1
|
Liu S, Ji S, Xu J, Zhang Y, Zhang H, Liu J, Lu D. Exploring spatiotemporal pattern in the association between short-term exposure to fine particulate matter and COVID-19 incidence in the continental United States: a Leroux-conditional-autoregression-based strategy. Front Public Health 2023; 11:1308775. [PMID: 38186711 PMCID: PMC10768722 DOI: 10.3389/fpubh.2023.1308775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 12/05/2023] [Indexed: 01/09/2024] Open
Abstract
Background Numerous studies have demonstrated that fine particulate matter (PM2.5) is adversely associated with COVID-19 incidence. However, few studies have explored the spatiotemporal heterogeneity in this association, which is critical for developing cost-effective pollution-related policies for a specific location and epidemic stage, as well as, understanding the temporal change of association between PM2.5 and an emerging infectious disease like COVID-19. Methods The outcome was state-level daily COVID-19 cases in 49 native United States between April 1, 2020 and December 31, 2021. The exposure variable was the moving average of PM2.5 with a lag range of 0-14 days. A latest proposed strategy was used to investigate the spatial distribution of PM2.5-COVID-19 association in state level. First, generalized additive models were independently constructed for each state to obtain the rough association estimations, which then were smoothed using a Leroux-prior-based conditional autoregression. Finally, a modified time-varying approach was used to analyze the temporal change of association and explore the potential causes spatiotemporal heterogeneity. Results In all states, a positive association between PM2.5 and COVID-19 incidence was observed. Nearly one-third of these states, mainly located in the northeastern and middle-northern United States, exhibited statistically significant. On average, a 1 μg/m3 increase in PM2.5 concentration led to an increase in COVID-19 incidence by 0.92% (95%CI: 0.63-1.23%). A U-shaped temporal change of association was examined, with the strongest association occurring in the end of 2021 and the weakest association occurring in September 1, 2020 and July 1, 2021. Vaccination rate was identified as a significant cause for the association heterogeneity, with a stronger association occurring at a higher vaccination rate. Conclusion Short-term exposure to PM2.5 and COVID-19 incidence presented positive association in the United States, which exhibited a significant spatiotemporal heterogeneity with strong association in the eastern and middle regions and with a U-shaped temporal change.
Collapse
Affiliation(s)
- Shiyi Liu
- Department of Hospital Infection Management, Chengdu First People’s Hospital, Chengdu, China
| | - Shuming Ji
- Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Jianjun Xu
- Department of Hospital Infection Management, Chengdu First People’s Hospital, Chengdu, China
| | - Yujing Zhang
- Department of Hospital Infection Management, Chengdu First People’s Hospital, Chengdu, China
| | - Han Zhang
- Department of Hospital Infection Management, Chengdu First People’s Hospital, Chengdu, China
| | - Jiahe Liu
- School of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
| | - Donghao Lu
- Faculty of Art and Social Science, University of Sydney, Sydney, NSW, Australia
| |
Collapse
|
2
|
Hyman S, Zhang J, Andersen ZJ, Cruickshank S, Møller P, Daras K, Williams R, Topping D, Lim YH. Long-term exposure to air pollution and COVID-19 severity: A cohort study in Greater Manchester, United Kingdom. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 327:121594. [PMID: 37030601 PMCID: PMC10079212 DOI: 10.1016/j.envpol.2023.121594] [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: 01/19/2023] [Revised: 04/03/2023] [Accepted: 04/06/2023] [Indexed: 05/19/2023]
Abstract
Exposure to outdoor air pollution may affect incidence and severity of coronavirus disease 2019 (COVID-19). In this retrospective cohort based on patient records from the Greater Manchester Care Records, all first COVID-19 cases diagnosed between March 1, 2020 and May 31, 2022 were followed until COVID-19 related hospitalization or death within 28 days. Long-term exposure was estimated using mean annual concentrations of particulate matter with diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10), nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2) and benzene (C6H6) in 2019 using a validated air pollution model developed by the Department for Environment, Food and Rural Affairs (DEFRA). The association of long-term exposure to air pollution with COVID-19 hospitalization and mortality were estimated using multivariate logistic regression models after adjusting for potential individual, temporal and spatial confounders. Significant positive associations were observed between PM2.5, PM10, NO2, SO2, benzene and COVID-19 hospital admissions with odds ratios (95% Confidence Intervals [CI]) of 1.27 (1.25-1.30), 1.15 (1.13-1.17), 1.12 (1.10-1.14), 1.16 (1.14-1.18), and 1.39 (1.36-1.42), (per interquartile range [IQR]), respectively. Significant positive associations were also observed between PM2.5, PM10, SO2, or benzene and COVID-19 mortality with odds ratios (95% CI) of 1.39 (1.31-1.48), 1.23 (1.17-1.30), 1.18 (1.12-1.24), and 1.62 (1.52-1.72), per IQR, respectively. Individuals who were older, overweight or obese, current smokers, or had underlying comorbidities showed greater associations between all pollutants of interest and hospital admission, compared to the corresponding groups. Long-term exposure to air pollution is associated with developing severe COVID-19 after a positive SARS-CoV-2 infection, resulting in hospitalization or death.
