Asymptomatic Plasmodium vivax infections induce robust IgG responses to multiple blood-stage proteins in a low-transmission region of western Thailand.

BACKGROUND: Thailand is aiming to eliminate malaria by the year 2024. Plasmodium vivax has now become the dominant species causing malaria within the country, and a high proportion of infections are asymptomatic. A better understanding of antibody dynamics to P. vivax antigens in a low-transmission setting, where acquired immune responses are poorly characterized, will be pivotal for developing new strategies for elimination, such as improved surveillance methods and vaccines. The objective of this study was to characterize total IgG antibody levels to 11 key P. vivax proteins in a village of western Thailand. METHODS: Plasma samples from 546 volunteers enrolled in a cross-sectional survey conducted in 2012 in Kanchanaburi Province were utilized. Total IgG levels to 11 different proteins known or predicted to be involved in reticulocyte binding or invasion (ARP, GAMA, P41, P12, PVX_081550, and five members of the PvRBP family), as well as the leading pre-erythrocytic vaccine candidate (CSP) were measured using a multiplexed bead-based assay. Associations between IgG levels and infection status, age, and spatial location were explored. RESULTS: Individuals from a low-transmission region of western Thailand reacted to all 11 P. vivax recombinant proteins. Significantly greater IgG levels were observed in the presence of a current P. vivax infection, despite all infected individuals being asymptomatic. IgG levels were also higher in adults (18 years and older) than in children. For most of the proteins, higher IgG levels were observed in individuals living closer to the Myanmar border and further away from local health services. CONCLUSIONS: Robust IgG responses were observed to most proteins and IgG levels correlated with surrogates of exposure, suggesting these antigens may serve as potential biomarkers of exposure, immunity, or both.

Projecting malaria elimination in Thailand using Bayesian hierarchical spatiotemporal models.

Thailand has set a goal of eliminating malaria by 2024 in its national strategic plan. In this study, we used the Thailand malaria surveillance database to develop hierarchical spatiotemporal models to analyze retrospective patterns and predict Plasmodium falciparum and Plasmodium vivax malaria incidences at the provincial level. We first describe the available data, explain the hierarchical spatiotemporal framework underlying the analysis, and then display the results of fitting various space-time formulations to the malaria data with the different model selection metrics. The Bayesian model selection process assessed the sensitivity of different specifications to obtain the optimal models. To assess whether malaria could be eliminated by 2024 per Thailand's National Malaria Elimination Strategy, 2017-2026, we used the best-fitted model to project the estimated cases for 2022-2028. The study results based on the models revealed different predicted estimates between both species. The model for P. falciparum suggested that zero P. falciparum cases might be possible by 2024, in contrast to the model for P. vivax, wherein zero P. vivax cases might not be reached. Innovative approaches in the P. vivax-specific control and elimination plans must be implemented to reach zero P. vivax and consequently declare Thailand as a malaria-free country.

Malaria Research for Tailored Control and Elimination Strategies in the Greater Mekong Subregion.

The malaria landscape in the Greater Mekong Subregion has experienced drastic changes with the ramp-up of the control efforts, revealing formidable challenges that slowed down the progress toward malaria elimination. Problems such as border malaria and cross-border malaria introduction, multidrug resistance in Plasmodium falciparum, the persistence of Plasmodium vivax, the asymptomatic parasite reservoirs, and insecticide resistance in primary vectors require integrated strategies tailored for individual nations in the region. In recognition of these challenges and the need for research, the Southeast Asian International Center of Excellence for Malaria Research has established a network of researchers and stakeholders and conducted basic and translational research to identify existing and emerging problems and develop new countermeasures. The installation of a comprehensive disease and vector surveillance system at sentinel sites in border areas with the implementation of passive/active case detection and cross-sectional surveys allowed timely detection and management of malaria cases, provided updated knowledge for effective vector control measures, and facilitated the efficacy studies of antimalarials. Incorporating sensitive molecular diagnosis to expose the significance of asymptomatic parasite reservoirs for sustaining transmission helped establish the necessary evidence to guide targeted control to eliminate residual transmission. In addition, this program has developed point-of-care diagnostics to monitor the quality of artemisinin combination therapies, delivering the needed information to the drug regulatory authorities to take measures against falsified and substandard antimalarials. To accelerate malaria elimination, this program has actively engaged with stakeholders of all levels, fostered vertical and horizontal collaborations, and enabled the effective dissemination of research findings.

