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Impact of government policies on the COVID-19 pandemic unraveled by mathematical modelling.
Wilk, Agata Malgorzata; Lakomiec, Krzysztof; Psiuk-Maksymowicz, Krzysztof; Fujarewicz, Krzysztof.
  • Wilk AM; Department of Systems Biology and Engineering, Silesian University of Technology, 44-100, Gliwice, Poland. agata.wilk@polsl.pl.
  • Lakomiec K; Department of Biostatistics and Bioinformatics, Maria Sklodowska-Curie National Research Institute Gliwice Branch, 44-100, Gliwice, Poland. agata.wilk@polsl.pl.
  • Psiuk-Maksymowicz K; Department of Systems Biology and Engineering, Silesian University of Technology, 44-100, Gliwice, Poland.
  • Fujarewicz K; Biotechnology Center, Silesian University of Technology, 44-100, Gliwice, Poland.
Sci Rep ; 12(1): 16987, 2022 Oct 10.
Article in English | MEDLINE | ID: covidwho-2062262
ABSTRACT
Since the very beginning of the COVID-19 pandemic, control policies and restrictions have been the hope for containing the rapid spread of the virus. However, the psychological and economic toll they take on society entails the necessity to develop an optimal control strategy. Assessment of the effectiveness of these interventions aided with mathematical modelling remains a non-trivial issue in terms of numerical conditioning due to the high number of parameters to estimate from a highly noisy dataset and significant correlations between policy timings. We propose a solution to the problem of parameter non-estimability utilizing data from a set of European countries. Treating a subset of parameters as common for all countries and the rest as country-specific, we construct a set of individualized models incorporating 13 different pandemic control measures, and estimate their parameters without prior assumptions. We demonstrate high predictive abilities of these models on an independent validation set and rank the policies by their effectiveness in reducing transmission rates. We show that raising awareness through information campaigns, providing income support, closing schools and workplaces, cancelling public events, and maintaining an open testing policy have the highest potential to mitigate the pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-21126-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-21126-2