Linking multiple serological assays to infer dengue virus infections from paired samples using mixture models.

Dengue virus (DENV) is an increasingly important human pathogen, with already half of the globe's population living in environments with transmission potential. Since only a minority of cases are captured by direct detection methods (RT-PCR or antigen tests), serological assays play an important role in the diagnostic process. However, individual assays can suffer from low sensitivity and specificity and interpreting results from multiple assays remains challenging, particularly because interpretations from multiple assays may differ, creating uncertainty over how to generate finalized interpretations.

Reconciling heterogeneous dengue virus infection risk estimates from different study designs.

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.

Protective Role of NS1-Specific Antibodies in the Immune Response to Dengue Virus Through Antibody-Dependent Cellular Cytotoxicity.

Background: Dengue virus (DENV) nonstructural protein 1 (NS1) has multiple functions within infected cells, on the cell surface, and in secreted form, and is highly immunogenic. Immunity from previous DENV infections is known to exert both positive and negative effects on subsequent DENV infections, but the contribution of NS1-specific antibodies to these effects is incompletely understood.

Methods: We investigated the functions of NS1-specific antibodies and their significance in DENV infection.

Household immunity and individual risk of infection with dengue virus in a prospective, longitudinal cohort study.

Although it is known that household infections drive the transmission of dengue virus (DENV), it is unclear how household composition and the immune status of inhabitants affect the individual risk of infection. Most population-based studies to date have focused on paediatric cohorts because more severe forms of dengue mainly occur in children, and the role of adults in dengue transmission is understudied. Here we analysed data from a multigenerational cohort study of 470 households, comprising 2,860 individuals, in Kamphaeng Phet, Thailand, to evaluate risk factors for DENV infection.

Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity.

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data.

Anti-Arbovirus Antibodies Cross-React With Severe Acute Respiratory Syndrome Coronavirus 2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is found in regions where dengue (DENV) and chikungunya (CHIKV) viruses are endemic. Any serological cross-reactivity between DENV, CHIKV, and SARS-CoV-2 is significant as it could lead to misdiagnosis, increased severity, or cross-protection. This study examined the potential cross-reactivity of anti-DENV and CHIKV antibodies with SARS-CoV-2 using acute and convalescent-phase samples collected before the SARS-CoV-2 pandemic.