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. 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 are 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 be used to infer FOI. Agreement of these measurements, however, have not been assessed. Using 26 years 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 was 2.46 to 4.33-times higher than case-derived FOI. Correlation between seroprevalence-derived and case-derived FOI was moderate (correlation coefficient=0.46) and no systematic bias. 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.

Dengue virus transmission risk in blood donation: Evidence from Thailand.

Individuals infected with dengue virus (DENV) often show no symptoms, which raises the risk of DENV transfusion transmission (TT-DENV) in areas where the virus is prevalent. This study aimed to determine the evidence of DENV infection in blood donors from different geographic regions of Thailand. A cross-sectional study was conducted on blood donor samples collected from the Thai Red Cross National Blood Center and four regional blood centers between March and September 2020. Screening for DENV nonstructural protein 1 (NS1), anti-DENV immunoglobulin G (IgG), and IgM antibodies was performed on residual blood from 1053 donors using enzyme-linked immunosorbent assay kits. Positive NS1 and IgM samples indicating acute infection were verified using four different techniques, including quantitative real-time (q) RT-PCR, nested PCR, virus isolation in C6/36 cells, and mosquito amplification. DENV IgG seropositivity was identified in 89% (938/1053) of blood donors. Additionally, 0.4% (4/1053) and 2.1% (22/1053) of Thai blood donors tested positive for NS1 and IgM, respectively. The presence of asymptomatic dengue virus infection in healthy blood donors suggests a potential risk of transmission through blood transfusion, posing a concern for blood safety.

Molecular and Entomological Characterization of 2023 Dengue Outbreak in Dhading District, Central Nepal.

In 2023, Nepal faced its second largest dengue outbreak ever, following a record-breaking number of dengue cases in 2022, characterized by the expansion of infections into areas of higher altitudes. However, the characteristics of the 2023 circulating dengue virus (DENV) and the vector density remain poorly understood. Therefore, we performed DENV serotyping, clinical and laboratory assessment, and entomological analysis of the 2023 outbreak in central Nepal. A total of 396 fever cases in Dhading hospital suspected of being DENV positive were enrolled, and blood samples were collected and tested by different techniques including PCR. Of these, 278 (70.2%) had confirmed DENV infection. Multiple serotypes (DENV-1, -2, and -3) were detected. DENV-2 (97.5%) re-emerged after six years in Dhading while DENV-3 was identified for the first time. Dengue inpatients had significantly higher frequency of anorexia, myalgia, rash, diarrhea, nausea, vomiting, abdominal pain, and thrombocytopenia (p < 0.05). In this area, Aedes mosquitoes largely predominated (90.7%) with the majority being A. aegypti (60.7%). We also found high levels of Aedes index (20.0%) and container index (16.7%). We confirmed multiple DENV serotype circulation with serotype re-emergence and new serotype introduction, and high vector density in 2023. These findings call for the urgent initiation and scaling up of DENV molecular surveillance in human and mosquito populations for dengue control and prevention in Nepal.

Antigenic distance between primary and secondary dengue infections correlates with disease risk.

Many pathogens continuously change their protein structure in response to immune-driven selection, resulting in weakened protection even in previously exposed individuals. In addition, for some pathogens, such as dengue virus, poorly targeted immunity is associated with increased risk of severe disease through a mechanism known as antibody-dependent enhancement. However, it remains unclear whether the antigenic distances between an individual's first infection and subsequent exposures dictate disease risk, explaining the observed large-scale differences in dengue hospitalizations across years. Here, we develop a framework that combines detailed antigenic and genetic characterization of viruses with details on hospitalized cases from 21 years of dengue surveillance in Bangkok, Thailand, to identify the role of the antigenic profile of circulating viruses in determining disease risk. We found that the risk of hospitalization depended on both the specific order of infecting serotypes and the antigenic distance between an individual's primary and secondary infections, with risk maximized at intermediate antigenic distances. These findings suggest that immune imprinting helps determine dengue disease risk and provide a pathway to monitor the changing risk profile of populations and to quantifying risk profiles of candidate vaccines.

