Urban-rural disparities in COVID-19 hospitalisations and mortality: A population-based study on national surveillance data from Germany and Italy
Recent literature has highlighted the overlapping contribution of demographic characteristics and spatial factors to urban-rural disparities in SARS-CoV-2 transmission and outcomes. Yet the interplay between individual characteristics, hospitalisation, and spatial factors for urban-rural disparities...
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| creator | Assche, Simona Bignami-Van Ferraccioli, Federico Riccetti, Nicola Gomez-Ramirez, Jaime Ghio, Daniela Stilianakis, Nikolaos I |
| description | Recent literature has highlighted the overlapping contribution of demographic characteristics and spatial factors to urban-rural disparities in SARS-CoV-2 transmission and outcomes. Yet the interplay between individual characteristics, hospitalisation, and spatial factors for urban-rural disparities in COVID-19 mortality have received limited attention.
To fill this gap, we use national surveillance data collected by the European Centre for Disease Prevention and Control and we fit a generalized linear model to estimate the association between COVID-19 mortality and the individuals' age, sex, hospitalisation status, population density, share of the population over the age of 60, and pandemic wave across urban, intermediate and rural territories.
We find that in what type of territory individuals live (urban-intermediate-rural) accounts for a significant difference in their probability of dying given SARS-COV-2 infection. Hospitalisation has a large and positive effect on the probability of dying given SARS-CoV-2 infection, but with a gradient across urban, intermediate and rural territories. For those living in rural areas, the risk of dying is lower than in urban areas but only if hospitalisation was not needed; while for those who were hospitalised in rural areas the risk of dying was higher than in urban areas.
Together with individuals' demographic characteristics (notably age), hospitalisation has the largest effect on urban-rural disparities in COVID-19 mortality net of other individual and regional characteristics, including population density and the share of the population over 60. |
| doi_str_mv | 10.1371/journal.pone.0301325 |
| format | Article |
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To fill this gap, we use national surveillance data collected by the European Centre for Disease Prevention and Control and we fit a generalized linear model to estimate the association between COVID-19 mortality and the individuals' age, sex, hospitalisation status, population density, share of the population over the age of 60, and pandemic wave across urban, intermediate and rural territories.
We find that in what type of territory individuals live (urban-intermediate-rural) accounts for a significant difference in their probability of dying given SARS-COV-2 infection. Hospitalisation has a large and positive effect on the probability of dying given SARS-CoV-2 infection, but with a gradient across urban, intermediate and rural territories. For those living in rural areas, the risk of dying is lower than in urban areas but only if hospitalisation was not needed; while for those who were hospitalised in rural areas the risk of dying was higher than in urban areas.
Together with individuals' demographic characteristics (notably age), hospitalisation has the largest effect on urban-rural disparities in COVID-19 mortality net of other individual and regional characteristics, including population density and the share of the population over 60.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0301325</identifier><identifier>PMID: 38696525</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Adult ; Age ; Age groups ; Aged ; Aged, 80 and over ; Agglomeration ; Binomial distribution ; Biology and life sciences ; Clinical outcomes ; COVID-19 ; COVID-19 - epidemiology ; COVID-19 - mortality ; Death & dying ; Demographic aspects ; Demographics ; Demography ; Disease control ; Disease transmission ; Earth Sciences ; Fatalities ; Female ; Generalized linear models ; Germany ; Germany - epidemiology ; Health aspects ; Health care disparities ; Hospital care ; Hospitalization ; Hospitalization - statistics & numerical data ; Humans ; Infections ; Intensive care ; Italy - epidemiology ; Male ; Medicine and health sciences ; Middle Aged ; Mortality ; Pandemics ; People and places ; Population density ; Population studies ; Regional disparities ; Respiratory diseases ; Rural areas ; Rural Population - statistics & numerical data ; SARS-CoV-2 - isolation & purification ; Severe acute respiratory syndrome coronavirus 2 ; Social aspects ; Social Sciences ; Statistical models ; Surveillance ; Urban areas ; Urban Population - statistics & numerical data ; Viral diseases ; Viruses ; Young Adult</subject><ispartof>PloS one, 2024-05, Vol.19 (5), p.e0301325-e0301325</ispartof><rights>Copyright: © 2024 Assche et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Assche et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Assche et al 2024 Assche et al</rights><rights>2024 Assche et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c642t-66aa839b30cb12d2c93aa7d32b1666fe95d24373e4726463b831726dd2f8237a3</cites><orcidid>0000-0002-8246-3046 ; 0000-0002-9440-7711 ; 0000-0002-3808-265X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11065260/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11065260/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38696525$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Assche, Simona Bignami-Van</creatorcontrib><creatorcontrib>Ferraccioli, Federico</creatorcontrib><creatorcontrib>Riccetti, Nicola</creatorcontrib><creatorcontrib>Gomez-Ramirez, Jaime</creatorcontrib><creatorcontrib>Ghio, Daniela</creatorcontrib><creatorcontrib>Stilianakis, Nikolaos I</creatorcontrib><title>Urban-rural disparities in COVID-19 hospitalisations and mortality: A population-based study on national surveillance data from Germany and Italy</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Recent literature has highlighted the overlapping contribution of demographic characteristics and spatial factors to urban-rural disparities in SARS-CoV-2 transmission and outcomes. Yet the interplay between individual characteristics, hospitalisation, and spatial factors for urban-rural disparities in COVID-19 mortality have received limited attention.
