Analyses

DR Dayana Rojas
JS Jorge Saavedra
MP Mariya Petrova
YP Yue Pan
JS José Szapocznik
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Aim 1. To determine the world-wide association between COVID-19 testing and fatality: first, we looked at the descriptive statistics for all variables; second, multivariate regression analyses were conducted to test the association between COVID-19 fatality and number of tests per 100 people, while controlling for case number per 1,000 people, critical case rate, government effectiveness, population aged 65 or older, hospital bed number per 1000 people, communicable disease death rate, and transport infrastructure quality. Country populations were used as weights to account for unequal variances. AIM 2. Comparing the analysis between the two time points allowed us to examine the extent to which testing affects COVID-19 fatality and how that relationship evolved from June 2020 to March 2021. For this aim, we compared the results obtained in AIM 1 to the results from the June 2020 study. Descriptive statistics were compared using Student’s t tests to calculate the differences between the COVID-19 related data at the two time-points, while the risk ratios that resulted from the regressions were compared using the ratio of risk ratios method [20]. Aim 3. Finally, using the same analytical approach as in Aim 1, the impact of testing on fatality rates for Latin America countries was compared to all other countries. The mean rate for the countries in each of the two groups were computed and the compared. Once more, Student’s t tests were used to compare the descriptive statistics between all-countries except Latin America and Latin American countries, while the regression risk ratios were compared using the ratio of risk ratios method [20]. Using the Encyclopedia Britannica’s definition of Latin America, we included the following Latin American countries in the study: Argentina, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela [21]. Analyses were performed using SAS 15.1

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