1
|
Mutlu A, Aydın Keskin G, Çıldır İ. Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:759. [PMID: 39046576 DOI: 10.1007/s10661-024-12908-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/11/2024] [Indexed: 07/25/2024]
Abstract
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory diseases and the levels of PM10 and SO2 pollutants, as well as local meteorological conditions, using data from 2017 to 2019. The objective of this study is to clarify the impact of air pollution on the well-being of the general population, specifically focusing on respiratory ailments. An ANN called a multilayer perceptron (MLP) was used. The network was trained using the Levenberg-Marquardt (LM) backpropagation algorithm. The data revealed a substantial increase in hospital admissions for upper respiratory tract diseases, amounting to a total of 11,746 cases. There were clear seasonal fluctuations, with fall having the highest number of cases of bronchitis (N = 181), sinusitis (N = 83), and upper respiratory infections (N = 194). The study also found demographic differences, with females and people aged 18 to 65 years having greater admission rates. The performance of the ANN model, measured using R2 values, demonstrated a high level of predictive accuracy. Specifically, the R2 value was 0.91675 during training, 0.99182 during testing, and 0.95287 for validating the prediction of asthma. The comparative analysis revealed that the ANN-MLP model provided the most optimal result. The results emphasize the effectiveness of ANNs in representing the complex relationships between air quality, climatic conditions, and respiratory health. The results offer crucial insights for formulating focused healthcare policies and treatments to alleviate the detrimental impact of air pollution and meteorological factors.
Collapse
Affiliation(s)
- Atilla Mutlu
- Department of Environmental Engineering, College of Engineering, Balikesir University, Balikesir, Turkey.
| | - Gülşen Aydın Keskin
- Department of Industrial Engineering, College of Engineering, Balikesir University, Balikesir, Turkey
| | - İhsan Çıldır
- Ministry of Health Edremit State Hospital, Edremit, Balikesir, Turkey
| |
Collapse
|
2
|
Labib SM. Greenness, air pollution, and temperature exposure effects in predicting premature mortality and morbidity: A small-area study using spatial random forest model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172387. [PMID: 38608883 DOI: 10.1016/j.scitotenv.2024.172387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 04/08/2024] [Accepted: 04/08/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Although studies have provided negative impacts of air pollution, heat or cold exposure on mortality and morbidity, and positive effects of increased greenness on reducing them, a few studies have focused on exploring combined and synergetic effects of these exposures in predicting these health outcomes, and most had ignored the spatial autocorrelation in analyzing their health effects. This study aims to investigate the health effects of air pollution, greenness, and temperature exposure on premature mortality and morbidity within a spatial machine-learning modeling framework. METHODS Years of potential life lost reflecting premature mortality and comparative illness and disability ratio reflecting chronic morbidity from 1673 small areas covering Greater Manchester for the year 2008-2013 obtained. Average annual levels of NO2 concentration, normalized difference vegetation index (NDVI) representing greenness, and annual average air temperature were utilized to assess exposure in each area. These exposures were linked to health outcomes using non-spatial and spatial random forest (RF) models while accounting for spatial autocorrelation. RESULTS Spatial-RF models provided the best predictive accuracy when accounted for spatial autocorrelation. Among the exposures considered, air pollution emerged as the most influential in predicting mortality and morbidity, followed by NDVI and temperature exposure. Nonlinear exposure-response relations were observed, and interactions between exposures illustrated specific ranges or sweet and sour spots of exposure thresholds where combined effects either exacerbate or moderate health conditions. CONCLUSION Air pollution exposure had a greater negative impact on health compared to greenness and temperature exposure. Combined exposure effects may indicate the highest influence of premature mortality and morbidity burden.
Collapse
Affiliation(s)
- S M Labib
- Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, the Netherlands.
| |
Collapse
|
3
|
Fania A, Monaco A, Amoroso N, Bellantuono L, Cazzolla Gatti R, Firza N, Lacalamita A, Pantaleo E, Tangaro S, Velichevskaya A, Bellotti R. Machine learning and XAI approaches highlight the strong connection between O 3 and N O 2 pollutants and Alzheimer's disease. Sci Rep 2024; 14:5385. [PMID: 38443419 PMCID: PMC11319812 DOI: 10.1038/s41598-024-55439-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 02/23/2024] [Indexed: 03/07/2024] Open
Abstract
Alzheimer's disease (AD) is the most common type of dementia with millions of affected patients worldwide. Currently, there is still no cure and AD is often diagnosed long time after onset because there is no clear diagnosis. Thus, it is essential to study the physiology and pathogenesis of AD, investigating the risk factors that could be strongly connected to the disease onset. Despite AD, like other complex diseases, is the result of the combination of several factors, there is emerging agreement that environmental pollution should play a pivotal role in the causes of disease. In this work, we implemented an Artificial Intelligence model to predict AD mortality, expressed as Standardized Mortality Ratio, at Italian provincial level over 5 years. We employed a set of publicly available variables concerning pollution, health, society and economy to feed a Random Forest algorithm. Using methods based on eXplainable Artificial Intelligence (XAI) we found that air pollution (mainly O 3 and N O 2 ) contribute the most to AD mortality prediction. These results could help to shed light on the etiology of Alzheimer's disease and to confirm the urgent need to further investigate the relationship between the environment and the disease.
Collapse
Affiliation(s)
- Alessandro Fania
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| | - Alfonso Monaco
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy.
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy.
| | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
| | - Loredana Bellantuono
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Biomedicina Traslazionale e Neuroscienze (DiBraiN), Università degli Studi di Bari Aldo Moro, 70124, Bari, Italy
| | - Roberto Cazzolla Gatti
- Department of Biological Sciences, Geological and Environmental (BiGeA), Alma Mater Studiorum - University of Bologna, 40126, Bologna, Italy
| | - Najada Firza
- Dipartimento di Economia e Finanza, Università degli Studi di Bari Aldo Moro, 70124, Bari, Italy
- Catholic University Our Lady of Good Counsel, 1031, Tirana, Albania
| | - Antonio Lacalamita
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| | - Ester Pantaleo
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| | - Sabina Tangaro
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, 70126, Bari, Italy
| | | | - Roberto Bellotti
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| |
Collapse
|
4
|
Zeng Y, Pang K, Cao S, Lin G, Tang J. Causal relationship between particulate matter 2.5 and infectious diseases: A two-sample Mendelian randomization study. Heliyon 2024; 10:e23412. [PMID: 38163134 PMCID: PMC10755308 DOI: 10.1016/j.heliyon.2023.e23412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/28/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024] Open
Abstract
Background Previous observational studies suggested a correlation between particulate matter 2.5 (PM2.5) and infectious diseases, but causality remained uncertain. This study utilized Mendelian randomization (MR) analysis to investigate causal relationships between PM2.5 concentrations and various infectious diseases (COVID-19 infection, hospitalized COVID-19, very severe COVID-19, urinary tract infection, bacterial pneumonia, and intestinal infection). Methods Inverse variance weighted (IVW) was the primary method for evaluating causal associations. For significant causal estimates, multiple sensitivity tests were further performed: (i) three additional MR methods (MR-Egger, weighted median, and maximum likelihood method) for supplementing IVW; (ii) Cochrane's Q test for assessing heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test for evaluating horizontal pleiotropy; (iv) leave-one-out sensitivity test for determining the stability. Results PM2.5 concentration significantly increased the risk of hospitalized COVID-19 (OR = 1.91, 95 % CI: 1.06-3.45, P = 0.032) and very severe COVID-19 (OR = 3.29, 95 % CI: 1.48-7.35, P = 3.62E-03). However, no causal effect was identified for PM2.5 concentration on other infectious diseases (P > 0.05). Furthermore, various sensitivity tests demonstrated the reliability of significant causal relationships. Conclusions Overall, lifetime elevated PM2.5 concentration increases the risk of hospitalized COVID-19 and very severe COVID-19. Therefore, controlling air pollution may help mitigate COVID-19 progression.
