Anuwat Wiratsudakul

Detection and phylogenetic characterization of hepatitis E virus genotype 3 in a captive wild boar in Thailand.

Hepatitis E virus (HEV) was studied in different types of wild boar captive settings in Thailand, including a wildlife breeding research station, zoo, and commercial wild boar farm, which were located in different locations of Thailand. Fifty-one fecal samples were collected and screened for HEV RNA and then analyzed. One sample obtained from a wildlife breeding research station in Ratchaburi province was HEV positive. Phylogenetic characterization revealed that the virus was HEV genotype 3 and belongs to subgroup 3e, which is closely related to HEV recently isolated from domestic pigs and humans in the country. It was hypothesized that HEV is shared among wild boars, domestic pigs, and humans in Thailand.

Evaluation of loop-mediated isothermal amplification method (LAMP) for pathogenic Leptospira spp. detection with leptospires isolation and real-time PCR

Leptospirosis has been one of the worldwide zoonotic diseases caused by pathogenic Leptospira spp. Many molecular techniques have consecutively been developed to detect such pathogen including loop–mediated isothermal amplification method (LAMP). The objectives of this study were to evaluate the diagnostic accuracy of LAMP assay and real-time PCR using bacterial culture as the gold standard and to assess the agreement among these three tests using Cohen’s kappa statistics. In total, 533 urine samples were collected from 266 beef and 267 dairy cattle reared in central region of Thailand. Sensitivity and specificity of LAMP were 96.8% (95% CI 81.5–99.8) and 97.0% (95% CI 94.9–98.2), respectively. The accuracy of LAMP (97.0%) was significantly higher than that of real-time PCR (91.9%) at 95% CI. With Cohen’s kappa statistics, culture method and LAMP were substantially agreed with each other (77.4%), whereas real-time PCR only moderately agreed with culture (47.7%) and LAMP (45.3%), respectively. Consequently, LAMP was more effective than real-time PCR in detecting Leptospira spp. in the urine of cattle. Besides, LAMP had less cost and was simpler than real-time PCR. Thus, LAMP was an excellent alternative for routine surveillance of leptospirosis in cattle.

Satellite Tracking on the Flyways of Brown-Headed Gulls and Their Potential Role in the Spread of Highly Pathogenic Avian Influenza H5N1 Virus

Brown-headed gulls (Larus brunnicephalus), winter visitors of Thailand, were tracked by satellite telemetry during 2008–2011 for investigating their roles in the highly pathogenic avian influenza (HPAI) H5N1 virus spread. Eight gulls negative for influenza virus infection were marked with solar-powered satellite platform transmitters at Bang Poo study site in Samut Prakarn province, Thailand; their movements were monitored by the Argos satellite tracking system, and locations were mapped. Five gulls completed their migratory cycles, which spanned 7 countries (China, Bangladesh, India, Myanmar, Thailand, Cambodia, and Vietnam) affected by the HPAI H5N1 virus. Gulls migrated from their breeding grounds in China to stay overwinter in Thailand and Cambodia; while Bangladesh, India, Myanmar, and Vietnam were the places of stopovers during migration. Gulls traveled an average distance of about 2400 km between Thailand and China and spent 1–2 weeks on migration. Although AI surveillance among gulls was conducted at the study site, no AI virus was isolated and no H5N1 viral genome or specific antibody was detected in the 75 gulls tested, but 6.6% of blood samples were positive for pan-influenza A antibody. No AI outbreaks were reported in areas along flyways of gulls in Thailand during the study period. Distance and duration of migration, tolerability of the captive gulls to survive the HPAI H5N1 virus challenge and days at viral shedding after the virus challenging suggested that the Brown-headed gull could be a potential species for AI spread, especially among Southeast Asian countries, the epicenter of H5N1 AI outbreak.

