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Zhao H, Yang Y, Feng C, Wang W, Yang C, Yin Y, Gong L, Lin T. Nonlinear effects of humidex on risk of outpatient visit for allergic conjunctivitis among children and adolescents in Shanghai, China: A time series analysis. J Glob Health 2023; 13:04132. [PMID: 37921044 PMCID: PMC10623378 DOI: 10.7189/jogh.13.04132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023] Open
Abstract
Background Various epidemiological studies have focused on the adverse health outcomes of meteorological factors. However, there has been little research on the impact of humidex on allergic conjunctivitis, especially in child and adolescent populations. We aimed to explore the impact of humidex, a comprehensive index of relative humidity and temperature, on child and adolescent allergic conjunctivitis admissions. Methods Outpatient visit data for allergic conjunctivitis, meteorological factors and air pollutants in Shanghai for the 2017-2022 period were retrieved. For the purpose of analysing the nonlinear connection and lag impact between humidex and admissions for paediatric and adolescent allergic conjunctivitis, the distributed lag nonlinear model (DLNM) was fitted. Results A total of 147 090 cases were included in our cohort. We found a significantly nonlinear effect on humidex and allergic conjunctivitis. In the single-day lag pattern, the relative risks (RR) of allergic conjunctivitis were significant at lag 0 (RR = 1.08, 95% confidence interval (CI) = 1.05-1.11) to lag 2 (RR = 1.01, 95% CI = 1.00-1.01), lag 5 (RR = 1.01, 95% CI = 1.00-1.01) to lag 9 (RR = 1.01, 95% CI = 1.00-1.01), and lag 14 (RR = 1.02, 95% CI: 1.01-1.03). In the cumulative-lag day pattern, the RR of allergic conjunctivitis were significant at lag 0-0 (RR = 1.08, 95% CI = 1.05-1.11) to lag 0-14 (RR = 1.21, 95% CI = 1.13-1.28). We found that boys, children aged 7-17 years, and children in the warm season were more vulnerable to humidex. In addition, the highest attributable fraction (AF) and attributable number (AN) of humidex are at lag 0-14 (AF = 0.17, AN = 25 026). Conclusions Humidex exposure markedly increased the risk of allergic conjunctivitis, especially in highly high humidex. Appropriate public health management is needed for disease management and early intervention.
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Affiliation(s)
- Han Zhao
- Department of Ophthalmology, Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Clinical Research Center of Ophthalmic Disease, Changsha, Hunan, China
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Yun Yang
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Changming Feng
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Wushuang Wang
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Chenhao Yang
- Department of Ophthalmology, Children's Hospital of Fudan University, Shanghai, China
| | - Yue Yin
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Lan Gong
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Tong Lin
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
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Bhadola P, Chaudhary V, Markandan K, Talreja RK, Aggarwal S, Nigam K, Tahir M, Kaushik A, Rustagi S, Khalid M. Analysing role of airborne particulate matter in abetting SARS-CoV-2 outbreak for scheming regional pandemic regulatory modalities. ENVIRONMENTAL RESEARCH 2023; 236:116646. [PMID: 37481054 DOI: 10.1016/j.envres.2023.116646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/24/2023]
Abstract
The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.
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Affiliation(s)
- Pradeep Bhadola
- Centre for Theoretical Physics & Natural Philosophy, Mahidol University, Nakhonsawan 60130, Thailand
| | - Vishal Chaudhary
- Department of Physics, Bhagini Nivedita College, University of Delhi, Delhi 110072, India.
| | - Kalaimani Markandan
- Department of Chemical & Petroleum Engineering, Faculty of Engineering, Technology and Built Environment, UCSI University, Cheras 56000, Kuala Lumpur, Malaysia
| | - Rishi Kumar Talreja
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi 110029, India
| | - Sumit Aggarwal
- Division of Epidemiology and Communicable Diseases (ECD), Indian Council of Medical Research (ICMR)-Headquaters, New Delhi 110029, India
| | - Kuldeep Nigam
- Division of Epidemiology and Communicable Diseases (ECD), Indian Council of Medical Research (ICMR)-Headquaters, New Delhi 110029, India
| | - Mohammad Tahir
- Department of Computing, University of Turku, FI-20014, Turun Yliopisto, Finland
| | - Ajeet Kaushik
- NanoBio Tech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, FL, 33805, USA; School of Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India
| | - Sarvesh Rustagi
- School of Applied and Life Sciences, Uttaranchal University, Dehradun, Uttrakhand, India
| | - Mohammad Khalid
- Sunway Centre for Electrochemical Energy and Sustainable Technology (SCEEST), School of Engineering and Technology, Sunway University, No. 5, Jalan University, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia; Division of Research and Development, Lovely Professional University, Phagwara, 144411, Punjab, India; School of Engineering and Technology, Sharda University, Greater Noida, 201310, India.
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3
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Marchetti S, Gualtieri M, Pozzer A, Lelieveld J, Saliu F, Hansell AL, Colombo A, Mantecca P. On fine particulate matter and COVID-19 spread and severity: An in vitro toxicological plausible mechanism. ENVIRONMENT INTERNATIONAL 2023; 179:108131. [PMID: 37586275 DOI: 10.1016/j.envint.2023.108131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/01/2023] [Accepted: 08/05/2023] [Indexed: 08/18/2023]
Abstract
COVID-19 pandemic had a significant impact on global public health. The spread of the disease was related to the high transmissibility of SARS-CoV-2 virus but incidence and mortality rate suggested a possible relationship with environmental factors. Air pollution has been hypothesized to play a role in the transmission of the virus and the resulting severity of the disease. Here we report a plausible in vitro toxicological mode of action by which fine particulate matter (PM2.5) could promote a higher infection rate of SARS-CoV-2 and severity of COVID-19 disease. PM2.5 promotes a 1.5 fold over-expression of the angiotensin 2 converting enzyme (ACE2) which is exploited by viral particles to enter human lung alveolar cells (1.5 fold increase in RAB5 protein) and increases their inflammatory state (IL-8 and NF-kB protein expression). Our results provide a basis for further exploring the possible synergy between biological threats and air pollutants and ask for a deeper understanding of how air quality could influence new pandemics in the future.
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Affiliation(s)
- S Marchetti
- POLARIS Research Centre, Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, Italy
| | - M Gualtieri
- POLARIS Research Centre, Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, Italy.
| | - A Pozzer
- Max Planck Institute for Chemistry, Atmospheric Chemistry Department, Mainz, Germany
| | - J Lelieveld
- Max Planck Institute for Chemistry, Atmospheric Chemistry Department, Mainz, Germany
| | - F Saliu
- POLARIS Research Centre, Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, Italy
| | - A L Hansell
- Centre for Environmental Health and Sustainability, University of Leicester, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Environmental Exposures and Health at the University of Leicester, United Kingdom; National Institute for Health Research NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, United Kingdom
| | - A Colombo
- POLARIS Research Centre, Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, Italy
| | - P Mantecca
- POLARIS Research Centre, Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, Italy
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Oduniyi OS, Riveros JM, Hassan SM, Çıtak F. Testing the theory of Kuznet curve on environmental pollution during pre- and post-Covid-19 era. Sci Rep 2023; 13:12851. [PMID: 37553418 PMCID: PMC10409723 DOI: 10.1038/s41598-023-38962-5] [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: 01/04/2023] [Accepted: 07/18/2023] [Indexed: 08/10/2023] Open
Abstract
Covid-19 has brought about significant changes in people's daily lives, leading to a slowdown in economic activities and the implementation of restrictions and lockdowns. As a result, there have been noticeable effects on the environment. In this study, we examine the impact of Covid-19 total cases on the monthly average of carbon monoxide emissions in developed economies known for heavy pollution, covering the period from 2014 to 2023. We apply the Ambiental Kuznets curve approach to analyze the data. By employing different panel estimation techniques such as fixed effects and Driscoll-Kraay regressions, we observe a marked shift in environmental dynamics during the post-Covid era. This shift alters the statistical significance of the N-shaped Kuznets curve, rendering the relationship between economic activity and environmental impact non-significant. Interestingly, the Covid-related variables utilized in the various estimations are not statistically significant in explaining the long-term environmental effects.