Collapse
Affiliation(s)
- Youjie Zeng
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
| | - Ke Pang
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
| | - Si Cao
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
| | - Guoxin Lin
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
| | - Juan Tang
- Department of Nephrology, Third Xiangya Hospital, Central South University, Critical Kidney Disease Research Center of Central South University, Changsha, 410013, China
| |
Collapse
|
5
|
Zhang J, Chen Z, Shan D, Wu Y, Zhao Y, Li C, Shu Y, Linghu X, Wang B. Adverse effects of exposure to fine particles and ultrafine particles in the environment on different organs of organisms. J Environ Sci (China) 2024; 135:449-473. [PMID: 37778818 DOI: 10.1016/j.jes.2022.08.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 08/04/2022] [Accepted: 08/08/2022] [Indexed: 10/03/2023]
Abstract
Particulate pollution is a global risk factor that seriously threatens human health. Fine particles (FPs) and ultrafine particles (UFPs) have small particle diameters and large specific surface areas, which can easily adsorb metals, microorganisms and other pollutants. FPs and UFPs can enter the human body in multiple ways and can be easily and quickly absorbed by the cells, tissues and organs. In the body, the particles can induce oxidative stress, inflammatory response and apoptosis, furthermore causing great adverse effects. Epidemiological studies mainly take the population as the research object to study the distribution of diseases and health conditions in a specific population and to focus on the identification of influencing factors. However, the mechanism by which a substance harms the health of organisms is mainly demonstrated through toxicological studies. Combining epidemiological studies with toxicological studies will provide a more systematic and comprehensive understanding of the impact of PM on the health of organisms. In this review, the sources, compositions, and morphologies of FPs and UFPs are briefly introduced in the first part. The effects and action mechanisms of exposure to FPs and UFPs on the heart, lungs, brain, liver, spleen, kidneys, pancreas, gastrointestinal tract, joints and reproductive system are systematically summarized. In addition, challenges are further pointed out at the end of the paper. This work provides useful theoretical guidance and a strong experimental foundation for investigating and preventing the adverse effects of FPs and UFPs on human health.
Collapse
Affiliation(s)
- Jianwei Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Zhao Chen
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Dan Shan
- Department of Medical, Tianjin Stomatological Hospital, School of Medicine, Nankai University, Tianjin 300041, China
| | - Yang Wu
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Yue Zhao
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Chen Li
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China; National Demonstration Center for Experimental Preventive Medicine Education (Tianjin Medical University), Tianjin 300070, China
| | - Yue Shu
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Xiaoyu Linghu
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Baiqi Wang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China; National Demonstration Center for Experimental Preventive Medicine Education (Tianjin Medical University), Tianjin 300070, China.
| |
Collapse
|
6
|
Houweling L, Maitland-Van der Zee AH, Holtjer JCS, Bazdar S, Vermeulen RCH, Downward GS, Bloemsma LD. The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2024; 240:117351. [PMID: 37852458 DOI: 10.1016/j.envres.2023.117351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/06/2023] [Accepted: 10/07/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes. METHODS On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality. RESULTS A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality. CONCLUSION This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.
Collapse
Affiliation(s)
- Laura Houweling
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Anke-Hilse Maitland-Van der Zee
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Judith C S Holtjer
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands
| | - Somayeh Bazdar
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Roel C H Vermeulen
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - George S Downward
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Lizan D Bloemsma
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| |
Collapse
|
7
|
Feng B, Wang W, Zhou B, Zhou Y, Wang J, Liao F. Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 324:121418. [PMID: 36898647 PMCID: PMC9994533 DOI: 10.1016/j.envpol.2023.121418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/06/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM2.5, O3, SO2, NO2, and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM2.5 and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO2 and SO2 were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner.
Collapse
Affiliation(s)
- Benying Feng
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China
| | - Wei Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Bo Zhou
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China
| | - Ying Zhou
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China
| | - Jinyu Wang
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China
| | - Fang Liao
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, 610072, China.
| |
Collapse
|
8
|
Yang Y, Wu S, Wang Y, Shao F, Lv P, Li R, Zhao X, Zhang J, Zhang X, Li J, Hou L, Xu J, Chen W. Lung-Targeted Transgene Expression of Nanocomplexed Ad5 Enhances Immune Response in the Presence of Preexisting Immunity. ENGINEERING (BEIJING, CHINA) 2023:S2095-8099(23)00010-3. [PMID: 36714358 PMCID: PMC9869631 DOI: 10.1016/j.eng.2022.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/26/2022] [Accepted: 12/12/2022] [Indexed: 06/18/2023]
Abstract
Recombinant adenovirus serotype 5 (Ad5) vector has been widely applied in vaccine development targeting infectious diseases, such as Ebola virus disease and coronavirus disease 2019 (COVID-19). However, the high prevalence of preexisting anti-vector immunity compromises the immunogenicity of Ad5-based vaccines. Thus, there is a substantial unmet need to minimize preexisting immunity while improving the insert-induced immunity of Ad5 vectors. Herein, we address this need by utilizing biocompatible nanoparticles to modulate Ad5-host interactions. We show that positively charged human serum albumin nanoparticles ((+)HSAnp), which are capable of forming a complex with Ad5, significantly increase the transgene expression of Ad5 in both coxsackievirus-adenovirus receptor-positive and -negative cells. Furthermore, in charge- and dose-dependent manners, Ad5/(+)HSAnp complexes achieve robust (up to 227-fold higher) and long-term (up to 60 days) transgene expression in the lungs of mice following intranasal instillation. Importantly, in the presence of preexisting anti-Ad5 immunity, complexed Ad5-based Ebola and COVID-19 vaccines significantly enhance antigen-specific humoral response and mucosal immunity. These findings suggest that viral aggregation and charge modification could be leveraged to engineer enhanced viral vectors for vaccines and gene therapies.
Collapse
Affiliation(s)
- Yilong Yang
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Shipo Wu
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Yudong Wang
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Fangze Shao
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Peng Lv
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Ruihua Li
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Xiaofan Zhao
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Jun Zhang
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Xiaopeng Zhang
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Jianmin Li
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Lihua Hou
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Junjie Xu
- Beijing Institute of Biotechnology, Beijing 100071, China
| | - Wei Chen
- Beijing Institute of Biotechnology, Beijing 100071, China
| |
Collapse
|
9
|
Cazzolla Gatti R, Di Paola A, Monaco A, Velichevskaya A, Amoroso N, Bellotti R. The spatial association between environmental pollution and long-term cancer mortality in Italy. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 855:158439. [PMID: 36113788 DOI: 10.1016/j.scitotenv.2022.158439] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/18/2022] [Accepted: 08/28/2022] [Indexed: 06/15/2023]
Abstract
Tumours are nowadays the second world‑leading cause of death after cardiovascular diseases. During the last decades of cancer research, lifestyle and random/genetic factors have been blamed for cancer mortality, with obesity, sedentary habits, alcoholism, and smoking contributing as supposed major causes. However, there is an emerging consensus that environmental pollution should be considered one of the main triggers. Unfortunately, all this preliminary scientific evidence has not always been followed by governments and institutions, which still fail to pursue research on cancer's environmental connections. In this unprecedented national-scale detailed study, we analyzed the links between cancer mortality, socio-economic factors, and sources of environmental pollution in Italy, both at wider regional and finer provincial scales, with an artificial intelligence approach. Overall, we found that cancer mortality does not have a random or spatial distribution and exceeds the national average mainly when environmental pollution is also higher, despite healthier lifestyle habits. Our machine learning analysis of 35 environmental sources of pollution showed that air quality ranks first for importance concerning the average cancer mortality rate, followed by sites to be reclaimed, urban areas, and motor vehicle density. Moreover, other environmental sources of pollution proved to be relevant for the mortality of some specific cancer types. Given these alarming results, we call for a rearrangement of the priority of cancer research and care that sees the reduction and prevention of environmental contamination as a priority action to put in place in the tough struggle against cancer.
Collapse
Affiliation(s)
- Roberto Cazzolla Gatti
- Department of Biological Sciences, Geological and Environmental (BiGeA), Alma Mater Studiorum - University of Bologna, 40126 Bologna, Italy
| | - Arianna Di Paola
- Institute for BioEconomy, National Research Council of Italy (IBE-CNR), 00100 Rome, Italy
| | - Alfonso Monaco
- Dipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "A. Moro", 70126 Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.
| | | | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy; Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari "A. Moro", 70125 Bari, Italy
| | - Roberto Bellotti
- Dipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "A. Moro", 70126 Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy
| |
Collapse
|
10
|
Hernandez Carballo I, Bakola M, Stuckler D. The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America. ENVIRONMENTAL RESEARCH 2022; 215:114155. [PMID: 36030916 PMCID: PMC9420033 DOI: 10.1016/j.envres.2022.114155] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 08/16/2022] [Accepted: 08/17/2022] [Indexed: 05/29/2023]
Abstract
BACKGROUND Air pollution is speculated to increase the risks of COVID-19 spread, severity, and mortality. OBJECTIVES We systematically reviewed studies investigating the relationship between air pollution and COVID-19 cases, non-fatal severity, and mortality in North America and Europe. METHODS We searched PubMed, Web of Science, and Scopus for studies investigating the effects of harmful pollutants, including particulate matter with diameter ≤2.5 or 10 μm (PM2.5 or PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO), on COVID-19 cases, severity, and deaths in Europe and North America through to June 19, 2021. Articles were included if they quantitatively measured the relationship between exposure to air pollution and COVID-19 health outcomes. RESULTS From 2,482 articles screened, we included 116 studies reporting 355 separate pollutant-COVID-19 estimates. Approximately half of all evaluations on incidence were positive and significant associations (52.7%); for mortality the corresponding figure was similar (48.1%), while for non-fatal severity this figure was lower (41.2%). Longer-term exposure to pollutants appeared more likely to be positively associated with COVID-19 incidence (63.8%). PM2.5, PM10, O3, NO2, and CO were most strongly positively associated with COVID-19 incidence, while PM2.5 and NO2 with COVID-19 deaths. All studies were observational and most exhibited high risk of confounding and outcome measurement bias. DISCUSSION Air pollution may be associated with worse COVID-19 outcomes. Future research is needed to better test the air pollution-COVID-19 hypothesis, particularly using more robust study designs and COVID-19 measures that are less prone to measurement error and by considering co-pollutant interactions.
