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.

Periodic synchronisation of dengue epidemics in Thailand over the last 5 decades driven by temperature and immunity.

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, less work has been done to understand how climate variability and change affects dengue in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatiotemporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last 30 years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronisation events. We show that although patterns in synchrony of dengue are similar to those observed in temperature, the relationship between the two is most consistent during synchronous periods, while during asynchronous periods, temperature plays a less prominent role. With simulations from temperature-driven models, we explore how dynamics of immunity interact with temperature to produce the observed patterns in synchrony. The simulations produced patterns in synchrony that were similar to observations, supporting an important role of immunity. We demonstrate that multiannual oscillations produced by immunity can lead to asynchronous dynamics and that synchrony in temperature can then synchronise these dengue dynamics. At higher mean temperatures, immune dynamics can be more predominant, and dengue dynamics more insensitive to multiannual fluctuations in temperature, suggesting that with rising mean temperatures, dengue dynamics may become increasingly asynchronous. These findings can help underpin predictions of disease patterns as global temperatures rise.

Assessing the role of multiple mechanisms increasing the age of dengue cases in Thailand.

The mean age of dengue hemorrhagic fever (DHF) cases increased considerably in Thailand from 8.1 to 24.3 y between 1981 and 2017 (mean annual increase of 0.45 y). Alternative proposed explanations for this trend, such as changes in surveillance practices, reduced mosquito­human contact, and shifts in population demographics, have different implications for global dengue epidemiology. To evaluate the contribution of each of these hypothesized mechanisms to the observed data, we developed 20 nested epidemiological models of dengue virus infection, allowing for variation over time in population demographics, infection hazards, and reporting rates. We also quantified the effect of removing or retaining each source of variation in simulations of the age trajectory. Shifts in the age structure of susceptibility explained 58% of the observed change in age. Adding heterogeneous reporting by age and reductions in per-serotype infection hazard to models with shifts in susceptibility explained an additional 42%. Reductions in infection hazards were mostly driven by changes in the number of infectious individuals at any time (another consequence of shifting age demographics) rather than changes in the transmissibility of individual infections. We conclude that the demographic transition drives the overwhelming majority of the observed change as it changes both the age structure of susceptibility and the number of infectious individuals. With the projected Thai population age structure, our results suggest a continuing increase in age of DHF cases, shifting the burden toward individuals with more comorbidity. These insights into dengue epidemiology may be relevant to many regions of the globe currently undergoing comparable changes in population demographics.

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

BACKGROUND: Dengue virus (DENV) non-structural 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. We analyzed plasma samples collected in a prospective cohort study prior to symptomatic or subclinical secondary DENV infection. We measured binding to purified recombinant NS1 protein and to NS1-expressing CEM cells, antibody-mediated NK cell activation by plate-bound NS1 protein, and antibody-dependent cellular cytotoxicity (ADCC) of NS1-expressing target cells. RESULTS: We found that antibody responses to NS1 were highly serotype-cross-reactive and that subjects who experienced subclinical DENV infection had significantly higher antibody responses to NS1 in pre-infection plasma than subjects who experienced symptomatic infection. We observed strong positive correlations between antibody binding and NK activation. CONCLUSIONS: These findings demonstrate the involvement of NS1-specific antibodies in ADCC and provide evidence for a protective effect of NS1-specific antibodies in secondary DENV infection.

Identifying villages and breeding habitats for dengue transmission in Thailand: insights from long-term larval surveys.

