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.

Added-value of mosquito vector breeding sites from street view images in the risk mapping of dengue incidence in Thailand.

Dengue is an emerging vector-borne viral disease across the world. The primary dengue mosquito vectors breed in containers with sufficient water and nutrition. Outdoor containers can be detected from geotagged images using state-of-the-art deep learning methods. In this study, we utilize such container information from street view images in developing a risk mapping model and determine the added value of including container information in predicting dengue risk. We developed seasonal-spatial models in which the target variable dengue incidence was explained using weather and container variable predictors. Linear mixed models with fixed and random effects are employed in our models to account for different characteristics of containers and weather variables. Using data from three provinces of Thailand between 2015 and 2018, the models are developed at the sub-district level resolution to facilitate the development of effective targeted intervention strategies. The performance of the models is evaluated with two baseline models: a classic linear model and a linear mixed model without container information. The performance evaluated with the correlation coefficients, R-squared, and AIC shows the proposed model with the container information outperforms both baseline models in all three provinces. Through sensitivity analysis, we investigate the containers that have a high impact on dengue risk. Our findings indicate that outdoor containers identified from street view images can be a useful data source in building effective dengue risk models and that the resulting models have potential in helping to target container elimination interventions.

Large scale detailed mapping of dengue vector breeding sites using street view images.

Targeted environmental and ecosystem management remain crucial in control of dengue. However, providing detailed environmental information on a large scale to effectively target dengue control efforts remains a challenge. An important piece of such information is the extent of the presence of potential dengue vector breeding sites, which consist primarily of open containers such as ceramic jars, buckets, old tires, and flowerpots. In this paper we present the design and implementation of a pipeline to detect outdoor open containers which constitute potential dengue vector breeding sites from geotagged images and to create highly detailed container density maps at unprecedented scale. We implement the approach using Google Street View images which have the advantage of broad coverage and of often being two to three years old which allows correlation analyses of container counts against historical data from manual surveys. Containers comprising eight of the most common breeding sites are detected in the images using convolutional neural network transfer learning. Over a test set of images the object recognition algorithm has an accuracy of 0.91 in terms of F-score. Container density counts are generated and displayed on a decision support dashboard. Analyses of the approach are carried out over three provinces in Thailand. The container counts obtained agree well with container counts from available manual surveys. Multi-variate linear regression relating densities of the eight container types to larval survey data shows good prediction of larval index values with an R-squared of 0.674. To delineate conditions under which the container density counts are indicative of larval counts, a number of factors affecting correlation with larval survey data are analyzed. We conclude that creation of container density maps from geotagged images is a promising approach to providing detailed risk maps at large scale.

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.

A one-year effective reproduction number of the 2014-2015 Ebola outbreaks in the widespread West African countries and quantitative evaluation of air travel restriction measure.

BACKGROUND: The 2014-2015 Ebola outbreak in West Africa is the largest and longest Ebola Virus Disease (EVD) outbreak in the history, and the virus has escaped across countries and continents via air travel in this outbreak. METHOD: The interpolated data from WHO Ebola situation reports were used to estimate number of weekly infectious individuals and daily effective reproduction numbers (Rt) in Guinea, Liberia and Sierra Leone. A stochastic dynamic model was performed to estimate the risk of EVD importation into the top 20 final destination countries of air travelers departing from within the three epidemic countries, and the effectiveness of air travel restriction was subsequently evaluated. RESULTS: The daily Rt was estimated at 0.72-1.32 in Guinea, 0.62-1.38 in Liberia and 0.81-1.38 in Sierra Leone. The peak of EVD importation probability was observed in early November 2014 and the restriction of air travel may mitigate the risk up to 67.7% (95% CI 66.6-68.7). CONCLUSIONS: Our results suggest that restriction of air travels is effective in reducing the risk of EVD importation but controlling of the virus at the original affected countries is vitally more important for preventing inter-terrestrial dissemination of EVD.

Assessment of potential public health impact of a quadrivalent inactivated influenza vaccine in Thailand.

BACKGROUND: Each year, an influenza B strain representing only one influenza B lineage is included in the trivalent inactivated influenza vaccine (IIV3); a mismatch between the selected lineage and circulating viruses can result in suboptimal vaccine effectiveness. We modeled the added potential public health impact of a quadrivalent inactivated influenza vaccine (IIV4) that includes strains from both influenza B lineages compared to IIV3 on influenza-associated morbidity and mortality in Thailand. METHODS: Using data on the incidence of influenza-associated hospitalizations and deaths, vaccine effectiveness, and vaccine coverage from the 2007-2012 influenza seasons in Thailand, we estimated rates of influenza-associated outcomes that might be averted using IIV4 instead of IIV3. We then applied these rates to national population estimates to calculate averted illnesses, hospitalizations, and deaths for each season. We assumed that the influenza B lineage included in IIV3 would provide a relative vaccine effectiveness of 75% against the other B lineage. RESULTS: Compared to use of IIV3, use of IIV4 might have led to an additional reduction ranging from 0·4 to 14·3 influenza-associated illnesses per 100 000 population/year, <0·1 to 0·5 hospitalizations per 100 000/year, and <0·1 to 0·4 deaths per 1000/year. Based on extrapolation to national population estimates, replacement of IIV3 with IIV4 might have averted an additional 267-9784 influenza-associated illnesses, 9-320 hospitalizations, and 0-3 deaths. CONCLUSION: Compared to use of IIV3, IIV4 has the potential to further reduce the burden of influenza-associated morbidity and mortality in Thailand.

