Estimating dengue force of infection from age-stratified surveillance data in Java, Indonesia

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. Competing Interest Statement The authors have declared no competing interest. Funding Statement BAD is supported by funding from the Program for Research in Epidemic Preparedness and Response (PREPARE) from the Ministry of Health, Singapore (A-8000642-01-00 PREPARE S2-2024-002). IRFE is supported by the Wellcome Africa Asia Program Vietnam (106680/Z/I4/Z) and the Strategic Partnership for Prevention, Surveillance and Response to Infectious Diseases across the Indo-Pacific Region (SPARKLE). HEC is supported by NUS Start up Grant awarded to her. SM acknowledges support from the National Research Foundation, Singapore, under its NRF FELLOWSHIP (NRF-NRFF15 - 2023 - 0010) awarded to him. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Moved seroprevalence estimates to main texts Data accessibility The codes to perform analyses in this article and data for Jakarta province are available at: Zenodo https://doi.org/10.5281/zenodo.17239255 and GitHub https://github.com/mlgh-sg/catalytic_dengue_java. The routine surveillance data for Jakarta are also freely accessible from: https://surveilans-dinkes.jakarta.go.id/