BACKGROUND: In Thailand, the Department of Disease Control (DDC) regularly performs visual larval surveys throughout the country to monitor dengue fever outbreaks. Since 2016, the DDC switched from a paper-based to a digital-based larval survey process. The significant amount of larval survey data collected digitally presents a valuable opportunity to precisely identify the villages and breeding habitats that are vulnerable to dengue transmission. METHODS: The study used digitally collected larval survey data from 2017 to 2019. It employed larval indices to evaluate the risk of dengue transmission in villages based on seasonal, regional, and categorical perspectives. Furthermore, the study comprehensively scrutinized each container category by employing different measures to determine its breeding preference ratio. RESULTS: The result showed that villages with a very high-risk of dengue transmission were present year-round in all regions, with the highest proportion during the rainy season. The Southern region had more high-risk villages during the winter season due to rainfall. Slums and residential communities were more vulnerable to dengue than commercial areas. All container categories could potentially serve as breeding habitats for dengue-carrying mosquitoes, with abandoned containers being the most significant breeding sites. CONCLUSIONS: The risk of dengue transmission was present year-round throughout Thailand. This underscores the importance of community and government initiatives, along with sustained public awareness campaigns and active community engagement, to efficiently and permanently eradicate mosquito breeding habitats. It should be noted that larval indices may not strongly correlate with dengue cases, as indicated by the preliminary analysis. However, they offer valuable insights into potential breeding sites for targeted preventive measures.

Individual, Household, and Community Drivers of Dengue Virus Infection Risk in Kamphaeng Phet Province, Thailand.

BACKGROUND: Dengue virus (DENV) often circulates endemically. In such settings with high levels of transmission, it remains unclear whether there are risk factors that alter individual infection risk. METHODS: We tested blood taken from individuals living in multigenerational households in Kamphaeng Phet province, Thailand for DENV antibodies (N = 2364, mean age 31 years). Seropositivity ranged from 45.4% among those 1-5 years old to 99.5% for those >30 years. Using spatially explicit catalytic models, we estimated that 11.8% of the susceptible population gets infected annually. RESULTS: We found that 37.5% of the variance in seropositivity was explained by unmeasured household-level effects with only 4.2% explained by spatial differences between households. The serostatus of individuals from the same household remained significantly correlated even when separated by up to 15 years in age. CONCLUSIONS: These findings show that despite highly endemic transmission, persistent differences in infection risk exist across households, the reasons for which remain unclear.

Multiple clades of SARS-CoV-2 were introduced to Thailand during the first quarter of 2020.

In early January 2020, Thailand became the first country where a coronavirus disease 2019 (COVID-19) patient was identified outside China. In this study, 23 whole genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from patients who were hospitalized from January to March 2020 were analyzed, along with their travel histories. Six lineages were identified including A, A.6, B, B.1, B.1.8, and B.58, among which lineage A.6 was dominant. Seven patients were from China who traveled to Thailand in January and early February. Five of them were infected with the B lineage virus, and the other two cases were infected with different lineages including A and A.6. These findings present clear evidence of the early introduction of diverse SARS-CoV-2 clades in Thailand.

Evaluation of different platforms for the detection of anti-SARS coronavirus-2 antibodies, Thailand.

BACKGROUND: Antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) help determine previous infection in individuals, regardless of whether they are asymptomatic or symptomatic. The detection of antibodies serves several purposes, including supporting other assays for disease diagnosis, conducting seroepidemiological studies, and evaluating vaccines. Many platforms of immunological methods for anti-SARS-CoV-2 antibody detection and their performance require validation. METHODS: This study evaluated the test performance of three autoanalyzer-based assays (Architect IgG, Vitros IgG, and Vitros total Ig) and one manual ELISA (Wantai total Ig) against a microneutralization (microNT) assay on the detection of SARS-CoV-2 antibodies. Furthermore, an indirect immunofluorescence assay verified the discordant results between the microNT and commercial assays. The test sensitivity, specificity, positive predictive value, and negative predictive value were determined based on four groups of 1005 serum samples: 102 COVID-19 prepandemic sera, 45 anti-SARS-CoV-2 positive sera, 366 sera of people at risk, and 492 sera of citizens returning from countries with a high prevalence of infection. RESULTS: The analyses as a whole showed that the performance of these commercial assays was comparable. Each group was also analysed separately to gain further insight into test performance. The Architect did not detect two positive sera of people at risk (prevalence of infection 0.55%). The other methods correctly identified these two positive sera but yielded varying false-positive results. The group of returning travellers with an infection rate of 28.3% (139 of 492) better differentiated the test performance of individual assays. CONCLUSIONS: High-throughput Architect and Vitros autoanalyzers appear appropriate for working on large sample sizes in countries that can afford the cost. The Wantai ELISA, while requiring more individual time and technical skill, may provide reliable results at a lower cost. The selection of assays will depend on the laboratory facilities and feasibility.

Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010-2014.

Dengue hemorrhagic fever (DHF), a severe manifestation of dengue viral infection that can cause severe bleeding, organ impairment, and even death, affects between 15,000 and 105,000 people each year in Thailand. While all Thai provinces experience at least one DHF case most years, the distribution of cases shifts regionally from year to year. Accurately forecasting where DHF outbreaks occur before the dengue season could help public health officials prioritize public health activities. We develop statistical models that use biologically plausible covariates, observed by April each year, to forecast the cumulative DHF incidence for the remainder of the year. We perform cross-validation during the training phase (2000-2009) to select the covariates for these models. A parsimonious model based on preseason incidence outperforms the 10-y median for 65% of province-level annual forecasts, reduces the mean absolute error by 19%, and successfully forecasts outbreaks (area under the receiver operating characteristic curve = 0.84) over the testing period (2010-2014). We find that functions of past incidence contribute most strongly to model performance, whereas the importance of environmental covariates varies regionally. This work illustrates that accurate forecasts of dengue risk are possible in a policy-relevant timeframe.

An Innovative, Prospective, Hybrid Cohort-Cluster Study Design to Characterize Dengue Virus Transmission in Multigenerational Households in Kamphaeng Phet, Thailand.

Difficulties inherent in the identification of immune correlates of protection or severe disease have challenged the development and evaluation of dengue vaccines. There persist substantial gaps in knowledge about the complex effects of age and sequential dengue virus (DENV) exposures on these correlations. To address these gaps, we were conducting a novel family-based cohort-cluster study for DENV transmission in Kamphaeng Phet, Thailand. The study began in 2015 and is funded until at least 2023. As of May 2019, 2,870 individuals in 485 families were actively enrolled. The families comprise at least 1 child born into the study as a newborn, 1 other child, a parent, and a grandparent. The median age of enrolled participants is 21 years (range 0-93 years). Active surveillance is performed to detect acute dengue illnesses, and annual blood testing identifies subclinical seroconversions. Extended follow-up of this cohort will detect sequential infections and correlate antibody kinetics and sequence of infections with disease outcomes. The central goal of this prospective study is to characterize how different DENV exposure histories within multigenerational family units, from DENV-naive infants to grandparents with multiple prior DENV exposures, affect transmission, disease, and protection at the level of the individual, household, and community.

Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries.

BACKGROUND: Reporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel. OBJECTIVE: This study aimed to develop and test an application that can support a local hospital to analyze routinely collected electronic data independently and generate AMR surveillance reports rapidly. METHODS: An offline application to generate standardized AMR surveillance reports from routinely available microbiology and hospital data files was written in the R programming language (R Project for Statistical Computing). The application can be run by double clicking on the application file without any further user input. The data analysis procedure and report content were developed based on the recommendations of the World Health Organization Global Antimicrobial Resistance Surveillance System (WHO GLASS). The application was tested on Microsoft Windows 10 and 7 using open access example data sets. We then independently tested the application in seven hospitals in Cambodia, Lao People's Democratic Republic, Myanmar, Nepal, Thailand, the United Kingdom, and Vietnam. RESULTS: We developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), which can support clinical microbiology laboratories to analyze their microbiology and hospital data files (in CSV or Excel format) onsite and promptly generate AMR surveillance reports (in PDF and CSV formats). The data files could be those exported from WHONET or other laboratory information systems. The automatically generated reports contain only summary data without patient identifiers. The AMASS application is downloadable from https://www.amass.website/. The participating hospitals tested the application and deposited their AMR surveillance reports in an open access data repository. CONCLUSIONS: The AMASS is a useful tool to support the generation and sharing of AMR surveillance reports.

