Time-dependent dynamic transmission potential and instantaneous reproduction number of COVID-19 pandemic in India.

IntroductionDynamic tools and methods to assess the ongoing transmission potential of COVID-19 in India are required. We aim to estimate time-dependent transmissibility of COVID-19 for India using a reproducible framework. MethodsDaily COVID-19 case incidence time series for India and its states was obtained from https://api.covid19india.org/ and pre-processed. Bayesian approach was adopted to quantify transmissibility at a given location and time, as indicated by the instantaneous reproduction number (Reff). Analysis was carried out in R version 4.0.2 using "EpiEstim_2.2-3" package. Serial interval distribution was estimated using "uncertain_si" algorithm with inputs of mean, standard deviation, minimum and maximum of mean serial interval as 5.1, 1.2, 3.9 and 7.5 days respectively; and mean, standard deviation, minimum, and maximum of standard deviations of serial interval as 3.7, 0.9, 2.3, and 4.7 respectively with 100 simulations and moving average of seven days. ResultsA total of 9,07,544 cumulative incident cases till July 13th, 2020 were analysed. Daily COVID-19 incidence in the country was seen on the rise; however, transmissibility showed a decline from the initial phases of COVID-19 pandemic in India. The maximum Reff reached at the national level during the study period was 2.57 (sliding week ending April 4th, 2020). Reff on July 13th, 2020 for India was 1.16 with a range from 0.59 to 2.98 across various states/UTs. ConclusionReff provides critical feedback for assessment of transmissibility of COVID-19 and thus is a potential dynamic decision support tool for on-ground public health decision making.