Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic
It has been a year since the outbreak of the coronavirus epidemic 2019 (COVID-19). In the face of the global epidemic, governments in all countries have taken different prevention measures, such as social isolation, mandatory health protection, and the closure of schools and workplaces. The situatio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/9/2/116 |
| _version_ | 1797408593216012288 |
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| author | Xianghui Wang Chang Chen Yan Du Yang Zhang Chengliang Wu |
| author_facet | Xianghui Wang Chang Chen Yan Du Yang Zhang Chengliang Wu |
| author_sort | Xianghui Wang |
| collection | DOAJ |
| description | It has been a year since the outbreak of the coronavirus epidemic 2019 (COVID-19). In the face of the global epidemic, governments in all countries have taken different prevention measures, such as social isolation, mandatory health protection, and the closure of schools and workplaces. The situation of the epidemic has clearly varied from country to country. In this context, research on the impact of policies for the control of the spread of the global epidemic is of great significance. In this paper, we examined data from a sample of 212 countries between 31 December 2019, and 21 May 2020, using multi-fuzzy regression discontinuity. We found that developed countries had relatively low sensitivity to the policy stringency index; however, policy control measures had a significant effect on epidemic control. In addition, the trend analysis showed that the corresponding management and control came into play only after the policy stringency index reached 50 or the policy management reached level II, and the robustness was optimal at this time. Therefore, the governments in all countries should realize that epidemic prevention and control are of great importance. They can strengthen policy stringency to control the spread of the epidemic, considering their national conditions in terms of the economy and health system. |
| first_indexed | 2024-03-09T04:01:43Z |
| format | Article |
| id | doaj.art-a57ff816b1e44e5d857cea6f20cc8b20 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T04:01:43Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
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| series | Healthcare |
| spelling | doaj.art-a57ff816b1e44e5d857cea6f20cc8b202023-12-03T14:13:17ZengMDPI AGHealthcare2227-90322021-01-019211610.3390/healthcare9020116Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus EpidemicXianghui Wang0Chang Chen1Yan Du2Yang Zhang3Chengliang Wu4School of Economics and Management, Beijing Forestry University, Beijing 100083, ChinaSchool of Economics and Management, Beijing Forestry University, Beijing 100083, ChinaSchool of Economics and Management, Beijing Forestry University, Beijing 100083, ChinaSchool of Economics and Management, Beijing Forestry University, Beijing 100083, ChinaSchool of Economics and Management, Beijing Forestry University, Beijing 100083, ChinaIt has been a year since the outbreak of the coronavirus epidemic 2019 (COVID-19). In the face of the global epidemic, governments in all countries have taken different prevention measures, such as social isolation, mandatory health protection, and the closure of schools and workplaces. The situation of the epidemic has clearly varied from country to country. In this context, research on the impact of policies for the control of the spread of the global epidemic is of great significance. In this paper, we examined data from a sample of 212 countries between 31 December 2019, and 21 May 2020, using multi-fuzzy regression discontinuity. We found that developed countries had relatively low sensitivity to the policy stringency index; however, policy control measures had a significant effect on epidemic control. In addition, the trend analysis showed that the corresponding management and control came into play only after the policy stringency index reached 50 or the policy management reached level II, and the robustness was optimal at this time. Therefore, the governments in all countries should realize that epidemic prevention and control are of great importance. They can strengthen policy stringency to control the spread of the epidemic, considering their national conditions in terms of the economy and health system.https://www.mdpi.com/2227-9032/9/2/116coronavirus (COVID-19)policy stringencyregression discontinuity |
| spellingShingle | Xianghui Wang Chang Chen Yan Du Yang Zhang Chengliang Wu Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic Healthcare coronavirus (COVID-19) policy stringency regression discontinuity |
| title | Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic |
| title_full | Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic |
| title_fullStr | Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic |
| title_full_unstemmed | Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic |
| title_short | Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic |
| title_sort | analysis of policies based on the multi fuzzy regression discontinuity in terms of the number of deaths in the coronavirus epidemic |
| topic | coronavirus (COVID-19) policy stringency regression discontinuity |
| url | https://www.mdpi.com/2227-9032/9/2/116 |
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