Background: Leptospirosis, a disease caused by Leptospira species, a spirochaete bacterium that can develop in an appropriate environment and/or grow in human and/or animal hosts, is a serious problem for the Ministry of Public Health, Thailand. Objective: To investigate people's perceptions and behavioral risks regarding leptospirosis infection. Methods: The cross-sectional descriptive study collected data in May, 2013. Data on individuals' perceptions and risky behaviors concerning leptospirosis were collected from 104 completed questionnaires. Results: Regarding perceptions of leptospirosis, we found them to be at a high level (97.1%) and risky behaviors regarding leptospirosis were reported at a moderate level (74.0%). The study found no correlation between perceptions and risky behaviors regarding leptospirosis (r 0.186, p-value 0.059). Conclusion: This study suggest that people in these areas have good knowledge about leptospirosis. However, some people have risky behavior associated with leptospirosis. Thus, a behavioral change campaign should be promoted to encourage people awareness of the dangers of such behavior.

Abstract Background Melioidosis is an infectious disease commonly found in Thailand. This infectious disease is caused by Burkholderia pseudomallei in soil. This study aims to analyze the association between spatial soil factors and B. pseudomallei detection, as well as to map the probability of B. pseudomallei contamination based on indicator kriging in paddy soil. Methods Seventy-eight soil samples were collected randomly on 22 April 2018 in various paddy fields. Oxidase, Gram staining and monoclonal antibody-based latex agglutination assays were performed to confirm the presence of B. pseudomallei in soil samples. The association between B. pseudomallei detection and spatial soil factors including soil temperature, soil pH, soil texture and soil drainage were analyzed by the Mann–Whitney U test and χ2 test. Subsequently, a semivariogram model and indicator kriging were used to map the probability of B. pseudomallei contamination. Results Of the 78 samples, B. pseudomallei was detected in 32 (41.03%). The presence or absence of B. pseudomallei was not significantly associated with spatial soil factors. The semivariogram model showed that the lag distance between positive B. pseudomallei samples was 90.51 m. Conclusion The empirical semivariogram and indicator kriging are an alternative option for predicting the spatial distribution of B. pseudomallei in soil.

Melioidosis is a public health problem in the tropical regions, occurring to meteorological variability. For 10 years of melioidosis outbreaks, we create probability maps of melioidosis distribution during 2009–2018 and determine the association with meteorological factors. The monthly average rainfall and incidence of melioidosis were high from July to September but they not significantly associated (P = 0.576). However, the monthly maximum and minimum temperature were significantly associated with melioidosis incidence (P = 0.002 and P = 0.029, respectively). We estimated the spatial distribution of rainfall and maximum and minimum temperature using the Co-Kriging interpolation method which found that the spatial distribution of the melioidosis incidence was significantly associated with rainfall in 2009, 2010, and 2015; with the maximum temperature in 2009, 2010, 2011, 2013, and 2015; and with the minimum temperature in 2010, 2011, and 2015. Our finding approach may support information and classify a pattern for melioidosis distribution. Keywords: Incidence, Melioidosis, Meteorological factors

Widespread use of pesticides in Thai agriculture has led to serious adverse health impacts on users. This study developed a GIS database using the QGIS tool to investigate insecticide usage and toxicity tofarmers in Ubon RatchathaniProvince in northeastern Thailand. Primary data collection involved recording exact locations of residential houses using geographic positioning system (GPS). Secondary dataincluding transport routes, natural and environmental resources, and records of rainfall and ground temperatureswere also collected. The data were integrated asGIS mapping data. Eighteen farmers participated in the study and submitted themselves tomeasurements of cholinesterase (ChE) levels and 2 blood sample collections for comparison with standard ChE levels. Results revealed the GIS database to bean effective tool to capture, store, manage, search, analyze, and represent spatial data and correlate them with insecticide usage. The GIS databaserevealed that ChE levels of volunteers for pre-post-exposure were within normal ranges. Liver enzymes (AST and ALT) were also within normal ranges. Further study should broaden collection of essential data including demographic information and basic knowledge and perceptions of self-protection regarding insecticides. Further evaluation and refining of the GIS databaseapproach arerecommended to improve itseffectiveness as an analytical tool to enhance safe use of pesticides.

Melioidosis, a bacterial, infectious disease contracted from contaminated soil or water, is a public health problem identified in tropical regions and endemic several regions of Thailand. Surveillance and prevention are important for determining its distribution patterns and mapping its risk, which have been analysed in the present study. Case reports in Thailand were collected from 1 January 2016 to 31 December 2020. Spatial autocorrelation was analyzed using Moran’s I and univariate local Moran’s I. Spatial point data of melioidosis incidence were calculated, with riskmapping interpolation performed by Kriging. It was highest in 2016, at 32.37 cases per 100,000 people, and lowest in 2020, at 10.83 cases per 100,000 people. General observations revealed that its incidence decreased slightly from 2016 to 2018 and drastically in 2019 and 2020. The Moran’s I values for melioidosis incidence exhibited a random spatial pattern in 2016 and clustered distribution from 2017 to 2020. The risk and variance maps show interval values. These findings may contribute to the monitoring and surveillance of melioidosis outbreaks.