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.

Effects of COVID-19 government travel restrictions on mobility in a rural border area of Northern Thailand: A mobile phone tracking study.

BACKGROUND: Thailand is among the top five countries with effective COVID-19 transmission control. This study examines how news of presence of COVID-19 in Thailand, as well as varying levels of government restriction on movement, affected human mobility in a rural Thai population along the border with Myanmar. METHODS: This study makes use of mobility data collected using a smartphone app. Between November 2019 and June 2020, four major events concerning information dissemination or government intervention give rise to five time intervals of analysis. Radius of gyration is used to analyze movement in each interval, and movement during government-imposed curfew. Human mobility network visualization is used to identify changes in travel patterns between main geographic locations of activity. Cross-border mobility analysis highlights potential for intervillage and intercountry disease transmission. RESULTS: Inter-village and cross-border movement was common in the pre-COVID-19 period. Radius of gyration and cross-border trips decreased following news of the first imported cases. During the government lockdown period, radius of gyration was reduced by more than 90% and cross-border movement was mostly limited to short-distance trips. Human mobility was nearly back to normal after relaxation of the lockdown. CONCLUSIONS: This study provides insight into the impact of the government lockdown policy on an area with extremely low socio-economic status, poor healthcare resources, and highly active cross-border movement. The lockdown had a great impact on reducing individual mobility, including cross-border movement. The quick return to normal mobility after relaxation of the lockdown implies that close monitoring of disease should be continued to prevent a second wave.

Application of 23 Novel Serological Markers for Identifying Recent Exposure to Plasmodium vivax Parasites in an Endemic Population of Western Thailand.

Thailand is aiming for malaria elimination by the year 2030. However, the high proportion of asymptomatic infections and the presence of the hidden hypnozoite stage of Plasmodium vivax are impeding these efforts. We hypothesized that a validated surveillance tool utilizing serological markers of recent exposure to P. vivax infection could help to identify areas of ongoing transmission. The objective of this exploratory study was to assess the ability of P. vivax serological exposure markers to detect residual transmission "hot-spots" in Western Thailand. Total IgG levels were measured against a panel of 23 candidate P. vivax serological exposure markers using a multiplexed bead-based assay. A total of 4,255 plasma samples from a cross-sectional survey conducted in 2012 of endemic areas in the Kanchanaburi and Ratchaburi provinces were assayed. We compared IgG levels with multiple epidemiological factors that are associated with an increased risk of P. vivax infection in Thailand, including age, gender, and spatial location, as well as Plasmodium infection status itself. IgG levels to all proteins were significantly higher in the presence of a P. vivax infection (n = 144) (T-test, p < 0.0001). Overall seropositivity rates varied from 2.5% (PVX_097625, merozoite surface protein 8) to 16.8% (PVX_082670, merozoite surface protein 7), with 43% of individuals seropositive to at least 1 protein. Higher IgG levels were associated with older age (>18 years, p < 0.05) and males (17/23 proteins, p < 0.05), supporting the paradigm that men have a higher risk of infection than females in this setting. We used a Random Forests algorithm to predict which individuals had exposure to P. vivax parasites in the last 9-months, based on their IgG antibody levels to a panel of eight previously validated P. vivax proteins. Spatial clustering was observed at the village and regional level, with a moderate correlation between PCR prevalence and sero-prevalence as predicted by the algorithm. Our data provides proof-of-concept for application of such surrogate markers as evidence of recent exposure in low transmission areas. These data can be used to better identify geographical areas with asymptomatic infection burdens that can be targeted in elimination campaigns.

