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Quantifying the Regional Disproportionality of COVID-19 Spread
Kenji Sasaki
Yoichi Ikeda
Takashi Nakano
Acceso Abierto
Atribución-NoComercial-SinDerivadas
https://doi.org/10.1101/2024.04.05.24305413
https://www.medrxiv.org/content/10.1101/2024.04.05.24305413v1
Background The COVID-19 pandemic has caused serious health problems and has had major economic and social consequences worldwide. Understanding how infectious diseases spread can help mitigating the social and economic impact. Objective The study focuses to capture the degrees of disproportionality in prevalence rates of infectious disease across different regions over time. Methods We analyze the numbers of daily COVID-19 confirmed cases in the United States collected by Johns Hopkins University over 1100 days since the first reported case in January 2020 in order to assess quantitatively the disproportionality of the confirmed cases using the Theil index, a measure of imbalance used in economics. Results: Our results reveal a dynamic pattern of interregional disproportionality in the confirmed cases by monitoring variations in regional contributions to the Theil index as the pandemic progresses. Conclusions The combined monitoring of this indicator and the confirmed cases is crucial for understanding regional differences in infectious diseases and for effective planning of response and resource allocation.
07-04-2024
Preimpreso
Inglés
Público en general
VIRUS RESPIRATORIOS
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