Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data.

Melioidosis is an endemic infectious disease caused by Burkholderia pseudomallei bacteria, which contaminates soil and water. To better understand the environmental changes that have contributed to melioidosis outbreaks, this study used spatiotemporal analyses to clarify the distribution pattern of melioidosis and the relationship between melioidosis morbidity rate and local environmental indicators (land surface temperature, normalised difference vegetation index, normalised difference water index) and rainfall. A retrospective study was conducted from January 2013 to December 2022, covering data from 219 sub-districts in Northeast Thailand, with each exhibiting a varying morbidity rate of melioidosis on a monthly basis. Spatial autocorrelation was determined using local Moran's I, and the relationship between the melioidosis morbidity rate and the environmental indicators was evaluated using a geographically weighted Poisson regression. The results revealed clustered spatiotemporal patterns of melioidosis morbidity rate across sub-districts, with hotspots predominantly observed in the northern region. Furthermore, we observed a range of coefficients for the environmental indicators, varying from negative to positive, which provided insights into their relative contributions to melioidosis in each local area and month. These findings highlight the presence of spatial heterogeneity driven by environmental indicators and underscore the importance of public health offices implementing targeted monitoring and surveillance strategies for melioidosis in different locations.

Spatiotemporal distribution and geostatistically interpolated mapping of the melioidosis risk in an endemic zone in Thailand.

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.

The viability of Leptospira is related to physicochemical properties of the surface water surrounding an agricultural area and HemO and LipL32 gene expression in response to iron in water.

BACKGROUND: The pathogenic Leptospira can survive and contaminate surface water based on physicochemical factors. This study aimed to determine how the physicochemical properties of water sources influence the growth and effect of iron on the gene expression of Leptospira spp. P47. METHODS: Surface water samples (n=55) were collected and used for Leptospira spp. P47 cultivation. Physicochemical factors, including iron, calcium, magnesium and pH, were analyzed. The association between Leptospira spp. P47 viability at days 5, 10 and 15 with the physicochemical factors were analyzed. In addition, this bacterium was cultured in six selected water samples. The effect of iron in water on HemO and LipL32 gene expression was determined by relative quantification real-time PCR. RESULTS: Leptospira viability at day 5 was not significantly correlated with physicochemical factors, while Leptospira viability at day 10 was associated with both pH and iron. The Leptospira viability rate at day 15 had a significantly positive association with pH and iron and a negative association with calcium. HemO expression was significantly increased, mostly in selected water samples and under iron-depleted conditions. Conversely, LipL32 expression was significantly decreased in all water samples. CONCLUSIONS: Physicochemical factors in natural surface waters are key factors for bacterial survival in the environment, which may increase the chance of Leptospira infection in humans.

Prevention and control of leptospirosis in people and surveillance of the pathogenic Leptospira in rats and in surface water found at villages.

BACKGROUND: Leptospirosis is a major public health problem in Thailand. This disease is caused by a Leptospira infection. Leptospira is found in rats and other animals that can contaminate soil and water resources. This research aimed to (1) study the perceptions and preventive measures taken to control leptospirosis among local populations and (2) to detect Leptospira in rats and natural surface water. METHODS: This cross-sectional study was performed in both villages with and without case histories of leptospirosis. The research procedures were divided into 2 parts. First, the perceptions and preventive measures for leptospirosis used data from 108 sampled subjects that were recruited in May 2015. Second, the rats and surface water samples were collected. DNA was extracted from collected samples and then specific genes specific to Leptospira were detected using PCR technique. RESULTS: The awareness of leptospirosis of samples in two villages was at high level with the same percentage being at 91.6%. However, the preventive behaviors to leptospirosis of participants from both villages were found to be at only the moderate level. Leptospira detection in rats and surface water used a PCR technique. There was no Leptospira found in any of the 270 rat samples and 100 surface water samples taken from both villages. CONCLUSION: Regardless, perception and preventive behaviors for dealing with leptospirosis should be continuously encouraged even when its presence is not detected. Clearly, people have to practice good behaviors for the prevention of this pathogen to be safe.

Perceptions and risky behaviors associated with Leptospirosis in an endemic area in a village of Ubon Ratchathani Province, Thailand.

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.

