Epidemic Landscape and Forecasting of SARS-CoV-2 in India

Aravind Lathika Rajendrakumar; Anand Thakarakkattil Narayanan Nair; Charvi Nangia; Prabal Kumar Chourasia; Mehul Kumar Chourasia; Mohammad Ghouse Syed; Anu Sasidharan Nair; Arun B Nair; Muhammed Shaffi Fazaludeen Koya

Control measures of SARS-CoV-2 are less effective in populations with high density. 20 India has a huge population and potential of SARS-CoV-2 for sustained transmission is well established. 21, 25 We relied solely on estimates from compartmental model which generates estimates from the infection parameters than depending on forecasts based on trend. Our findings are based on simulations and further measures at policy level can alter the trajectory of the disease. Lipsitch et al recommends a strategy combining epidemiological studies, testing and lab studies as more effective strategy in generating evidence for suppressing the epidemic. 26 Our analysis has certain limitations. Firstly, there may be underreporting of cases and lack of validated data for research purposes available to the public.However, we compared the incidence from our dataset to the aggregated numbers elsewhere like European Disease Prevention and Control 23 and Worldometer 5 and the figures were similar. Another issue in estimating the parameters is the presence of super spreaders and asymptomatic cases. The estimated proportion of asymptomatic cases can be as high as 10% in the population. 27 The virus can be spread around during asymptomatic stage and delays from onset to reporting or treatment can be as high as 11 days. 28 Nonetheless, pooling estimates across several studies will aid in computing values that are closer to the true estimates.