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Affiliation(s)
| | - John M Riveros
- Estudios Y Evaluación de La Gestión Pública Colombian, Colombia, USA
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5
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Sangkham S, Islam MA, Sarndhong K, Vongruang P, Hasan MN, Tiwari A, Bhattacharya P. Effects of fine particulate matter (PM 2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand. CASE STUDIES IN CHEMICAL AND ENVIRONMENTAL ENGINEERING 2023; 8:100410. [PMID: 38620170 PMCID: PMC10286573 DOI: 10.1016/j.cscee.2023.100410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/20/2023] [Accepted: 06/21/2023] [Indexed: 04/17/2024]
Abstract
The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.
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Affiliation(s)
- Sarawut Sangkham
- Department of Environmental Health, School of Public Health, University of Phayao, Phayao, 56000, Thailand
| | - Md Aminul Islam
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
- Advanced Molecular Lab, Department of Microbiology, President Abdul Hamid Medical College, Karimganj, Kishoreganj, Bangladesh
| | - Kritsada Sarndhong
- Department of Community Health, School of Public Health, University of Phayao, Phayao, 56000, Thailand
| | - Patipat Vongruang
- Department of Environmental Health, School of Public Health, University of Phayao, Phayao, 56000, Thailand
- Atmospheric Pollution and Climate Change Research Unit, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand
| | - Mohammad Nayeem Hasan
- Department of Statistics, Shahjalal University of Science & Technology, Sylhet, Bangladesh
| | - Ananda Tiwari
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, 70701, Kuopio, Finland
| | - Prosun Bhattacharya
- COVID-19 Research, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 10B, SE, 10044, Stockholm, Sweden
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6
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El Samaty HS, Waseef AAE, Badawy NM. The effects of city morphology on airborne transmission of COVID-19. Case study: Port Said City, Egypt. URBAN CLIMATE 2023:101577. [PMID: 37362005 PMCID: PMC10258588 DOI: 10.1016/j.uclim.2023.101577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/21/2023] [Accepted: 06/05/2023] [Indexed: 06/28/2023]
Abstract
Looking beyond COVID-19 outbreak, Scholars continue to develop innovative approaches to bring the city on to health and safety. Recent studies have indicated that urban spaces could produce or propagate pathogens, which is an urgent topic at the city level. However, there is a dearth of studies investigating the interrelationship between urban morphology and pandemics outbreak at the neighborhood level. Accordingly, this research will trace the effect of cities morphologies on the rate of spread of COVID-19 through a simulation study held on five areas that form the urban morphology of Port Said City, using Envi-met software. Results are explored based on the degree of concentration and rate of diffusion of coronavirus particles. It was observed on a regular basis that wind speed has a directly proportional relationship with the diffusion of the particles and an inversely proportional relationship with the concentration of the particles. However, certain urban characteristics led to inconsistent and opposing results like wind tunnels, shaded arcades, height variance, and spacious in-between spaces. Moreover, it is obvious that the city morphology is being transformed over time toward safer conditions; urban areas constructed recently have low vulnerability to respiratory pandemics outbreak compared to older areas.
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Affiliation(s)
- Hosam Salah El Samaty
- Dar Al Uloom University (DAU), College of Architectural Engineering and Digital Design, Al Riyadh, Saudi Arabia
- Port Said University, Faculty of Engineering, Architectural Engineering and Urban Planning Dept., Port Said, Egypt
| | - Ahmed Abd Elaziz Waseef
- Port Said University, Faculty of Engineering, Architectural Engineering and Urban Planning Dept., Port Said, Egypt
- Architectural Engineering Dept., College of Engineering, University of Business and Technology (UBT), Jeddah 21448, Saudi Arabia
| | - Nancy Mahmoud Badawy
- Port Said University, Faculty of Engineering, Architectural Engineering and Urban Planning Dept., Port Said, Egypt
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7
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Zhou Y, Ji A, Tang E, Liu J, Yao C, Liu X, Xu C, Xiao H, Hu Y, Jiang Y, Li D, Du N, Li Y, Zhou L, Cai T. The role of extreme high humidex in depression in chongqing, China: A time series-analysis. ENVIRONMENTAL RESEARCH 2023; 222:115400. [PMID: 36736551 DOI: 10.1016/j.envres.2023.115400] [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: 11/03/2022] [Revised: 01/18/2023] [Accepted: 01/30/2023] [Indexed: 06/18/2023]
Abstract
As global climate change intensifies, people are paying increasing attention to the impact of temperature changes on adverse mental health outcomes, especially depression. While increasing attention has been paid to the effect of temperature, there is little research on the effect of humidity. We aimed to investigate the association between humidex, an index combining temperature and humidity to reflect perceived temperature, and outpatient visits for depression from 2014 to 2019 in Chongqing, the largest and one of the most hot and humid cities of China. We also aimed to further identify susceptible subgroups. A distributed lag non-linear model (DLNM) was used to explore the concentration-response relationship between humidex and depression outpatient visits. Hierarchical analysis was carried out by age and gender. A total of 155,436 visits for depression were collected from 2014 to 2019 (2191 days). We found that depression outpatient visits were significantly associated with extremely high humidex (≥40). The significant positive single-lag day effect existed at lag 0 (RR = 1.029, 95%CI: 1.000-1.059) to lag 2 (RR = 1.01, 95%CI: 1.004-1.028), and lag 12 (RR = 1.013, 95%CI: 1.002-1.024). The significant cumulative adverse effects lasted from lag 01 to lag 014. Hierarchical analyses showed that females and the elderly (≥60 years) appeared to be more susceptible to extremely high humidex. The attributable numbers (AN) and fraction (AF) of extremely high humidex on depression outpatients were 1709 and 1.10%, respectively. Extremely high humidex can potentially increase the risk of depression, especially in females and the elderly. More protective measures should be taken in vulnerable populations.
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Affiliation(s)
- Yumeng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ailing Ji
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China
| | - Enjie Tang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Jianghong Liu
- Department of Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, PA, 19104, USA
| | - Chunyan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Xiaoling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710032, China
| | - Hua Xiao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yuegu Hu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yuexu Jiang
- Department of Nutrition and Food Hygiene, School of Public Health Guizhou Medical University, Guiyang, 550025, China
| | - Dawei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ning Du
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yafei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Laixin Zhou
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Tongjian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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Beloconi A, Vounatsou P. Long-term air pollution exposure and COVID-19 case-severity: An analysis of individual-level data from Switzerland. ENVIRONMENTAL RESEARCH 2023; 216:114481. [PMID: 36206929 PMCID: PMC9531360 DOI: 10.1016/j.envres.2022.114481] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/27/2022] [Accepted: 09/30/2022] [Indexed: 05/05/2023]
Abstract
Several studies are pointing out that exposure to elevated air pollutants could contribute to increased COVID-19 mortality. However, literature on the associations between air pollution exposure and COVID-19 severe morbidity is rather sparse. In addition, the majority of the studies used an ecological study design and were applied in regions with rather high air pollution levels. Here, we study the differential effects of long-term exposure to air pollution on severe morbidity and mortality risks from COVID-19 in various population subgroups in Switzerland, a country known for clean air. We perform individual-level analyses using data covering the first two major waves of COVID-19 between February 2020 and May 2021. High-resolution maps of particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations were produced for the 6 years preceding the pandemic using Bayesian geostatistical models. Air pollution exposure for each patient was measured by the long-term average concentration across the municipality of residence. The models were adjusted for the effects of individual characteristics, socio-economic, health-system, and climatic factors. The variables with an important association to COVID-19 case-severity were identified using Bayesian spatial variable selection. The results have shown that the individual-level characteristics are important factors related to COVID-19 morbidity and mortality in all the models. Long-term exposure to air pollution appears to influence the severity of the disease only when analyzing data during the first wave; this effect is attenuated upon adjustment for health-system related factors during the entire study period. Our findings suggest that the burden of air pollution increased the risks of COVID-19 in Switzerland during the first wave of the pandemic, but not during the second wave, when the national health system was better prepared.