Early transmission patterns of coronavirus disease 2019 (COVID-19) in travellers from Wuhan to Thailand, January 2020.

We report two cases of coronavirus disease 2019 (COVID-19) in travellers from Wuhan, China to Thailand. Both were independent introductions on separate flights, discovered with thermoscanners and confirmed with RT-PCR and genome sequencing. Both cases do not seem directly linked to the Huanan Seafood Market in Hubei but the viral genomes are identical to four other sequences from Wuhan, suggesting early spread within the city already in the first week of January.

Spatiotemporal multi-disease transmission dynamic measure for emerging diseases: an application to dengue and zika integrated surveillance in Thailand.

BACKGROUND: New emerging diseases are public health concerns in which policy makers have to make decisions in the presence of enormous uncertainty. This is an important challenge in terms of emergency preparation requiring the operation of effective surveillance systems. A key concept to investigate the dynamic of infectious diseases is the basic reproduction number. However it is difficult to be applicable in real situations due to the underlying theoretical assumptions. METHODS: In this paper we propose a robust and flexible methodology for estimating disease strength varying in space and time using an alternative measure of disease transmission within the hierarchical modeling framework. The proposed measure is also extended to allow for incorporating knowledge from related diseases to enhance performance of surveillance system. RESULTS: A simulation was conducted to examine robustness of the proposed methodology and the simulation results demonstrate that the proposed method allows robust estimation of the disease strength across simulation scenarios. A real data example is provided of an integrative application of Dengue and Zika surveillance in Thailand. The real data example also shows that combining both diseases in an integrated analysis essentially decreases variability of model fitting. CONCLUSIONS: The proposed methodology is robust in several simulated scenarios of spatiotemporal transmission force with computing flexibility and practical benefits. This development has potential for broad applicability as an alternative tool for integrated surveillance of emerging diseases such as Zika.

Prediction of dengue outbreaks based on disease surveillance, meteorological and socio-economic data.

BACKGROUND: The goal of this research is to create a system that can use the available relevant information about the factors responsible for the spread of dengue and; use it to predict the occurrence of dengue within a geographical region, so that public health experts can prepare for, manage and control the epidemic. Our study presents new geospatial insights into our understanding and management of health, disease and health-care systems. METHODS: We present a machine learning-based methodology capable of providing forecast estimates of dengue prediction in each of the fifty districts of Thailand by leveraging data from multiple data sources. Using a set of prediction variables, we show an increase in prediction accuracy of the model with an optimal combination of predictors which include: meteorological data, clinical data, lag variables of disease surveillance, socioeconomic data and the data encoding spatial dependence on dengue transmission. We use Generalized Additive Models (GAMs) to fit the relationships between the predictors (with a lag of one month) and the clinical data of Dengue hemorrhagic fever (DHF) using the data from 2008 to 2012. Using the data from 2013 to 2015 and a comparative set of prediction models, we evaluate the predictive ability of the fitted models according to RMSE and SRMSE as well as using adjusted R-squared value, deviance explained and change in AIC. RESULTS: The model allows for combining different predictors to make forecasts with a lead time of one month and also describe the statistical significance of the variables used to characterize the forecast. The discriminating ability of the final model was evaluated against Bangkok specific constant threshold and WHO moving threshold of the epidemic in terms of specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV). CONCLUSIONS: The out-of-sample validation showed poorer results than the in-sample validation, however it demonstrated ability in detecting outbreaks up-to one month ahead. We also determine that for the predicting dengue outbreaks within a district, the influence of dengue incidences and socioeconomic data from the surrounding districts is statistically significant. This validates the influence of movement patterns of people and spatial heterogeneity of human activities on the spread of the epidemic.

