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Estimation of Effective Reproduction Numbers for COVID-19 using Real-Time Bayesian Method for India and its States

Rishabh Tyagi, Max Planck Institute for Demographic Research (MPIDR)
Laxmi Kant Dwivedi, International Institute for Population Sciences (IIPS)
Ashutosh Sanzgiri, Xandr

WHO declared the outbreak of the novel Coronavirus, COVID-19, as a pandemic on 11th March. Effective Reproduction Number (Rt) helps understand how effective preventive measures have been in controlling an outbreak. This study assesses the impact of nation-wide lockdown in slowing down the spread of the COVID-19 at the national and state level. An attempt has also been made to examine the important state-level factors responsible for the uneven distribution of Rt of COVID-19 across India's different states. The authors used a crowd-sourced database which is available in the public domain. After preparing the data for analysis, the Bayesian approach based on the probabilistic formulation of standard SIR disease transmission models has been employed, assuming a serial interval of 4 days and basic reproduction number (R0) of three. India’s Rt has declined from 1.81 (90% HDI: 1.64, 2.00) on 1st April 2020 to Rt =1.04 (90% HDI: 0.96, 1.13) on 9th May 2020. Testing Rate is the most significant factor at the state level, as testing and isolating patients sooner significantly reduces the disease spread. Future curtailment and mitigation strategies thus may take into account these findings while formulating further course of action.

Keywords: Bayesian methods / estimation, COVID-19, Spatial analysis/regression, Health and morbidity

See paper.

  Presented in Session 149. Estimating COVID-19 Risks and Self-Perceptions