Collapse
Affiliation(s)
- Ireri Hernandez Carballo
- Department of Social and Political Sciences, Bocconi University, Milan, Lombardy, Italy; RFF-CMCC European Institute of Economics and the Environment, Centro Euro-Mediterraneo Sui Cambiamenti Climatici, Milan, Lombardy, Italy.
| | - Maria Bakola
- Research Unit for General Medicine and Primary Health Care, Faculty of Medicine, School of Health Science, University of Ioannina, Ioannina, Greece
| | - David Stuckler
- Department of Social and Political Sciences, Bocconi University, Milan, Lombardy, Italy; DONDENA Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Lombardy, Italy
| |
Collapse
|
11
|
Puertas R, Carracedo P, Marti L. Environmental policies for the treatment of waste generated by COVID-19: Text mining review. WASTE MANAGEMENT & RESEARCH : THE JOURNAL OF THE INTERNATIONAL SOLID WASTES AND PUBLIC CLEANSING ASSOCIATION, ISWA 2022; 40:1480-1493. [PMID: 35282720 DOI: 10.1177/0734242x221084073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The rapid transmission of COVID-19 has meant that all economic and human efforts have been focused on confronting it, ignoring environmental aspects whose consequences are causing adverse situations all over the planet. The saturation of the sanitary system and confinement measures have multiplied the waste generated, which implies the need to adapt environmental policies to this new situation caused by the pandemic. It is a review article whose objective was to identify the environmental policies that would facilitate an adequate treatment of the waste generated by the pandemic. It was proposed to analyse the current lines of research developed on this paradigm, applying the text mining methodology. A systematic review of 111 studies published in environmental journals indexed in the Web of Science was carried out. The results identified three areas of interest: knowledge of transmission routes, management of the massive generation of plastics and appropriate treatment of solid waste in extreme situations. Leaders are called upon to implement the contingency plans to sustainably alleviate the enormous waste burden caused by society's adaptation to the restrictions imposed by the pandemic. Specifically, innovation aimed at achieving the reuse of medical products, the promotion of the circular economy and educational campaigns to promote clean environments should be encouraged.
Collapse
Affiliation(s)
- Rosa Puertas
- Universitat Politècnica de València, Valencia, Spain
| | | | - Luisa Marti
- Universitat Politècnica de València, Valencia, Spain
| |
Collapse
|
12
|
Zorena K, Jaskulak M, Michalska M, Mrugacz M, Vandenbulcke F. Air Pollution, Oxidative Stress, and the Risk of Development of Type 1 Diabetes. Antioxidants (Basel) 2022; 11:1908. [PMID: 36290631 PMCID: PMC9598917 DOI: 10.3390/antiox11101908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/19/2022] [Accepted: 09/21/2022] [Indexed: 11/25/2022] Open
Abstract
Despite multiple studies focusing on environmental factors conducive to the development of type 1 diabetes mellitus (T1DM), knowledge about the involvement of long-term exposure to air pollution seems insufficient. The main focus of epidemiological studies is placed on the relationship between exposure to various concentrations of particulate matter (PM): PM1, PM2.5, PM10, and sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (O3), versus the risk of T1DM development. Although the specific molecular mechanism(s) behind the link between increased air pollution exposure and a higher risk of diabetes and metabolic dysfunction is yet unknown, available data indicate air pollution-induced inflammation and oxidative stress as a significant pathway. The purpose of this paper is to assess recent research examining the association between inhalation exposure to PM and associated metals and the increasing rates of T1DM worldwide. The development of modern and more adequate methods for air quality monitoring is also introduced. A particular emphasis on microsensors, mobile and autonomous measuring platforms, satellites, and innovative approaches of IoT, 5G connections, and Block chain technologies are also presented. Reputable databases, including PubMed, Scopus, and Web of Science, were used to search for relevant literature. Eligibility criteria involved recent publication years, particularly publications within the last five years (except for papers presenting a certain novelty or mechanism for the first time). Population, toxicological and epidemiological studies that focused particularly on fine and ultra-fine PM and associated ambient metals, were preferred, as well as full-text publications.
Collapse
Affiliation(s)
- Katarzyna Zorena
- Department of Immunobiology and Environment Microbiology, Faculty of Health Sciences, Institute of Maritime and Tropical Medicine, Medical University of Gdańsk, Dębinki 7, 80-210 Gdańsk, Poland
| | - Marta Jaskulak
- Department of Immunobiology and Environment Microbiology, Faculty of Health Sciences, Institute of Maritime and Tropical Medicine, Medical University of Gdańsk, Dębinki 7, 80-210 Gdańsk, Poland
| | - Małgorzata Michalska
- Department of Immunobiology and Environment Microbiology, Faculty of Health Sciences, Institute of Maritime and Tropical Medicine, Medical University of Gdańsk, Dębinki 7, 80-210 Gdańsk, Poland
| | - Małgorzata Mrugacz
- Department of Ophthalmology and Eye Rehabilitation, Medical University of Bialystok, Kilinskiego 1, 15-089 Białystok, Poland
| | - Franck Vandenbulcke
- Laboratoire de Génie Civil et Géo-Environnement, Univ. Lille, IMT Lille Douai, University Artois, YncreaHauts-de-France, ULR4515-LGCgE, F-59000 Lille, France
| |
Collapse
|
13
|
Song Y, Chen X, Zhang Z, Cao S, Du T, Guo H. Research on a push-pull industrial trough-side exhaust hood based on CFD simulation and experiment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 827:154265. [PMID: 35259371 DOI: 10.1016/j.scitotenv.2022.154265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 02/21/2022] [Accepted: 02/27/2022] [Indexed: 06/14/2023]
Abstract
The traditional industrial trough-side exhaust hood requires large energy consumption for one-way airflow because the air inlet and outlet are on both sides of the industrial slot. In this research, based on the improvement of the traditional push-pull trough-side exhaust hood, a double-sided symmetrical push-pull industrial trough-side exhaust hood is researched. Simulation software ICEM and FLUENT were used to research the relationship between the distance of air inlet and outlet and the air volume ratio, and the relationship between the air volume ratio and mass fraction of pollutant gases, using carbon monoxide as the pollutant gas. The research found that when the pollutant mass fraction reaches the specified level, the air inlet and outlet distance is quadratically related to the air volume ratio. When the distance between the inlet and outlet is 0.12 m and the corresponding minimum flow ratio is 1.7, the interference of the suction air outlet pressure on the blowing air outlet jet reaches the minimum. By comparing the energy consumption with the traditional industrial trough-side exhaust hood, the energy saving rate is 75.8% with the same pollutant control effect. The double-sided symmetrical push-pull industrial trough-side exhaust hood reduce the cost of treating and discharging pollutants and provides a new idea for industrial pollutant treatment.
Collapse
Affiliation(s)
- Yanli Song
- Northeastern University, Shenyang, China
| | - Xin Chen
- Shenyang Jianzhu University, Shenyang, China
| | - Zhao Zhang
- Shenyang Jianzhu University, Shenyang, China
| | - Shi Cao
- Shenyang Jianzhu University, Shenyang, China
| | - Tao Du
- Northeastern University, Shenyang, China.
| | - Haifeng Guo
- Shenyang Jianzhu University, Shenyang, China
| |
Collapse
|
14
|
Neo EX, Hasikin K, Mokhtar MI, Lai KW, Azizan MM, Razak SA, Hizaddin HF. Towards Integrated Air Pollution Monitoring and Health Impact Assessment Using Federated Learning: A Systematic Review. Front Public Health 2022; 10:851553. [PMID: 35664109 PMCID: PMC9160600 DOI: 10.3389/fpubh.2022.851553] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 04/01/2022] [Indexed: 12/12/2022] Open
Abstract
Environmental issues such as environmental pollutions and climate change are the impacts of globalization and become debatable issues among academics and industry key players. One of the environmental issues which is air pollution has been catching attention among industrialists, researchers, and communities around the world. However, it has always neglected until the impacts on human health become worse, and at times, irreversible. Human exposure to air pollutant such as particulate matters, sulfur dioxide, ozone and carbon monoxide contributed to adverse health hazards which result in respiratory diseases, cardiorespiratory diseases, cancers, and worst, can lead to death. This has led to a spike increase of hospitalization and emergency department visits especially at areas with worse pollution cases that seriously impacting human life and health. To address this alarming issue, a predictive model of air pollution is crucial in assessing the impacts of health due to air pollution. It is also critical in predicting the air quality index when assessing the risk contributed by air pollutant exposure. Hence, this systemic review explores the existing studies on anticipating air quality impact to human health using the advancement of Artificial Intelligence (AI). From the extensive review, we highlighted research gaps in this field that are worth to inquire. Our study proposes to develop an AI-based integrated environmental and health impact assessment system using federated learning. This is specifically aims to identify the association of health impact and pollution based on socio-economic activities and predict the Air Quality Index (AQI) for impact assessment. The output of the system will be utilized for hospitals and healthcare services management and planning. The proposed solution is expected to accommodate the needs of the critical and prioritization of sensitive group of publics during pollution seasons. Our finding will bring positive impacts to the society in terms of improved healthcare services quality, environmental and health sustainability. The findings are beneficial to local authorities either in healthcare or environmental monitoring institutions especially in the developing countries.
