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Factors affecting COVID-19 cases before epidemic peaks
Andika1, P Wulandari1, Halmar Halide2
1Earth Sciences Department, FITB, Institut Teknologi Bandung, Bandung, Indonesia.
Gaceta Sanitaria
|December 21, 2021
Summary
COVID-19 case prediction in India and Indonesia revealed differing factors. While increased testing capacity drives cases in Indonesia, policy stringency is more critical in India.
Area of Science:
- Epidemiology
- Public Health Policy
- Mathematical Modeling
Background:
- The COVID-19 pandemic necessitated stringent public health measures, including lockdowns and increased testing, to curb viral spread.
- Understanding the drivers of COVID-19 transmission is crucial for effective pandemic management.
Purpose of the Study:
- To predict daily COVID-19 cases in India and Indonesia using stringency index and daily testing data.
- To identify the key factors influencing COVID-19 case numbers in these two Asian countries.
Main Methods:
- Utilized Stepwise Multiple Regression (SWMR) to model daily COVID-19 cases.
- Incorporated daily testing data (including 14-day lags) and stringency index as predictor variables.
- Selected significant factors at a 0.01 level before the epidemic peak.
Main Results:
- Achieved high model predictability: 94% for Indonesia and 99% for India.
- In Indonesia, increased daily COVID-19 cases correlated with higher testing capacity.
- In India, stringency indices were the primary determinant of daily COVID-19 cases.
Conclusions:
- Testing capacity and policy stringency have differential impacts on COVID-19 case numbers in India and Indonesia.
- Further research is needed to elucidate the reasons behind these distinct relationships in the two countries.
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