Association between Opisthorchis viverrini infection in cats and humans: Non-spatial and spatial analyses.

Cats are recognized as significant reservoir hosts for human opisthorchiasis, particularly in areas with a high prevalence of infection. Despite this, the precise role of cats in the transmission of Opisthorchis viverrini between humans and felines remains unclear. This study investigates the association between these two hosts through both spatial and non-spatial analyses in the endemic Thanya sub-district of Thailand. A total of 105 owned cats were randomly sampled from 15 villages within the sub-district for stool examination. A questionnaire was administered to 66 cat owners to explore the human-pet relationship. Household locations were collected using GPS devices. Non-spatial analyses revealed a positive association between the two hosts (P= 0.011; OR 7, 95% CI: 1.6-30.9), highlighting two independent significant risk factors: cat owners consuming raw fish (P = 0.028; OR = 4.52, 95% CI: 1.25-19.45) and feeding cats raw fish (P = 0.011; OR = 16.41, 95% CI: 2.78-317.04) according to multivariate analysis. Spatial analysis provided further support to the non-spatial findings (p = 0.0123; OR = 3.45, 95% CI = 0.88-13.61). Multiple autologistic regression confirmed two significant risk factors: cat owners consuming raw fish (p = 0.054; OR = 3.37, 95% CI: 0.98-11.59) and feeding cats raw fish (p = 0.014; OR = 7.43, 95% CI: 1.49-37.05). Risk mapping identified the western part of the study site as a hotspot for O. viverrini infection. Hyper-endemic focusing revealed a union of human and cat buffers at 0.46 km², with an overlapping area of 0.22 km² (47.83%). This study underscores the impact of owners' behaviors, specifically consuming and feeding raw fish to cats, on the increased probability of infection in cats. It emphasizes the need for effective opisthorchiasis control through health education targeting cat owners in endemic areas.

Coastal Erosion and Flood Coping Mechanisms in Southern Thailand: A Qualitative Study.

Communities in coastal regions are affected by the impacts of extreme climatic events causing flooding and erosion. Reducing the impacts of flood and erosion in these areas by adopting coping strategies that fortify the resilience of individuals and their localities is desirable. This study used summative content analysis to explore the coping mechanisms of coastal communities before, during, and after various dangers relating to flooding and erosion. The findings from the study show that effective surveillance systems, disaster preparedness, risk mapping, early warning systems, availability of databases and functional command systems, as well as reliable funding are essential to efficiently cope with hazards of coastal flooding and erosion. As flooding and erosion have been predicted to be more severe due to climate change in the coming years, the adoption of effective natural and artificial mechanisms with modern technologies could help coastal regions to be more resilient in coping with the dangers associated with flooding and erosion. Pragmatic policies and programs to this end by actors are critical to averting crises induced by flooding and erosion in coastal areas.

Coastal dynamism in Southern Thailand: An application of the CoastSat toolkit.

In Thailand, 17% of the population lives by the coast, approximately 11 million people. A combination of coastal erosion, sea level rise and coastal land subsidence are critical issues threatening the livelihoods of coastal communities. Thailand has invested a lot of money and installed conservation policies to restore and protect coastal mangroves and realign or replenish their beaches. This study assessed the use of the toolkit Coastsat to digitise a time series of shoreline positions from open access satellite images between 1990 and 2019 along 560 km of coastline in the provinces of Krabi and Nakhon Si Thammarat (NST). Based on these digitised shorelines and the use of the software Digital Shoreline Analysis System (DSAS), it was possible to identify shoreline change, which varied between -66 to +16.4 m/y in the mangroves of NST and -22.2 to +10.6 m/year on its sandy beaches. Shoreline change rates along the Krabi coast varied -34.5 to +21.7 m/year in the mangroves and -4.1 to +4 m/year on sandy beaches. Analysis of the spatial and temporal variations of the shoreline position during the survey period reveals a linkage between extreme weather conditions and coastal erosion along the NST coast while that linkage is less clear along the Krabi coast. CoastSat delivers crucial and accurate time series shoreline data over extensive areas that are vital to coastal managers and researchers in a completely remote manner, which is key with the presence of COVID-19 travel bans.

Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand.

Dengue is the most widespread mosquito-borne viral disease of man and spreading at an alarming rate. Socio-economic inequality has long been thought to contribute to providing an environment for viral propagation. However, identifying socio-economic (SE) risk factors is confounded by intra-urban daily human mobility, with virus being ferried across cities. This study aimed to identify SE variables associated with dengue at a subdistrict level in Bangkok, analyse how they explain observed dengue hotspots and assess the impact of mobility networks on such associations. Using meteorological, dengue case, national statistics, and transport databases from the Bangkok authorities, we applied statistical association and spatial analyses to identify SE variables associated with dengue and spatial hotspots and the extent to which incorporating transport data impacts the observed associations. We identified three SE risk factors at the subdistrict level: lack of education, % of houses being cement/brick, and number of houses as being associated with increased risk of dengue. Spatial hotspots of dengue were found to occur consistently in the centre of the city, but which did not entirely have the socio-economic risk factor characteristics. Incorporation of the intra-urban transport network, however, much improved the overall statistical association of the socio-economic variables with dengue incidence and reconciled the incongruous difference between the spatial hotspots and the SE risk factors. Our study suggests that incorporating transport networks enables a more real-world analysis within urban areas and should enable improvements in the identification of risk factors.

Socio-Economic Resilience to Floods in Coastal Areas of Thailand.