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Affiliation(s)
- Anton Beloconi
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Penelope Vounatsou
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland.
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9
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Jiang S, Lin X, Qi L, Zhang Y, Sharp B. The macro-economic and CO 2 emissions impacts of COVID-19 and recovery policies in China. ECONOMIC ANALYSIS AND POLICY 2022; 76:981-996. [PMID: 36277034 PMCID: PMC9580236 DOI: 10.1016/j.eap.2022.10.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/29/2022] [Accepted: 10/10/2022] [Indexed: 06/16/2023]
Abstract
The outbreak and ongoing evolution of the COVID-19 pandemic have dramatically impacted economic development and CO2 emissions. China is under simultaneous pressure to recover from the outbreak and meet its carbon reduction targets, and the government is endeavouring to stimulate economic recovery through fiscal and monetary policies. This paper uses a computable general equilibrium model to measure the impact on China's economic recovery and carbon emissions by incorporating the pandemic shock and related economic recovery policies of loan prime rate (LPR) and value-added tax (VAT) reduction. The study found that COVID-19 led to a simultaneous shock on China's supply and demand sides in which GDP dropped by 2.62% and carbon emissions fell by 2.53%, compared to the period prior to COVID-19. Although the LPR and VAT reduction effectively mitigated economic loss, the combined LPR and VAT reduction had a more substantial effect on boosting GDP than the single policies. The VAT cut expands production and was used to overcome supply-side shocks, while lowering LPR mitigates the damage of demand-side shocks. Compared to the VAT reduction policy, reduced LPR has smaller carbon emissions per unit of GDP output. Consequently, we recommend that the government concentrate on a combination of policies to navigate pandemic shocks, as the two economic stimulus policies are confirmed to complement one another in terms of strengths and shortcomings.
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Affiliation(s)
- Shiqi Jiang
- School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China
| | - Xinyue Lin
- School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China
| | - Lingli Qi
- Energy Center, University of Auckland, New Zealand
| | - Yongqiang Zhang
- School of Public Finance and Taxation, Zhejiang University of Finance and Economics, China
| | - Basil Sharp
- Energy Center, University of Auckland, New Zealand
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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.
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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
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Investigating the impacts of COVID-19 lockdown on air quality, surface Urban Heat Island, air temperature and lighting energy consumption in City of Melbourne. ENERGY STRATEGY REVIEWS 2022; 44:100963. [PMCID: PMC9452421 DOI: 10.1016/j.esr.2022.100963] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 08/15/2022] [Accepted: 09/06/2022] [Indexed: 06/17/2023]
Abstract
The COVID-19 pandemic has threatened city economies and residents' public health and quality of life. Similar to most cities, Melbourne imposed extreme preventive lockdown measures to address this situation. It would be reasonable to assume that during the two phases of lockdowns, in autumn (March) and winter (June to August) 2020, air quality parameters, air temperature, Surface Urban Heat Island (SUHI), and lighting energy consumption most likely increased. As such, to test this assumption, Sentinel 5, ERA-5 LAND, Sentinel 1 and 2, NASA SRTM, MODIS Aqua and Terra, and VIIRS satellite imageries are utilized to investigate the alterations of NO₂, SO₂, CO, UV Aerosol Index (UAI), air temperature, SUHI, and lighting energy consumption factors in the City of Melbourne. Furthermore, satellite imageries of SentiThe results indicate that the change rates of NO₂ (1.17 mol/m2) and CO (1.64 mol/m2) factors were positive. Further, the nighttime SUHI values increased by approximately 0.417 °C during the winter phase of the lockdown, while during the summer phase of the lockdown, the largest negative change rate was in NO₂ (−100.40 mol/m2). By contrast, the largest positive change rate was in SO₂ and SUHI at night. The SO₂ values increased from very low to 330 μm mol/m2, and the SUHI nighttime values increased by approximately 4.8 °C. From the spatial point of view, this study also shows how the effects on such parameters shifted based on the urban form and land types across the City of Melbourne by using satellite data as a significant resource to analyze the spatial coverage of these factors. The findings of this study demonstrate how air quality factors, SUHI, air temperature, and lighting energy consumption changed from pre-lockdown (2019) to lockdown (2020), offering valuable insights regarding practices for managing SUHI, lighting energy consumption, and air pollution.
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Hammam EE, Al Ghamdi MA, Almazroui M, Hassan IA. The COVID-19 Pandemic: Quantification of Temporal Variations in Air Pollutants Before, During and Post the Lockdown in Jeddah City, Saudi Arabia. EARTH SYSTEMS AND ENVIRONMENT 2022; 6:917-926. [PMID: 36185412 PMCID: PMC9513300 DOI: 10.1007/s41748-022-00328-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/24/2022] [Accepted: 09/03/2022] [Indexed: 06/16/2023]
Abstract
The government of Saudi Arabia imposed a strict lockdown between March and July 2020 to stop the spread of the coronavirus disease (COVID-19), which has led to a sharp decline in economic activities. The daily temporal variations of PM10, PM2.5, carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3) were used to investigate the changes in air quality in response to COVID-19 lockdown control measures from January to December 2020 in Jeddah, Saudi Arabia. Meteorological parameters (wind speed, direction, temperature, relative humidity) were also analyzed to understand the changes during the pandemic. As a result, significant reductions in the concentrations of NO2 (- 44.5%), CO (- 41.5%), and PM2.5, PM10 (- 29.5%, each) were measured in the capital city of Jeddah during the quarantine compared to the pre-lockdown average. In contrast, the lockdown caused a significant increase in O3 by 41%. The changes in air quality during the COVID-19 outbreak by comparing the average pollutant concentration before lockdown (January 1-March 21, 2020) and the following 12 weeks during the partial lockdown (March 22-July 28, 2020), reveal a very significant decrease in pollutants, and consequently a significant improvement in air quality. Observed differences are attributable to changes in point source emissions associated with changes in localized activities, possibly related to decreased economic and industrial activity in response to the lockdown. The results of the present study show during the study period indicated a positive response to lockdown during the COVID-19 pandemic. Furthermore, the results can be used to establish future control measures and strategies to improve air quality.
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Affiliation(s)
| | - Mansour A. Al Ghamdi
- Faculty of Meteorology, Environment and Agriculture of Arid Regions, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mansour Almazroui
- Center of Excellence for Climate Change Research/Department of Meteorology, King Abdulaziz University, Jeddah, 21589 Saudi Arabia
- Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
| | - Ibrahim A. Hassan
- Faculty of Science, Alexandria University, 21511 Moharem Bay, Alexandria, Egypt
- Scientific Committee of Environmental Problems (SCOPE), Academy of Scientific Research & Technology (ASRT), 101 Kasr Al Ini Street, Cairo, Egypt
- Centre of Excellence in Environmental Studies, King Abdulaziz University, Jeddah, Saudi Arabia
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13
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Galán-Madruga D. Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY : IJEST 2022; 20:7083-7098. [PMID: 36035638 PMCID: PMC9391654 DOI: 10.1007/s13762-022-04464-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 03/08/2022] [Accepted: 08/05/2022] [Indexed: 06/12/2023]
Abstract
This work aims to quantify potential pollution level changes in an urban environment (Madrid city, Spain) located in South Europe due to the lockdown measures for preventing the SARS-CoV-2 transmission. Polluting 11 species commonly monitored in urban zones were attended. Except for O3, a prompt target pollutant levels abatement was reached, intensely when implanted stricter measures and moderately along those measures' relaxing period. In the case of TH and CH4, it is evidenced a progressive diminution over the lockdown period. While the highest decreasing average changes relapsed on NOx (NO2: - 40.0% and NO: - 33.3%) and VOCs (C7H8: - 36.3% and C6H6: - 32.8%), followed by SO2 (- 27.0%), PM10 (- 19.7%), CO (- 16.6%), CH4 (- 14.7%), TH (- 11.6%) and PM2.5 (- 10.1%), the O3 level slightly raised 0.4%. These changes were consistently dependent on the measurement station location, emphasizing urban background zones for SO2, CO, C6H6, C7H8, TH and CH4, suburban zones for PM2.5 and O3, urban traffic sites for NO and PM10, and keeping variations reasonably similar at all the stations in the case of NO2. Those pollution changes were not translated in variations on geospatial pattern, except for NO, O3 and SO2. Although the researched urban atmosphere improvement was not attributable to meteorological conditions' variations, it was in line with the decline in traffic intensity. The evidenced outcomes might offer valuable clues to air quality managers in urban environments regarding decision-making in favor of applying punctual severe measures for quickly and considerably relieving polluting high load occurred in urban environments. Supplementary Information The online version contains supplementary material available at 10.1007/s13762-022-04464-6.
