Background : After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the virus in the country. This included restricted testing, isolation, contact tracing and quarantine, and enforcement of a nation-wide lockdown starting 25 March 2020. The objectives of this study were to i) describe the age, gender distribution, and mortality among COVID-19 patients identified till 14 April 2020 and predict the range of contact rate; and ii) predict the number of COVID-19 infections after 40 days of lockdown. Methods : We used a cross-sectional descriptive design for the first objective and a susceptible-infected-removed model for in silico predictions. We collected data from government-controlled and crowdsourced websites. Results : Studying age and gender parameters of 1161 Indian COVID-19 patients, the median age was 38 years (IQR, 27-52) with 20-39 year-old males being the most affected group. The number of affected patients were 854 (73.6%) men and 307 (26.4%) women. If the current contact rate continues (0.25-27), India may have 110460 to 220575 infected persons at the end of 40 days lockdown. Conclusion : The disease is majorly affecting a younger age group in India. Interventions have been helpful in preventing the worst-case scenario in India but will be unable to prevent the spike in the number of cases.
【저자키워드】 COVID-19, coronavirus, India, SIR model, 【초록키워드】 SARS-CoV-2, Mortality, lockdown, quarantine, cross-sectional, Gender, Contact tracing, in silico, virus, Spread, COVID-19 infection, male, Patient, Isolation, age, women, distribution, disease, predict, COVID-19 patients, Contact, COVID-19 patient, collected data, parameter, men, country, Prevent, limit, Result, affected, affecting, age and gender, IQR, the median, 【제목키워드】 Intervention, in silico, epidemiological, Analysis, SARS-CoV-2 epidemic, feature,