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BackgroundReporting 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. ObjectiveThis 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. MethodsAn 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. ResultsWe 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. ConclusionsThe AMASS is a useful tool to support the generation and sharing of AMR surveillance reports.

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. [ABSTRACT FROM AUTHOR]

The average of travellers is 417 travellers/day (range 79-913 travellers/day). However, the infected cases were found primarily from international inbound travellers and they were quarantined at mandatory state quarantine facilities.[2],[3] Thereafter, lockdown measures, travel restrictions and COVID-19 risks have battered Thailand's tourism industry significantly. Keywords: COVID-19; Sandbox; tourism; Phuket; disease control EN COVID-19 Sandbox tourism Phuket disease control 1 5 5 09/13/23 20230701 NES 230701 Introduction Since the epidemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019,[1] there is an outbreak worldwide. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

Objectives. We examined findings from a randomized controlled intervention trial designed to improve the quality of life of people living with HIV in Thailand. Methods. A total of 507 people living with HIV were recruited from 4 district hospitals in northern and northeastern Thailand and were randomized to an intervention group (n = 260) or a standard care group (n = 247). Computer-assisted personal interviews were administered at baseline and at 6 and 12 months. Results. At baseline, the characteristics of participants in the intervention and standard care conditions were comparable. The mixed-effects models used to assess the impact of the intervention revealed significant improvements in general health (B=2.51; P=.001) and mental health (B=1.57; P=.02) among participants in the intervention condition over 12 months and declines among those in the standard care condition. Conclusions. Our results demonstrate that a behavioral intervention was successful in improving the quality of life of people living with HIV. Such interventions must be performed in a systematic, collaborative manner to ensure their cultural relevance, sustainability, and overall success. (Am J Public Health. 2010; 100:2418-2425. doi: 10.2105/AJPH.2009.185462)

This study determined the presence of anti-SARS-CoV-2 antibodies in 4964 individuals, comprising 300 coronavirus disease-19 (COVID-19) prepandemic serum samples, 142 COVID-19 patients, 2113 individuals at risk due to their occupations, 1856 individuals at risk due to sharing workplaces or communities with COVID-19 patients, and 553 Thai citizens returning after spending extended periods of time in countries with a high disease prevalence. We recruited participants between May 2020 and May 2021, which spanned the first two epidemic waves and part of the third wave of the COVID-19 outbreaks in Thailand. Their sera were tested in a microneutralization and a chemiluminescence immunoassay for IgG against the N protein. Furthermore, we performed an immunofluorescence assay to resolve discordant results between the two assays. None of the prepandemic sera contained anti-SARS-CoV-2 antibodies, while antibodies developed in 88% (15 of 17) of the COVID-19 patients at 8–14 days and in 94–100% of the patients between 15 and 60 days after disease onset. Neutralizing antibodies persisted for at least 8 months, longer than IgG antibodies. Of the 2113 individuals at risk due to their occupation, none of the health providers, airport officers, or public transport drivers were seropositive, while antibodies were present in 0.44% of entertainment workers. Among the 1856 individuals at risk due to sharing workplaces or communities with COVID-19 patients, seropositivity was present in 1.9, 1.5, and 7.5% of the Bangkok residents during the three epidemic waves, respectively, and in 1.3% of the Chiang Mai people during the first epidemic wave. The antibody prevalence varied between 6.5 and 47.0% in 553 Thai people returning from high-risk countries. This serosurveillance study found a low infection rate of SARS-CoV-2 in Thailand before the emergence of the Delta variant in late May 2021. The findings support the Ministry of Public Health's data, which are based on numbers of patients and contact tracing. [ABSTRACT FROM AUTHOR]

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. This study shows that spatially large-scale shifts in temperature can synchronize dengue dynamics across Thailand; however, as average temperatures rise, dengue dynamics may increasingly be dictated by dynamics of immunity, which may in turn mean fewer synchronous outbreaks in the future. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the latest World Health Organization (WHO) recommendation for Dengvaxia implementation, either serological testing or a person's history of prior dengue illness may be used as supporting evidence to identify dengue virus (DENV)-immune individuals eligible for vaccination, in areas with limited capacity for laboratory confirmation. This analysis aimed to estimate the concordance between self-reported dengue illness histories and seropositivity in a prospective cohort study for dengue virus infection in Kamphaeng Phet province, a dengue-endemic area in northern Thailand. The study enrolled 2,076 subjects from 516 multigenerational families, with a median age of 30.6 years (range 0–90 years). Individual and family member dengue illness histories were obtained by questionnaire. Seropositivity was defined based on hemagglutination inhibition (HAI) assays. Overall seropositivity for DENV was 86.5% among those aged 9–45 years, which increased with age. 18.5% of participants reported a history of dengue illness prior to enrollment; 30.1% reported a previous DENV infection in the family, and 40.1% reported DENV infection in either themselves or a family member. Relative to seropositivity by HAI in the vaccine candidate group, the sensitivity and specificity of individual prior dengue illness history were 18.5% and 81.6%, respectively; sensitivity and specificity of reported dengue illness in a family member were 29.8% and 68.0%, and of either the individual or a family member were 40.1% and 60.5%. Notably, 13.4% of individuals reporting prior dengue illness were seronegative. Given the high occurrence of asymptomatic and mild DENV infection, self-reported dengue illness history is poorly sensitive for prior exposure and may misclassify individuals as 'exposed' when they were not. This analysis highlights that a simple, highly sensitive, and highly specific test for determining serostatus prior to Dengvaxia vaccination is urgently needed. Author summary: Dengue is common worldwide and more effective counter-measures are needed. The only DENV vaccine to have achieved licensure is more effective in DENV-immune individuals and is contra-indicated in DENV-naïve individuals due to safety concerns. Self-reports of prior dengue illness have been proposed to serve as a proxy for DENV exposure, due to limited resources for serological testing in many DENV-endemic locales. Here, we compare the concordance of self-reported DENV infection histories relative to serological confirmation of prior DENV exposure and report very low sensitivity and limited specificity, perhaps placing as many as one in seven individuals reporting a history of prior dengue illness at risk for an adverse outcome with receipt of Dengvaxia. We propose that reported histories of dengue illness are not sufficiently accurate to replace serological testing prior to vaccination. [ABSTRACT FROM AUTHOR]