To fill this gap, we use national surveillance data collected by the European Centre for Disease Prevention and Control and we fit a generalized linear model to estimate the association between COVID-19 mortality and the individuals' age, sex, hospitalisation status, population density, share of the population over the age of 60, and pandemic wave across urban, intermediate and rural territories.
We find that in what type of territory individuals live (urban-intermediate-rural) accounts for a significant difference in their probability of dying given SARS-COV-2 infection. Hospitalisation has a large and positive effect on the probability of dying given SARS-CoV-2 infection, but with a gradient across urban, intermediate and rural territories. For those living in rural areas, the risk of dying is lower than in urban areas but only if hospitalisation was not needed; while for those who were hospitalised in rural areas the risk of dying was higher than in urban areas.
Together with individuals' demographic characteristics (notably age), hospitalisation has the largest effect on urban-rural disparities in COVID-19 mortality net of other individual and regional characteristics, including population density and the share of the population over 60.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Age</subject><subject>Age groups</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Agglomeration</subject><subject>Binomial distribution</subject><subject>Biology and life sciences</subject><subject>Clinical outcomes</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - mortality</subject><subject>Death & dying</subject><subject>Demographic aspects</subject><subject>Demographics</subject><subject>Demography</subject><subject>Disease control</subject><subject>Disease transmission</subject><subject>Earth Sciences</subject><subject>Fatalities</subject><subject>Female</subject><subject>Generalized linear models</subject><subject>Germany</subject><subject>Germany - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Assche, Simona Bignami-Van</au><au>Ferraccioli, Federico</au><au>Riccetti, Nicola</au><au>Gomez-Ramirez, Jaime</au><au>Ghio, Daniela</au><au>Stilianakis, Nikolaos I</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Urban-rural disparities in COVID-19 hospitalisations and mortality: A population-based study on national surveillance data from Germany and Italy</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-05-02</date><risdate>2024</risdate><volume>19</volume><issue>5</issue><spage>e0301325</spage><epage>e0301325</epage><pages>e0301325-e0301325</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Recent literature has highlighted the overlapping contribution of demographic characteristics and spatial factors to urban-rural disparities in SARS-CoV-2 transmission and outcomes. Yet the interplay between individual characteristics, hospitalisation, and spatial factors for urban-rural disparities in COVID-19 mortality have received limited attention.
To fill this gap, we use national surveillance data collected by the European Centre for Disease Prevention and Control and we fit a generalized linear model to estimate the association between COVID-19 mortality and the individuals' age, sex, hospitalisation status, population density, share of the population over the age of 60, and pandemic wave across urban, intermediate and rural territories.
We find that in what type of territory individuals live (urban-intermediate-rural) accounts for a significant difference in their probability of dying given SARS-COV-2 infection. Hospitalisation has a large and positive effect on the probability of dying given SARS-CoV-2 infection, but with a gradient across urban, intermediate and rural territories. For those living in rural areas, the risk of dying is lower than in urban areas but only if hospitalisation was not needed; while for those who were hospitalised in rural areas the risk of dying was higher than in urban areas.
Together with individuals' demographic characteristics (notably age), hospitalisation has the largest effect on urban-rural disparities in COVID-19 mortality net of other individual and regional characteristics, including population density and the share of the population over 60.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38696525</pmid><doi>10.1371/journal.pone.0301325</doi><tpages>e0301325</tpages><orcidid>https://orcid.org/0000-0002-8246-3046</orcidid><orcidid>https://orcid.org/0000-0002-9440-7711</orcidid><orcidid>https://orcid.org/0000-0002-3808-265X</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | PloS one, 2024-05, Vol.19 (5), p.e0301325-e0301325 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3069285011 |
| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adolescent Adult Age Age groups Aged Aged, 80 and over Agglomeration Binomial distribution Biology and life sciences Clinical outcomes COVID-19 COVID-19 - epidemiology COVID-19 - mortality Death & dying Demographic aspects Demographics Demography Disease control Disease transmission Earth Sciences Fatalities Female Generalized linear models Germany Germany - epidemiology Health aspects Health care disparities Hospital care Hospitalization Hospitalization - statistics & numerical data Humans Infections Intensive care Italy - epidemiology Male Medicine and health sciences Middle Aged Mortality Pandemics People and places Population density Population studies Regional disparities Respiratory diseases Rural areas Rural Population - statistics & numerical data SARS-CoV-2 - isolation & purification Severe acute respiratory syndrome coronavirus 2 Social aspects Social Sciences Statistical models Surveillance Urban areas Urban Population - statistics & numerical data Viral diseases Viruses Young Adult |
| title | Urban-rural disparities in COVID-19 hospitalisations and mortality: A population-based study on national surveillance data from Germany and Italy |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T05%3A39%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Urban-rural%20disparities%20in%20COVID-19%20hospitalisations%20and%20mortality:%20A%20population-based%20study%20on%20national%20surveillance%20data%20from%20Germany%20and%20Italy&rft.jtitle=PloS%20one&rft.au=Assche,%20Simona%20Bignami-Van&rft.date=2024-05-02&rft.volume=19&rft.issue=5&rft.spage=e0301325&rft.epage=e0301325&rft.pages=e0301325-e0301325&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0301325&rft_dat=%3Cgale_plos_%3EA792379570%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3069285011&rft_id=info:pmid/38696525&rft_galeid=A792379570&rft_doaj_id=oai_doaj_org_article_def646b7be134f9a8fc3eacc21fc7c81&rfr_iscdi=true |