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10.1016/j.jobcr.2020.08.005

http://scihub22266oqcxt.onion/10.1016/j.jobcr.2020.08.005
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suck abstract from ncbi


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pmid32834983      J+Oral+Biol+Craniofac+Res 2020 ; 10 (4): 504-513
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  • Analysing governmental response to the COVID-19 pandemic #MMPMID32834983
  • Imtyaz A; Abid Haleem; Javaid M
  • J Oral Biol Craniofac Res 2020[Oct]; 10 (4): 504-513 PMID32834983show ga
  • BACKGROUND AND AIMS: COVID-19, which started as an epidemic from China in November 2019, was first reported to WHO in December 2019. It had spread to almost all countries globally by March 2020. The pandemic severely affected health and economy globally, prompting countries to take drastic measures to combat the virus. This study aims to analyze different governments' responses to the pandemic to gain insights on how best to fight the Coronavirus. METHODOLOGY: Various data analysis operations like clustering and bivariate analysis were carried out using Python, Pandas, Scikit-Learn, and Matplotlib to clean up, consolidate, and visualize data. Insights were drawn from the analysis conducted. RESULTS: We identified that the mortality rate/case fatality rate is directly proportional to the percentage of elderly (people above 65 years of age) for the top thirty countries by cases. Countries in Western Europe showed the highest mortality rates, whereas countries in South Asia and the Middle East showed the lowest mortality rate (controlling for all other variables). CONCLUSION: Lockdowns are effective in curbing the spread of the virus. A higher amount of testing resulted in a lesser spreading of the virus and better control. In most regions, countries that were conducting a large number of tests also seemed to have lower mortality rates.
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