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10.1016/j.bsheal.2020.09.003

http://scihub22266oqcxt.onion/10.1016/j.bsheal.2020.09.003
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suck abstract from ncbi


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pmid32935084      Biosaf+Health 2021 ; 3 (1): 4-7
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  • Estimation of the case fatality rate of COVID-19 epidemiological data in Nigeria using statistical regression analysis #MMPMID32935084
  • Suleiman AA; Suleiman A; Abdullahi UA; Suleiman SA
  • Biosaf Health 2021[Feb]; 3 (1): 4-7 PMID32935084show ga
  • Following the emergence of COVID-19 outbreak, numbers of studies have been conducted to curtail the global spread of the virus by identifying epidemiological changes of the disease through developing statistical models, estimation of the basic reproduction number, displaying the daily reports of confirmed and deaths cases, which are closely related to the present study. Reliable and comprehensive estimation method of the epidemiological data is required to understand the actual situation of fatalities caused by the epidemic. Case fatality rate (CFR) is one of the cardinal epidemiological parameters that adequately explains epidemiology of the outbreak of a disease. In the present study, we employed two statistical regression models such as the linear and polynomial models in order to estimate the CFR, based on the early phase of COVID-19 outbreak in Nigeria (44 days since first reported COVID-19 death). The estimate of the CFR was determined based on cumulative number of confirmed cases and deaths reported from 23 March to 30 April, 2020. The results from the linear model estimated that the CFR was 3.11% (95% CI: 2.59% - 3.80%) with R (2) value of 90% and p-value of < 0.0001. The findings from the polynomial model suggest that the CFR associated with the Nigerian outbreak is 3.0% and may range from 2.23% to 3.42% with R (2) value of 93% and p-value of <0.0001. Therefore, the polynomial regression model with the higher R (2) value fits the dataset well and provides better estimate of CFR for the reported COVID-19 cases in Nigeria.
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