Detection of Leptospira in Rats Trapped from Households in Phraroj Village, Muang Sam Sip District, Ubon Ratchathani Province Using Polymerase Chain Reaction Technique.

BACKGROUND: Leptospirosis, a zoonotic disease caused by Leptospira, has been a health problem in Thailand for several years. Rats are a major reservoir host for Leptospira, and the people who are usually in contact with environments contaminated with rats' urine are at risk of infection. The prevalence rate of Leptospira infection in rats may result in the spread of leptospirosis in humans. OBJECTIVE: This study aimed to determine the prevalence rate ofLeptospira infection in a total of 28 rats and develop a spatial database for leptospirosis surveillance in Phraroj village in Muang Sam Sip District, Ubon Ratchathani Province. MATERIAL AND METHOD: The positions of the households and the rat-trapping area were tagged by using of a Global Positioning System (GPS). DNA samples were isolated fromn rats' kidneys. The polymerase chain reaction (PCR) technique was used for the detection of 16s rRNA and LipL32 genes specific to genus and pathogenic Leptospira respectively. All of the data were used to develop a geo-data base by the connection of spatial data and attributed data to be used for query and retrieval. RESULTS: A map of the positions of the households and the rat-trapping area in Phraroj village was created. No rats were found to be infected in the Leptospira survey. CONCLUSION: There was no trapped rat infected with Leptospira in Phraroj village. This result may involve unreported leptospirosis in patients in this village. The Leptospira survey in rats and the geo-database will be used as a primary resource to support and make decisions about surveillance, prevention, and control of leptospirosis.

Survey of pathogenic Leptospira in rats by polymerase chain reaction in Sisaket Province.

BACKGROUND: Leptospirosis, a zoonotic disease caused by Leptospira, has been a health problem in Thailand for several years. It can be transmitted to humans via rats' urine, which may contaminate the environment. The prevalence rate of Leptospira infection in rats may result in the spread of leptospirosis in humans. OBJECTIVE: The present study aimed to determine the prevalence rate of Leptospira infection in a total of 87 rats from areas where patients with leptospirosis had been reported compared to areas with no reports of leptospirosis in Sisaket Province. MATERIAL AND METHOD: DNA samples were isolated from rats' kidneys. The polymerase chain reaction (PCR) technique was used for the detection of 16s rRNA and LipL32 genes specific to genus and pathogenic Leptospira, respectively. RESULTS: In areas where patients with leptospirosis had been reported, 8.7% (4/46) of rats were infected with pathogenic Leptospira; no infected rats were found in non-endemic areas. CONCLUSION: This indicated the prevalence rate of Leptospira infection in rats between endemic and non-endemic areas of human leptospirosis. The prevalence rate of Leptospira infection in rats may result in the spread of leptospirosis to humans. These results may be of benefit in the prevention and/or control of the spread of leptospirosis in humans due to Leptospira-infected rats.

Geo-database use to promote dengue infection prevention and control.

Dengue infection (DI) is a major health problem in Thailand and is especially prevalent in Ubon Ratchathani Province. The objectives of the project were: (1) to develop a geo-database system for DI prevention and control, (2) to perform an Aedes aegypti larval vector survey for DI prevention and control in Ubon Ratchathani Province, (3) to study the behavior and perceptions regarding DI prevention among the target population in Ubon Ratchathani Province. Ten villages with high incidences of DI over a 3 year period from 2005 to 2007 were selected. The survey was divided into 2 periods, pre-outbreak period (February-April 2008) and outbreak period (June-August 2008). The data were collected in April and June 2008. The households in each village were purposively sampled. Water containers inside and outside of the houses were surveyed using the World Health Organization's house index (HI), container index (CI), and Breteau index (BI). The location of each household was recorded using the global positioning system (GPS). Data regarding people's perceptions and behaviors concerning DI prevention were collected during interviews of 383 families in Mach 2008. A database for DI was developed using ArcView version 9.2. The results showed during the pre-outbreak period, Non Jig, Non Sawang, and Huai Teeneu villages had the highest risk level (BI > or =50). During the outbreak period, Non Jig and Huai Teeneu village had the highest risk level (BI > or =50). Results regarding DI perceptions showed the target population had high levels of DI perceptions. DI preventive behavior was found in 50.9%.