Time-dependent dynamic transmission potential and instantaneous reproduction number of COVID-19 pandemic in India
Abstract
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 was obtained from <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://api.covid19india.org/">https://api.covid19india.org/</ext-link> and pre-processed. Bayesian approach was adopted to quantify transmissibility at a given location and time, as indicated by the instantaneous reproduction number (R eff ). 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.
Results
A total of 9,07,544 cumulative incident cases till July 13 th , 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 R eff reached at the national level during the study period was 2.57 (sliding week ending April 4 th , 2020). R eff on July 13 th , 2020 for India was 1.16 with a range from 0.59 to 2.98 across various states/UTs.
Conclusion
R eff 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.
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