Seroprevalence of antibodies to enterovirus 71 and coxsackievirus A16 among people of various age groups in a northeast province of Thailand.

BACKGROUND: Hand, foot and mouth disease (HFMD) is endemic among population of young children in Thailand. The disease is mostly caused by enterovirus 71 (EV71) and coxsackievirus A16 (CA16). METHODS: This study conducted serosurveillance for neutralizing (NT) antibodies to EV71 subgenotypes B5 and C4a, and to CA16 subgenotypes B1a and B1b, in 579 subjects of various ages using a microneutralization assay in human rhabdomyosarcoma (RD) cells. These test viruses were the major circulating subgenotypes associated with HFMD in Thailand during the study period. RESULTS: We found that the levels of seropositivity against all 4 study viruses were lowest in the age group of 6-11 months, i.e., 5.5% had antibody to both EV71 subgenotypes, while 14.5% and 16.4% had antibody to CA16 subgenotypes B1a and B1b, respectively. The percentages of subjects with antibodies to these 4 viruses gradually increased with age, but were still less than 50% in children younger than 3 years. These laboratory data were consistent with the epidemiological data collected by the Ministry of Public Health which showed repeatedly that the highest number of HFMD cases was in children aged 1 year. Analyses of amino acid sequences of the test viruses showed 97% identity between the two subgenotypes of EV71, and 99% between the two subgenotypes of CA16. Nevertheless, the levels of seropositivity and antibody titer against the two subgenotypes of EV71 and of CA16 were not significantly different. CONCLUSIONS: This study clearly demonstrated NT antibody activity across EV71-B5 and EV71-C4a subgenotypes, and also across CA16-B1a and CA16-B1b subgenotypes. Moreover, there were no significant differences by gender in the seropositive rates and antibody levels to any of the 4 virus subgenotypes.

Region-wide synchrony and traveling waves of dengue across eight countries in Southeast Asia.

Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼ 10(7) km(2). We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.

SURVEILLANCE IN 2013 OF AVIAN INFLUENZA VIRUS FROM LIVE-BIRD MARKETS IN BANGKOK, THAILAND.

Live-bird markets have been implicated in transmission of avian influenza viruses, most recently of influenza A (H7N9) in China. Low pathogenic avian influenza (LPAI) viruses, such as H7N9, cause asymptomatic infections in poultry, and active surveillance is required to detect infection and to prevent transmission to humans. Although limited numbers of live birds for consumption are sold in Bangkok live bird markets (LBM), transmission of H7N9 in nearby China has prompted a program of active surveillance for avian influenza in Bangkok LBM to determine LPAI viruses. In November 2013, Bangkok One Health team organized avian influenza surveillance in all nine districts of Bangkok with LBMs. Oropharyngeal swabs (n = 834), sera (n = 375) and fresh feces (n = 420) were taken from 400 chickens, 20 ducks, 20 geese and 394 pet birds from 75/87 shops. Additionally, drinking water (n = 208) and waste water (n = 26) were collected. Samples were tested for influenza A viruses using RT-PCR. In addition, samples were inoculated in eggs and tested by hemagglutination (HA) and hemagglutination inhibition (HI) assays using H5N1- and H7N9-specific antigens. Sera were tested by HI assay using similar antigens. No sample was found positive for influenza A virus. These data provide evidence that avian influenza viruses, including LPAI viruses such as H7N9, were not circulating in Bangkok LBMs during the period surveyed.

Cross-reactive antibodies against H7N9 and H5N1 avian influenza viruses in Thai population.

