An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India

Abstract

After originating from Wuhan, China, in late 2019, with a gradual spread in the last few months, COVID-19 has become a pandemic crossing 9 million confirmed positive cases and 450 thousand deaths. India is not only an overpopulated country but has a high population density as well, and at present, a high-risk nation where COVID-19 infection can go out of control. In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. We analyze the impact of lockdown and the number of tests conducted per day on the prediction and bring out the scenarios in which the infection can be controlled faster. Our findings indicate that increasing the tests per day at a rapid pace (10k per day increase), stringent measures on social-distancing for the coming months and strict lockdown in the month of July all have a significant impact on the disease spread.

Mass Screening Vs Lockdown Vs Combination of Both to Control Covid-19: A Systematic Review

“…The extent of lockdown and capacity of mass testing also influenced the effectiveness of these interventions on flattening the incidence and mortality curve, as illustrated by Mahajan et al . 30 This study showed that with the same number of tests per day, the stricter the lockdown is, the greater the reduction of confirmed, active, and total death cases. This study also illustrated that with the same level of lockdown, the higher the daily number of tests done per day (8,000 vs 4,000 increase of tests per day, saturated at 300,000 and 200,000 tests/ day respectively) would result in lower number of confirmed, active, and total death cases.…”

The effect of occupant distribution on energy consumption and COVID-19 infection in buildings: A case study of university building

“…Since no validations have been performed in this context before, there is no pre-specified acceptable range of accuracy for this validation. However, accuracy of the model in most of the cases is within the accepted accuracy range of some other related research models [ 77 , 78 ]. Therefore, the results successfully confirm the mathematical model.…”

Real-time measurement of the uncertain epidemiological appearances of COVID-19 infections

“…Other different methods can be found in literature with similar objectives, some above mentioned. For example, a mathematical model named SIPHERD has also been used to predict the total number of confirmed, active and death cases in India [44] . Also focusing on the country level, other authors propose the ARIMA prediction model to forecast the expected daily number of COVID-19 cases in Saudi Arabia for the next four weeks, from the collected data of almost two months in the country [45] .…”