Dynamics of Zika virus outbreaks: an overview of mathematical modeling approaches

Background The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics. Survey Methodology In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms “dynamics,” “mathematical model,” “modeling,” and “vector-borne” together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were “compartmental,” “spatial,” “metapopulation,” “network,” “individual-based,” “agent-based” AND “Zika.” All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases. Results We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks. Discussion Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.

Investigation on predominant Leptospira serovars and its distribution in humans and livestock in Thailand, 2010-2015

Background Leptospirosis is a worldwide zoonotic bacterial disease caused by infection with leptospires. Leptospirosis in humans and livestock is an endemic and epidemic disease in Thailand. Livestock may act as reservoirs for leptospires and source for human infection. Methodology/Principal findings Data on leptospirosis infection in humans and livestock (Buffaloes, Cattle, and Pigs) species during 2010 to 2015 were analyzed. Serum samples were examined using Microscopic Agglutination Test (MAT) to identify antibodies against Leptospira serovars using a cut-off titer ≥ 1:100. The seroprevalence was 23.7% in humans, 24.8% in buffaloes, 28.1% in cattle, and 11.3% in pigs. Region specific prevalence among humans and livestock was found in a wide range. The most predominant serovars were Shermani, followed by Bratislava, Panama, and Sejroe in human, Shermani, Ranarum, and Tarassovi in buffaloes, and Shermani and Ranarum in cattle and pigs. Equally highest MAT titers against multiple serovars per one sample were found mainly in buffaloes and cattle showing equally titers against Ranarum and Shermani. The correlations of distribution of serovars across Thailand’s regions were found to be similar in pattern for cattle but not for buffaloes. In humans, the serovar distribution in the south differed from other regions. By logistic regression, the results indicated that livestock is more susceptible to infection by serovar Shermani when compared to humans. Conclusions/Significance This study gives a detailed picture of the predominance of Leptospira serovars in relation to region, humans and typical livestock. The broad spatial distribution of seroprevalence was analyzed across and within species as well as regions in Thailand. Our finding may guide public health policy makers to implement appropriate control measures and help to reduce the impact of leptospirosis in Thailand.

A traditional cattle trade network in Tak province, Thailand and its potential in the spread of infectious diseases

Cattle in Thailand are traded by cattle dealers in the cattle markets through informal negotiation processes. The present study aimed to explore a traditional cattle trade network and its potential in the spread of infectious diseases. A cross-sectional questionnaire-based survey was conducted in cattle markets located in Tak province, Thailand. A static weighted directed one-mode network was constructed and geographic locations of sources and destinations of animals were plotted. A total of 210 cattle dealers responded to the questionnaires. The cattle trade network contained 112 sources and destinations of animals and 168 trading activities. The highest generalised weighed in- and out-degree centralities and k-core were observed in the same cattle market at 53.4, 106.7 and 4, respectively. Spatially, cattle dealers could transport animals as far as 774.4 km from the original markets and natural barriers such as mountainous areas tended to dictate the trading routes, premises of animals and magnitude of trading activities. Traditional cattle trading patterns described in this study pose some important challenges to veterinary authorities in tailoring effective prevention and control measures for confronting infectious diseases. This study quantitatively analysed the traffic within a network of cattle trade and found a wide range of spatial movements and a high connectivity of markets to sources and destinations of animals, which may accommodate the spread of infectious diseases within the network. This peace time network analysis could help related authorities to better focus on possible infected premises and to immediately respond once an epidemic occurs.

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.