Collapse
Affiliation(s)
- En Xin Neo
- Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Khairunnisa Hasikin
- Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
- Center of Image and Signal Processing (CISIP), Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Mohd Istajib Mokhtar
- Department of Science and Technology Studies, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Khin Wee Lai
- Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Muhammad Mokhzaini Azizan
- Department of Electrical and Electronic Engineering, Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, Nilai, Malaysia
| | - Sarah Abdul Razak
- Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Hanee Farzana Hizaddin
- Department of Chemical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
| |
Collapse
|
15
|
Fiorito S, Soligo M, Gao Y, Ogulur I, Akdis C, Bonini S. Is the epithelial barrier hypothesis the key to understanding the higher incidence and excess mortality during COVID-19 pandemic? The case of Northern Italy. Allergy 2022; 77:1408-1417. [PMID: 35102595 PMCID: PMC9304271 DOI: 10.1111/all.15239] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/21/2022] [Accepted: 01/27/2022] [Indexed: 01/28/2023]
Abstract
The high incidence and increased mortality of COVID-19 make Italy among the most impacted countries by SARS-CoV-2 outbreak. In the beginning of the pandemic, Northern regions accounted for 40% of cases and 45% of deaths from COVID-19 in Italy. Several factors have been suggested to explain the higher incidence and excess mortality from COVID-19 in these regions. It is noticed that Northern Italian regions, and particularly the cities in Po Valley, are the areas with the highest air pollution due to commercial vehicle traffic, industry and a stagnant meteorological condition, with one of the highest levels in Italy and Europe of fine particulate matter 2.5 micron or smaller in size (PM2.5). PM2.5, the major environmental pollutant deriving mainly by factory and automobile exhaust emissions and coal combustion, increases the expression of angiotensin-converting enzyme 2, the epithelial cell entry receptor for SARS-CoV-2, and thus increase the susceptibility to this virus. The epithelial barrier hypothesis proposes that many diverse diseases may rise from the disruption of epithelial barrier of skin, respiratory tract and gastrointestinal system, including allergic diseases, metabolic and autoimmune diseases, and chronic neuropsychiatric conditions. There is evidence of a close correlation between air pollution and airway epithelial barrier dysfunction. Air pollution, causing lung epithelial barrier dysfunction, may contribute to local chronic inflammation, microbiome dysbiosis and impaired antiviral immune response against SARS-CoV-2, all of which contribute to the high incidence and excess mortality from COVID-19. In addition, air pollution and epithelial barrier dysfunction contribute also to the higher prevalence of several comorbidities of COVID-19, such as diabetes, chronic obstructive pulmonary disease and obesity, which have been identified as risk factors for mortality of COVID-19. In this article, on the basis of epidemiological and environmental monitoring data in Northern Italy, it is suggested that epithelial barrier hypothesis may help to understand the excess burden and mortality from COVID-19.
Collapse
Affiliation(s)
- Silvana Fiorito
- Institute of Translational PharmacologyItalian National Research CouncilRomeItaly
| | - Marzia Soligo
- Institute of Translational PharmacologyItalian National Research CouncilRomeItaly
| | - Yadong Gao
- Department of AllergologyZhongnan Hospital of Wuhan UniversityWuhanChina
| | - Ismail Ogulur
- Swiss Institute of Allergy and Asthma Research (SIAF)University of ZurichDavosSwitzerland
| | - Cezmi A. Akdis
- Swiss Institute of Allergy and Asthma Research (SIAF)University of ZurichDavosSwitzerland
| | - Sergio Bonini
- Institute of Translational PharmacologyItalian National Research CouncilRomeItaly
| |
Collapse
|
16
|
Amoroso N, Cilli R, Maggipinto T, Monaco A, Tangaro S, Bellotti R. Satellite data and machine learning reveal a significant correlation between NO 2 and COVID-19 mortality. ENVIRONMENTAL RESEARCH 2022; 204:111970. [PMID: 34474031 PMCID: PMC8403556 DOI: 10.1016/j.envres.2021.111970] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/30/2021] [Accepted: 08/21/2021] [Indexed: 06/13/2023]
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic has officially spread all over the world since the beginning of 2020. Although huge efforts are addressed by scientists to shed light over the several questions raised by the novel SARS-CoV-2 virus, many aspects need to be clarified, yet. In particular, several studies have pointed out significant variations between countries in per-capita mortality. In this work, we investigated the association between COVID-19 mortality with climate variables and air pollution throughout European countries using the satellite remote sensing images provided by the Sentinel-5p mission. We analyzed data collected for two years of observations and extracted the concentrations of several pollutants; we used these measurements to feed a Random Forest regression. We performed a cross-validation analysis to assess the robustness of the model and compared several regression strategies. Our findings reveal a significant statistical association between air pollution (NO2) and COVID-19 mortality and a significant role played by the socio-demographic features, like the number of nurses or the hospital beds and the gross domestic product per capita.
Collapse
Affiliation(s)
- Nicola Amoroso
- Dipartimento di Farmacia - Scienze del Farmaco, Università di Bari, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy
| | - Roberto Cilli
- Dipartimento Interateneo di Fisica, Università di Bari, Bari, Italy
| | - Tommaso Maggipinto
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento Interateneo di Fisica, Università di Bari, Bari, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy.
| | - Sabina Tangaro
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università di Bari, Bari, Italy
| | - Roberto Bellotti
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento Interateneo di Fisica, Università di Bari, Bari, Italy
| |
Collapse
|
17
|
Interpolation-Based Fusion of Sentinel-5P, SRTM, and Regulatory-Grade Ground Stations Data for Producing Spatially Continuous Maps of PM2.5 Concentrations Nationwide over Thailand. ATMOSPHERE 2022. [DOI: 10.3390/atmos13020161] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Atmospheric pollution has recently drawn significant attention due to its proven adverse effects on public health and the environment. This concern has been aggravated specifically in Southeast Asia due to increasing vehicular use, industrial activity, and agricultural burning practices. Consequently, elevated PM2.5 concentrations have become a matter of intervention for national authorities who have addressed the needs of monitoring air pollution by operating ground stations. However, their spatial coverage is limited and the installation and maintenance are costly. Therefore, alternative approaches are necessary at national and regional scales. In the current paper, we investigated interpolation models to fuse PM2.5 measurements from ground stations and satellite data in an attempt to produce spatially continuous maps of PM2.5 nationwide over Thailand. Four approaches are compared, namely the inverse distance weighted (IDW), ordinary kriging (OK), random forest (RF), and random forest combined with OK (RFK) leveraging on the NO2, SO2, CO, HCHO, AI, and O3 products from the Sentinel-5P satellite, regulatory-grade ground PM2.5 measurements, and topographic parameters. The results suggest that RFK is the most robust, especially when the pollution levels are moderate or extreme, achieving an RMSE value of 7.11 μg/m3 and an R2 value of 0.77 during a 10-day long period in February, and an RMSE of 10.77 μg/m3 and R2 and 0.91 during the entire month of March. The proposed approach can be adopted operationally and expanded by leveraging regulatory-grade stations, low-cost sensors, as well as upcoming satellite missions such as the GEMS and the Sentinel-5.
