Sero-catalytic and spatial modeling of dengue virus force of infection in Timor-Leste.
16 affiliations
- 1Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Dili, Timor-Leste. [email protected].
- 2Department of Infectious Diseases, Faculty of Medicine, Imperial College, London, UK. [email protected].
- 3Instituto Nacional de Saude Publica de Timor-Leste, Timor-Leste Ministry of Health, Dili, Timor-Leste.
- 4Departmanto Vigilancia no Epidemiojia, Timor-Leste Ministry of Health, Dili, Timor-Leste.
- 5MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College, London, UK.
- 6Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Dili, Timor-Leste.
- 7Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, Australia.
- 8National Centre for Immunisation Research and Surveillance (NCIRS), Sydney, NSW, Australia.
- 9Daffodil Centre, The University of Sydney, a joint venture with Cancer Council New South Wales, Sydney, NSW, Australia.
- 10School of Medicine & Dentistry, Griffith University, Gold Coast, QLD, Australia.
- 11Infectious Diseases Data Observatory, Oxford University, Oxford, UK.
- 12Northern Territory Centre for Disease Control, Public Health Division, NT Health, Darwin, NT, Australia.
- 13National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT, Australia.
- 14Laboratório Nacional da Saúde, Dili, Timor-Leste.
- 15Department of Statistics, University of Oxford, Oxford, UK.
- 16Pandemic Sciences Institute, University of Oxford, Oxford, UK.
Abstract
Dengue virus (DENV) infection causes significant morbidity and mortality across tropical and sub-tropical regions, including in Timor-Leste. In this study we present the results of a national, population-representative serological survey, used to determine the drivers of observed variations in DENV force-of-infection (FOI, i.e. the average annual per-capita risk of infection for a susceptible person) at high spatial resolution. Households were randomly selected from census data and occupants aged above one year were tested using the Panbio Indirect dengue IgG enzyme-linked immunosorbent assay between October 2021 and February 2023. Sero-catalytic models accounting for household effect were applied to estimate the DENV FOI in enumeration areas (EAs, roughly equivalent to neighbourhoods/villages). Spatial models were applied to the local FOI estimates to assess their associations with climate and environmental factors, and to predict the FOI across the rest of Timor-Leste. A total of 4780 individuals from 1755 households across 102 EAs participated. DENV seroprevalence and FOI estimates were highly spatially heterogeneous across Timor-Leste, ranging from 0.010 (95% Credible Interval (CrI): 0.005, 0.018) in EA 10104032 in Fatubossa, municipality Aileu, to 0.519 (0.295, 0.816) in EA 40403012 in Goulolo, municipality Bobonaro. Relative humidity was negatively associated with DENV FOI. The spatial models predicted highest DENV FOI along the Northern and Eastern coasts, with hotspots of transmission in Dili and Baucau cities. Findings will strengthen surveillance and guide the implementation of additional DENV control strategies such as Wolbachia-carrying mosquitoes (currently being deployed in some parts of Timor-Leste), or vaccination.
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BibTeX
@article{arkell2026serocatalytic,
title = {{Sero-catalytic and spatial modeling of dengue virus force of infection in Timor-Leste.}},
author = {Paul Arkell and Filipe de Neri Machado and Anna Vicco and Victoria M Cox and Maria Y Tanesi and Deolindo Ximenes and Wes Hinsley and Frederico Bosco and Nelia Gomes and Tessa Oakley and Vanessa Solano and Sarah L Sheridan and Michael David and Salvador Amaral and Luzia Freitas and Anthony Dk Draper and Nevio Sarmento and Endang Soares da Silva and Lucsendar Alves and Neil Ferguson and Christl A Donnelly and Jennifer Yan and Joshua R Francis and Ilaria Dorigatti and Nelson Martins},
journal = {Nature communications},
year = {2026},
month = sep,
doi = {10.1038/s41467-026-76716-9},
url = {https://europepmc.org/article/MED/42875433},
note = {CC BY},
}
RIS
TY - JOUR
TI - Sero-catalytic and spatial modeling of dengue virus force of infection in Timor-Leste.
AU - Paul Arkell
AU - Filipe de Neri Machado
AU - Anna Vicco
AU - Victoria M Cox
AU - Maria Y Tanesi
AU - Deolindo Ximenes
AU - Wes Hinsley
AU - Frederico Bosco
AU - Nelia Gomes
AU - Tessa Oakley
AU - Vanessa Solano
AU - Sarah L Sheridan
AU - Michael David
AU - Salvador Amaral
AU - Luzia Freitas
AU - Anthony Dk Draper
AU - Nevio Sarmento
AU - Endang Soares da Silva
AU - Lucsendar Alves
AU - Neil Ferguson
AU - Christl A Donnelly
AU - Jennifer Yan
AU - Joshua R Francis
AU - Ilaria Dorigatti
AU - Nelson Martins
PY - 2026
DA - 2026/09/15
JO - Nature communications
DO - 10.1038/s41467-026-76716-9
UR - https://europepmc.org/article/MED/42875433
AB - Dengue virus (DENV) infection causes significant morbidity and mortality across tropical and sub-tropical regions, including in Timor-Leste. In this study we present the results of a national, population-representative serological survey, used to determine the drivers of observed variations in DENV force-of-infection (FOI, i.e. the average annual per-capita risk of infection for a susceptible person) at high spatial resolution. Households were randomly selected from census data and occupants aged above one year were tested using the Panbio Indirect dengue IgG enzyme-linked immunosorbent assay between October 2021 and February 2023. Sero-catalytic models accounting for household effect were applied to estimate the DENV FOI in enumeration areas (EAs, roughly equivalent to neighbourhoods/villages). Spatial models were applied to the local FOI estimates to assess their associations with climate and environmental factors, and to predict the FOI across the rest of Timor-Leste. A total of 4780 individuals from 1755 households across 102 EAs participated. DENV seroprevalence and FOI estimates were highly spatially heterogeneous across Timor-Leste, ranging from 0.010 (95% Credible Interval (CrI): 0.005, 0.018) in EA 10104032 in Fatubossa, municipality Aileu, to 0.519 (0.295, 0.816) in EA 40403012 in Goulolo, municipality Bobonaro. Relative humidity was negatively associated with DENV FOI. The spatial models predicted highest DENV FOI along the Northern and Eastern coasts, with hotspots of transmission in Dili and Baucau cities. Findings will strengthen surveillance and guide the implementation of additional DENV control strategies such as Wolbachia-carrying mosquitoes (currently being deployed in some parts of Timor-Leste), or vaccination.
SN - 2041-1723
ER -