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1000
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Abstract/Summary
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Background and objective!#!It has not been adequately answered whether the spread of SARS-CoV‑2 is influenced by social and economic factors. Earlier studies generally looked at cumulative incidences up to the analysis date and did not take into account the development of the spread over time. This study therefore focuses on the regional dynamic of new infections and their relationship to socioeconomic factors. Based on the literature we describe the state of knowledge and present our own analyses of administrative data from Germany.!##!Methods!#!For this study, we examined regional progress data of reported COVID-19 cases for 401 cities and counties in Germany and associated them with socioeconomic characteristics of the areas. Age-standardized weekly incidence rates were calculated for the period from 3 February 2020 to 28 March 2021. Macroindicators were added from the INKAR database (e.g., income, employment rate, and crowding).!##!Results!#!While areas with higher incomes and lower poverty had higher incidences in the first and at the beginning of the second wave of the pandemic, they increased significantly in low-income regions from December 2020 on. Regions with a high proportion of gainfully employed people in general and especially those in the manufacturing sector had high incidences, especially in the second wave and at the beginning of the third wave. A low mean living space per inhabitant was related to higher incidence rates since November 2020.!##!Conclusion!#!The regional temporal course of the pandemic correlates with social and economic indicators. A differentiated consideration of these differences could provide information on target group-specific protection and test strategies and help to identify social factors that generally favor infections. An English full-text version of this article is available at SpringerLink as Supplementary Information.
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1000
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Hinweis
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DeepGreen-ID: 4eb41e9a334b4c31b5a859fe3d9748b5 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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