ArticleInternational journal of public health2026
Comparative analysis of ARIMA and Holt-Winter's additive models for describing human respiratory syncytial virus activity in Yaoundé, Cameroon.
Article in International journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: Human respiratory syncytial virus (HRSV) is a major cause of respiratory infections in children and older adults. This study compared the Autoregressive Integrative Moving Average (ARIMA) and Holt-Winter's Additive models to describe HRSV activity in Yaoundé, Cameroon. Methods: In a three-year retrospective study (July 2020-December 2022), analyzed 1,774 nasopharyngeal samples from patients with severe acute respiratory infections (SARI) and influenza-like illness (ILI) were analysed across five sentinel sites in Yaoundé. The ARIMA model assessed the relationship between HRSV activity and meteorological factors (temperature, humidity, rainfall, solar radiation), while Holt-Winter's Additive model described HRSV activity without climate variables. Model performance was evaluated using stationary R Results: HRSV was detected in 8.5% (151/1774) samples. Holt-Winter's model outperformed ARIMA, achieving a stationary R Conclusion: Holt-Winter's model is more effective for predicting HRSV activity. These findings can guide public health interventions to reduce HRSV's impact in Cameroon.
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