COVID-19?Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19.This study must conclude that a strategy to prevent future epidemics similar to COVID 19 has also to be designed in environmental and sustainability science and not only in terms of biology.
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492
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Jamil T, Alam I, Gojobori T, Duarte CM. No Evidence for Temperature-Dependence of the COVID-19 Epidemic. Front Public Health 2020. [PMID: 32984240 DOI: 10.1101/2020.03.29.20046706] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2023] Open
Abstract
The pandemic of the COVID-19 extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. The hypothesis that COVID-19 spread is temperature-dependent was tested based on data derived from nations across the world and provinces in China. No evidence of a pattern between spread rates and ambient temperature was found, suggesting that the SARS-CoV-2 is unlikely to behave as a seasonal respiratory virus.
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Affiliation(s)
- Tahira Jamil
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Red Sea Research Centre (RSRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Intikhab Alam
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Takashi Gojobori
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Carlos M Duarte
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Red Sea Research Centre (RSRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
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493
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Gupta A, Pradhan B, Maulud KNA. Estimating the Impact of Daily Weather on the Temporal Pattern of COVID-19 Outbreak in India. EARTH SYSTEMS AND ENVIRONMENT 2020; 4:523-534. [PMID: 34723072 PMCID: PMC7494434 DOI: 10.1007/s41748-020-00179-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 09/05/2020] [Indexed: 05/21/2023]
Abstract
The COVID-19 pandemic has spread obstreperously in India. The increase in daily confirmed cases accelerated significantly from ~ 5 additional new cases (ANC)/day during early March up to ~ 249 ANC/day during early June. An abrupt change in this temporal pattern was noticed during mid-April, from which can be inferred a much reduced impact of the nationwide lockdown in India. Daily maximum (T Max), minimum (T Min), mean (T Mean) and dew point temperature (T Dew), wind speed (WS), relative humidity, and diurnal range in temperature and relative humidity during March 01 to June 04, 2020 over 9 major affected cities are analyzed to look into the impact of daily weather on COVID-19 infections on that day and 7, 10, 12, 14, 16 days before those cases were detected (i.e., on the likely transmission days). Spearman's correlation exhibits significantly lower association with WS, T Max, T Min, T Mean, T Dew, but is comparatively better with a lag of 14 days. Support Vector regression successfully estimated the count of confirmed cases (R 2 > 0.8) at a lag of 12-16 days, thus reflecting a probable incubation period of 14 ± 02 days in India. Approximately 75% of total cases were registered when T Max, T Mean, T Min, T Dew, and WS at 12-16 days previously were varying within the range of 33.6-41.3 °C, 29.8-36.5 °C, 24.8-30.4 °C, 18.7-23.6 °C, and 4.2-5.75 m/s, respectively. Thus, we conclude that coronavirus transmission is not well correlated (linearly) with any individual weather parameter; rather, transmission is susceptible to a certain weather pattern. Hence multivariate non-linear approach must be employed instead.
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Affiliation(s)
- Amitesh Gupta
- Remote Sensing and GIS Department, JIS University, Agarpara, Kolkata, India
| | - Biswajeet Pradhan
- Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Information, Systems and Modelling, Faculty of Engineering and IT, University of Technology Sydney (UTS), Sydney, Australia
- Earth Observation Centre, Institute of Climate Change (IPI), Universiti Kebangsaan Malaysia (UKM), 43600 UKM Bangi, Selangor Malaysia
| | - Khairul Nizam Abdul Maulud
- Earth Observation Centre, Institute of Climate Change (IPI), Universiti Kebangsaan Malaysia (UKM), 43600 UKM Bangi, Selangor Malaysia
- Department of Civil Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Malaysia
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494
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Chien LC, Chen LW. Meteorological impacts on the incidence of COVID-19 in the U.S. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT : RESEARCH JOURNAL 2020; 34:1675-1680. [PMID: 32837311 PMCID: PMC7334896 DOI: 10.1007/s00477-020-01835-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Since the World Health Organization has declared the current outbreak of the novel coronavirus (COVID-19) a global pandemic, some have been anticipating that the mitigation could happen in the summer like seasonal influenza, while medical solutions are still in a slow progress. Experimental studies have revealed a few evidences that coronavirus decayed quickly under the exposure of heat and humidity. This study aims to carry out an epidemiological investigation to establish the association between meteorological factors and COVID-19 in high risk areas of the United States (U.S.). We analyzed daily new confirmed cases of COVID-19 and seven meteorological measures in top 50 U.S. counties with the most accumulative confirmed cases from March 22, 2020 to April 22, 2020. Our analyses indicate that each meteorological factor and COVID-19 more likely have a nonlinear association rather than a linear association over the wide ranges of temperature, relative humidity, and precipitation observed. Average temperature, minimum relative humidity, and precipitation were better predictors to address the meteorological impact on COVID-19. By including all the three meteorological factors in the same model with their lagged effects up to 3 days, the overall impact of the average temperature on COVID-19 was found to peak at 68.45 °F and decrease at higher degrees, though the overall relative risk percentage (RR %) reduction did not become significantly negative up to 85 °F. There was a generally downward trend of RR % with the increase of minimum relative humidity; nonetheless, the trend reversed when the minimum relative humidity exceeded 91.42%. The overall RR % of COVID-19 climbed to the highest level of 232.07% (95% confidence interval = 199.77, 267.85) with 1.60 inches of precipitation, and then started to decrease. When precipitation exceeded 1.85 inches, its impact on COVID-19 became significantly negative. Our findings alert people to better have self-protection during the pandemic rather than expecting that the natural environment can curb coronavirus for human beings.