Anopheles bionomics in a malaria endemic area of southern Thailand.

BACKGROUND: Ivermectin mass drug administration (MDA) could accelerate malaria elimination in the Greater Mekong Subregion. This study was performed to characterize the bionomics of Anopheles in Surat Thani province, Thailand. METHODS: Mosquitoes were collected via human landing collections between February and October 2019. Anopheles mosquitoes were morphologically identified to species. Primary Anopheles malaria vectors were dissected to assess parity status, and a subset were evaluated for molecular identification and Plasmodium detection. RESULTS: A total of 17,348 mosquitoes were collected during the study period; of these, 5777 were Anopheles mosquitoes. Morphological studies identified 15 Anopheles species, of which the most abundant were Anopheles minimus (s.l.) (87.16%, n = 5035), An. dirus s.l. (7.05%, n = 407) and An. barbirostris s.l. (2.86%, n = 165). Molecular identification confirmed that of the An. minimus s.l. mosquitoes collected, 99.80% were An. minimus (s.s.) (n = 484) and 0.2% were An. aconitus (n = 1), of the An. dirus (s.l.) collected, 100% were An. baimaii (n = 348), and of the An. maculatus (s.l.) collected, 93.62% were An. maculatus (s.s.) (n = 44) and 6.38% were An. sawadwongporni (n = 3). No Anopheles mosquito tested was Plasmodium positive (0/879). An average of 11.46 Anopheles were captured per collector per night. There were differences between species in hour of collection (Kruskal-Wallis H-test: χ2 = 80.89, P < 0.0001, n = 5666), with more An. barbirostris (s.l.) and An. maculatus (s.l.) caught earlier compared to An. minimus (s.l.) (P = 0.0001 and P < 0.0001, respectively) and An. dirus (s.l.) (P = 0.0082 and P < 0.001, respectively). The proportion of parous An. minimus (s.l.) captured by hour increased throughout the night (Wald Chi-square: χ2 = 17.31, P = 0.000, odds ratio = 1.0535, 95% confidence interval 1.0279-1.0796, n = 3400). Overall, An. minimus (s.l.) parity was 67.68% (2375/3509) with an intra-cluster correlation of 0.0378. A power calculation determined that an An. minimus (s.l.) parity reduction treatment effect size = 34%, with four clusters per treatment arm and a minimum of 300 mosquitoes dissected per cluster, at an α = 0.05, will provide 82% power to detect a significant difference following ivermectin MDA. CONCLUSIONS: The study area in Surat Thani province is an ideal location to evaluate the impact of ivermectin MDA on An. minimus parity.

Complexity-Based Spatial Hierarchical Clustering for Malaria Prediction.

Targeted intervention and resource allocation are essential in effective control of infectious diseases, particularly those like malaria that tend to occur in remote areas. Disease prediction models can help support targeted intervention, particularly if they have fine spatial resolution. But, choosing an appropriate resolution is a difficult problem since choice of spatial scale can have a significant impact on accuracy of predictive models. In this paper, we introduce a new approach to spatial clustering for disease prediction we call complexity-based spatial hierarchical clustering. The technique seeks to find spatially compact clusters that have time series that can be well characterized by models of low complexity. We evaluate our approach with 2 years of malaria case data from Tak Province in northern Thailand. We show that the technique's use of reduction in Akaike information criterion (AIC) and Bayesian information criterion (BIC) as clustering criteria leads to rapid improvement in predictability and significantly better predictability than clustering based only on minimizing spatial intra-cluster distance for the entire range of cluster sizes over a variety of predictive models and prediction horizons.

Spatiotemporal Bayesian networks for malaria prediction.

Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating village level models with weekly temporal resolution for Tha Song Yang district in northern Thailand. The networks are learned using data on cases and environmental covariates. Three types of networks are explored: networks for numeric prediction, networks for outbreak prediction, and networks that incorporate spatial autocorrelation. Evaluation of the numeric prediction network shows that the Bayes net has prediction accuracy in terms of mean absolute error of about 1.4 cases for 1 week prediction and 1.7 cases for 6 week prediction. The network for outbreak prediction has an ROC AUC above 0.9 for all prediction horizons. Comparison of prediction accuracy of both Bayes nets against several traditional modeling approaches shows the Bayes nets to outperform the other models for longer time horizon prediction of high incidence transmission. To model spread of malaria over space, we elaborate the models with links between the village networks. This results in some very large models which would be far too laborious to build by hand. So we represent the models as collections of probability logic rules and automatically generate the networks. Evaluation of the models shows that the autocorrelation links significantly improve prediction accuracy for some villages in regions of high incidence. We conclude that spatiotemporal Bayesian networks are a highly promising modeling alternative for prediction of malaria and other vector-borne diseases.

Very high carriage of gametocytes in asymptomatic low-density Plasmodium falciparum and P. vivax infections in western Thailand.

BACKGROUND: Low-density asymptomatic infections of Plasmodium spp. are common in low endemicity areas worldwide, but outside Africa, their contribution to malaria transmission is poorly understood. Community-based studies with highly sensitive molecular diagnostics are needed to quantify the asymptomatic reservoir of Plasmodium falciparum and P. vivax infections in Thai communities. METHODS: A cross-sectional survey of 4309 participants was conducted in three endemic areas in Kanchanaburi and Ratchaburi provinces of Thailand in 2012. The presence of P. falciparum and P. vivax parasites was determined using 18S rRNA qPCR. Gametocytes were also detected by pfs25 / pvs25 qRT-PCRs. RESULTS: A total of 133 individuals were found infected with P. vivax (3.09%), 37 with P. falciparum (0.86%), and 11 with mixed P. vivax/ P. falciparum (0.26%). The clear majority of both P. vivax (91.7%) and P. falciparum (89.8%) infections were not accompanied by any febrile symptoms. Infections with either species were most common in adolescent and adult males. Recent travel to Myanmar was highly associated with P. falciparum (OR = 9.0, P = 0.001) but not P. vivax infections (P = 0.13). A large number of P. vivax (71.5%) and P. falciparum (72.0%) infections were gametocyte positive by pvs25/pfs25 qRT-PCR. Detection of gametocyte-specific pvs25 and pfs25 transcripts was strongly dependent on parasite density. pvs25 transcript numbers, a measure of gametocyte density, were also highly correlated with parasite density (r 2 = 0.82, P < 0.001). CONCLUSIONS: Asymptomatic infections with Plasmodium spp. were common in western Thai communities in 2012. The high prevalence of gametocytes indicates that these infections may contribute substantially to the maintenance of local malaria transmission.

Hepatitis B vaccination for international travelers to Asia.

There is a wide range in prevalence of hepatitis B virus (HBV) infection and HBV immunization programs between different regions. Hepatitis B is a vaccine preventable disease yet is still endemic in the majority of countries in Asia. Despite the decreasing global prevalence of chronic HBV infection, there is still considerable risk of HBV infection among international travelers to high endemic areas. Numbers of international travelers are expected to increase year by year; thus immunization among this cohort is a crucial preventive measure. Among international travelers to Asia, HBV immunization should be recommended for those without previous HBV vaccination who plan to travel to countries with intermediate to high prevalence of HBV, and especially for those individuals at greater risk of HBV infection; including travelers engaging in casual sex, getting a tattoo or piercing, and those having dental surgery or other medical procedures. Longer duration of travel is also associated with a greater risk of HBV infection. Travelers from low HBV prevalence countries, especially those born before implementation of universal HBV vaccination, might benefit from HBV vaccination during long-term traveling to HBV intermediate to high endemic country.