The complex relationship between weather and dengue virus transmission in Thailand.

Using a novel analytical approach, weather dynamics and seasonal dengue virus transmission cycles were profiled for each Thailand province, 1983-2001, using monthly assessments of cases, temperature, humidity, and rainfall. We observed systematic differences in the structure of seasonal transmission cycles of different magnitude, the role of weather in regulating seasonal cycles, necessary versus optimal transmission "weather-space," basis of large epidemics, and predictive indicators that estimate risk. Larger epidemics begin earlier, develop faster, and are predicted at Onset change-point when case counts are low. Temperature defines a viable range for transmission; humidity amplifies the potential within that range. This duality is central to transmission. Eighty percent of 1.2 million severe dengue cases occurred when mean temperature was 27-29.5°C and mean humidity was > 75%. Interventions are most effective when applied early. Most cases occur near Peak, yet small reductions at Onset can substantially reduce epidemic magnitude. Monitoring the Quiet-Phase is fundamental in effectively targeting interventions pre-emptively

Contact Mixing Patterns and Population Movement among Migrant Workers in an Urban Setting in Thailand.

Data relating to contact mixing patterns among humans are essential for the accurate modeling of infectious disease transmission dynamics. Here, we describe contact mixing patterns among migrant workers in urban settings in Thailand, based on a survey of 369 migrant workers of three nationalities. Respondents recorded their demographic data, including age, sex, nationality, workplace, income, and education. Each respondent chose a single day to record their contacts; this resulted in a total of more than 8300 contacts. The characteristics of contacts were recorded, including their age, sex, nationality, location of contact, and occurrence of physical contact. More than 75% of all contacts occurred among migrants aged 15 to 39 years. The contacts were highly clustered in this age group among migrant workers of all three nationalities. There were far fewer contacts between migrant workers with younger and older age groups. The pattern varied slightly among different nationalities, which was mostly dependent upon the types of jobs taken. Half of migrant workers always returned to their home country at most once a year and on a seasonal basis. The present study has helped us gain a better understanding of contact mixing patterns among migrant workers in urban settings. This information is useful both when simulating disease epidemics and for guiding optimal disease control strategies among this vulnerable section of the population

Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models

Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and incorporate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods

Non-linear effect of different humidity types on scrub typhus occurrence in endemic provinces, Thailand.

BACKGROUND: Reported monthly scrub typhus (ST) cases in Thailand has an increase in the number of cases during 2009-2014. Humidity is a crucial climatic factor for the survival of chiggers, which is the disease vectors. The present study was to determine the role of humidity in ST occurrence in Thailand and its delayed effect. METHODS: We obtained the climate data from the Department of Meteorology, the disease data from Ministry of Public Health. Negative binomial regression combined with a distributed lag non-linear model (NB-DLNM) was employed to determine the non-linear effects of different types of humidity on the disease. This model controlled overdispersion and confounder, including seasonality, minimum temperature, and cumulative total rainwater. RESULTS: The occurrence of the disease in the 6-year period showed the number of cases gradually increased summer season (Mid-February - Mid-May) and then reached a plateau during the rainy season (Mid-May - Mid-October) and then steep fall after the cold season (Mid-October - Mid-February). The high level (at 70%) of minimum relative humidity (RHmin) was associated with a 33% (RR 1.33, 95% CI 1.13-1.57) significant increase in the number of the disease; a high level (at 14 g/m3) of minimum absolute humidity (AHmin) was associated with a 30% (RR 1.30, 95% CI 1.14-1.48); a high level (at 1.4 g/kg) of minimum specific humidity (SHmin) was associated with a 28% (RR 1.28, 95% CI 1.04-1.57). The significant effects of these types of humidity occurred within the past month. CONCLUSION: Humidity played a significant role in enhancing ST cases in Thailand, particularly at a high level and usually occurred within the past month. NB-DLNM had good controlled for the overdispersion and provided the precise estimated relative risk of non-linear associations. Results from this study contributed the evidence to support the Ministry of Public Health on warning system which might be useful for public health intervention and preparation in Thailand

