Estimating dengue force of infection from age-stratified surveillance data in Java, Indonesia
Authors:
- Bimandra DjaafaraBDBimandra Djaafara
- Iqbal R. F. ElyazarIEIqbal R. F. Elyazar
- Asik SuryaASAsik Surya
- Fadjar S. M. SilalahiFSFadjar S. M. Silalahi
- Agus HanditoAHAgus Handito
- Desfalina AryaniDADesfalina Aryani
- Mushtofa KamalMKMushtofa Kamal
- Dyana GunawanDGDyana Gunawan
- Hipokrates HipokratesHHHipokrates Hipokrates
- Anzala Khoirun NisaANAnzala Khoirun Nisa
- Edi PriantoEPEdi Prianto
- Iriani SamadISIriani Samad
Open Access
- 26 November 2025
- journal article
- Published by The Royal Society in Journal of The Royal Society Interface
- Vol. 22 (232) , 20250445
Abstract
Targeted dengue interventions require reliable estimates of transmission intensity and population immunity at the local level. The force of infection (FOI) provides an objective measure of transmission intensity, but its estimation traditionally relies on resource-intensive seroprevalence surveys. We developed a hierarchical extension of existing catalytic models to estimate FOI using routine age-stratified surveillance data, allowing partial pooling of information across districts within provinces. We applied this approach to dengue surveillance data from Jakarta and West Java provinces, Indonesia, and compared it with non-hierarchical implementations. Both hierarchical and non-hierarchical approaches produced FOI estimates consistent with 2014 seroprevalence data. The hierarchical framework provided more robust estimates through partial pooling under varied data availability scenarios but showed sensitivity to age-stratification choices and could miss district-specific patterns when local epidemiology differed from regional trends. Model comparison using expected log pointwise predictive density showed that accounting for overdispersion through negative binomial likelihood improved model performance regardless of hierarchical structure. Our analysis showed distinct patterns in reporting parameters between provinces, with Jakarta showing higher reporting rates despite lower FOI estimates than West Java. Implementation of the hierarchical framework requires understanding of local dengue epidemiology, as clustering districts with different epidemiological profiles could produce inaccurate estimates.Keywords
Funding Information
- NUS start up grant
- Strategic Partnership for Prevention, Surveillance and Response to Infectious Diseases across the Indo-Pacific Region
- the National Research Foundation, Singapore
- Program for Research in Epidemic Preparedness and Response (PREPARE), Ministry of Health, Singapore
- Wellcome Africa Asia Program Vietnam
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