TIME SERIES ANALYSIS TO FORECAST COVID-19 CASES IN CENTRAL ASIA

Abstract

According to the study, the cases are expected to increase in
the upcoming days. An exponential rise in the number of cases is also noticeable
in a time series analysis. The current forecast models are expected to help the
government and medical professionals plan for future circumstances and
enhance healthcare system readiness. The proposed study employs a support
vector regression model for forecasting the overall number of deaths, recovered
cases, cumulative number of reported cases, and regular case count. The starting
information is retrieved from the 1st of March to the 30th of April, 2021 (61
Days). The model predicts deaths, recoveries, and the total number of confirmed
cases with an accuracy of over 97 percent, and regular new cases with an
accuracy of 87 percent. The findings point to a Gaussian reduction in the number
of cases, which may take another 3 to 4 months to reach the bare minimum of no
new cases registered.