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. In cross-validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric significantly improved model performance.

Seroprevalence of dengue, Japanese encephalitis and Zika among long-term expatriates in Thailand.

BACKGROUND: Travel to Southeast Asia increases the likelihood of acquiring mosquito-borne Flavivirus infections such as dengue (DENV), Japanese encephalitis (JEV) and Zika viruses (ZIKV). Expatriates are long-term travellers who have a higher risk of mosquito-borne illness at their destination country. The purpose of this study was to evaluate the seroprevalence of DENV, JEV and ZIKV infections and the determinants contributing to seropositivity among expatriates living in Thailand. METHODS: A cross-sectional study was performed from December 2017 to February 2020. Expatriates from non-Flavivirus endemic countries were recruited. 5 mL of blood was collected for DENV 1-4, JEV and ZIKV antibody testing by plaque reduction neutralization test (PRNT50). Individuals with vaccination histories or diagnoses for dengue, Japanese encephalitis, yellow fever and tick-borne encephalitis were excluded. RESULTS: Among 254 participants, most participants (83.1%) were male, the mean age was 65 years and the median duration of stay in Thailand was 6 years. Seroprevalence rate of any Flavivirus, non-specific DENV, DENV1-4, JEV and ZIKV were 34.3, 30.7, 20.5, 18.1, 18.9, 10.6, 4.7 and 2.8%, respectively. The presence of neutralizing antibodies against DENV1-4 positively correlates with the duration of stay in Thailand. DENV seropositivity was associated with living in urban areas (aOR 2.75, 95% CI 1.36-5.57). Expatriates were unlikely to have detectable anti-JEV antibodies regardless of time spent in a JEV-endemic area. No risk factors were identified that were significantly associated with JEV or ZIKV seropositivity. Only 48.4% received pre-travel counselling services, while only 18.9% visited a travel medicine specialist. CONCLUSIONS: A high proportion (34.3%) of long-term expatriates living in Thailand were seropositive for flavivirus, mainly from dengue (30.7%). To minimize risk, travel medicine practitioners should provide adequate pre-travel health risk information on mosquito-borne flavivirus infection and offer advice on mosquito bite prevention strategies. Dengue vaccine might be considered in high-risk travellers such as long-term expatriate.

Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission.

This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.

An unusual diarrheal outbreak in the community in Eastern Thailand caused by Norovirus GII.3[P25].

BACKGROUND: Sentinel laboratory surveillance for diarrheal disease determined norovirus to be the most common cause of non-bacterial gastroenteritis in people during the COVID-19 pandemic in Thailand. An increase in patients presenting with diarrhea and vomiting in hospitals across Chanthaburi province between December 2021 and January 2022 led to the need for the identification of viral pathogens that may be responsible for the outbreak. METHODS: Fecal samples (rectal swabs or stool) from 93 patients, of which 65 patients were collected during the December 2021 to January 2022 outbreak, were collected and screened for viral infection by real-time RT-PCR. Positive samples for norovirus GII were then genotyped by targeted amplification and sequencing of partial polymerase and capsid genes. Full genome sequencing was performed from the predominant strain, GII.3[P25]. RESULTS: Norovirus was the most common virus detected in human fecal samples in this study. 39 of 65 outbreak samples (60%) and 3 of 28 (10%) non-outbreak samples were positive for norovirus genogroup II. One was positive for rotavirus, and one indicated co-infection with rotavirus and norovirus genogroups I and II. Nucleotide sequences of VP1 and RdRp gene were successfully obtained from 28 of 39 positive norovirus GII and used for dual-typing; 25/28 (89.3%) were GII.3, and 24/28 (85.7) were GII.P25, respectively. Norovirus GII.3[P25] was the predominant strain responsible for this outbreak. The full genome sequence of norovirus GII.3[P25] from our study is the first reported in Thailand and has 98.62% and 98.57% similarity to norovirus found in China in 2021 and the USA in 2022, respectively. We further demonstrate the presence of multiple co-circulating norovirus genotypes, including GII.21[P21], GII.17[P17], GII.3[P12] and GII.4[P31] in our study. CONCLUSIONS: An unusual diarrhea outbreak was found in December 2021 in eastern Thailand. Norovirus strain GII.3[P25] was the cause of the outbreak and was first detected in Thailand. The positive rate during GII.3[P25] outbreak was six times higher than sporadic cases (GII.4), and, atypically, adults were the primary infected population rather than children.