Collapse
Affiliation(s)
- Samuel Hyman
- Department of Earth and Environmental Science, Centre for Atmospheric Science, School of Natural Sciences, The University of Manchester, Manchester, UK; Institute of Immunology and Inflammation, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK.
| | - Jiawei Zhang
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Zorana Jovanovic Andersen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Sheena Cruickshank
- Institute of Immunology and Inflammation, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK
| | - Peter Møller
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Konstantinos Daras
- Department of Public Health, Policy and Systems, Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Richard Williams
- Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; NIHR Greater Manchester Patient Safety Translational Research Centre, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK; NIHR Applied Research Collaboration Greater Manchester, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - David Topping
- Department of Earth and Environmental Science, Centre for Atmospheric Science, School of Natural Sciences, The University of Manchester, Manchester, UK
| | - Youn-Hee Lim
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
3
|
Zoran MA, Savastru RS, Savastru DM, Tautan MN. Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis. ENVIRONMENTAL RESEARCH 2023; 228:115907. [PMID: 37080275 PMCID: PMC10111861 DOI: 10.1016/j.envres.2023.115907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 05/03/2023]
Abstract
As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.
Collapse
Affiliation(s)
- Maria A Zoran
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania.
| | - Roxana S Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Dan M Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Marina N Tautan
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| |
Collapse
|
4
|
G. A, J. JP, I. TMB, Packiavathy SV, Gautam S. Internet of Things (IoT) based automated sanitizer dispenser and COVID-19 statistics reporter in a post-pandemic world. HEALTH AND TECHNOLOGY 2023; 13:327-341. [PMID: 36694669 PMCID: PMC9851904 DOI: 10.1007/s12553-023-00728-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 01/05/2023] [Indexed: 01/22/2023]
Abstract
Purpose Coronavirus is among the deadliest viruses of the 21st century. There is still a Coronavirus epidemic that affects most countries worldwide today. To prevent future outbreaks and protect public health, it is essential to invest in research and innovation on vaccines, treatments, diagnostic tests, public health infrastructure, and emergency response planning. Additionally, we need to work on mitigation strategies and take a comprehensive and multidisciplinary approach to prevent and fight against the virus. Methods For the purpose of preventing the spread of microbial organisms, it is essential to take advantage of automatic sanitizer dispensers by deploying them in public places. This is one of the most feasible and effective ways to ensure that people have easy access to hand sanitizer and can reduce the spread of germs. Results The proposed solution is a contactless sanitizer dispenser with an integrated temperature monitoring system, as well as an alert system for users who exhibit the symptom of infection. Moreover, the proposed solution has added advantage of interfacing with an electronic door so that we can easily implement it at the entrance of a public building/public transportation. This dispenser will also collect data that can be used to identify a symptomatic user and alert the appropriate authorities for safe quarantine. In addition, it is also used to monitor usage metrics, record user entries, and conduct statistical surveys using the ThinkSpeak platform. Conclusions The proposed model could be a feasible solution to prevent the entry of infected persons and asymptomatic carriers indoors. This can be achieved by implementing automated temperature screening before allowing entry into the building. This can help identify individuals who are potentially infected with the virus and prevent them from entering the premises and potentially spreading the disease to others. Overall, the proposed model is a comprehensive and practical solution that can help to prevent the entry of infected persons and asymptomatic carriers indoors and help to keep the public safe.
Collapse
Affiliation(s)
- Ashok G.
- Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India
| | - John Paul J.
- Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India
| | | | | | - Sneha Gautam
- Department of Civil Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu 641 114, India
- Water Institute, A Centre of Excellence, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu 641 114 India
| |
Collapse
|