Graphical trajectory comparison to identify errors in data of covid-19: A cross-country analysis

Abstract

Data from the early stage of a novel infectious disease outbreak provide vital information in risk assessment, prediction, and precise disease management. Since the first reported case of COVID-19, the pattern of the novel coronavirus transmission in Wuhan has become the interest of researchers in epidemiology and public health. To thoroughly map the mechanism of viral spreading, we used the patterns of data at the early onset of COVID-19 from seven countries to estimate the time lag between peak days of cases and deaths. This study compared these data with those of Wuhan and estimated the natural history of disease across the infected population and the time lag. The findings suggest that comparative analyses of data from different regions and countries reveal the differences between peaks of cases and deaths caused by COVID-19 and the incomplete and underestimated cases in Wuhan. Different countries may show different patterns of cases peak days, deaths peak days, and peak periods. Error in the early COVID-19 statistics in Brazil was identified. This study provides sound evidence for policymakers to understand the local circumstances in diagnosing the health of a population and propose precise and timely public health interventions to control and prevent infectious diseases.