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Affiliation(s)
- D. Galán-Madruga
- Department of Atmospheric Pollution, National Center for Environment Health, Health Institute Carlos III, Ctra. Majadahonda a Pozuelo Km 2,2. Majadahonda, 28220 Madrid, Spain
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14
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Chaudhary V, Bhadola P, Kaushik A, Khalid M, Furukawa H, Khosla A. Assessing temporal correlation in environmental risk factors to design efficient area-specific COVID-19 regulations: Delhi based case study. Sci Rep 2022; 12:12949. [PMID: 35902653 PMCID: PMC9333075 DOI: 10.1038/s41598-022-16781-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 07/15/2022] [Indexed: 12/12/2022] Open
Abstract
Amid ongoing devastation due to Serve-Acute-Respiratory-Coronavirus2 (SARS-CoV-2), the global spatial and temporal variation in the pandemic spread has strongly anticipated the requirement of designing area-specific preventive strategies based on geographic and meteorological state-of-affairs. Epidemiological and regression models have strongly projected particulate matter (PM) as leading environmental-risk factor for the COVID-19 outbreak. Understanding the role of secondary environmental-factors like ammonia (NH3) and relative humidity (RH), latency of missing data structuring, monotonous correlation remains obstacles to scheme conclusive outcomes. We mapped hotspots of airborne PM2.5, PM10, NH3, and RH concentrations, and COVID-19 cases and mortalities for January, 2021-July,2021 from combined data of 17 ground-monitoring stations across Delhi. Spearmen and Pearson coefficient correlation show strong association (p-value < 0.001) of COVID-19 cases and mortalities with PM2.5 (r > 0.60) and PM10 (r > 0.40), respectively. Interestingly, the COVID-19 spread shows significant dependence on RH (r > 0.5) and NH3 (r = 0.4), anticipating their potential role in SARS-CoV-2 outbreak. We found systematic lockdown as a successful measure in combatting SARS-CoV-2 outbreak. These outcomes strongly demonstrate regional and temporal differences in COVID-19 severity with environmental-risk factors. The study lays the groundwork for designing and implementing regulatory strategies, and proper urban and transportation planning based on area-specific environmental conditions to control future infectious public health emergencies.
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Affiliation(s)
- Vishal Chaudhary
- Research Cell and Department of Physics, Bhagini Nivedita College, University of Delhi, New Delhi, 110043, India.
| | - Pradeep Bhadola
- Centre for Theoretical Physics and Natural Philosophy, Nakhonsawan Studiorum for Advanced Studies, Mahidol University, Nakhonsawan, 60130, Thailand.
| | - Ajeet Kaushik
- NanoBioTech Laboratory, Health System Engineering, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, FL, 33805, USA
- School of Engineering, University of Petroleum and Energy Studies (UPES) , Dehradun, Uttarakhand, India
| | - Mohammad Khalid
- Graphene and Advanced 2D Materials Research Group (GAMRG), School of Engineering and Technology, Sunway University, No. 5, Jalan University, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia
- Sunway Materials Smart Science & Engineering (SMS2E) Research Cluster, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia
| | - Hidemitsu Furukawa
- Department of Mechanical Systems Engineering, Graduate School of Science and Engineering, Yamagata University, Yonezawa, Yamagata, 992-8510, Japan
| | - Ajit Khosla
- School of Advanced Materials and Nanotechnology, Xidian University, Xi'an, 710126, People's Republic of China.
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15
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Sannigrahi S, Pilla F, Maiti A, Bar S, Bhatt S, Kaparwan A, Zhang Q, Keesstra S, Cerda A. Examining the status of forest fire emission in 2020 and its connection to COVID-19 incidents in West Coast regions of the United States. ENVIRONMENTAL RESEARCH 2022; 210:112818. [PMID: 35104482 PMCID: PMC8800502 DOI: 10.1016/j.envres.2022.112818] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 01/10/2022] [Accepted: 01/19/2022] [Indexed: 05/30/2023]
Abstract
Forest fires impact on soil, water, and biota resources. The current forest fires in the West Coast of the United States (US) profoundly impacted the atmosphere and air quality across the ecosystems and have caused severe environmental and public health burdens. Forest fire led emissions could significantly exacerbate the air pollution level and, therefore, would play a critical role if the same occurs together with any epidemic and pandemic health crisis. Limited research is done so far to examine its impact in connection to the current pandemic. As of October 21, nearly 8.2 million acres of forest area were burned, with more than 25 casualties reported so far. In-situ air pollution data were utilized to examine the effects of the 2020 forest fire on atmosphere and coronavirus (COVID-19) casualties. The spatial-temporal concentrations of particulate matter (PM2.5 and PM10) and Nitrogen Dioxide (NO2) were collected from August 1 to October 30 for 2020 (the fire year) and 2019 (the reference year). Both spatial (Multiscale Geographically Weighted Regression) and non-spatial (Negative Binomial Regression) analyses were performed to assess the adverse effects of fire emission on human health. The in-situ data-led measurements showed that the maximum increases in PM2.5, PM10, and NO2 concentrations (μg/m3) were clustered in the West Coastal fire-prone states during August 1 - October 30, 2020. The average concentration (μg/m3) of particulate matter (PM2.5 and PM10) and NO2 was increased in all the fire states severely affected by forest fires. The average PM2.5 concentrations (μg/m3) over the period were recorded as 7.9, 6.3, 5.5, and 5.2 for California, Colorado, Oregon, and Washington in 2019, increasing up to 24.9, 13.4, 25.0, and 17.0 in 2020. Both spatial and non-spatial regression models exhibited a statistically significant association between fire emission and COVID-19 incidents. Such association has been demonstrated robust and stable by a total of 30 models developed for analyzing the spatial non-stationary and local association. More in-depth research is needed to better understand the complex relationship between forest fire emission and human health.
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Affiliation(s)
- Srikanta Sannigrahi
- School of Architecture, Planning and Environmental Policy, University College Dublin Richview, Clonskeagh, Dublin, D14 E099, Ireland.
| | - Francesco Pilla
- School of Architecture, Planning and Environmental Policy, University College Dublin Richview, Clonskeagh, Dublin, D14 E099, Ireland
| | - Arabinda Maiti
- Department of Geography, Vidyasagar University, Midnapore, West Bengal, India
| | - Somnath Bar
- Department of Geoinformatics, Central University of Jharkhand, Ranchi, India
| | - Sandeep Bhatt
- Department of Earth Sciences, Indian Institute of Technology Roorkee, India
| | - Ankit Kaparwan
- Department of Statistics, Hemvati Nandan Bahuguna Garhwal University, Srinagar, India
| | - Qi Zhang
- Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Saskia Keesstra
- Team Soil, Water and Land Use, Wageningen Environmental Research, Wageningen University & Research, Wageningen, Netherlands; Civil, Surveying and Environmental Engineering and Centre for Water Security and Environmental Sustainability, The University of Newcastle, Callaghan, 2308, Australia
| | - Artemi Cerda
- Soil Erosion and Degradation Research Group, Department of Geography, Valencia University, Blasco Ibàñez, 28, 46010, Valencia, Spain
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16
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Culqui DR, Díaz J, Blanco A, Lopez JA, Navas MA, Sánchez-Martínez G, Luna MY, Hervella B, Belda F, Linares C. Short-term influence of environmental factors and social variables COVID-19 disease in Spain during first wave (Feb-May 2020). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:50392-50406. [PMID: 35230631 PMCID: PMC8886199 DOI: 10.1007/s11356-022-19232-9] [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: 10/20/2021] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
This study aims to identify the combined role of environmental pollutants and atmospheric variables at short term on the rate of incidence (TIC) and on the hospital admission rate (TIHC) due to COVID-19 disease in Spain. This study used information from 41 of the 52 provinces of Spain (from Feb. 1, 2021 to May 31, 2021). Using TIC and TIHC as dependent variables, and average daily concentrations of PM10 and NO2 as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). Generalized linear models (GLM) with Poisson link were carried out for each provinces The GLM model controlled for trend, seasonalities, and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 μg/m3 in PM10 and NO2 and by 1 °C in the case of Tmax and 1 g/m3 in the case of HA. Later, a linear regression was carried out that included the social determinants of health. Statistically significant associations were found between PM10, NO2, and the rate of COVID-19 incidence. NO2 was the variable that showed greater association, both for TIC as well as for TIHC in the majority of provinces. Temperature and HA do not seem to have played an important role. The geographic distribution of RR in the studied provinces was very much heterogeneous. Some of the health determinants considered, including income per capita, presence of airports, average number of diesel cars per inhabitant, average number of nursing personnel, and homes under 30 m2 could explain the differential geographic behavior. As findings indicates, environmental factors only could modulate the incidence and severity of COVID-19. Moreover, the social determinants and public health measures could explain some patterns of geographically distribution founded.
