Short-Term Predictions of the Trajectory of Mpox in East Asian Countries, 2022–2023: A Comparative Study of Forecasting Approaches

The 2022–2023 mpox outbreak exhibited an uneven global distribution. While countries such as the UK, Brazil, and the USA were most heavily affected in 2022, many Asian countries, specifically China, Japan, South Korea, and Thailand, experienced the outbreak later, in 2023, with significantly fewer reported cases relative to their populations. This variation in timing and scale distinguishes the outbreaks in these Asian countries from those in the first wave. This study evaluates the predictability of mpox outbreaks with smaller case counts in Asian countries using popular epidemic forecasting methods, including the ARIMA, Prophet, GLM, GAM, n-Sub-epidemic, and Sub-epidemic Wave frameworks. Despite the fact that the ARIMA and GAM models performed well for certain countries and prediction windows, their results were generally inconsistent and highly dependent on the country, i.e., the dataset, as well as the prediction interval length. In contrast, n-Sub-epidemic Ensembles demonstrated more reliable and robust performance across different datasets and predictions, indicating the effectiveness of this model on small datasets and its utility in the early stages of future pandemics.

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Publication Details

Journal
Mathematics
Published
2024-11-23
DOI
https://doi.org/10.3390/math12233669
Citations
4
Primary Topic
Poxvirus research and outbreaks
Type
article
Field-Weighted Citation Impact
1.17
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article

Short-Term Predictions of the Trajectory of Mpox in East Asian Countries, 2022–2023: A Comparative Study of Forecasting Approaches

Ruiyan Luo, Pavel Skums, Alexander Kirpich, Gerardo Chowell et al.
4 citations
Mathematics
Poxvirus research and outbreaks
1.17
article

Short-Term Predictions of the Trajectory of Mpox in East Asian Countries, 2022–2023: A Comparative Study of Forecasting Approaches

Ruiyan Luo, Pavel Skums, Alexander Kirpich, Gerardo Chowell, Amanda Bleichrodt, Aleksandr Shishkin
article en
4 citations

Abstract

The 2022–2023 mpox outbreak exhibited an uneven global distribution. While countries such as the UK, Brazil, and the USA were most heavily affected in 2022, many Asian countries, specifically China, Japan, South Korea, and Thailand, experienced the outbreak later, in 2023, with significantly fewer reported cases relative to their populations. This variation in timing and scale distinguishes the outbreaks in these Asian countries from those in the first wave. This study evaluates the predictability of mpox outbreaks with smaller case counts in Asian countries using popular epidemic forecasting methods, including the ARIMA, Prophet, GLM, GAM, n-Sub-epidemic, and Sub-epidemic Wave frameworks. Despite the fact that the ARIMA and GAM models performed well for certain countries and prediction windows, their results were generally inconsistent and highly dependent on the country, i.e., the dataset, as well as the prediction interval length. In contrast, n-Sub-epidemic Ensembles demonstrated more reliable and robust performance across different datasets and predictions, indicating the effectiveness of this model on small datasets and its utility in the early stages of future pandemics.

MathematicsVol. 12(23)
University of Connecticut (US), Georgia State University (US)
Openalex Percentile: Top 21%
Poxvirus research and outbreaks
1.17
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Short-Term Predictions of the Trajectory of Mpox in East Asian Countries, 2022–2023: A Comparative Study of Forecasting Approaches — Ruiyan Luo, Pavel Skums, et al. · Mathematics (2024) | TGRS Research Map | TGRS