Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index

Abstract Multiple small- to middle-scale cities, mostly located in northern China, became epidemic hotspots during the second wave of the spread of COVID-19 in early 2021. Despite qualitative discussions of potential social-economic causes, it remains unclear how this unordinary pattern could be sub...

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Autores principales:	Tianyi Li, Jiawen Luo, Cunrui Huang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/db103c837b084d5aaa4a4c37cdc4be81
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spelling	oai:doaj.org-article:db103c837b084d5aaa4a4c37cdc4be812021-12-02T16:17:33ZUnderstanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index10.1038/s41598-021-94144-12045-2322https://doaj.org/article/db103c837b084d5aaa4a4c37cdc4be812021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94144-1https://doaj.org/toc/2045-2322Abstract Multiple small- to middle-scale cities, mostly located in northern China, became epidemic hotspots during the second wave of the spread of COVID-19 in early 2021. Despite qualitative discussions of potential social-economic causes, it remains unclear how this unordinary pattern could be substantiated with quantitative explanations. Through the development of an urban epidemic hazard index (EpiRank) for Chinese prefectural districts, we came up with a mathematical explanation for this phenomenon. The index is constructed via epidemic simulations on a multi-layer transportation network interconnecting local SEIR transmission dynamics, which characterizes intra- and inter-city population flow with a granular mathematical description. Essentially, we argue that these highlighted small towns possess greater epidemic hazards due to the combined effect of large local population and small inter-city transportation. The ratio of total population to population outflow could serve as an alternative city-specific indicator of such hazards, but its effectiveness is not as good as EpiRank, where contributions from other cities in determining a specific city’s epidemic hazard are captured via the network approach. Population alone and city GDP are not valid signals for this indication. The proposed index is applicable to different epidemic settings and can be useful for the risk assessment and response planning of urban epidemic hazards in China. The model framework is modularized and the analysis can be extended to other nations.Tianyi LiJiawen LuoCunrui HuangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tianyi Li Jiawen Luo Cunrui Huang Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index
description	Abstract Multiple small- to middle-scale cities, mostly located in northern China, became epidemic hotspots during the second wave of the spread of COVID-19 in early 2021. Despite qualitative discussions of potential social-economic causes, it remains unclear how this unordinary pattern could be substantiated with quantitative explanations. Through the development of an urban epidemic hazard index (EpiRank) for Chinese prefectural districts, we came up with a mathematical explanation for this phenomenon. The index is constructed via epidemic simulations on a multi-layer transportation network interconnecting local SEIR transmission dynamics, which characterizes intra- and inter-city population flow with a granular mathematical description. Essentially, we argue that these highlighted small towns possess greater epidemic hazards due to the combined effect of large local population and small inter-city transportation. The ratio of total population to population outflow could serve as an alternative city-specific indicator of such hazards, but its effectiveness is not as good as EpiRank, where contributions from other cities in determining a specific city’s epidemic hazard are captured via the network approach. Population alone and city GDP are not valid signals for this indication. The proposed index is applicable to different epidemic settings and can be useful for the risk assessment and response planning of urban epidemic hazards in China. The model framework is modularized and the analysis can be extended to other nations.
format	article
author	Tianyi Li Jiawen Luo Cunrui Huang
author_facet	Tianyi Li Jiawen Luo Cunrui Huang
author_sort	Tianyi Li
title	Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index
title_short	Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index
title_full	Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index
title_fullStr	Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index
title_full_unstemmed	Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index
title_sort	understanding small chinese cities as covid-19 hotspots with an urban epidemic hazard index
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/db103c837b084d5aaa4a4c37cdc4be81
work_keys_str_mv	AT tianyili understandingsmallchinesecitiesascovid19hotspotswithanurbanepidemichazardindex AT jiawenluo understandingsmallchinesecitiesascovid19hotspotswithanurbanepidemichazardindex AT cunruihuang understandingsmallchinesecitiesascovid19hotspotswithanurbanepidemichazardindex
_version_	1718384260477353984

Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index

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