Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026

Zaw Lin Oo; Theint Win Laı

doi:10.34110/forecasting.1923517

Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026

Abstract

Dengue fever remains a significant public health challenge in Myanmar, with Yangon Region consistently reporting the highest number of cases. Mayangone Township, an urban area in Yangon, experiences distinct seasonal outbreaks, predominantly during the rainy season (June–August), driven by increased Aedes mosquito breeding following monsoon rainfall. Accurate forecasting is vital for early warning and effective vector control. This study conducted a comparative analysis of XGBoost (gradient boosting machine learning) and Prophet (additive time series model) for predicting monthly dengue cases in Mayangone Township. Yearly national and regional dengue statistics were used to derive monthly incidence estimates for the township from January 2022 to December 2025, integrated with meteorological variables including rainfall, temperature, and humidity. XGBoost utilized engineered features such as cyclical time encodings, lagged cases, and rainy season indices, while Prophet incorporated the same variables with multiplicative seasonality. Models were evaluated using time series cross-validation with R², MAE, RMSE, and MAPE metrics. Both models produced similar annual forecasts for 2026 (XGBoost: 254.62 cases; Prophet: 252.70 cases). Prophet demonstrated superior predictive performance (R² = 0.9869, MAE = 1.92, RMSE = 2.50, MAPE = 9.54%) compared to XGBoost. Rainfall was identified as the most influential predictor in both models. Prophet projected a higher concentration of cases (66.3%) during the rainy season. The findings suggest Prophet is more accurate for forecasting, while XGBoost offers better interpretability of climatic drivers. The 2026 projections indicate continued seasonal risk, emphasizing the need for proactive vector control measures in Mayangone Township.

Keywords

Supporting Institution

Not applicable.

Project Number

This research did not receive funding from any specific grant or project number.

Ethical Statement

The authors declare that this study was conducted in accordance with ethical standards. As this research utilized only publicly available, anonymized, and aggregated secondary data obtained from official government reports, social media channels of the Ministry of Health and Sports (Myanmar), Vector Borne Disease Control Programme, and national newspapers, no primary data involving human subjects were collected. Therefore, formal ethical approval was not required. All data sources have been appropriately cited. The authors confirm that there is no conflict of interest related to this study. Artificial intelligence tools were used only for grammar and spell checking, specifically Grammarly, and no AI was used for content generation, literature review, data analysis, or evaluation.

Thanks

The authors thank the Vector Borne Disease Control Programme, Ministry of Health and Sports, Myanmar, for making dengue surveillance data publicly available, and ECMWF for providing ERA5-Land climate data via Google Earth Engine. The authors also thank the Turkish Journal of Forecasting for considering this manuscript.

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Details

Primary Language

English

Subjects

Deep Learning, Machine Learning (Other), Modelling and Simulation

Journal Section

Research Article

Authors

Zaw Lin Oo ^*
0000-0001-8132-3263
Myanmar

Theint Win Laı
0000-0002-4148-5812
Myanmar

Publication Date

September 14, 2026

Submission Date

April 5, 2026

Acceptance Date

May 30, 2026

Published in Issue

Year 2026 Volume: 10 Number: 2

DOI

https://doi.org/10.34110/forecasting.1923517

IZ

https://izlik.org/JA52LJ39MB

Cite

RIS / Bibtex

APA

Oo, Z. L., & Laı, T. W. (2026). Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026. Turkish Journal of Forecasting, 10(2), 83-96. https://doi.org/10.34110/forecasting.1923517

AMA

1.Oo ZL, Laı TW. Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026. TJF. 2026;10(2):83-96. doi:10.34110/forecasting.1923517

Chicago

Oo, Zaw Lin, and Theint Win Laı. 2026. “Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026”. Turkish Journal of Forecasting 10 (2): 83-96. https://doi.org/10.34110/forecasting.1923517.

EndNote

Oo ZL, Laı TW (September 1, 2026) Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026. Turkish Journal of Forecasting 10 2 83–96.

IEEE

[1]Z. L. Oo and T. W. Laı, “Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026”, TJF, vol. 10, no. 2, pp. 83–96, Sept. 2026, doi: 10.34110/forecasting.1923517.

ISNAD

Oo, Zaw Lin - Laı, Theint Win. “Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026”. Turkish Journal of Forecasting 10/2 (September 1, 2026): 83-96. https://doi.org/10.34110/forecasting.1923517.

JAMA

1.Oo ZL, Laı TW. Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026. TJF. 2026;10:83–96.

MLA

Oo, Zaw Lin, and Theint Win Laı. “Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026”. Turkish Journal of Forecasting, vol. 10, no. 2, Sept. 2026, pp. 83-96, doi:10.34110/forecasting.1923517.

Vancouver

1.Zaw Lin Oo, Theint Win Laı. Comparative Analysis of XGBoost and Prophet Models for Monthly Dengue Cases Forecasting in Mayangone Township, Yangon, Myanmar: Projections for 2026. TJF. 2026 Sep. 1;10(2):83-96. doi:10.34110/forecasting.1923517