How influenza vaccination policy may affect vaccine logistics.

BACKGROUND: When policymakers make decision about the target populations and timing of influenza vaccination, they may not consider the impact on the vaccine supply chains, which may in turn affect vaccine availability. PURPOSE: Our goal is to explore the effects on the Thailand vaccine supply chain of introducing influenza vaccines and varying the target populations and immunization time-frames. METHODS: We Utilized our custom-designed software HERMES (Highly Extensible Resource for Modeling Supply Chains), we developed a detailed, computational discrete-event simulation model of the Thailand's National Immunization Program (NIP) supply chain in Trang Province, Thailand. A suite of experiments simulated introducing influenza vaccines for different target populations and over different time-frames prior to and during the annual influenza season. RESULTS: Introducing influenza vaccines creates bottlenecks that reduce the availability of both influenza vaccines as well as the other NIP vaccines, with provincial to district transport capacity being the primary constraint. Even covering only 25% of the Advisory Committee on Immunization Practice-recommended population while administering the vaccine over six months hinders overall vaccine availability so that only 62% of arriving patients can receive vaccines. Increasing the target population from 25% to 100% progressively worsens these bottlenecks, while increasing influenza vaccination time-frame from 1 to 6 months decreases these bottlenecks. CONCLUSION: Since the choice of target populations for influenza vaccination and the time-frame to deliver this vaccine can substantially affect the flow of all vaccines, policy-makers may want to consider supply chain effects when choosing target populations for a vaccine.

Economic value of dengue vaccine in Thailand.

With several candidate dengue vaccines under development, this is an important time to help stakeholders (e.g., policy makers, scientists, clinicians, and manufacturers) better understand the potential economic value (cost-effectiveness) of a dengue vaccine, especially while vaccine characteristics and strategies might be readily altered. We developed a decision analytic Markov simulation model to evaluate the potential health and economic value of administering a dengue vaccine to an individual (≤ 1 year of age) in Thailand from the societal perspective. Sensitivity analyses evaluated the effects of ranging various vaccine (e.g., cost, efficacy, side effect), epidemiological (dengue risk), and disease (treatment-seeking behavior) characteristics. A ≥ 50% efficacious vaccine was highly cost-effective [< 1× per capita gross domestic product (GDP) ($4,289)] up to a total vaccination cost of $60 and cost-effective [< 3× per capita GDP ($12,868)] up to a total vaccination cost of $200. When the total vaccine series was $1.50, many scenarios were cost saving.

Seroprevalence of antibodies to avian influenza virus A (H5N1) among residents of villages with human cases, Thailand, 2005.

In 2005, we assessed the seroprevalence of neutralizing antibodies to avian influenza virus A (H5N1) among 901 residents of 4 villages in Thailand where at least 1 confirmed human case of influenza (H5N1) had occurred during 2004. Although 68.1% of survey participants (median age 40 years) were exposed to backyard poultry and 25.7% were exposed to sick or dead chickens, all participants were seronegative for influenza virus (H5N1).

Low frequency of infection with avian influenza virus (H5N1) among poultry farmers, Thailand, 2004.

In Thai provinces where avian influenza outbreaks in poultry had been confirmed in the preceding 6 months, serum from 322 poultry farmers was tested for antibodies to avian influenza virus subtype H5N1 by microneutralization assay. No study participant met the World Health Organization serologic criteria for confirmed infection.

The incidence of pneumonia in rural Thailand.

BACKGROUND: Pneumonia continues to be a leading infectious disease killer, yet accurately measuring incidence remains a challenge. In 2002, Thailand began active, population-based surveillance for radiographically confirmed pneumonia in Sa Kaeo Province. METHODS: Full-time surveillance officers conducted active case ascertainment at every hospital, and routine audits and a community cluster survey promoted complete and accurate reporting. A case of pneumonia was defined as acute infection with signs or symptoms of lower respiratory tract infection and evidence of new infiltrates. An independent panel of radiologists reviewed digital images of all radiographs. RESULTS: Between September 2002 and August 2003, 777 patients met the case definition. The measured minimum incidence was 177/100,000 but the estimated incidence was as high as 580/100,000 with full adjustment for incomplete chest radiography and access to health care. Seventy-two (9%) patients died and 28% were known to be HIV positive. Fifteen (2%) patients had pneumonia twice during the year. The average cost of hospitalization for an episode of pneumonia ranged from US$490.80 to $628.60. CONCLUSIONS: Pneumonia is a significant and costly public health problem in Thailand. This surveillance system allows precise assessment and monitoring of radiologically confirmed pneumonia and lays the groundwork for the introduction of new vaccines against pneumonia pathogens.

Poultry-handling practices during avian influenza outbreak, Thailand.

With poultry outbreaks of avian influenza H5N1 continuing in Thailand, preventing human infection remains a priority. We surveyed residents of rural Thailand regarding avian influenza knowledge, attitudes, and practices. Results suggest that public education campaigns have been effective in reaching those at greatest risk, although some high-risk behavior continues.