Reconciling heterogeneous dengue virus infection risk estimates from different study designs

• 成果类型: Article
• 署名作者: Huang, Angkana T.; Buddhari, Darunee; Kaewhiran, Surachai; Iamsirithaworn, Sopon; Khampaen, Direk; Farmer, Aaron; Fernandez, Stefan; Thomas, Stephen J.; Rodriguez-Barraquer, Isabel; Hunsawong, Taweewun; Srikiatkhachorn, Anon; dos Santos, Gabriel Ribeiro; O'Driscoll, Megan; Hamins-Puertolas, Marco; Endy, Timothy; Rothman, Alan L.; Cummings, Derek A. T.; Anderson, Kathryn; Salje, Henrik
• 署名单位: University of Cambridge; United States Department of Defense; United States Army; Walter Reed Army Institute of Research (WRAIR); Armed Forces Research Institute of Medical Science (AFRIMS); State University System of Florida; University of Florida; Ministry of Public Health - Thailand; State University of New York (SUNY) System; SUNY Upstate Medical University; University of California System; University of California San Francisco; University of Rhode Island
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-13622
• DOI: 10.1073/pnas.2411768121
• 发表日期: 2025-01-07
• 关键词: hemagglutination inhibition; kamphaeng phet; transmission; epidemiology; seroprevalence; thailand; FORCE

摘要

Uncovering rates at which susceptible individuals become infected with a pathogen, i.e., the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population. For dengue, reconstructing exposure and susceptibility statuses from the measured FOI is of particular significance as prior exposure is a strong risk factor for severe disease. FOI can be measured via many study designs. Longitudinal serology is considered gold standard measurements, as they directly track the transition of seronegative individuals to seropositive due to incident infections (seroincidence). Cross-sectional serology can provide estimates of FOI by contrasting seroprevalence across ages. Age of reported cases can also used to infer FOI. Agreement of these measurements, however, has not been assessed. Using 26 y of data from cohort studies and hospital-attended cases from Kamphaeng Phet province, Thailand, we found FOI estimates from the three sources to be highly inconsistent. Annual FOI estimates from seroincidence were 1.75 to 4.05 times higher than case-derived FOI. Seroprevalence-derived was moderately correlated with case derived FOI (correlation coefficient = 0.47) with slightly lower estimates. Through extensive simulations and theoretical analysis, we show that incongruences between methods can result from failing to account for dengue antibody kinetics, assay noise, and heterogeneity in FOI across ages. Extending standard inference models to include these processes reconciled the FOI and susceptibility estimates. Our results highlight the importance of comparing inferences across multiple data types to uncover additional insights not attainable through a single data type/analysis.