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Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model
Particulate matter (PM) may play a role in differential distribution and transmission rates of SARS-CoV-2. For public health surveillance, identification of factors affecting the transmission dynamics concerning the endemic (persistent sporadic) and epidemic (rapidly clustered) component of infectio...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164771/ https://www.ncbi.nlm.nih.gov/pubmed/35667404 http://dx.doi.org/10.1016/j.envres.2022.113617 |
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author | Di Biagio, Katiuscia Baldini, Marco Dolcini, Jacopo Serafini, Pietro Sarti, Donatella Dorillo, Irene Ranzi, Andrea Settimo, Gaetano Bartolacci, Silvia Simeoni, Thomas Valerio Prospero, Emilia |
author_facet | Di Biagio, Katiuscia Baldini, Marco Dolcini, Jacopo Serafini, Pietro Sarti, Donatella Dorillo, Irene Ranzi, Andrea Settimo, Gaetano Bartolacci, Silvia Simeoni, Thomas Valerio Prospero, Emilia |
author_sort | Di Biagio, Katiuscia |
collection | PubMed |
description | Particulate matter (PM) may play a role in differential distribution and transmission rates of SARS-CoV-2. For public health surveillance, identification of factors affecting the transmission dynamics concerning the endemic (persistent sporadic) and epidemic (rapidly clustered) component of infection can help to implement intervention strategies to reduce the disease burden. The aim of this study is to assess the effect of long-term residential exposure to outdoor PM ≤ 10 μm (PM(10)) concentrations on SARS-CoV-2 incidence and on its spreading dynamics in Marche region (Central Italy) during the first wave of the COVID-19 pandemic (February to May 2020), using the endemic-epidemic spatio-temporal regression model for individual-level data. Environmental and climatic factors were estimated at 10 km(2) grid cells. 10-years average exposure to PM(10) was associated with an increased risk of new endemic (Rate Ratio for 10 μg/m(3) increase 1.14, 95%CI 1.04–1.24) and epidemic (Rate Ratio 1.15, 95%CI 1.08–1.22) infection. Male gender, older age, living in Nursing Homes and Long-Term Care Facilities residence and socio-economic deprivation index increased Rate Ratio (RR) in epidemic component. Lockdown increased the risk of becoming positive to SARS-CoV-2 as concerning endemic component while it reduced virus spreading in epidemic one. Increased temperature was associated with a reduction of endemic and epidemic infection. Results showed an increment of RR for exposure to increased levels of PM(10) both in endemic and epidemic components. Targeted interventions are necessary to improve air quality in most polluted areas, where deprived populations are more likely to live, to minimize the burden of endemic and epidemic COVID-19 disease and to reduce unequal distribution of health risk. |
format | Online Article Text |
id | pubmed-9164771 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91647712022-06-04 Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model Di Biagio, Katiuscia Baldini, Marco Dolcini, Jacopo Serafini, Pietro Sarti, Donatella Dorillo, Irene Ranzi, Andrea Settimo, Gaetano Bartolacci, Silvia Simeoni, Thomas Valerio Prospero, Emilia Environ Res Article Particulate matter (PM) may play a role in differential distribution and transmission rates of SARS-CoV-2. For public health surveillance, identification of factors affecting the transmission dynamics concerning the endemic (persistent sporadic) and epidemic (rapidly clustered) component of infection can help to implement intervention strategies to reduce the disease burden. The aim of this study is to assess the effect of long-term residential exposure to outdoor PM ≤ 10 μm (PM(10)) concentrations on SARS-CoV-2 incidence and on its spreading dynamics in Marche region (Central Italy) during the first wave of the COVID-19 pandemic (February to May 2020), using the endemic-epidemic spatio-temporal regression model for individual-level data. Environmental and climatic factors were estimated at 10 km(2) grid cells. 10-years average exposure to PM(10) was associated with an increased risk of new endemic (Rate Ratio for 10 μg/m(3) increase 1.14, 95%CI 1.04–1.24) and epidemic (Rate Ratio 1.15, 95%CI 1.08–1.22) infection. Male gender, older age, living in Nursing Homes and Long-Term Care Facilities residence and socio-economic deprivation index increased Rate Ratio (RR) in epidemic component. Lockdown increased the risk of becoming positive to SARS-CoV-2 as concerning endemic component while it reduced virus spreading in epidemic one. Increased temperature was associated with a reduction of endemic and epidemic infection. Results showed an increment of RR for exposure to increased levels of PM(10) both in endemic and epidemic components. Targeted interventions are necessary to improve air quality in most polluted areas, where deprived populations are more likely to live, to minimize the burden of endemic and epidemic COVID-19 disease and to reduce unequal distribution of health risk. Elsevier Inc. 2022-09 2022-06-03 /pmc/articles/PMC9164771/ /pubmed/35667404 http://dx.doi.org/10.1016/j.envres.2022.113617 Text en © 2022 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Di Biagio, Katiuscia Baldini, Marco Dolcini, Jacopo Serafini, Pietro Sarti, Donatella Dorillo, Irene Ranzi, Andrea Settimo, Gaetano Bartolacci, Silvia Simeoni, Thomas Valerio Prospero, Emilia Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model |
title | Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model |
title_full | Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model |
title_fullStr | Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model |
title_full_unstemmed | Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model |
title_short | Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model |
title_sort | atmospheric particulate matter effects on sars-cov-2 infection and spreading dynamics: a spatio-temporal point process model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164771/ https://www.ncbi.nlm.nih.gov/pubmed/35667404 http://dx.doi.org/10.1016/j.envres.2022.113617 |
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