ESTIMATING THE POSSIBLE ROLE OF TESTING CAPACITY AND SOCIAL DISTANCING IN PREDICTING THE GROWTH RATE OF DAILY COVID-19 CASES.

Background: The purpose of this study was to estimate the effect of social distancing (days since the imposition of a lock-down) and the number of daily tests conducted per million population on the daily growth rate of COVID-19 cases. Methods: After excluding the first 30 days since the announcement of an index case in a country, relevant data for the next forty days was collected from four countries: Belgium, Italy, South Korea and United Kingdom. Two online databases: Our World in Data and worldometer were used for the collection of data which included the number of new COVID-19 cases and the number of tests conducted on a given day. The acquired figures were transformed into per million population of the given country. The growth rate of daily COVID-19 cases was derived and was used as the regress and in a multiple linear regression with the number of tests per million population per day and the number of days since a lock-down was imposed as the regressors. Results: It was found that the growth rate of daily COVID-19 cases decreased by .051% when the number of daily tests conducted per million population increased by 1. A .532% decrease in the growth rate of daily COVID-19 cases was observed with each passing day of a lock-down, which essentially represented the most effective form of social distancing. A significant regression was calculated (F (2, 155) = 35.191, p=.014), with an R2 of .054. Neither the daily number of tests conducted per million population nor the number of days of maintaining social distancing (lock-down) was individually significant contributors to the prediction of the growth rate of daily COVID-19 cases (p=.267 and p=.554 respectively). Conclusion: An extensive and rapid increase in the daily number of testing capacity and maintaining social distancing can decrease the growth rate of daily COVID-19 cases. Depending on the availability of the required resources, timely implementation of these measures can lead to better outcomes for a given population. [ABSTRACT FROM AUTHOR]