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Affiliation(s)
- Dante R. Culqui
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - Julio Díaz
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - Alejandro Blanco
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - José A. Lopez
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - Miguel A. Navas
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | | | | | | | | | - Cristina Linares
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
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17
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Aloisi V, Gatto A, Accarino G, Donato F, Aloisio G. The effect of known and unknown confounders on the relationship between air pollution and Covid-19 mortality in Italy: A sensitivity analysis of an ecological study based on the E-value. ENVIRONMENTAL RESEARCH 2022; 207:112131. [PMID: 34619131 PMCID: PMC8487852 DOI: 10.1016/j.envres.2021.112131] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/22/2021] [Accepted: 09/23/2021] [Indexed: 05/09/2023]
Abstract
Back in December 2019, the novel coronavirus disease 2019 (Covid-19) started rapidly spreading worldwide, especially in Italy that was among the most affected countries. The geographical distribution of air pollution and Covid-19 mortality in Italy suggested atmospheric pollution as a worsening factor of severe Covid-19 health outcomes. The present nationwide ecological study focused on all 107 Italian territorial areas, aiming to assess the potential association between Particulate Matter concentration, less than 2.5 μm in diameter (exposure), and Covid-19 mortality rate (outcome) throughout 2020, by looking at 28 potential confounders. A potential positive association between exposure and outcome was observed when performing a multivariate regression analysis with a Negative Binomial model, suggesting that an increase of 1 μg/m3 in the exposure is associated with an increase of 9.0% (95% CI: 6.5%-11.6%) in the average Covid-19 mortality rate, conditional on all 28 potential confounders. A sensitivity analysis, based on the E-value, shows that a hypothetical unmeasured confounder would have to be associated with both PM2.5 concentration and Covid-19 mortality rate by a rate ratio of at least 1.40-fold each to explain away the exposure-outcome association, conditional on all 28 covariates included in the main analysis model. Moreover, the Observed Covariate E-value (OCE) was reported to provide a contextualization of the E-value on the observed covariates included in the study. The OCE sensitivity analysis shows that a set of unknown confounders similar in size and magnitude to the set of the considered climatic factors could potentially explain away the estimated exposure-outcome association. Consequently, the role of climatic factors in the Covid-19 pandemic is worth of further investigation.
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Affiliation(s)
- Valeria Aloisi
- Department of Innovation Engineering, 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.
| | - Andrea Gatto
- Department of Innovation Engineering, 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.
| | - 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.
| | - Francesco Donato
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Unit of Hygiene, Epidemiology, and Public Health, University of Brescia, Viale Europa 11, 25123, Brescia, Italy.
| | - Giovanni Aloisio
- Department of Innovation Engineering, 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.
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Ibarra-Espinosa S, Dias de Freitas E, Ropkins K, Dominici F, Rehbein A. Negative-Binomial and quasi-poisson regressions between COVID-19, mobility and environment in São Paulo, Brazil. ENVIRONMENTAL RESEARCH 2022; 204:112369. [PMID: 34767818 PMCID: PMC8577054 DOI: 10.1016/j.envres.2021.112369] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/31/2021] [Accepted: 11/08/2021] [Indexed: 05/08/2023]
Abstract
Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to monitor quarantines and prevent the transmissions of SARS-CoV-2. In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in São Paulo, Brazil. We applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between RMI and COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 4 and 21 days, and 2) the association between COVID-19 and exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility. We found that an RMI of 45.28% results in 1212 cases (95% CI: 1189 to 1235) and 44 deaths (95% CI: 40 to 47). Increasing the isolation from 45.28% to 50% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 μg⋅m-³ of PM2.5 results in a risk of 1.140 (95% CI: 1.021 to 1.274) for cases and 1.086 (95% CI: 1.008 to 1.170) for deaths, while O3 produces a relative risk of 1.075 (95% CI: 1.006 to 1.150) for cases and 1.063 (95% CI: 1.006 to 1.124) for deaths, respectively. We compared our results with observations and literature review, finding well agreement. Policymakers can use such mobility indices as tools to control social distance activities. Spatial distancing is an important factor to control COVID-19, however, measuring face-mask usage would enhance the understanding the pandemic dynamic. Small increments of air pollution result in an increased number of COVID-19 cases and deaths.
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Affiliation(s)
- Sergio Ibarra-Espinosa
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Brazil.
| | - Edmilson Dias de Freitas
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Brazil
| | - Karl Ropkins
- Institute for Transport Studies, University of Leeds, UK
| | - Francesca Dominici
- Harvard Data Science Initiative, Harvard University, Boston, MA, 02138, USA
| | - Amanda Rehbein
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Brazil
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Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring. SENSORS 2022; 22:s22031093. [PMID: 35161837 PMCID: PMC8839978 DOI: 10.3390/s22031093] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 01/07/2022] [Accepted: 01/25/2022] [Indexed: 12/10/2022]
Abstract
With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to have diversity in LCS selection for the same task. However, this diversity in sensor types adds complexity to appropriate sensor selection for monitoring tasks. In addition, LCS devices are often associated with low confidence in terms of sensing accuracy because of the complexities in sensing principles and the interpretation of monitored data. From the data analytics point of view, data quality is a major concern as low-quality data more often leads to low confidence in the monitoring systems. Therefore, any applications on building monitoring systems using LCS devices need to focus on two main techniques: sensor selection and calibration to improve data quality. In this paper, data-driven techniques were presented for sensor calibration techniques. To validate our methodology and techniques, an air quality monitoring case study from the Bradford district, UK, as part of two European Union (EU) funded projects was used. For this case study, the candidate sensors were selected based on the literature and market availability. The candidate sensors were narrowed down into the selected sensors after analysing their consistency. To address data quality issues, four different calibration methods were compared to derive the best-suited calibration method for the LCS devices in our use case system. In the calibration, meteorological parameters temperature and humidity were used in addition to the observed readings. Moreover, we uniquely considered Absolute Humidity (AH) and Relative Humidity (RH) as part of the calibration process. To validate the result of experimentation, the Coefficient of Determination (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) were compared for both AH and RH. The experimental results showed that calibration with AH has better performance as compared with RH. The experimental results showed the selection and calibration techniques that can be used in designing similar LCS based monitoring systems.