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Affiliation(s)
- Lung-Chang Chien
- Department of Epidemiology and Biostatistics, School of Public Health, University of Nevada, Las Vegas, 4700 S. Maryland Parkway, Suite 335, Las Vegas, NV 89119 USA
| | - Lung-Wen Chen
- Department of Environmental and Occupational Health, School of Public Health, University of Nevada, Las Vegas, 4700 S. Maryland Parkway, Suite 335, Las Vegas, NV 89119 USA
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495
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Al-Kindi KM, Alkharusi A, Alshukaili D, Al Nasiri N, Al-Awadhi T, Charabi Y, El Kenawy AM. Spatiotemporal Assessment of COVID-19 Spread over Oman Using GIS Techniques. EARTH SYSTEMS AND ENVIRONMENT 2020; 4:797-811. [PMID: 34723076 PMCID: PMC7721548 DOI: 10.1007/s41748-020-00194-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 11/19/2020] [Indexed: 05/18/2023]
Abstract
UNLABELLED Coronavirus disease (COVID-19), caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide challenge effecting millions of people in more than 210 countries, including the Sultanate of Oman (Oman). Spatiotemporal analysis was adopted to explore the spatial patterns of the spread of COVID-19 during the period from 29th April to 30th June 2020. Our assessment was made using five geospatial techniques within a Geographical Information System (GIS) context, including a weighted mean centre (WMC), standard deviational ellipses, Moran's I autocorrelation coefficient, Getis-Ord General-G high/low clustering, and Getis-Ord G i ∗ statistic. The Moran's I-/G- statistics proved that COVID-19 cases in datasets (numbers of cases) were clustered throughout the study period. The Moran's I and Z scores were above the 2.25 threshold (a confidence level above 95%), ranging from 2274 cases on 29th April to 40,070 cases on 30th June 2020. The results of G i ∗ showed varying rates of infections, with a large spatial variability between the different wilayats (district). The epidemic situation in some wilayats, such as Mutrah, As-Seeb, and Bowsher in the Muscat Governorate, was more severe, with Z score higher than 5, and the current transmission still presents an increasing trend. This study indicated that the directional pattern of COVID-19 cases has moved from northeast to northwest and southwest, with the total impacted region increasing over time. Also, the results indicate that the rate of COVID-19 infections is higher in the most populated areas. The findings of this paper provide a solid basis for future study by investigating the most resolute hotspots in more detail and may help decision-makers identify targeted zones for alleviation plans. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s41748-020-00194-2.
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Affiliation(s)
| | - Amira Alkharusi
- Physiology Department, Colege of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman
| | | | - Noura Al Nasiri
- Geography Department, Sultan Qaboos University, Muscat, Oman
- Center for Environmental Studies and Research, Geography Department, Sultan Qaboos University, Muscat, Oman
| | - Talal Al-Awadhi
- Geography Department, Sultan Qaboos University, Muscat, Oman
| | - Yassine Charabi
- Geography Department, Sultan Qaboos University, Muscat, Oman
- Center for Environmental Studies and Research, Geography Department, Sultan Qaboos University, Muscat, Oman
| | - Ahmed M. El Kenawy
- Geography Department, Sultan Qaboos University, Muscat, Oman
- Department of Geography, Mansoura University, Mansoura, 35516 Egypt
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496
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Roy M. Temperature and COVID- 19: Delhi. J Family Med Prim Care 2020; 9:4496. [PMID: 33110902 PMCID: PMC7586577 DOI: 10.4103/jfmpc.jfmpc_880_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 06/14/2020] [Accepted: 06/18/2020] [Indexed: 11/09/2022] Open
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