Introduction: Dynamic 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.
Methods: Daily COVID-19 case incidence time series for India and its states were obtained from https://api.covid19india.org/ and pre-processed. The Bayesian approach was adopted to quantify transmissibility at a given location and time, as indicated by the instantaneous reproduction number (Reff). The 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 intervals as 5.1, 1.2, 3.9 and 7.5 days respectively; and mean, standard deviation, minimum, and maximum of standard deviations of the serial interval as 3.7, 0.9, 2.3, and 4.7 respectively with 100 simulations and moving average of seven days.
Results. A 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.
Conclusion. Reff 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