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Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt
Fonggi Yudi Aryatama1, Felix Indra Kurniadi2, Ngarap Im Manik1
1Mathematic Department, School of Computer Science, Bina Nusantara University, Jakarta, 11530, Indonesia.
Procedia Computer Science
|January 16, 2023
Summary
A new application predicts COVID-19 in Indonesia using public compliance data and the SPCIRD model. Despite poor R2 scores, users found the application usable and satisfactory for understanding pandemic patterns.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- The COVID-19 pandemic rapidly spread globally, necessitating effective surveillance and prediction tools.
- Indonesia required a dedicated application to monitor and forecast the COVID-19 situation.
Purpose of the Study:
- To propose and evaluate a COVID-19 prediction application for Indonesia.
- To assess the impact of public compliance with surveillance policies on pandemic prediction.
- To utilize the SPCIRD model with Levenberg-Marquardt optimization for forecasting.
Main Methods:
- Development of a prediction application incorporating public compliance data.
- Application of the SPCIRD (Susceptible-Public Compliance-Infectious-Recovered-Deceased) model.
- Utilizing the Levenberg-Marquardt algorithm for curve fitting and optimization.
- Validation through questionnaire and black box testing.
Main Results:
- The SPCIRD model with Levenberg-Marquardt optimization yielded R2 scores of -1.248 (active cases), -0.235 (recovered), and -3.982 (deaths).
- Despite suboptimal R2 values, 93.3% of users agreed/strongly agreed on the application's usability for understanding and predicting COVID-19 patterns.
- 83.3% of respondents expressed satisfaction with the prototype's usability.
Conclusions:
- The developed application demonstrates potential usability for COVID-19 surveillance in Indonesia.
- Further refinement of the SPCIRD model and optimization methods may be necessary to improve predictive accuracy.
- Public compliance remains a critical factor in managing and predicting infectious disease outbreaks.
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