Collapse
|
18
|
Monaco A, Pantaleo E, Amoroso N, Bellantuono L, Stella A, Bellotti R. Country-level factors dynamics and ABO/Rh blood groups contribution to COVID-19 mortality. Sci Rep 2021; 11:24527. [PMID: 34972836 PMCID: PMC8720090 DOI: 10.1038/s41598-021-04162-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 12/15/2021] [Indexed: 11/08/2022] Open
Abstract
The identification of factors associated to COVID-19 mortality is important to design effective containment measures and safeguard at-risk categories. In the last year, several investigations have tried to ascertain key features to predict the COVID-19 mortality tolls in relation to country-specific dynamics and population structure. Most studies focused on the first wave of the COVID-19 pandemic observed in the first half of 2020. Numerous studies have reported significant associations between COVID-19 mortality and relevant variables, for instance obesity, healthcare system indicators such as hospital beds density, and bacillus Calmette-Guerin immunization. In this work, we investigated the role of ABO/Rh blood groups at three different stages of the pandemic while accounting for demographic, economic, and health system related confounding factors. Using a machine learning approach, we found that the "B+" blood group frequency is an important factor at all stages of the pandemic, confirming previous findings that blood groups are linked to COVID-19 severity and fatal outcome.
Collapse
Affiliation(s)
- Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125, Bari, Italy
| | - Ester Pantaleo
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125, Bari, Italy
- Dipartimento di Scienze mediche di base, Neuroscienze e organi di senso, Piazza G. Cesare 11, 70124, Bari, Italy
- Dipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "'Aldo Moro", Via G. Amendola 173, 70125, Bari, Italy
| | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125, Bari, Italy
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli Studi di Bari "Aldo Moro", Via A. Orabona 4, 70125, Bari, Italy
| | - Loredana Bellantuono
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125, Bari, Italy
- Dipartimento di Scienze mediche di base, Neuroscienze e organi di senso, Piazza G. Cesare 11, 70124, Bari, Italy
| | - Alessandro Stella
- Dipartimento di Scienze biomediche e oncologia umana, Università degli Studi di Bari "Aldo Moro", Bari, Italy.
| | - Roberto Bellotti
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125, Bari, Italy
- Dipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "'Aldo Moro", Via G. Amendola 173, 70125, Bari, Italy
| |
Collapse
|
19
|
Analyzing the Contribution of Human Mobility to Changes in Air Pollutants: Insights from the COVID-19 Lockdown in Wuhan. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2021. [DOI: 10.3390/ijgi10120836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
During the COVID-19 lockdown in Wuhan, transportation, industrial production and other human activities declined significantly, as did the NO2 concentration. In order to assess the relative contributions of different factors to reductions in air pollutants, we implemented sensitivity experiments by Random Forest (RF) models, with the comparison of the contributions of meteorological conditions, human mobility, and emissions from industry and households between different periods. In addition, we conducted scenario analyses to suggest an appropriate limit for control of human mobility. Different mechanisms for air pollutants were shown in the pre-pandemic, pre-lockdown, lockdown, and post-pandemic periods. Wind speed and the Within-city Migration index, representing intra-city mobility intensity, were excluded from stepwise multiple linear models in the pre-lockdown and lockdown periods. The results of sensitivity experiments show that, in the COVID-19 lockdown period, 73.3% of the reduction can be attributed to decreased human mobility. In the post-pandemic period, meteorological conditions control about 42.2% of the decrease, and emissions from industry and households control 40.0%, while human mobility only contributes 17.8%. The results of the scenario analysis suggest that the priority of restriction should be given to human mobility within the city than other kinds of human mobility. The reduction in the NO2 concentration tends to be smaller when human mobility within the city decreases by more than 70%. A limit of less than 40% on the control of the human mobility can achieve a better effect, especially in cities with severe traffic pollution.
Collapse
|
20
|
Hadei M, Hopke PK, Shahsavani A, Raeisi A, Jafari AJ, Yarahmadi M, Farhadi M, Rahmatinia M, Bazazpour S, Bandpey AM, Zali A, Kermani M, Vaziri MH, Aghazadeh M. Effect of short-term exposure to air pollution on COVID-19 mortality and morbidity in Iranian cities. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2021; 19:1807-1816. [PMID: 34729185 PMCID: PMC8553398 DOI: 10.1007/s40201-021-00736-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 08/30/2021] [Indexed: 05/14/2023]
Abstract
PURPOSE The association between air pollutant (PM2.5, PM10, NO2, and O3) concentrations and daily number of COVID-19 confirmed cases and related deaths were evaluated in three major Iranian cities (Tehran, Mashhad, and Tabriz). METHODS Hourly concentrations of air pollutants and daily number of PCR-confirmed cases and deaths of COVID-19 were acquired (February 20th, 2020 to January 4th, 2021). A generalized additive model (GAM) assuming a quasi-Poisson distribution was used to model the associations in each city up to lag-day 7 (for mortality) and 14 (for morbidity). Then, the city-specific estimates were meta-analyzed using a fixed effect model to obtain the overall relative risks (RRs). RESULTS A total of 114,964 confirmed cases and 21,549 deaths were recorded in these cities. For confirmed cases, exposure to PM2.5, NO2, and O3 for several lag-days showed significant associations. In case of mortality, meta-analysis estimated that the RRs for PM2.5, PM10, NO2, and O3 concentrations were 1.06 (95% CI: 0.99, 1.13), 1.06 (95% CI: 0.93, 1.19), 1.15 (95% CI: 0.93, 1.38), and 1.07 (95% CI: 0.84, 1.31), respectively. Despite several positive associations with all air pollutants over multiple lag-days, COVID-19 mortality was only significantly associated with NO2 on lag-days 0-1 and 1 with the RRs of 1.35 (95% CI: 1.04, 1.67) and 1.16 (95% CI: 1.02, 1.31), respectively. CONCLUSION This study showed that air pollution can be a factor exacerbating COVID-19 infection and clinical outcomes. Actions should be taken to reduce the exposure of the public and particularly patients to ambient air pollutants. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40201-021-00736-4.
Collapse
Affiliation(s)
- Mostafa Hadei
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Philip K. Hopke
- Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY 13699 USA
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642 USA
| | - Abbas Shahsavani
- Air Quality and Climate Change Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Alireza Raeisi
- Department of Internal Medicine, School of Medicine, Tehran University of Medical Sciences, Shiraz, Iran
| | - Ahmad Jonidi Jafari
- Research Center for Environmental Health Technology, Iran University of Medical Sciences, Tehran, Iran
| | - Maryam Yarahmadi
- Environmental and Occupational Health Center, Ministry of Health and Medical Education, Tehran, Iran
| | - Mohsen Farhadi
- Environmental and Occupational Health Center, Ministry of Health and Medical Education, Tehran, Iran
| | - Masoumeh Rahmatinia
- Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Shahriar Bazazpour
- Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Alireza Zali
- Department of Neurosurgery, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Majid Kermani
- Research Center for Environmental Health Technology, Iran University of Medical Sciences, Tehran, Iran
| | - Mohmmad Hossien Vaziri
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehrab Aghazadeh
- Environmental and Occupational Health Center, Ministry of Health and Medical Education, Tehran, Iran
| |
Collapse
|
21
|
Ravina M, Esfandabadi ZS, Panepinto D, Zanetti M. Traffic-induced atmospheric pollution during the COVID-19 lockdown: Dispersion modeling based on traffic flow monitoring in Turin, Italy. JOURNAL OF CLEANER PRODUCTION 2021; 317:128425. [PMID: 34316101 PMCID: PMC8297952 DOI: 10.1016/j.jclepro.2021.128425] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 05/20/2021] [Accepted: 07/21/2021] [Indexed: 05/19/2023]
Abstract
The COVID-19 pandemic, as a worldwide threat to public health, has led many governments to impose mobility restrictions and adopt partial or full lockdown strategies in many regions to control the disease outbreak. Although these lockdowns are imposed to save public health by reducing the transmission of the virus, rather significant improvements of the air quality in this period have been reported in different areas, mainly as a result of the reduction in vehicular trips. In this research, the city of Turin in the northern part of Italy has been considered as the study area, because of its special meteorology and geographic location in one of the most polluted regions in Europe, and also its high density of vehicular emissions. A Lagrangian approach is applied to illustrate and analyze the effect of imposing full lockdown restrictions on the reduction of traffic-induced air pollution in the city. To do this, the real-time traffic flow during the lockdown period is recorded, and by utilizing CALPUFF version 7, the dispersion of PM2.5, Total Suspended Particulate (TSP), Benzo(a)pyrene (BaP), NOx, and Black Carbon (BC) emitted from all circulating vehicles during and before the lockdown period are compared. Results indicate that the concentration of pollutants generated by road traffic sources (including passenger cars, busses, heavy-duty vehicles, light-duty vehicles, mopeds, and motorcycles) reduced at least 70% (for PM2.5) up to 88.1% (for BaP) during the studied period. Concentration maps show that the concentration reduction varied in different areas of the town, mainly due to the characteristics and strength of the emission sources and the geophysical features of the area.
