Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms

Debashree Ray; Maxwell Salvatore; Rupam Bhattacharyya; Lili Wang; Shariq Mohammed; Soumik Purkayastha; Aritra Halder; Alexander Rix; Daniel Barker; Michael Kleinsasser; Yiwang Zhou; Peter Song; Debraj Bose; Mousumi Banerjee; Veerabhadran Baladandayuthapani; Parikshit Ghosh; Bhramar Mukherjee

demographics, the number of COVID-19 diagnostic tests administered per day, testing criteria, accuracy of the test results, and heterogeneity in implementation of different government-initiated interventions and community-level protective measures across the country. We have neither accounted for age-structure, contact patterns or spatial information to finesse our predictions [37] [38] [39] nor considered the possibility of a latent number of true cases, only a fraction of which are ascertained and observed. 16 Increase in frequency and scale of testing, and community transmission of the SARS-CoV-2 virus may lead to a spike in a single day and that can shift the projection curve significantly upwards. COVID-19 hotspots in India are not uniformly spread across the country, and state-level forecasts 43 may be more meaningful for state-level policymaking. We are assuming that the implementation and effects of public health interventions and policies are the same everywhere in India by treating India as a homogeneous unit. Future opportunities for improving our model include incorporating contagion network, age-structure, estimating SEIR model, incorporating test imperfection, and estimating true fatality/death rates. Regardless of the caveats in our study, our analyses show the impact and necessity of lockdown and of suppressed activity post-lockdown in India. Rather than over-interpreting exact numerical projections, we recommend focusing more on the qualitative takeaway messages.