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During the global Covid-19 pandemic, governments implemented various policies, including school closures, workplace closures, and gathering restrictions, to combat the virus and mitigate its severity. However, the effectiveness of these policies varies, and each policy can also negatively impact daily life and the economy. Therefore, it is crucial to study the effectiveness of Covid-19 policies and identify those that are not so much efficient. In this study, we collected data on various policies, alongside daily new Covid-19 cases and deaths, from 183 countries worldwide. We then applied different machine learning approaches to analyze this data, aiming to determine the efficiency of individual policies and combinations of policies. Additionally, we clustered countries based on their Covid-19 policies. The results of this research can serve as a guideline for policymakers to choose optimal policies in future pandemics.

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Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Hanieh Khorashadizadeh,
  • Jinghua Groppe,
  • Jessica Lückert,
  • Sanju Tiwari,
  • Sven Groppe

摘要

During the global Covid-19 pandemic, governments implemented various policies, including school closures, workplace closures, and gathering restrictions, to combat the virus and mitigate its severity. However, the effectiveness of these policies varies, and each policy can also negatively impact daily life and the economy. Therefore, it is crucial to study the effectiveness of Covid-19 policies and identify those that are not so much efficient. In this study, we collected data on various policies, alongside daily new Covid-19 cases and deaths, from 183 countries worldwide. We then applied different machine learning approaches to analyze this data, aiming to determine the efficiency of individual policies and combinations of policies. Additionally, we clustered countries based on their Covid-19 policies. The results of this research can serve as a guideline for policymakers to choose optimal policies in future pandemics.