Time to and extent of widespread testing for COVID-19 outbreak: Experience from the first wave in Australia and Italy

Abstract

Background: At the beginning of COVID-19 outbreak, very little was known about its control options and most of the intervention options relied mainly on other virus outbreak and influenza epidemic. Different countries started responding to this epidemic somewhat in different ways to achieve a common goal of transmission reduction. Population-wide intervention measures such as social distancing, testing and isolation were implemented in different countries. However, commonly adopted intervention measures impacted different countries in different ways. Differential effects of those interventions become apparent in Australia and Italy, where Australia's success to control the epidemic has been in limelight. Differences in time to and extent of widespread testing are likely to have differential effects on the daily number of confirmed cases in both countries.Methods: We apply panel generalized linear models for daily number of cases to explore differential effects of timing to and extent of widespread testing on daily number of cases. We have analyzed daily number of confirmed cases data from the first reported cases in Australia and Italy to 31 May 2020. Our data sets can be downloaded from an open source database at https://ourworldindata.org.Results: More tests during the early stage of outbreak prior to reach the peak may reduce the daily number of cases by almost 40%. Only 1% increase in test positivity on the (t-5)th day may incur 1.84% increase in daily number of cases on the t-th day. For 1% increase in test positivity rate on the (t-5)th day, a country with one unit higher logarithm of population density may result in 2.82 times higher number of cases on the t-th day.Conclusion: Conducting widespread testing during the early stage prior to reaching the peak has favored Australia to control the outbreak much faster than Italy. Early adoption of widespread testing with lower degree of test positivity rates flattens the curve faster. Population density has a moderating effect. Even if the test positivity rate is the same, a region with higher population density is likely to experience a peak with higher number of daily confirmed cases.