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Mas JF, Pérez-Vega A. Spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level. PeerJ 2022; 9:e12685. [PMID: 35036159 PMCID: PMC8711283 DOI: 10.7717/peerj.12685] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 12/03/2021] [Indexed: 01/08/2023] Open
Abstract
In recent history, Coronavirus Disease 2019 (COVID-19) is one of the worst infectious disease outbreaks affecting humanity. The World Health Organization has defined the outbreak of COVID-19 as a pandemic, and the massive growth of the number of infected cases in a short time has caused enormous pressure on medical systems. Mexico surpassed 3.7 million confirmed infections and 285,000 deaths on October 23, 2021. We analysed the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We computed weekly Moran’s I index to assess spatial autocorrelation over time and identify clusters of the disease using the “flexibly shaped spatial scan” approach. Finally, we compared Euclidean, cost, resistance distances and gravitational model to select the best-suited approach to predict inter-municipality contagion. We found that COVID-19 pandemic in Mexico is characterised by clusters evolving in space and time as parallel epidemics. The gravitational distance was the best model to predict newly infected municipalities though the predictive power was relatively low and varied over time. This study helps us understand the spread of the epidemic over the Mexican territory and gives insights to model and predict the epidemic behaviour.
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Affiliation(s)
- Jean-François Mas
- Laboratorio de análisis espacial, Centro de Investigaciones en Geografía Ambiental, Universidad Nacional Autónoma de México, Morelia, Michoacán, Mexico
| | - Azucena Pérez-Vega
- Departamento de Geomática e Hidraúlica, Universidad de Guanajuato, Guanajuato, Guanajuato, Mexico
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21
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Páez-Osuna F, Valencia-Castañeda G, Rebolledo UA. The link between COVID-19 mortality and PM 2.5 emissions in rural and medium-size municipalities considering population density, dust events, and wind speed. CHEMOSPHERE 2022; 286:131634. [PMID: 34325266 PMCID: PMC8296377 DOI: 10.1016/j.chemosphere.2021.131634] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 07/16/2021] [Accepted: 07/20/2021] [Indexed: 05/02/2023]
Abstract
One contemporary issue is how environmental pollution and climate can affect the dissemination and severity of COVID-19 in humans. We documented the first case of association between particulate matter ≤2.5 μm (PM2.5) and COVID-19 mortality rates that involved rural and medium-sized municipalities in northwestern Mexico, where direct air quality monitoring is absent. Alternatively, anthropogenic PM2.5 emissions were used to estimate the PM2.5 exposure in each municipality using two scenarios: 1) considering the fraction derived from combustion of vehicle fuel; and 2) the one derived from modeled anthropogenic sources. This study provides insights to better understand and face future pandemics by examining the relation between PM2.5 pollution and COVID-19 mortality considering the population density and the wind speed. The main findings are: (i) municipalities with high PM2.5 emissions and high population density have a higher COVID-19 mortality rate; (ii) the exceptionally high COVID-19 mortality rates of the rural municipalities could be associated to dust events, which are common in these regions where soils without vegetation are dominant; and (iii) the influence of wind speed on COVID-19 mortality rate was evidenced only in municipalities with <100 inhabitants per km2. These results confirm the suggestion that high levels of air pollutants associated with high population density and an elevated frequency of dust events may promote an extended prevalence and severity of viral particles in the polluted air of urban, suburban, and rural communities. This supports an additional means of dissemination of the coronavirus SARS-CoV-2, in addition to the direct human-to-human transmission.
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Affiliation(s)
- Federico Páez-Osuna
- Universidad Nacional Autónoma de México, Instituto de Ciencias del Mar y Limnología, Unidad Académica Mazatlán, P.O. Box 811, Mazatlán, 82000, Sinaloa, Mexico; Miembro de El Colegio de Sinaloa, Antonio Rosales 435 Poniente, Culiacán, Sinaloa, Mexico.
| | - Gladys Valencia-Castañeda
- Universidad Nacional Autónoma de México, Instituto de Ciencias del Mar y Limnología, Unidad Académica Mazatlán, P.O. Box 811, Mazatlán, 82000, Sinaloa, Mexico
| | - Uriel Arreguin Rebolledo
- Universidad Nacional Autónoma de México, Instituto de Ciencias del Mar y Limnología, Unidad Académica Mazatlán, P.O. Box 811, Mazatlán, 82000, Sinaloa, Mexico
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22
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Marquès M, Domingo JL. Positive association between outdoor air pollution and the incidence and severity of COVID-19. A review of the recent scientific evidences. ENVIRONMENTAL RESEARCH 2022; 203:111930. [PMID: 34425111 PMCID: PMC8378989 DOI: 10.1016/j.envres.2021.111930] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 08/19/2021] [Indexed: 05/04/2023]
Abstract
In June 2020, we published a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus. The results of most of those reviewed studies suggested that chronic exposure to certain air pollutants might lead to more severe and lethal forms of COVID-19, as well as delays/complications in the recovery of the patients. Since then, a notable number of studies on this topic have been published, including also various reviews. Given the importance of this issue, we have updated the information published since our previous review. Taking together the previous results and those of most investigations now reviewed, we have concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM2.5, PM10, O3, NO2, SO2 and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease. Unfortunately, studies on the potential influence of other important air pollutants such as VOCs, dioxins and furans, or metals, are not available in the scientific literature. In relation to the influence of outdoor air pollutants on the transmission of SARS-CoV-2, although the scientific evidence is much more limited, some studies point to PM2.5 and PM10 as potential airborne transmitters of the virus. Anyhow, it is clear that environmental air pollution plays an important negative role in COVID-19, increasing its incidence and mortality.
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Affiliation(s)
- Montse Marquès
- Laboratory of Toxicology and Environmental Health, Universitat Rovira i Virgili, School of Medicine, Sant Llorens 21, 43201, Reus, Catalonia, Spain.
| | - José L Domingo
- Laboratory of Toxicology and Environmental Health, Universitat Rovira i Virgili, School of Medicine, Sant Llorens 21, 43201, Reus, Catalonia, Spain
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23
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Franch‐Pardo I, Desjardins MR, Barea‐Navarro I, Cerdà A. A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020. TRANSACTIONS IN GIS : TG 2021; 25:2191-2239. [PMID: 34512103 PMCID: PMC8420105 DOI: 10.1111/tgis.12792] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
COVID-19 has infected over 163 million people and has resulted in over 3.9 million deaths. Regarding the tools and strategies to research the ongoing pandemic, spatial analysis has been increasingly utilized to study the impacts of COVID-19. This article provides a review of 221 scientific articles that used spatial science to study the pandemic published from June 2020 to December 2020. The main objectives are: to identify the tools and techniques used by the authors; to review the subjects addressed and their disciplines; and to classify the studies based on their applications. This contribution will facilitate comparisons with the body of work published during the first half of 2020, revealing the evolution of the COVID-19 phenomenon through the lens of spatial analysis. Our results show that there was an increase in the use of both spatial statistical tools (e.g., geographically weighted regression, Bayesian models, spatial regression) applied to socioeconomic variables and analysis at finer spatial and temporal scales. We found an increase in remote sensing approaches, which are now widely applied in studies around the world. Lockdowns and associated changes in human mobility have been extensively examined using spatiotemporal techniques. Another dominant topic studied has been the relationship between pollution and COVID-19 dynamics, which enhance the impact of human activities on the pandemic's evolution. This represents a shift from the first half of 2020, when the research focused on climatic and weather factors. Overall, we have seen a vast increase in spatial tools and techniques to study COVID-19 transmission and the associated risk factors.