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. Using a gradient-boosted regression model trained on annual haemagglutination inhibition antibody titre inputs, we identified 1,049 infections, 90% of which were subclinical. By analysing imputed infections, we found that individual antibody titres, household composition and antibody titres of other members in the same household affect an individual's risk of DENV infection. Those individuals living in households with high average antibody titres, or households with more adults, had a reduced risk of infection. We propose that herd immunity to dengue acts at the household level and may provide insight into the drivers of the recent change in the shifting age distribution of dengue cases in Thailand.

High Transmission Rates of Early Omicron Subvariant BA.2 in Bangkok, Thailand.

The emergence of Omicron as the fifth variant of concern within the SARS-CoV-2 pandemic in late 2021, characterized by its rapid transmission and distinct spike gene mutations, underscored the pressing need for cost-effective and efficient methods to detect viral variants, especially given their evolving nature. This study sought to address this need by assessing the effectiveness of two SARS-CoV-2 variant classification platforms based on RT-PCR and mass spectrometry. The primary aim was to differentiate between Delta, Omicron BA.1, and Omicron BA.2 variants using 618 COVID-19-positive samples collected from Bangkok patients between November 2011 and March 2022. The analysis revealed that both BA.1 and BA.2 variants exhibited significantly higher transmission rates, up to 2-3 times, when compared to the Delta variant. This research presents a cost-efficient approach to virus surveillance, enabling a quantitative evaluation of variant-specific public health implications, crucial for informing and adapting public health strategies.

Maternally derived antibody titer dynamics and risk of hospitalized infant dengue disease.

Infants less than 1 y of age experience high rates of dengue disease in dengue virus (DENV) endemic countries. This burden is commonly attributed to antibody-dependent enhancement (ADE), whereby concentrations of maternally derived DENV antibodies become subneutralizing, and infection-enhancing. Understanding antibody-related mechanisms of enhanced infant dengue disease risk represents a significant challenge due to the dynamic nature of antibodies and their imperfect measurement processes. Further, key uncertainties exist regarding the impact of long-term shifts in birth rates, population-level infection risks, and maternal ages on the DENV immune landscape of newborns and their subsequent risks of severe dengue disease in infancy. Here, we analyze DENV antibody data from two infant cohorts (N = 142 infants with 605 blood draws) and 40 y of infant dengue hospitalization data from Thailand. We use mathematical models to reconstruct maternally derived antibody dynamics, accounting for discretized measurement processes and limits of assay detection. We then explore possible antibody-related mechanisms of enhanced infant dengue disease risk and their ability to reconstruct the observed age distribution of hospitalized infant dengue cases. We find that ADE mechanisms are best able to reconstruct the observed data. Finally, we describe how the shifting epidemiology of dengue in Thailand, combined with declining birth rates, have decreased the absolute risk of infant dengue disease by 88% over a 40-y period while having minimal impact on the mean age of infant hospitalized dengue disease.

Antigenic diversity and dengue disease risk.

Many pathogens continuously change their protein structure in response to immune-driven selection, resulting in weakened protection. In addition, for some pathogens such as dengue virus, poorly targeted immunity is associated with increased risk of severe disease, through a mechanism known as antibody-dependent enhancement. However, it remains a mystery whether the antigenic distance between an individual's first infection and subsequent exposures dictate disease risk, explaining the observed large-scale differences in dengue hospitalisations across years. Here we develop an inferential framework that combines detailed antigenic and genetic characterisation of viruses, and hospitalised cases from 21 years of surveillance in Bangkok, Thailand to identify the role of the antigenic profile of circulating viruses in determining disease risk. We find that the risk of hospitalisation depends on both the specific order of infecting serotypes and the antigenic distance between an individual's primary and secondary infections, with risk maximised at intermediate antigenic distances. These findings suggest immune imprinting helps determine dengue disease risk, and provides a pathway to monitor the changing risk profile of populations and to quantifying risk profiles of candidate vaccines.