Collapse
Affiliation(s)
- Marco Ravina
- Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129, Torino, Italy
| | - Zahra Shams Esfandabadi
- Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129, Torino, Italy
- Energy Center Lab, Politecnico di Torino, Via Paolo Borsellino 38/16, 10138, Torino, Italy
| | - Deborah Panepinto
- Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129, Torino, Italy
| | - Mariachiara Zanetti
- Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129, Torino, Italy
| |
Collapse
|
22
|
Mendoza DL, Benney TM, Bares R, Crosman ET. Intra-city variability of fine particulate matter during COVID-19 lockdown: A case study from Park City, Utah. ENVIRONMENTAL RESEARCH 2021; 201:111471. [PMID: 34102162 PMCID: PMC8178539 DOI: 10.1016/j.envres.2021.111471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 05/20/2021] [Accepted: 05/26/2021] [Indexed: 06/12/2023]
Abstract
Urban air quality is a growing concern due a range of social, economic, and health impacts. Since the SARS-CoV-19 pandemic began in 2020, governments have produced a range of non-medical interventions (NMIs) (e.g. lockdowns, stay-at-home orders, mask mandates) to prevent the spread of COVID-19. A co-benefit of NMI implementation has been the measurable improvement in air quality in cities around the world. Using the lockdown policy of the COVID-19 pandemic as a natural experiment, we traced the changing emissions patterns produced under the pandemic in a mid-sized, high-altitude city to isolate the effects of human behavior on air pollution. We tracked air pollution over time periods reflecting the Pre-Lockdown, Lockdown, and Reopening stages, using high quality, research grade sensors in both commercial and residential areas to better understand how each setting may be uniquely impacted by pollution downturn events. Based on this approach, we found the commercial area of the city showed a greater decrease in air pollution than residential areas during the lockdown period, while both areas experienced a similar rebound post lockdown. The easing period following the lockdown did not lead to an immediate rebound in human activity and the air pollution increase associated with reopening, took place nearly two months after the lockdown period ended. We hypothesize that differences in heating needs, travel demands, and commercial activity, are responsible for the corresponding observed changes in the spatial distribution of pollutants over the study period. This research has implications for climate policy, low-carbon energy transitions, and may even impact local policy due to changing patterns in human exposure that could lead to important public health outcomes, if left unaddressed.
Collapse
Affiliation(s)
- Daniel L Mendoza
- Department of Atmospheric Sciences, University of Utah, 135 S 1460 E, Room 819, Salt Lake City, UT 84112, USA; Department of City & Metropolitan Planning, University of Utah, 375 S 1530 E, Suite 220, Salt Lake City, UT 84112, USA; University of Utah School of Medicine, Pulmonary Division, 26 N 1900 E, Salt Lake City, UT 84132, USA.
| | - Tabitha M Benney
- Department of Political Science and Environmental Studies Program, University of Utah, 260 S Central Campus Drive, Salt Lake City, UT 84112, USA
| | - Ryan Bares
- Department of Atmospheric Sciences, University of Utah, 135 S 1460 E, Room 819, Salt Lake City, UT 84112, USA
| | - Erik T Crosman
- Department of Life, Earth and Environmental Sciences, West Texas A&M University, Natural Sciences Building 324, Canyon, TX 79016, USA
| |
Collapse
|
23
|
Sharma GD, Tiwari AK, Jain M, Yadav A, Srivastava M. COVID-19 and environmental concerns: A rapid review. RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2021; 148:111239. [PMID: 34234623 PMCID: PMC8189823 DOI: 10.1016/j.rser.2021.111239] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 05/03/2021] [Accepted: 05/17/2021] [Indexed: 05/02/2023]
Abstract
COVID-19 has slowed global economic growth and consequently impacted the environment as well. Parallelly, the environment also influences the transmission of this novel coronavirus through various factors. Every nation deals with varied population density and size; air quality and pollutants; the nature of land and water, which significantly impact the transmission of coronavirus. The WHO (Ziaeepour et al., 2008) [1] has recommended rapid reviews to provide timely evidence to the policymakers to respond to the emergency. The present study follows a rapid review along with a brief bibliometric analysis of 328 research papers, which synthesizes the evidence regarding the environmental concerns of COVID-19. The novel contribution of this rapid review is threefold. One, we take stock of the diverse findings as regards the transmission of the novel coronavirus in different types of environments for providing conclusive directions to the ongoing debate regarding the transmission of the virus. Two, our findings provide topical insights as well as methodological guidance for future researchers in the field. Three, we inform the policymakers on the efficacy of environmental measures for controlling the spread of COVID-19.
Collapse
Affiliation(s)
- Gagan Deep Sharma
- University School of Management Studies, Guru Gobind Singh Indraprastha University, Sector 16 C, Dwarka, New Delhi, India
| | | | - Mansi Jain
- University School of Management Studies, Guru Gobind Singh Indraprastha University, Sector 16 C, Dwarka, New Delhi, India
| | - Anshita Yadav
- University School of Management Studies, Guru Gobind Singh Indraprastha University, Sector 16 C, Dwarka, New Delhi, India
| | - Mrinalini Srivastava
- University School of Management Studies, Guru Gobind Singh Indraprastha University, Sector 16 C, Dwarka, New Delhi, India
| |
Collapse
|
24
|
Shao L, Ge S, Jones T, Santosh M, Silva LFO, Cao Y, Oliveira MLS, Zhang M, BéruBé K. The role of airborne particles and environmental considerations in the transmission of SARS-CoV-2. GEOSCIENCE FRONTIERS 2021; 12:101189. [PMID: 38620834 PMCID: PMC8020609 DOI: 10.1016/j.gsf.2021.101189] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 03/15/2021] [Accepted: 03/17/2021] [Indexed: 05/06/2023]
Abstract
Corona Virus Disease 2019 (COVID-19) caused by the novel coronavirus, results in an acute respiratory condition coronavirus 2 (SARS-CoV-2) and is highly infectious. The recent spread of this virus has caused a global pandemic. Currently, the transmission routes of SARS-CoV-2 are being established, especially the role of environmental transmission. Here we review the environmental transmission routes and persistence of SARS-CoV-2. Recent studies have established that the transmission of this virus may occur, amongst others, in the air, water, soil, cold-chain, biota, and surface contact. It has also been found that the survival potential of the SARS-CoV-2 virus is dependent on different environmental conditions and pollution. Potentially important pathways include aerosol and fecal matter. Particulate matter may also be a carrier for SARS-CoV-2. Since microscopic particles can be easily absorbed by humans, more attention must be focused on the dissemination of these particles. These considerations are required to evolve a theoretical platform for epidemic control and to minimize the global threat from future epidemics.
Collapse
Affiliation(s)
- Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Shuoyi Ge
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Tim Jones
- School of Earth and Environmental Sciences, Cardiff University, Museum Avenue, Cardiff, CF10 3YE, UK
| | - M Santosh
- School of Earth Sciences and Resources, China University of Geosciences Beijing, Beijing 100083, China
- Department of Earth Science, University of Adelaide, Adelaide, SA 5005, Australia
| | - Luis F O Silva
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
| | - Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Marcos L S Oliveira
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
- Departamento de Ingeniería Civil y Arquitectura, Universidad de Lima, Avenida Javier Prado Este 4600 - Santiago de, Surco 1503, Peru
| | - Mengyuan Zhang
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, Wales, UK
| |
Collapse
|
25
|
Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. J Am Med Inform Assoc 2021; 28:2050-2067. [PMID: 34151987 PMCID: PMC8344463 DOI: 10.1093/jamia/ocab098] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 05/03/2021] [Accepted: 05/06/2021] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE To summarize how artificial intelligence (AI) is being applied in COVID-19 research and determine whether these AI applications integrated heterogenous data from different sources for modeling. MATERIALS AND METHODS We searched 2 major COVID-19 literature databases, the National Institutes of Health's LitCovid and the World Health Organization's COVID-19 database on March 9, 2021. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, 2 reviewers independently reviewed all the articles in 2 rounds of screening. RESULTS In the 794 studies included in the final qualitative analysis, we identified 7 key COVID-19 research areas in which AI was applied, including disease forecasting, medical imaging-based diagnosis and prognosis, early detection and prognosis (non-imaging), drug repurposing and early drug discovery, social media data analysis, genomic, transcriptomic, and proteomic data analysis, and other COVID-19 research topics. We also found that there was a lack of heterogenous data integration in these AI applications. DISCUSSION Risk factors relevant to COVID-19 outcomes exist in heterogeneous data sources, including electronic health records, surveillance systems, sociodemographic datasets, and many more. However, most AI applications in COVID-19 research adopted a single-sourced approach that could omit important risk factors and thus lead to biased algorithms. Integrating heterogeneous data for modeling will help realize the full potential of AI algorithms, improve precision, and reduce bias. CONCLUSION There is a lack of data integration in the AI applications in COVID-19 research and a need for a multilevel AI framework that supports the analysis of heterogeneous data from different sources.