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Affiliation(s)
- Ivan Franch‐Pardo
- GIS LaboratoryEscuela Nacional de Estudios Superiores MoreliaUniversidad Nacional Autónoma de MéxicoMichoacánMexico
| | - Michael R. Desjardins
- Department of EpidemiologySpatial Science for Public Health CenterJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
| | - Isabel Barea‐Navarro
- Soil Erosion and Degradation Research GroupDepartment of GeographyValencia UniversityValenciaSpain
| | - Artemi Cerdà
- Soil Erosion and Degradation Research GroupDepartment of GeographyValencia UniversityValenciaSpain
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24
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Zheng HL, Guo ZL, Wang ML, Yang C, An SY, Wu W. Effects of climate variables on the transmission of COVID-19: a systematic review of 62 ecological studies. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:54299-54316. [PMID: 34398375 PMCID: PMC8364942 DOI: 10.1007/s11356-021-15929-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/07/2021] [Indexed: 04/15/2023]
Abstract
The new severe acute respiratory syndrome coronavirus 2 was initially discovered at the end of 2019 in Wuhan City in China and has caused one of the most serious global public health crises. A collection and analysis of studies related to the association between COVID-19 (coronavirus disease 2019) transmission and meteorological factors, such as humidity, is vital and indispensable for disease prevention and control. A comprehensive literature search using various databases, including Web of Science, PubMed, and Chinese National Knowledge Infrastructure, was systematically performed to identify eligible studies from Dec 2019 to Feb 1, 2021. We also established six criteria to screen the literature to obtain high-quality literature with consistent research purposes. This systematic review included a total of 62 publications. The study period ranged from 1 to 8 months, with 6 papers considering incubation, and the lag effect of climate factors on COVID-19 activity being taken into account in 22 studies. After quality assessment, no study was found to have a high risk of bias, 30 studies were scored as having moderate risks of bias, and 32 studies were classified as having low risks of bias. The certainty of evidence was also graded as being low. When considering the existing scientific evidence, higher temperatures may slow the progression of the COVID-19 epidemic. However, during the course of the epidemic, these climate variables alone could not account for most of the variability. Therefore, countries should focus more on health policies while also taking into account the influence of weather.
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Affiliation(s)
- Hu-Li Zheng
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Ze-Li Guo
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Mei-Ling Wang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Chuan Yang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Shu-Yi An
- Liaoning Provincial Centers for Disease Control and Prevention, Shenyang, Liaoning, China
| | - Wei Wu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.
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25
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Milicevic O, Salom I, Rodic A, Markovic S, Tumbas M, Zigic D, Djordjevic M, Djordjevic M. PM 2.5 as a major predictor of COVID-19 basic reproduction number in the USA. ENVIRONMENTAL RESEARCH 2021; 201:111526. [PMID: 34174258 PMCID: PMC8223012 DOI: 10.1016/j.envres.2021.111526] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/05/2021] [Accepted: 06/09/2021] [Indexed: 05/04/2023]
Abstract
Many studies have proposed a relationship between COVID-19 transmissibility and ambient pollution levels. However, a major limitation in establishing such associations is to adequately account for complex disease dynamics, influenced by e.g. significant differences in control measures and testing policies. Another difficulty is appropriately controlling the effects of other potentially important factors, due to both their mutual correlations and a limited dataset. To overcome these difficulties, we will here use the basic reproduction number (R0) that we estimate for USA states using non-linear dynamics methods. To account for a large number of predictors (many of which are mutually strongly correlated), combined with a limited dataset, we employ machine-learning methods. Specifically, to reduce dimensionality without complicating the variable interpretation, we employ Principal Component Analysis on subsets of mutually related (and correlated) predictors. Methods that allow feature (predictor) selection, and ranking their importance, are then used, including both linear regressions with regularization and feature selection (Lasso and Elastic Net) and non-parametric methods based on ensembles of weak-learners (Random Forest and Gradient Boost). Through these substantially different approaches, we robustly obtain that PM2.5 is a major predictor of R0 in USA states, with corrections from factors such as other pollutants, prosperity measures, population density, chronic disease levels, and possibly racial composition. As a rough magnitude estimate, we obtain that a relative change in R0, with variations in pollution levels observed in the USA, is typically ~30%, which further underscores the importance of pollution in COVID-19 transmissibility.
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Affiliation(s)
- Ognjen Milicevic
- Department for Medical Statistics and Informatics, School of Medicine, University of Belgrade, Serbia
| | - Igor Salom
- Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Serbia
| | - Andjela Rodic
- Quantitative Biology Group, Institute of Physiology and Biochemistry, Faculty of Biology, University of Belgrade, Serbia
| | - Sofija Markovic
- Quantitative Biology Group, Institute of Physiology and Biochemistry, Faculty of Biology, University of Belgrade, Serbia
| | - Marko Tumbas
- Quantitative Biology Group, Institute of Physiology and Biochemistry, Faculty of Biology, University of Belgrade, Serbia
| | - Dusan Zigic
- Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Serbia
| | - Magdalena Djordjevic
- Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Serbia
| | - Marko Djordjevic
- Quantitative Biology Group, Institute of Physiology and Biochemistry, Faculty of Biology, University of Belgrade, Serbia.
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26
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Baboli Z, Neisi N, Babaei AA, Ahmadi M, Sorooshian A, Birgani YT, Goudarzi G. On the airborne transmission of SARS-CoV-2 and relationship with indoor conditions at a hospital. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2021; 261:118563. [PMID: 34177342 PMCID: PMC8215890 DOI: 10.1016/j.atmosenv.2021.118563] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 05/06/2023]
Abstract
The limited knowledge about the mechanism of SARS-CoV-2 transmission is a current challenge on a global scale. Among possible transmission routes, air transfer of the virus is thought to be prominent. To investigate this further, measurements were conducted at Razi hospital in Ahvaz, Iran, which was selected to treat COVID-19 severe cases in the Khuzestan province. Passive and active sampling methods were employed and compared with regard to their efficiency for collection of airborne SARS-COV-2 virus particles. Fifty one indoor air samples were collected in two areas, with distances of less than or equal to 1 m (patient room) and more than 3 m away (hallway and nurse station) from patient beds. A simulation method was used to obtain the virus load released by a regularly breathing or coughing individual including a range of microdroplet emissions. Using real-time reverse transcription polymerase chain reaction (RT-PCR), 11.76% (N = 6) of all indoor air samples (N = 51) collected in the COVID-19 ward tested positive for SARS-CoV-2 virus, including 4 cases in patient rooms and 2 cases in the hallway. Also, 5 of the 6 positive cases were confirmed using active sampling methods with only 1 based on passive sampling. The results support airborne transmission of SARS-CoV-2 bioaerosols in indoor air. Multivariate analysis showed that among 15 parameters studied, the highest correlations with PCR results were obtained for temperature, relative humidity, PM levels, and presence of an air cleaner.
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Affiliation(s)
- Zeynab Baboli
- Student Research Committee, Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Niloofar Neisi
- Clinical Sciences Research Institute, Alimentary Tract Research Center, Department of Medical Virology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Ali Akbar Babaei
- Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Mehdi Ahmadi
- Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - Yaser Tahmasebi Birgani
- Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Gholamreza Goudarzi
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
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27
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Bherwani H, Kumar S, Musugu K, Nair M, Gautam S, Gupta A, Ho CH, Anshul A, Kumar R. Assessment and valuation of health impacts of fine particulate matter during COVID-19 lockdown: a comprehensive study of tropical and sub tropical countries. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:44522-44537. [PMID: 33852112 PMCID: PMC8044290 DOI: 10.1007/s11356-021-13813-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/01/2021] [Indexed: 05/10/2023]
Abstract
A novel coronavirus disease (COVID-19) continues to challenge the whole world. The disease has claimed many fatalities as it has transcended from one country to another since it was first discovered in China in late 2019. To prevent further morbidity and mortality associated with COVID-19, most of the countries initiated a countrywide lockdown. While physical distancing and lockdowns helped in curbing the spread of this novel coronavirus, it led to massive economic losses for the nations. Positive impacts have been observed due to lockdown in terms of improved air quality of the nations. In the current research, ten tropical and subtropical countries have been analysed from multiple angles, including air pollution, assessment and valuation of health impacts and economic loss of countries during COVID-19 lockdown. Countries include Brazil, India, Iran, Kenya, Malaysia, Mexico, Pakistan, Peru, Sri Lanka, and Thailand. Validated Simplified Aerosol Retrieval Algorithm (SARA) binning model is used on data collated from moderate resolution imaging spectroradiometer (MODIS) for particulate matters with a diameter of less than 2.5 μm (PM2.5) for all the countries for the month of January to May 2019 and 2020. The concentration results of PM2.5 show that air pollution has drastically reduced in 2020 post lockdown for all countries. The highest average concentration obtained by converting aerosol optical depth (AOD) for 2020 is observed for Thailand as 121.9 μg/m3 and the lowest for Mexico as 36.27 μg/m3. As air pollution is found to decrease in the April and May months of 2020 for nearly all countries, they are compared with respective previous year values for the same duration to calculate the reduced health burden due to lockdown. The present study estimates that cumulative about 100.9 Billion US$ are saved due to reduced air pollution externalities, which are about 25% of the cumulative economic loss of 435.9 Billion US$.
