An approximation-based approach for periodic estimation of effective reproduction number: a tool for decision-making in the context of coronavirus disease 2019 (COVID-19) outbreak

Abstract

ObjectivesThe effective reproduction number (R) is a more practical epidemiological parameter than basic reproduction number (R0) for characterization of infectious disease epidemics as it takes into account presence of immune individuals in the population which R0 does not. Periodic assessment of R can inform public health strategies during long-standing epidemics such as the current coronavirus disease 2019 (COVID-19) situation. This is especially relevant for large and resource-poor countries such as India, which may require differential intervention strategies in different regions. However, the complexity of the calculation involved often proves to be a barrier for calculation of R. This communication proposes a simpler data collection and analytical method – involving a combination approach instead of full-fledged primary data collection – to estimate R for public health decision-making. Study designLiterature review. MethodsData from available sources (time series data of new cases at population level) can be combined with some primary data (time interval between infection of index and secondary cases in family clusters) that can be collected with little resources. These data can then be fed into an approximation-based method (Wallinga and Lipsitch) for R calculation at the state/regional levels. The calculations can be repeated every fortnight using newly available data. ResultsThe value of R, estimated using the proposed method, from subsequent periods can be used for assessing the status of the epidemic and values from subsequent periods can be compared for decision-making regarding implementation/modification of control measures. ConclusionsThe approximate R may be a little inaccurate but can still prove useful for rough estimation of epidemic evolution and for comparison between different periods, as the extent of error in R values across different periods is likely to be similar. Thus, the approximate R may not only be used to estimate the epidemic change in smaller geographies such as states/regions but also used for making appropriate changes to public health measures for managing a pandemic such as COVID-19.