Collapse
Affiliation(s)
- Yi Guo
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA
- Cancer Informatics Shared Resource, University of Florida Health Cancer Center, Gainesville, Florida, USA
| | - Yahan Zhang
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Tianchen Lyu
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA
- Cancer Informatics Shared Resource, University of Florida Health Cancer Center, Gainesville, Florida, USA
| | - Mattia Prosperi
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Hua Xu
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA
- Cancer Informatics Shared Resource, University of Florida Health Cancer Center, Gainesville, Florida, USA
| |
Collapse
|
26
|
Cazzolla Gatti R. Why We Will Continue to Lose Our Battle with Cancers If We Do Not Stop Their Triggers from Environmental Pollution. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:6107. [PMID: 34198930 PMCID: PMC8201328 DOI: 10.3390/ijerph18116107] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/21/2021] [Accepted: 06/01/2021] [Indexed: 12/11/2022]
Abstract
Besides our current health concerns due to COVID-19, cancer is a longer-lasting and even more dramatic pandemic that affects almost a third of the human population worldwide. Most of the emphasis on its causes has been posed on genetic predisposition, chance, and wrong lifestyles (mainly, obesity and smoking). Moreover, our medical weapons against cancers have not improved too much during the last century, although research is in progress. Once diagnosed with a malignant tumour, we still rely on surgery, radiotherapy, and chemotherapy. The main problem is that we have focused on fighting a difficult battle instead of preventing it by controlling its triggers. Quite the opposite, our knowledge of the links between environmental pollution and cancer has surged from the 1980s. Carcinogens in water, air, and soil have continued to accumulate disproportionally and grow in number and dose, bringing us to today's carnage. Here, a synthesis and critical review of the state of the knowledge of the links between cancer and environmental pollution in the three environmental compartments is provided, research gaps are briefly discussed, and some future directions are indicated. New evidence suggests that it is relevant to take into account not only the dose but also the time when we are exposed to carcinogens. The review ends by stressing that more dedication should be put into studying the environmental causes of cancers to prevent and avoid curing them, that the precautionary approach towards environmental pollutants must be much more reactionary, and that there is an urgent need to leave behind the outdated petrochemical-based industry and goods production.
Collapse
Affiliation(s)
- Roberto Cazzolla Gatti
- Konrad Lorenz Institute for Evolution and Cognition Research, 3400 Klosterneuburg, Austria;
- Biological Institute, Tomsk State University, 634050 Tomsk, Russia
| |
Collapse
|
27
|
Rahman MM, Paul KC, Hossain MA, Ali GGMN, Rahman MS, Thill JC. Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:72420-72450. [PMID: 34786314 PMCID: PMC8545207 DOI: 10.1109/access.2021.3079121] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 05/07/2021] [Indexed: 05/19/2023]
Abstract
The ongoing COVID-19 global pandemic is touching every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and non-pharmaceutical interventions of lockdown and confinement implemented citywide, regionally or nationally are affecting virus transmission, people's travel patterns, and air quality. Many studies have been conducted to predict the diffusion of the COVID-19 disease, assess the impacts of the pandemic on human mobility and on air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This literature review aims to analyze the results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 viral transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also explores the spatio-temporal aspects of lockdown and confinement measures on coronavirus diffusion, human mobility, and air quality. Additionally, we discuss policy implications, which will be helpful for policy makers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.
Collapse
Affiliation(s)
- Md. Mokhlesur Rahman
- The William States Lee College of EngineeringUniversity of North Carolina at CharlotteCharlotteNC28223USA
- Department of Urban and Regional PlanningKhulna University of Engineering and Technology (KUET)Khulna9203Bangladesh
| | - Kamal Chandra Paul
- Department of Electrical and Computer EngineeringThe William States Lee College of EngineeringUniversity of North Carolina at CharlotteCharlotteNC28223USA
| | - Md. Amjad Hossain
- Department of Computer Science, Mathematics and EngineeringShepherd UniversityShepherdstownWV25443USA
| | - G. G. Md. Nawaz Ali
- Department of Applied Computer ScienceUniversity of CharlestonCharlestonWV25304USA
| | - Md. Shahinoor Rahman
- Department of Earth and Environmental SciencesNew Jersey City UniversityJersey CityNJ07305USA
| | - Jean-Claude Thill
- Department of Geography and Earth SciencesSchool of Data ScienceUniversity of North Carolina at CharlotteCharlotteNC28223USA
| |
Collapse
|
28
|
Isaia G, Diémoz H, Maluta F, Fountoulakis I, Ceccon D, di Sarra A, Facta S, Fedele F, Lorenzetto G, Siani AM, Isaia G. Does solar ultraviolet radiation play a role in COVID-19 infection and deaths? An environmental ecological study in Italy. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 757:143757. [PMID: 33272604 PMCID: PMC7678486 DOI: 10.1016/j.scitotenv.2020.143757] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 11/09/2020] [Accepted: 11/10/2020] [Indexed: 05/21/2023]
Abstract
A significantly stronger impact in mortality and morbidity by COVID-19 has been observed in the northern Italian regions compared to the southern ones. The reasons of this geographical pattern might involve several concurrent factors. The main objective of this work is to investigate whether any correlations exist between the spatial distribution of COVID-19 cases and deaths in the different Italian regions and the amount of solar ultraviolet (UV) radiation at the Earth's surface. To this purpose, in this environmental ecological study a mixed-effect exponential regression was built to explain the incidence of COVID-19 based on the environmental conditions, and demographic and pathophysiologic factors. Observations and estimates of the cumulative solar UV exposure have been included to quantify the amount of radiation available e.g., for pre-vitamin D3 synthesis or SARS-CoV-2 inactivation by sunlight. The analysis shows a significant correlation (p-value <5 × 10-2) between the response variables (death percentage, incidence of infections and positive tests) and biologically effective solar UV radiation, residents in nursing homes per inhabitant (NHR), air temperature, death percentage due to the most frequent comorbidities. Among all factors, the amount of solar UV radiation is the variable contributing the most to the observed correlation, explaining up to 83.2% of the variance of the COVID-19 affected cases per population. While the statistical outcomes of the study do not directly entail a specific cause-effect relationship, our results are consistent with the hypothesis that solar UV radiation impacted on the development of the infection and on its complications, e.g. through the effect of vitamin D on the immune system or virus inactivation by sunlight. The analytical framework used in this study, based on commonly available data, can be easily replicated in other countries and geographical domains to identify possible correlations between exposure to solar UV radiation and the spread of the pandemic.
Collapse
Affiliation(s)
- Giancarlo Isaia
- Department of Medical Sciences, University of Turin, Italy; Academy of Medicine of Turin, Italy.
| | - Henri Diémoz
- Regional Environmental Protection Agency (ARPA), Valle d'Aosta, Italy
| | - Francesco Maluta
- Department of Industrial Chemistry, University of Bologna, Italy
| | | | - Daniela Ceccon
- Provincial Environmental Protection Agency (APPA), Bolzano, Italy
| | - Alcide di Sarra
- Italian Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Italy
| | - Stefania Facta
- Regional Environmental Protection Agency (ARPA), Piemonte, Italy
| | | | | | | | - Gianluca Isaia
- Geriatrics and Metabolic Bone Diseases, AOU Città della Salute e della Scienza of Turin, Italy
| |
Collapse
|
29
|
Signorini C, Pignatti P, Coccini T. How Do Inflammatory Mediators, Immune Response and Air Pollution Contribute to COVID-19 Disease Severity? A Lesson to Learn. Life (Basel) 2021; 11:182. [PMID: 33669011 PMCID: PMC7996623 DOI: 10.3390/life11030182] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 02/16/2021] [Accepted: 02/21/2021] [Indexed: 02/07/2023] Open
Abstract
Inflammatory and immune processes are defensive mechanisms that aim to remove harmful agents. As a response to infections, inflammation and immune response contribute to the pathophysiological mechanisms of diseases. Coronavirus disease 2019 (COVID-19), whose underlying mechanisms remain not fully elucidated, has posed new challenges for the knowledge of pathophysiology. Chiefly, the inflammatory process and immune response appear to be unique features of COVID-19 that result in developing a hyper-inflammatory syndrome, and air pollution, the world's largest health risk factor, may partly explain the behaviour and fate of COVID-19. Understanding the mechanisms involved in the progression of COVID-19 is of fundamental importance in order to avoid the late stage of the disease, associated with a poor prognosis. Here, the role of the inflammatory and immune mediators in COVID-19 pathophysiology is discussed.