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. In cross validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric, significantly improved model performance.

Secondary dengue serotype 1 infection causing dengue shock syndrome with rhombencephalitis and bleeding associated with refractory thrombocytopenia: A case report.

Background: Dengue has a wide spectrum of manifestations, from an asymptomatic condition to dengue shock syndrome. Extensive plasma leakage, severe bleeding, or both, could lead to dengue shock syndrome, a common cause of death in dengue-infected patients. Thrombocytopenia is a common laboratory finding in dengue, which correlates with the disease severity and rapidly resolves during the recovery phase. Therefore, refractory thrombocytopenia is rare in patients with dengue. Rhombencephalitis is an inflammatory disease affecting the hindbrain, rarely associated with dengue. We report the second case of dengue-associated rhombencephalitis, wherein the patient developed dengue shock syndrome and severe bleeding associated with refractory thrombocytopenia. Case report: A 47-year-old Thai female with secondary dengue serotype 1 infection developed dengue shock syndrome with rhombencephalitis, manifested as altered sensorium and status epilepticus in the critical phase. Cerebrospinal fluid analysis showed pleocytosis with predominantly mononuclear cells and high protein levels. Magnetic resonance imaging of the brain showed multifocal brain signal abnormalities involving the medulla oblongata, pons, midbrain, bilateral hippocampi, thalami, posterior limb of internal capsules, external capsules, and deep hemispheric white matter. The patient had partial neurological recovery following rhombencephalitis for one month. During the recovery phase, severe bleeding with refractory thrombocytopenia and acute kidney injury were observed. Methylprednisolone with eltrombopag was administered, which resulted in an increased the platelet count, cessation of bleeding and recovery of kidney function within 4 days. Conclusions: Dengue is a potential cause of rhombencephalitis. Dengue-associated rhombencephalitis develops during the critical phase, with only partial neurological recovery. However, severe bleeding and refractory thrombocytopenia were also observed during the recovery phase. Methylprednisolone with a thrombopoietin receptor agonist could be an effective treatment for increasing platelet count and stopping bleeding in dengue.

Tracing the transmission of mpox through wastewater surveillance in Southeast Asia.

High population density and tourism in Southeast Asia increase the risk of mpox due to frequent interpersonal contacts. Our wastewater surveillance in six Southeast Asian countries revealed positive signals for Monkeypox virus (MPXV) DNA, indicating local transmission. This alerts clinicians and helps allocate resources like testing, vaccines and therapeutics in resource-limited countries.

Standardization of in-house anti-IgG and IgA ELISAs for the detection of COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). RT-PCR detection of viral RNA represents the gold standard method for diagnosis of COVID-19. However, multiple diagnostic tests are needed for acute disease diagnosis and assessing immunity during the COVID-19 outbreak. Here, we developed in-house anti-RBD IgG and IgA enzyme-linked immunosorbent assays (ELISAs) using a well-defined serum sample panel for screening and identification of human SARS-CoV-2 infection. We found that our in-house anti-SARS-CoV-2 IgG ELISA displayed a 93.5% sensitivity and 98.8% specificity whereas our in-house anti-SARS-CoV-2 IgA ELISA provided assay sensitivity and specificity at 89.5% and 99.4%, respectively. The agreement kappa values of our in-house anti-SARS-CoV-2 IgG and IgA ELISA assays were deemed to be excellent and fair, respectively, when compared to RT-PCR and excellent for both assays when compared to Euroimmun anti-SARS-CoV-2 IgG and IgA ELISAs. These data indicate that our in-house anti-SARS-CoV-2 IgG and IgA ELISAs are compatible performing assays for the detection of SARS-CoV-2 infection.