Key findings and comparisons from analogous case-cluster studies for dengue virus infection conducted in Machala, Ecuador, and Kamphaeng Phet, Thailand

The Thai research study presented here was funded by an R01 award from the National Institutes of Health (PI: TE, GM83224-01A1). This Ecuadorian research study was supported, in part, by the Department of Defense Global Emerging Infection Surveillance (GEIS) grant (P0220_13_OT) and the Department of Medicine of SUNY Upstate Medical University. AS-I and SR were additionally supported by NSF DEB EEID 1518681 and NSF DEB RAPID 1641145.Dengue viruses (DENV) pose a significant and increasing threat to human health across broad regions of the globe. Currently, prevention, control, and treatment strategies are limited. Promising interventions are on the horizon, including multiple vaccine candidates under development and a renewed and innovative focus on controlling the vector, Aedes aegypti. However, significant gaps persist in our understanding of the similarities and differences in DENV epidemiology across regions of potential implementation and evaluation. In this manuscript, we highlight and compare findings from two analogous cluster-based studies for DENV transmission and pathogenesis conducted in Thailand and Ecuador to identify key features and questions for further pursuit. Despite a remarkably similar incidence of DENV infection among enrolled neighborhood contacts at the two sites, we note a higher occurrence of secondary infection and severe illness in Thailand compared to Ecuador. A higher force of infection in Thailand, defined as the incidence of infection among susceptible individuals, is suggested by the higher number of captured Aedes mosquitoes per household, the increasing proportion of asymptomatic infections with advancing age, and the high proportion of infections identified as secondary-type infections by serology. These observations should be confirmed in long-term, parallel prospective cohort studies conducted across regions, which would advantageously permit characterization of baseline immune status (susceptibility) and contemporaneous assessment of risks and risk factors for dengue illness.Publisher PDFPeer reviewe

Entomological risk assessment for dengue virus transmission during 2016-2020 in Kamphaeng Phet, Thailand

Individual houses with high risks of dengue virus (DENV) transmission might be a source of virus transmission within the neighborhood. We conducted an entomological risk assessment for DENV transmission at the household level, comprising family cohort members residing in the same location, to assess the risk for dengue virus transmitted by mosquito vectors. The studies were conducted in Kamphaeng Phet Province, Thailand, during 2016–2020. Entomological investigations were performed in 35 cohort families on day 1 and day 14 after receiving dengue case reports. DENV was found in 22 Aedes samples (4.9%) out of 451 tested samples. A significantly higher DENV infection rate was detected in vectors collected on day 1 (6.64%) compared to those collected on day 14 (1.82%). Annual vector surveillance was carried out in 732 houses, with 1002 traps catching 3653 Aedes females. The majority of the 13,228 water containers examined were made from plastic and clay, with used tires serving as a primary container, with 59.55% larval abundance. Larval indices, as indicators of dengue epidemics and to evaluate disease and vector control approaches, were calculated. As a result, high values of larval indices indicated the considerably high risk of dengue transmission in these communities

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 mosquito–human 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

Reconstructing unseen transmission events to infer dengue dynamics from viral sequences.

For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We develop a spatiotemporally structured phylogenetic framework that addresses these limitations by considering individual transmission events, reconstructed across spatial scales. We apply it to geocoded dengue virus sequences from Thailand (N = 726 over 18 years). We find infected individuals spend 96% of their time in their home community compared to 76% for the susceptible population (mainly children) and 42% for adults. Dynamic pockets of local immunity make transmission more likely in places with high heterotypic immunity and less likely where high homotypic immunity exists. Age-dependent mixing of individuals and vector distributions are not important in determining spread. This approach provides previously unknown insights into one of the most complex disease systems known and will be applicable to other pathogens

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