Abstract Background Pre-travel health assessments aim to promote risk reduction through preventive measures and safe behavior, including ensuring travelers are up-to-date with their immunizations. However, studies assessing pre-travel health-seeking practices from a variety of medical and non-medical sources and vaccine uptake prior to travel to both developing and developed countries within the Asia-Pacific region are scarce. Methods Cross-sectional surveys were conducted between July and December 2007 to assess pre-travel health seeking practices, including advice from health professionals, health information from other sources and vaccine uptake, in a sample of travelers departing Sydney and Bangkok airports. A two-stage cluster sampling technique was used to ensure representativeness of travelers and travel destinations. Pre-travel health seeking practices were assessed using a self-administered questionnaire distributed at the check-in queues of departing flights. Logistic regression models were used to identify significant factors associated with seeking pre-travel health advice from a health professional, reported separately for Australian residents, residents of other Western countries and residents of countries in Asia. Results A total of 843 surveys were included in the final sample (Sydney 729, response rate 56%; Bangkok 114, response rate 60%). Overall, pre-travel health information from any source was sought by 415 (49%) respondents with 298 (35%) seeking pre-travel advice from a health professional, the majority through general practice. Receipt of a pre-travel vaccine was reported by 100 (12%) respondents. Significant factors associated with seeking pre-travel health advice from a health professional differed by region of residence. Asian travelers were less likely to report seeking pre-travel health advice and uptake of pre-travel vaccines than Australian or other Western travelers. Migrant Australians were less likely to report seeking pre-travel health advice than Australian-born travelers. Conclusions This study highlights differences in health-seeking practices including the uptake of pre-travel health advice by region of residence and country of birth. There is a public health need to identify strategies targeting these travel groups. This includes the promotion of affordable and accessible travel clinics in low resource countries as traveler numbers increase and travel health promotion targeting migrant groups in high resource countries. General practitioners should play a central role. Determining the most appropriate strategies for increasing pre-travel health preparation, particularly for vaccine preventable diseases in travelers is the next stage in advancing travel medicine research.

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. [ABSTRACT FROM AUTHOR]

Differentiating dengue patients from other acute febrile illness patients is a great challenge among physicians. Several dengue diagnosis methods are recommended by WHO. The application of specific laboratory tests is still limited due to high cost, lack of equipment, and uncertain validity. Therefore, clinical diagnosis remains a common practice especially in resource limited settings. Bayesian networks have been shown to be a useful tool for diagnostic decision support. This study aimed to construct Bayesian network models using basic demographic, clinical, and laboratory profiles of acute febrile illness patients to diagnose dengue. Data of 397 acute undifferentiated febrile illness patients who visited the fever clinic of the Bangkok Hospital for Tropical Diseases, Thailand, were used for model construction and validation. The two best final models were selected: one with and one without NS1 rapid test result. The diagnostic accuracy of the models was compared with that of physicians on the same set of patients. The Bayesian network models provided good diagnostic accuracy of dengue infection, with ROC AUC of 0.80 and 0.75 for models with and without NS1 rapid test result, respectively. The models had approximately 80% specificity and 70% sensitivity, similar to the diagnostic accuracy of the hospital’s fellows in infectious disease. Including information on NS1 rapid test improved the specificity, but reduced the sensitivity, both in model and physician diagnoses. The Bayesian network model developed in this study could be useful to assist physicians in diagnosing dengue, particularly in regions where experienced physicians and laboratory confirmation tests are limited. [ABSTRACT FROM AUTHOR]

A retrospective cohort study was conducted to assess the effect of early (1-4 days after fever onset) and delayed (≥5 days) care-seeking on outcomes of dengue-infected patients. We used data of adult dengue-infected patients treated in Bangkok, Thailand between June 2012 and September 2013. There were 110 patients in the early care-seeking group and 100 in the delayed care-seeking group. There were no deaths. Bleeding complications were not significantly different between the two groups while the latter group had a significantly higher rate of admission compared with the former (98% versus 91.8%, respectively; P = 0.04). Being female was the only factor significantly associated with delayed care-seeking (63.0% versus 45.5%; P = 0.01). [ABSTRACT FROM AUTHOR]

Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidence at short and long time scales will improve public health response to outbreaks. However, scientists and public health officials face many obstacles in trying to create such real-time forecasts of infectious disease incidence. Dengue is a mosquito-borne virus that annually infects over 400 million people worldwide. We developed a real-time forecasting model for dengue hemorrhagic fever in the 77 provinces of Thailand. We created a practical computational infrastructure that generated multi-step predictions of dengue incidence in Thai provinces every two weeks throughout 2014. These predictions show mixed performance across provinces, out-performing seasonal baseline models in over half of provinces at a 1.5 month horizon. Additionally, to assess the degree to which delays in case reporting make long-range prediction a challenging task, we compared the performance of our real-time predictions with predictions made with fully reported data. This paper provides valuable lessons for the implementation of real-time predictions in the context of public health decision making. [ABSTRACT FROM AUTHOR]