COVID-19 in India: State-wise Analysis and Prediction.

BACKGROUND: COVID-19, a highly infectious disease, was first detected in Wuhan, China, in December 2019, and subsequently spread to 212 countries and territories around the world infecting millions of people. In India, a huge country of about 1.3 billion people, the disease was first detected on 30 January 2020 in a student returning from Wuhan. The total number of confirmed infections in India as of 3 May 2020 is more than 37000, and is currently growing very fast. OBJECTIVE: Most of the prior research and media coverage focused on the number of infections in the entire country. However, given the size and diversity of India, it is important to look at the spread of the disease in each state separately, wherein the situations are quite different. In this article, we aim to analyze data on the number of infected people in each Indian state (restricting to only those states with enough data for prediction) and predict the number of infections for that state in the next 30 days. We hope that such state-wise predictions would help the state governments better channelize their limited healthcare resources. METHODS: Since predictions from any one model can potentially be misleading, we consider three growth models, namely, the logistic, the exponential, and the susceptible-infectious-susceptible (SIS) models, and finally develop a data-driven ensemble of predictions from the logistic and the exponential models using functions of the model-free maximum daily infection-rate (DIR) over the last two weeks (a measure of recent trend) as weights. The DIR is used to measure the success of the nationwide lockdown. We jointly interpret the results from all models along with the recent DIR values for each state, and categorize the states as severe, moderate or controlled. RESULTS: We find that seven states, namely, Maharashtra, Delhi, Gujarat, Madhya Pradesh, Andhra Pradesh, Uttar Pradesh, and West Bengal fall in the severe category. Among the remaining states, Tamil Nadu, Rajasthan, Punjab, and Bihar are in the moderate category, whereas Kerala, Haryana, Jammu and Kashmir, Karnataka, and Telangana are in the controlled category. We also tabulate actual predicted numbers from various models for each state. All the R2 values corresponding to the logistic and the exponential models are above 0.90, indicating a reasonable goodness of fit. We also provide a web-app (https://palash.shinyapps.io/IITG_COVID-19-India/) to see the forecast based on recent data that is updated regularly. CONCLUSIONS: States with non-decreasing DIR values need to immediately ramp up the preventive measures in order to combat the COVID-19 pandemic. On the other hand, the states with decreasing DIR can maintain the same status to see the DIR slowly become zero or negative for consecutive 14 days to be able to declare the end of the pandemic. CLINICALTRIAL: Not Applicable.