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Affiliation(s)
- Hemant Bherwani
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, Maharashtra 440020 India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh 201002 India
| | - Suman Kumar
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, Maharashtra 440020 India
| | - Kavya Musugu
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, Maharashtra 440020 India
| | - Moorthy Nair
- Asian Development Research Institute (ADRI), Patna, Bihar 800013 India
| | - Sneha Gautam
- Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu 641114 India
| | - Ankit Gupta
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, Maharashtra 440020 India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh 201002 India
| | - Chang-Hoi Ho
- School of Earth and Environmental Sciences, Seoul National University, Seoul, 08826 South Korea
| | - Avneesh Anshul
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, Maharashtra 440020 India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh 201002 India
| | - Rakesh Kumar
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, Maharashtra 440020 India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh 201002 India
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28
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Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China. ATMOSPHERE 2021. [DOI: 10.3390/atmos12060788] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.
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29
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Gao C, Li S, Liu M, Zhang F, Achal V, Tu Y, Zhang S, Cai C. Impact of the COVID-19 pandemic on air pollution in Chinese megacities from the perspective of traffic volume and meteorological factors. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 773:145545. [PMID: 33940731 PMCID: PMC7857078 DOI: 10.1016/j.scitotenv.2021.145545] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Revised: 01/26/2021] [Accepted: 01/27/2021] [Indexed: 05/09/2023]
Abstract
During 2020, the COVID-19 pandemic resulted in a widespread lockdown in many cities in China. In this study, we assessed the impact of changes in human activities on air quality during the COVID-19 pandemic by determining the relationships between air quality, traffic volume, and meteorological conditions. The megacities of Wuhan, Beijing, Shanghai, and Guangzhou were selected as the study area, and the variation trends of air pollutants for the period January-May between 2016 and 2020 were analyzed. The passenger volume of public transportation (PVPT) and the passenger volume of taxis (PVT) along with data on precipitation, temperature, relative humidity, wind speed, and boundary layer height were used to identify and quantify the driving force of the air pollution variation. The results showed that the change rates of fine particulate matter (PM2.5), NO2, and SO2 before and during the lockdown in the four megacities ranged from -49.9% to 78.2% (average: -9.4% ± 59.3%), -55.4% to -32.3% (average: -43.0% ± 9.7%), and - 21.1% to 11.9% (average: -10.9% ± 15.4%), respectively. The response of NO2 to the lockdown was the most sensitive, while the response of PM2.5 was smaller and more delayed. During the lockdown period, haze from uninterrupted industrial emissions and fireworks under the effect of air mass transport from surrounding areas and adverse climate conditions was probably the cause of abnormally high PM2.5 concentrations in Beijing. In addition, the PVT was the most significant factor for NO2, and meteorology had a greater impact on PM2.5 than NO2 and SO2. There is a need for more national-level policies for limiting firework displays and traffic emissions, as well as further studies on the formation and transmission of secondary air pollutants.
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Affiliation(s)
- Chanchan Gao
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
| | - Shuhui Li
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
| | - Min Liu
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China; Institute of Eco-Chongming (IEC), Shanghai 200062, China.
| | - Fengying Zhang
- China National Environmental Monitoring Center, Beijing 100012, China
| | - V Achal
- Environmental Engineering Program, Guangdong Technion Israel Institute of Technology, Shantou 515063, China
| | - Yue Tu
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
| | - Shiqing Zhang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
| | - Chaolin Cai
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
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30
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Othman M, Latif MT. Air pollution impacts from COVID-19 pandemic control strategies in Malaysia. JOURNAL OF CLEANER PRODUCTION 2021; 291:125992. [PMID: 33495674 PMCID: PMC7816958 DOI: 10.1016/j.jclepro.2021.125992] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 12/08/2020] [Accepted: 01/12/2021] [Indexed: 05/09/2023]
Abstract
Mitigation measures and control strategies relating to novel coronavirus disease 2019 (COVID-19) have been widely applied in many countries in order to reduce the transmission of this pandemic disease. A Movement Control Order (MCO) was implemented in Malaysia starting from the March 18, 2020 as a pandemic control strategy which restricted all movement and daily outdoor activities. To investigate the impact of MCO, air pollutants: particulate matter with an aerodynamic diameter less than 10 μm (PM10), particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and carbon monoxide (CO) in nine major cities in Malaysia were measured before and during the implementation of the MCO. The non-carcinogenic health risk assessments of the air pollutants are also determined using the United States Environmental Protection Agency (USEPA) Health Risk Assessment method. Overall, NO2 recorded an average percentage reduction of 40% with the highest reduction observed at Kota Kinabalu (62%). The largest reductions of PM10, PM2.5, SO2, O3 and CO were recorded at Kota Kinabalu (17%), Kuantan (9.5%), Alor Star (38%), Kota Bharu (15%), and Ipoh (27%) respectively. All cities had hazard quotient (HQ) values of <1 suggesting no non-carcinogenic health effects. The highest HQ was observed for PM2.5 during the MCO period (4.53E-02) in Kuala Lumpur. An average hazard index (HI) value of 1.44E-01 (before the MCO) and 1.40E-01 (during the MCO) showed higher human health risks before the MCO than during the MCO. This study gives confidence to regulatory bodies that the reduction of human activities significantly reduces air pollution and increases human health and so good air pollution control strategies can provide crucial impacts, especially in reducing air pollution and improving human health.
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Affiliation(s)
- Murnira Othman
- Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
| | - Mohd Talib Latif
- Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
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31
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Al-Dawsari SR, Sultan KS. Modeling of daily confirmed Saudi COVID-19 cases using inverted exponential regression. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:2303-2330. [PMID: 33892547 DOI: 10.3934/mbe.2021117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic caused by the coronavirus strain has had massive global impact, and has interrupted economic and social activity. The daily confirmed COVID-19 cases in Saudi Arabia are shown to be affected by some explanatory variables that are recorded daily: recovered COVID-19 cases, critical cases, daily active cases, tests per million, curfew hours, maximal temperatures, maximal relative humidity, maximal wind speed, and maximal pressure. Restrictions applied by the Saudi Arabia government due to the COVID-19 outbreak, from the suspension of Umrah and flights, and the lockdown of some cities with a curfew are based on information about COVID-15. The aim of the paper is to propose some predictive regression models similar to generalized linear models (GLMs) for fitting COVID-19 data in Saudi Arabia to analyze, forecast, and extract meaningful information that helps decision makers. In this direction, we propose some regression models on the basis of inverted exponential distribution (IE-Reg), Bayesian (BReg) and empirical Bayesian regression (EBReg) models for use in conjunction with inverted exponential distribution (IE-BReg and IE-EBReg). In all approaches, we use the logarithm (log) link function, gamma prior and two loss functions in the Bayesian approach, namely, the zero-one and LINEX loss functions. To deal with the outliers in the proposed models, we apply Huber and Tukey's bisquare (biweight) functions. In addition, we use the iteratively reweighted least squares (IRLS) algorithm to estimate Bayesian regression coefficients. Further, we compare IE-Reg, IE-BReg, and IE-EBReg using some criteria, such as Akaike's information criterion (AIC), Bayesian information criterion (BIC), deviance (D), and mean squared error (MSE). Finally, we apply the collected data of the daily confirmed from March 23 - June 21, 2020 with the corresponding explanatory variables to the theoretical findings. IE-EBReg shows good model for the COVID-19 cases in Saudi Arabia compared with the other models.
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Affiliation(s)
- Sarah R Al-Dawsari
- Department of Statistics and Operations Research, College of Science, King Saud University, P.O.Box 2455, Riyadh 11451, Saudi Arabia
| | - Khalaf S Sultan
- Department of Statistics and Operations Research, College of Science, King Saud University, P.O.Box 2455, Riyadh 11451, Saudi Arabia
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