Collapse
Affiliation(s)
- Cinzia Signorini
- Department of Molecular and Developmental Medicine, University of Siena, Via Aldo Moro, 53100 Siena, Italy
| | - Patrizia Pignatti
- Allergy and Immunology Unit, Istituti Clinici Scientifici Maugeri IRCCS, 27100 Pavia, Italy;
| | - Teresa Coccini
- Laboratory of Clinical and Experimental Toxicology, Pavia Poison Centre, National Toxicology Information Centre, Toxicology Unit, Istituti Clinici Scientifici Maugeri IRCCS, 27100 Pavia, Italy;
| |
Collapse
|
30
|
COVID-19 and Air Pollution: Measuring Pandemic Impact to Air Quality in Five European Countries. ATMOSPHERE 2021. [DOI: 10.3390/atmos12030290] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The rapid spread of the coronavirus (COVID-19) pandemic affected the economy, trade, transport, health care, social services, and other sectors. To control the rapid dispersion of the virus, most countries imposed national lockdowns and social distancing policies. This led to reduced industrial, commercial, and human activities, followed by lower air pollution emissions, which caused air quality improvement. Air pollution monitoring data from the European Environment Agency (EEA) datasets were used to investigate how lockdown policies affected air quality changes in the period before and during the COVID-19 lockdown, comparing to the same periods in 2018 and 2019, along with an assessment of the Index of Production variation impact to air pollution changes during the pandemic in 2020. Analysis results show that industrial and mobility activities were lower in the period of the lockdown along with the reduced selected pollutant NO2, PM2.5, PM10 emissions by approximately 20–40% in 2020.
Collapse
|
31
|
Cazzolla Gatti R, Menéndez LP, Laciny A, Bobadilla Rodríguez H, Bravo Morante G, Carmen E, Dorninger C, Fabris F, Grunstra NDS, Schnorr SL, Stuhlträger J, Villanueva Hernandez LA, Jakab M, Sarto-Jackson I, Caniglia G. Diversity lost: COVID-19 as a phenomenon of the total environment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 756:144014. [PMID: 33279199 DOI: 10.1016/j.scitotenv.2020.144014] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/12/2020] [Accepted: 11/15/2020] [Indexed: 05/18/2023]
Abstract
If we want to learn how to deal with the COVID-19 pandemic, we have to embrace the complexity of this global phenomenon and capture interdependencies across scales and contexts. Yet, we still lack systematic approaches that we can use to deal holistically with the pandemic and its effects. In this Discussion, we first introduce a framework that highlights the systemic nature of the COVID-19 pandemic from the perspective of the total environment as a self-regulating and evolving system comprising of three spheres, the Geosphere, the Biosphere, and the Anthroposphere. Then, we use this framework to explore and organize information from the rapidly growing number of scientific papers, preprints, preliminary scientific reports, and journalistic pieces that give insights into the pandemic crisis. With this work, we point out that the pandemic should be understood as the result of preconditions that led to depletion of human, biological, and geochemical diversity as well as of feedback that differentially impacted the three spheres. We contend that protecting and promoting diversity, is necessary to contribute to more effective decision-making processes and policy interventions to face the current and future pandemics.
Collapse
Affiliation(s)
- Roberto Cazzolla Gatti
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Biological Institute, Tomsk State University, Tomsk, Russia.
| | - Lumila Paula Menéndez
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Anthropology of the Americas, University of Bonn, Bonn, Germany
| | - Alice Laciny
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Entomology Collection, Natural History Museum Vienna, Vienna, Austria
| | - Hernán Bobadilla Rodríguez
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Philosophy, University of Vienna, Vienna, Austria
| | - Guillermo Bravo Morante
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Legal Medicine, Toxicology and Physical Anthropology, University of Granada, Granada, Spain
| | - Esther Carmen
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Environment and Geography, University of York, UK
| | - Christian Dorninger
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria
| | - Flavia Fabris
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria
| | - Nicole D S Grunstra
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Evolutionary Biology, University of Vienna, Vienna, Austria; Mammal Collection, Natural History Museum Vienna, Vienna, Austria
| | - Stephanie L Schnorr
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Anthropology, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Julia Stuhlträger
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria; Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | | | - Manuel Jakab
- Department for Academic Communication, Sigmund Freud University, Vienna, Austria
| | | | - Guido Caniglia
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria
| |
Collapse
|
32
|
Mottaqi MS, Mohammadipanah F, Sajedi H. Contribution of machine learning approaches in response to SARS-CoV-2 infection. INFORMATICS IN MEDICINE UNLOCKED 2021; 23:100526. [PMID: 33869730 PMCID: PMC8044633 DOI: 10.1016/j.imu.2021.100526] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 01/19/2021] [Accepted: 01/20/2021] [Indexed: 12/19/2022] Open
Abstract
PROBLEM The lately emerged SARS-CoV-2 infection, which has put the whole world in an aberrant demanding situation, has generated an urgent need for developing effective responses through artificial intelligence (AI). AIM This paper aims to overview the recent applications of machine learning techniques contributing to prevention, diagnosis, monitoring, and treatment of coronavirus disease (SARS-CoV-2). METHODS A progressive investigation of the recent publications up to November 2020, related to AI approaches towards managing the challenges of COVID-19 infection was made. RESULTS For patient diagnosis and screening, Convolutional Neural Network (CNN) and Support Vector Machine (SVM) are broadly applied for classification purposes. Moreover, Deep Neural Network (DNN) and homology modeling are the most used SARS-CoV-2 drug repurposing models. CONCLUSION While the fields of diagnosis of the SARS-CoV-2 infection by medical image processing and its dissemination pattern through machine learning have been sufficiently studied, some areas such as treatment outcome in patients and drug development need to be further investigated using AI approaches.
Collapse
Affiliation(s)
- Mohammad Sadeq Mottaqi
- Department of Microbial Biotechnology, School of Biology and Center of Excellence in Phylogeny of Living Organisms, College of Science, University of Tehran, 14155-6455, Tehran, Iran
| | - Fatemeh Mohammadipanah
- Department of Microbial Biotechnology, School of Biology and Center of Excellence in Phylogeny of Living Organisms, College of Science, University of Tehran, 14155-6455, Tehran, Iran
| | - Hedieh Sajedi
- Department of Computer Science, School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, 14155-6455, Tehran, Iran
| |
Collapse
|
33
|
Accarino G, Lorenzetti S, Aloisio G. Assessing correlations between short-term exposure to atmospheric pollutants and COVID-19 spread in all Italian territorial areas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 268:115714. [PMID: 33120339 PMCID: PMC7561302 DOI: 10.1016/j.envpol.2020.115714] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 09/10/2020] [Accepted: 09/21/2020] [Indexed: 05/09/2023]
Abstract
The spread of SARS-CoV-2, the beta coronavirus responsible for the current pneumonia pandemic outbreak, has been speculated to be linked to short-term and long-term atmospheric pollutants exposure. The present work has been aimed at analyzing the atmospheric pollutants concentrations (PM10, PM2.5, NO2) and spatio-temporal distribution of cases and deaths (specifically incidence, mortality and lethality rates) across the whole Italian national territory, down to the level of each individual territorial area, with the goal of checking any potential short-term correlation between these two phenomena. The data analysis has been limited to the first quarter of 2020 to reduce the lockdown-dependent biased effects on the atmospheric pollutant levels as much as possible. The analysis looked at non-linear, monotonic correlations using the Spearman non-parametric correlation index. The statistical significance of the Spearman correlations has also been evaluated. The results of the statistical analysis suggest the hypothesis of a moderate-to-strong correlation between the number of days exceeding the annual regulatory limits of PM10, PM2.5 and NO2 atmospheric pollutants and COVID-19 incidence, mortality and lethality rates for all the 107 territorial areas in Italy. A weak-to-moderate correlation seems to exist when considering the 36 territorial areas in four of the most affected regions (Lombardy, Piedmont, Emilia-Romagna and Veneto). Overall, PM10 and PM2.5 showed a higher non-linear correlation than NO2 with incidence, mortality and lethality rates. As to particulate matters, PM10 profile has been compared with the incidence rate variation that occurred in three of the most affected territorial areas in Northern Italy (i.e., Milan, Brescia, and Bergamo). All areas showed a similar PM10 time trend but a different incidence rate variation, that was less severe in Milan compared with Brescia and Bergamo.
Collapse
Affiliation(s)
- Gabriele Accarino
- Department of Biological and Environmental Sciences and Technologies, University of Salento, Via Prov.le Lecce-Monteroni, Lecce, Italy; Euro-Mediterranean Center on Climate Change (CMCC) Foundation, Via Augusto Imperatore, 16, 73100, Lecce, Italy
| | - Stefano Lorenzetti
- Italian National Institute of Health (ISS), Dpt. of Food Safety, Nutrition and Veterinary Public Health, Viale Regina Elena, 299 - I-00161, Rome, Italy
| | - Giovanni Aloisio
- Euro-Mediterranean Center on Climate Change (CMCC) Foundation, Via Augusto Imperatore, 16, 73100, Lecce, Italy; Department of Innovation Engineering, University of Salento, Via Prov.le Lecce-Monteroni, Lecce, Italy.
| |
Collapse
|