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http://hdl.handle.net/10362/142483| Título: | Effectiveness of Non-Pharmaceutical Interventions on Reducing COVID-19 Mortality - A comparative study across six European countries |
| Autor: | Silva, Joel Pereira da |
| Orientador: | Mendes, Jorge Morais |
| Palavras-chave: | COVID-19 Non-pharmaceutical interventions Multiple linear regression Restrictions SDG 3 - Good health and well-being |
| Data de Defesa: | 7-Jul-2022 |
| Resumo: | Since the early stages of the COVID-19 pandemic, governments resorted to non-pharmaceutical interventions (NPI) to contain the spread of the disease. Despite being considered the most effective measures in the absence of specific treatments and vaccines, NPI's raise several concerns as they are closely associated with severe negative social and economic impacts. We evaluate the effect of NPI on reducing COVID-19 mortality and assess if stricter NPI's are associated with fewer fatalities. A multiple linear regression model linking the COVID-19 mortality rate with a set of ten NPI's is estimated for six countries European countries using data from the disease's first wave. From the analysis, no clear and consistent pattern emerges across the six countries regarding the effectiveness of the implemented NPI's. Stay-at-home requirements is the measure most associated with a reduction in the mortality rate. The relationship between higher levels of strictness and a reduction in mortality was also scarce. The identified variation in the effectiveness of NPI provides support for a strategy in which restrictions are implemented with a tailored approach rather than in a standardised way. This study helps inform health authorities and policy makers on the most effective practices in the application of NPI's in either present or future epidemics, with the aim of balancing safety with wellbeing and the overall functioning of society and the economy. |
| Descrição: | Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management |
| URI: | http://hdl.handle.net/10362/142483 |
| Designação: | Mestrado em Estatística e Gestão de Informação, especialização em Análise e Gestão de Informação |
| Aparece nas colecções: | NIMS - Dissertações de Mestrado em Estatística e Gestão da Informação (Statistics and Information Management) |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| TEGI0606.pdf | 775,51 kB | Adobe PDF | Ver/Abrir |
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