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Metadados | Descrição | Idioma |
---|---|---|
Autor(es): dc.contributor | Universidade Estadual Paulista (Unesp) | - |
Autor(es): dc.creator | Fortaleza, C. M.C.B. [UNESP] | - |
Autor(es): dc.creator | Guimarães, R. B. [UNESP] | - |
Autor(es): dc.creator | De Almeida, G. B. [UNESP] | - |
Autor(es): dc.creator | Pronunciate, M. [UNESP] | - |
Autor(es): dc.creator | Ferreira, C. P. [UNESP] | - |
Data de aceite: dc.date.accessioned | 2022-02-22T00:31:23Z | - |
Data de disponibilização: dc.date.available | 2022-02-22T00:31:23Z | - |
Data de envio: dc.date.issued | 2020-12-11 | - |
Data de envio: dc.date.issued | 2020-12-11 | - |
Data de envio: dc.date.issued | 2019-12-31 | - |
Fonte completa do material: dc.identifier | http://dx.doi.org/10.1017/S095026882000134X | - |
Fonte completa do material: dc.identifier | http://hdl.handle.net/11449/200676 | - |
Fonte: dc.identifier.uri | http://educapes.capes.gov.br/handle/11449/200676 | - |
Descrição: dc.description | Even though the impact of COVID-19 in metropolitan areas has been extensively studied, the geographic spread to smaller cities is also of great concern. We conducted an ecological study aimed at identifying predictors of early introduction, incidence rates of COVID-19 and mortality (up to 8 May 2020) among 604 municipalities in inner São Paulo State, Brazil. Socio-demographic indexes, road distance to the state capital and a classification of regional relevance were included in predictive models for time to COVID-19 introduction (Cox Regression), incidence and mortality rates (Zero-Inflated Binomial Negative Regression). In multivariable analyses, greater demographic density and higher classification of regional relevance were associated with both early introduction and increased rates of COVID-19 incidence and mortality. Other predictive factors varied, but distance from the State Capital (São Paulo City) was negatively associated with time-to-introduction and with incidence rates of COVID-19. Our results reinforce the hypothesis of two patterns of geographical spread of SARS-Cov-2 infection: one that is spatial (from the metropolitan area into the inner state) and another which is hierarchical (from urban centres of regional relevance to smaller and less connected municipalities). Those findings may apply to other settings, especially in developing and highly heterogeneous countries, and point to a potential benefit from strengthening non-pharmaceutical control strategies in areas of greater risk. | - |
Descrição: dc.description | Department of Infectious Diseases Botucatu School of Medicine São Paulo State University (UNESP), Av. Prof. Mário Rubens Guimarães Montenegro, s/n | - |
Descrição: dc.description | Department of Geography Faculty of Science and Technology São Paulo State University (UNESP) | - |
Descrição: dc.description | Department of Biostatistics Botucatu Institute of Biosciences São Paulo State University (UNESP) | - |
Descrição: dc.description | Department of Infectious Diseases Botucatu School of Medicine São Paulo State University (UNESP), Av. Prof. Mário Rubens Guimarães Montenegro, s/n | - |
Descrição: dc.description | Department of Geography Faculty of Science and Technology São Paulo State University (UNESP) | - |
Descrição: dc.description | Department of Biostatistics Botucatu Institute of Biosciences São Paulo State University (UNESP) | - |
Idioma: dc.language | en | - |
Relação: dc.relation | Epidemiology and Infection | - |
???dc.source???: dc.source | Scopus | - |
Título: dc.title | Taking the inner route: Spatial and demographic factors affecting vulnerability to COVID-19 among 604 cities from inner São Paulo State, Brazil. | - |
Tipo de arquivo: dc.type | livro digital | - |
Aparece nas coleções: | Repositório Institucional - Unesp |
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