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate

BackgroundMathematical modeling has become a tool used to address many emerging diseases. One of the most basic and popular modeling frameworks is the compartmental model. Unfortunately, most of the available compartmental models developed for Zika virus (ZIKV) transmission were designed to describe and reconstruct only past, short-time ZIKV outbreaks in which the effects of seasonal change to entomological parameters can be ignored. To make an accurate long-term prediction of ZIKV transmission, the inclusion of seasonal effects into an epidemic model is unavoidable.MethodsWe developed a vector-borne compartmental model to analyze the spread of the ZIKV during the 2015–2016 outbreaks in Bahia, Brazil and to investigate the impact of two vector control strategies, namely, reducing mosquito biting rates and reducing mosquito population size. The model considered the influences of seasonal change on the ZIKV transmission dynamics via the time-varying mosquito biting rate. The model was also validated by comparing the model prediction with reported data that were not used to calibrate the model.ResultsWe found that the model can give a very good fit between the simulation results and the reported Zika cases in Bahia (R-square = 0.9989). At the end of 2016, the total number of ZIKV infected people was predicted to be 1.2087 million. The model also predicted that there would not be a large outbreak from May 2016 to December 2016 due to the decrease of the susceptible pool. Implementing disease mitigation by reducing the mosquito biting rates was found to be more effective than reducing the mosquito population size. Finally, the correlation between the time series of estimated mosquito biting rates and the average temperature was also suggested.ConclusionsThe proposed ZIKV transmission model together with the estimated weekly biting rates can reconstruct the past long-time multi-peak ZIKV outbreaks in Bahia.

A nationwide survey of pathogenic leptospires in urine of cattle and buffaloes by Loop-mediated isothermal amplification (LAMP) method in Thailand, 2011–2013

Leptospirosis is a worldwide distributed zoonosis which has long been endemic in Thailand. Cattle and buffaloes are important livestock species that live in close contact with humans, especially in rural areas. These animals may, therefore, act as long-term carriers of leptospirosis for humans and other livestock species. The present study employed loop-mediated isothermal amplification (LAMP) method to detect pathogenic leptospiral 16S rDNA in the urine of cattle and buffaloes for assessing associations between uroprevalence and species, sex, age and spatial distribution. A total of 3,657 urine samples were collected for laboratory diagnosis, and 312 of which turned positive to the test (true prevalence 5.90%; 95% CI 4.98–6.91). The highest true uroprevalence was found in lower northern region at 19.80% (95% CI 15.83–24.32) followed by upper and lower northeastern regions at 15.22% and 6.25%, respectively. However, the highest true uroprevalence in beef cattle, the majority of cattle in Thailand, was recorded in northeastern region which is the endemic area of human leptospirosis. The uroprevalence was not statistically different among species and types of examined animals. Male animals were over twice more likely to be infected compared to females. Excluding animals younger than one year of age due to small sample size, the uroprevalence upraised with increasing age. A collaborative investigation between veterinary and public health sectors is required to holistically explore the link between leptospirosis in humans and livestock, especially in high prevalent areas.

The implementation of cattle market closure strategies to mitigate the foot-and-mouth disease epidemics: A contact modeling approach

Foot-and-mouth disease (FMD) is one of the most endemic diseases in livestock worldwide. The disease occurrence generally results in a huge economic impact. The virus may distribute across countries or even continents along the contact network of animal movements. The present study, therefore, aimed to explore a cattle movement network originated in Tak, a Thailand-Myanmar bordered province and to demonstrate how FMDV spread among the nodes of market, source and destination. Subsequently, we examined the effectiveness of market closure intervention. The market-market (M-M) network was constructed to highlight the inter-market connections and the FMDV was modeled to spread along the trade chain. Four market closure scenarios based on rapidness and duration of implementation were examined. Our results indicate that two of the three major markets located in the province were highly connected and a strongly connected component was identified. The intra-provincial animal movements, which were currently overlooked, should be moved into sights as most of the high-risk sources for FMD epidemics were recognized in a close proximity to the cattle markets. Simultaneously, remote destinations across the country were identified. The inter-provincial animal movement control must be strengthened once FMD outbreak is notified. Based on our simulations, closing markets with low inter-market connectivity may not prevent the spread of FMDV. A selective market closure strategy targeting highly connected markets together with cattle trader tracking system was an alternative approach. However, socio-economic consequences regarding this intervention must be considered.