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Forecasting the Monkeypox Outbreak Using Limited Data: A Case Study of Thailand.

Sherif Eneye Shuaib1, Jirapond Muangprathub2, Arthit Intarasit1

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Forecasting mpox (monkeypox) cases in Thailand using advanced models indicates low case counts for late 2024. Continued vigilance is advised due to potential uncertainties in mpox transmission.

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Area of Science:

  • Epidemiology
  • Public Health
  • Mathematical Modeling

Background:

  • The World Health Organization declared mpox (monkeypox) a Public Health Emergency of International Concern on August 14, 2024.
  • Thailand reported its first Clade Ib mpox case shortly after the PHEIC declaration.
  • Accurate short-term mpox case forecasting is crucial for Thailand due to its high international travel volume.

Purpose of the Study:

  • To forecast monthly mpox cases in Thailand.
  • To evaluate the performance of various statistical and machine learning models for mpox forecasting.
  • To provide decision-support for public health planning.

Main Methods:

  • Utilized Department of Disease Control (DDC) mpox data from July 2022 to September 2024.
  • Compared Poisson and negative binomial generalized linear models (GLMs), Holt-Winters exponential smoothing, NeuralProphet, and a stacked ensemble.
  • Employed rolling-origin cross-validation to assess accuracy (MAE, RMSE, MAPE) and interval coverage (80%, 95%).

Main Results:

  • Holt-Winters exponential smoothing demonstrated the highest accuracy based on Root Mean Squared Error (RMSE).
  • A stacked ensemble model provided the most reliable uncertainty calibration.
  • Forecasts for October-December 2024 predict low mpox case numbers but highlight non-negligible uncertainty.

Conclusions:

  • The study offers exploratory insights for adaptive public health planning in Thailand.
  • Findings complement existing surveillance efforts and can inform responses to both low and high mpox incidence scenarios.
  • Continued monitoring and preparedness are essential despite projected low case counts.