Forecasting Public Health Risks in Malaysia: Insights from SEIR Modelling of Infectious Diseases

  • Nuha Rahim
  • , Sakinah Ali Pitchay*
  • , Murtadha Arif Sahbudin
  • , A H Azni
  • , Ilfita Sahbudin
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

During the global pandemic of 2020, the Malaysian government implemented a Movement Control Order (MCO) as a mitigation plan to control the spreading of COVID-19. This effort demonstrates a significant decrease in active cases. However, it is disturbing the nation economically. The lack of a visualization hub to predict the spread of infectious diseases in Malaysia disrupts decision-makers’ efficiency in optimizing health sectors. Therefore, this paper aims to forecast infectious diseases in Malaysia using the Susceptible, Exposed, Infectious, Removed (SEIR) model. The SEIR Model predicts the projection of disease-spread cases based on the sample of previous cases. The samples used public health data from the COVID-19 Open Data Repository, which covers 12 states in Malaysia. The finding revealed that the SEIR model demonstrates a sharp decline in susceptible individuals after three months into 2022, a peak in exposed and infectious individuals around the same time, and a steady rise in recovered individuals as most of the population becomes immune. This forecast data can provide earlier insights on the infection trend, allowing actionable recommendations for policymakers and healthcare.
Original languageEnglish
Pages (from-to)34-42
Number of pages9
JournalMalaysian Journal of Science, Health & Technology
Volume11
Issue number1
Early online date18 Feb 2025
DOIs
Publication statusPublished - 24 Feb 2025

Keywords

  • Public Health
  • Infectious Disease
  • Disease Forecasting
  • COVID-19
  • Healthcare

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