How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries
Objective We study the predetermined characteristics of countries in addition to their government non-pharmaceutical interventions (NPIs) to shed light on the correlates of the variation in COVID-19 infection outcomes across countries.Methods and analysis We conduct a systematic investigation of the...
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BMJ Publishing Group
2024-04-01
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| Series: | BMJ Public Health |
| Online Access: | https://bmjpublichealth.bmj.com/content/2/1/e000032.full |
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| author | Gordon G Liu Junjian Yi Hanmo Yang Xiaoyun Peng |
| author_facet | Gordon G Liu Junjian Yi Hanmo Yang Xiaoyun Peng |
| author_sort | Gordon G Liu |
| collection | DOAJ |
| description | Objective We study the predetermined characteristics of countries in addition to their government non-pharmaceutical interventions (NPIs) to shed light on the correlates of the variation in COVID-19 infection outcomes across countries.Methods and analysis We conduct a systematic investigation of the validity of government responses in 84 countries by gradually adding the predetermined cultural, natural and socioeconomic factors of each country using a fixed-effect model and daily panel data. A relative importance analysis is conducted to isolate the contribution of each variable to the R2 of the model.Results Government NPIs are effective in containing the virus spread and explain approximately 9% of the variations in the pandemic outcomes. COVID-19 is more prevalent in countries that are more individual-oriented or with a higher gross domestic product (GDP) per capita, while a country’s government expenditure on health as a proportion of GDP and median age are negatively associated with the infection outcome. The SARS-CoV-2 lifecycle and the impacts of other unobserved factors together explain more than half of the variation in the prevalence of COVID-19 across countries. The degree of individualism explains 9.30% of the variation, and the explanatory power of the other socioeconomic factors is less than 4% each.Conclusion The COVID-19 infection outcomes are correlated with multivariate factors, ranging from state NPIs, culture-influenced human behaviours, geographical conditions and socioeconomic conditions. As expected, the stronger or faster are the government responses, the lower is the level of infections. In the meantime, many other factors underpin a major part of the variation in the control of COVID-19. As such, from a scientific perspective, it is important that country-specific conditions are taken into account when evaluating the impact of NPIs in order to conduct more cost-effective policy interventions. |
| format | Article |
| id | doaj-art-7e9afc5272d94a4bae9ab2c4bc148bdf |
| institution | Kabale University |
| issn | 2753-4294 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | BMJ Publishing Group |
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| series | BMJ Public Health |
| spelling | doaj-art-7e9afc5272d94a4bae9ab2c4bc148bdf2025-01-29T03:35:12ZengBMJ Publishing GroupBMJ Public Health2753-42942024-04-012110.1136/bmjph-2023-000032How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countriesGordon G Liu0Junjian Yi1Hanmo Yang2Xiaoyun Peng3China Center for Economic Research, National School of Development, Peking University, Beijing, Beijing, ChinaChina Center for Economic Research, National School of Development, Peking University, Beijing, Beijing, ChinaDepartment of Global Health and Population, T H Chan School of Public Health, Harvard University, Boston, Massachusetts, USAChina Center for Economic Research, National School of Development, Peking University, Beijing, Beijing, ChinaObjective We study the predetermined characteristics of countries in addition to their government non-pharmaceutical interventions (NPIs) to shed light on the correlates of the variation in COVID-19 infection outcomes across countries.Methods and analysis We conduct a systematic investigation of the validity of government responses in 84 countries by gradually adding the predetermined cultural, natural and socioeconomic factors of each country using a fixed-effect model and daily panel data. A relative importance analysis is conducted to isolate the contribution of each variable to the R2 of the model.Results Government NPIs are effective in containing the virus spread and explain approximately 9% of the variations in the pandemic outcomes. COVID-19 is more prevalent in countries that are more individual-oriented or with a higher gross domestic product (GDP) per capita, while a country’s government expenditure on health as a proportion of GDP and median age are negatively associated with the infection outcome. The SARS-CoV-2 lifecycle and the impacts of other unobserved factors together explain more than half of the variation in the prevalence of COVID-19 across countries. The degree of individualism explains 9.30% of the variation, and the explanatory power of the other socioeconomic factors is less than 4% each.Conclusion The COVID-19 infection outcomes are correlated with multivariate factors, ranging from state NPIs, culture-influenced human behaviours, geographical conditions and socioeconomic conditions. As expected, the stronger or faster are the government responses, the lower is the level of infections. In the meantime, many other factors underpin a major part of the variation in the control of COVID-19. As such, from a scientific perspective, it is important that country-specific conditions are taken into account when evaluating the impact of NPIs in order to conduct more cost-effective policy interventions.https://bmjpublichealth.bmj.com/content/2/1/e000032.full |
| spellingShingle | Gordon G Liu Junjian Yi Hanmo Yang Xiaoyun Peng How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries BMJ Public Health |
| title | How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries |
| title_full | How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries |
| title_fullStr | How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries |
| title_full_unstemmed | How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries |
| title_short | How much does government’s short-term response matter for explaining cross-country variation in COVID-19 infection outcomes? A regression-based relative importance analysis of 84 countries |
| title_sort | how much does government s short term response matter for explaining cross country variation in covid 19 infection outcomes a regression based relative importance analysis of 84 countries |
| url | https://bmjpublichealth.bmj.com/content/2/1/e000032.full |
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