BACKGROUD: Avian influenza H5N1 and H7N9 viruses have jumped across species from avian to humans and become a threat to public health. Not much is known about pre-existing cross-reactive antibodies against these avian viruses in human population. OBJECTIVE: To determine the prevalence of cross-reactive anti-HA and anti-NA antibodies to avian influenza H5N1 and H7N9 viruses in Thai population. METHOD: Archival serum samples from 100 blood donors and 21 patients infected with 2009 pandemic influenza A (H1N1) (pdmH1N1) virus were investigated by hemagglutination-inhibition (HAI) and neuraminidase-inhibition (NAI) assays for anti-HA and anti-NA antibodies, respectively. The test antigens comprised 2 human viruses (pdmH1N1 and H3N2 viruses), and 6 reassortant viruses carrying HA and NA genes of avian H5N1 or H7N9 virus generated by reverse genetics. RESULTS: HAI antibody titers ≥ 10 were found in 58, 89, 0 and 15% of blood donors as tested against pdmH1N1, H3N2, H5N1 and H7N9 viruses, respectively. On the other hand, NAI antibodies were detected in 98, 94, 73 and 53% of blood donors when reverse genetic-derived viruses harboring NA gene from pdmH1N1, H3N2, H5N1 or H7N9 virus were used as the test antigens. Moreover, 66.7% of pdmH1N1 patients who had > 4 fold increase in HAI antibody titers in paired sera developed > 4 fold increase in NAI antibody titers. CONCLUSIONS: Anti-NA antibody has broader reactivity than anti-HA antibody, therefore, it can be a supplement to anti-HA antibody in the prevention against novel influenza viruses.

Deciphering the impacts of vaccination and immunity on pertussis epidemiology in Thailand.

Pertussis is a highly infectious respiratory disease that is currently responsible for nearly 300,000 annual deaths worldwide, primarily in infants in developing countries. Despite sustained high vaccine uptake, a resurgence in pertussis incidence has been reported in a number of countries. This resurgence has led to critical questions regarding the transmission impacts of vaccination and pertussis immunology. We analyzed pertussis incidence in Thailand--both age-stratified and longitudinal aggregate reports--over the past 30 y. To dissect the contributions of waning pertussis immunity and repeat infections to pertussis epidemiology in Thailand following a pronounced increase in vaccine uptake, we used likelihood-based statistical inference methods to evaluate the support for multiple competing transmission models. We found that, in contrast to other settings, there is no evidence for pertussis resurgence in Thailand, with each model examined pointing to a substantial rise in herd immunity over the past 30 y. Using a variety of empirical metrics, we verified our findings by documenting signatures of changing herd immunity over the study period. Importantly, this work leads to the conclusion that repeat infections have played little role in shaping pertussis epidemiology in Thailand. Our results are surprisingly emphatic in support of measurable impact of herd immunity given the uncertainty associated with pertussis epidemiology.

Revisiting Rayong: shifting seroprofiles of dengue in Thailand and their implications for transmission and control.

Dengue virus has traditionally caused substantial morbidity and mortality among children less than 15 years of age in Southeast Asia. Over the last 2 decades, a significant increase in the mean age of cases has been reported, and a once pediatric disease now causes substantial burden among the adult population. An age-stratified serological study (n = 1,736) was conducted in 2010 among schoolchildren in the Mueang Rayong district of Thailand, where a similar study had been conducted in 1980/1981. Serotype-specific forces of infection (λ(t)) and basic reproductive numbers (R0) of dengue were estimated for the periods 1969-1980 and 1993-2010. Despite a significant increase in the age at exposure and a decrease in λ(t) from 0.038/year to 0.019/year, R0 changed only from 3.3 to 3.2. Significant heterogeneity was observed across subdistricts and schools, with R0 ranging between 1.7 and 6.8. These findings are consistent with the idea that the observed age shift might be a consequence of the demographic transition in Thailand. Changes in critical vaccination fractions, estimated by using R0, have not accompanied the increase in age at exposure. These results have implications for dengue control interventions because multiple countries in Southeast Asia are undergoing similar demographic transitions. It is likely that dengue will never again be a disease exclusively of children.