COVID-19 Spread in India: Dynamics, Modeling, and Future Projections

COVID-19 is an extremely infectious disease with a relatively large virus incubation period in the affected people who may be asymptomatic. Therefore, to reduce the transmission of this pathogen, several countries have taken many intervention measures. In this paper, we show that the impact of these measures in India is different from several other countries. It is shown that an early lockdown in late March 2020 changed the initial exponential growth curve of COVID-19 to a linear one, but a surge in the number of cases from late April 2020 brought India back to a quadratic trajectory. A regional analysis shows the disparate impact of the intervention in different states. It is further shown that the number of reported infections correlates with the number of tests, and therefore regions with limited diagnostics resources may not have a realistic estimate of the virus spread. This insufficiency of diagnostic test data is also reflected in an increasing positivity rate for India nearly 2.5 months after the lockdown, inconsistent with the trends observed for other geographical regions. Nonetheless, future projections are made using different epidemiological models based on the available data, and a comparative study is presented. In the absence of a reliable estimate of the true number of infections, these projections will have a limited accuracy: with that limitation, the most optimistic prediction suggests a continuing virus transmission through September 2020.