Krabi and Nakhon Si Thammarat are two coastal provinces in Thailand facing substantial threats from climate change induced hydrometeorological hazards, including enhanced coastal erosion and flooding. Human populations and livelihoods in these coastal provinces are at greater risk than those in inland provinces. However, little is known about the communities' resilience and coping capacities regarding hydrometeorological hazards of varying magnitudes. The study conducted a quantitative socio-economic assessment of how people in Krabi and Nakhon Si Thammarat provinces manage and respond to hydrometeorological hazards, examining their resilience and coping capacities. This was a cross-sectional study based on secondary data collection on the social and economic dimensions of resilience, and a review of literature on coping mechanisms to hydrometeorological hazards within the study area. Measuring and mapping socio-economic resilience was based on the available data gathered from the social and economic dimensions, with existing or standard indicators on exposure and vulnerability applied uniformly across subdistricts. A combination of social and economic dimensions produced novel socio-economic resilience index scores by subdistrict, which were mapped accordingly for the two coastal provinces. The study also derived a coping capacity index scores by combining availability of skills or soft capacity and availability of structural resources or hard coping capacity. Socio-economic resilience index scores varied greatly amongst subdistricts. Combining the soft and hard coping capacities, the average score across districts in both provinces was 3 out of a possible 4, meaning that most of the districts were largely resilient. However, variations also existed by subdistrict. Few subdistricts in both Krabi and Nakhon Si Thammarat provinces had low coping capacity index scores between 1 and 2 out of 4. District averages of socio-economic resilience scores mask the variations at subdistrict level. More studies with rigorous methodologies at village or neighborhood level is needed to obtain a nuanced understanding of community resilience to hydrometeorological hazards.

Climate variability and dengue hemorrhagic fever in Southeast Sulawesi Province, Indonesia.

To determine the association of climatic factors and dengue hemorrhagic fever and to develop the prediction approach of future dengue transmission. The study used totally monthly dengue hemorrhagic fever cases at Health Office Kendari, Southeast Sulawesi, Indonesia. Monthly meteorological data, consisting of temperature, rainfall, and humidity, was obtained from the Meteorology, Climatology and Geophysics Agency in Kendari district. All data analysis, including Spearman and Poisson distribution, was carried out in R Studio (version 3.3.2) utilizing the R statistical language version 2.15. The highest rate of dengue hemorrhagic fever cases was found in January, February, and March. Temperature averages at lag 2 (p = 0.53, p < 0.0001), lag 3 (p = 0.59, p < 0.0001), and lag 4 (p = 0.41, p < 0.01)) correlated with the incident rate of DHF. The average temperature at lag 2 was found to have a positive impact on the incidence of DHF by Poisson function. This study provides preliminary evidence of the influence of climatic factors on dengue transmission.

An information value based analysis of physical and climatic factors affecting dengue fever and dengue haemorrhagic fever incidence.

BACKGROUND: Vector-borne diseases are the most dreaded worldwide health problems. Although many campaigns against it have been conducted, Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) are still the major health problems of Thailand. The reported number of dengue incidences in 1998 for the Thailand was 129,954, of which Sukhothai province alone reported alarming number of 682. It was the second largest epidemic outbreak of dengue after 1987. Government arranges the remedial facilities as and when dengue is reported. But, the best way to control is to prevent it from happening. This will be possible only when knowledge about the relationship of DF/DHF with climatic and physio-environmental agents is discovered. This paper explores empirical relationship of climatic factors rainfall, temperature and humidity with the DF/DHF incidences using multivariate regression analysis. Also, a GIS based methodology is proposed in this paper to explore the influence of physio-environmental factors on dengue incidences. Remotely sensed data provided important data about physical environment and have been used for many vector borne diseases. Information Values (IV) method was utilised to derive influence of various factors in the quantitative terms. Researchers have not applied this type of analysis for dengue earlier. Sukhothai province was selected for the case study as it had high number of dengue cases in 1998 and also due to its diverse physical setting with variety of land use/land cover types. RESULTS: Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF/DHF. A composite analysis of these three factors with dengue incidences was carried out using multivariate regression analysis. Three empirical models ER-1, ER-2 and ER-3 were evaluated. It was found that these three factors have significant relation with DF/DHF incidences and can be related to the forecast expected number of dengue cases. The results have shown significantly high coefficient of determination if applied only for the rainy season using empirical relation-2 (ER-2). These results have shown further improvement once a concept of time lag of one month was applied using the ER-3 empirical relation. ER-3 model is most suitable for the Sukhothai province in predicting possible dengue incidence with 0.81 coefficient of determination. The spatial statistical relationship of various land use/land cover classes with dengue-affected areas was quantified in the form of information value received from GIS analysis. The highest information value was obtained for the Built-up area. This indicated that Built-up area has the maximum influence on the incidence of dengue. The other classes showing negative values indicate lesser influence on dengue epidemics. Agricultural areas have yielded moderate risk areas based on their medium high information values. Water bodies have shown significant information value for DF/DHF only in one district. Interestingly, forest had shown no influence on DF/DHF. CONCLUSION: This paper explores the potential of remotely sensed data and GIS technology to analyze the spatial factors affecting DF/DHF epidemic. Three empirical models were evaluated. It was found that Empirical Relatrion-3 (ER-3) has yielded very high coefficient of determination to forecast the number of DF/DHF incidence. An analysis of physio-environmental factors such as land use/land cover types with dengue incidence was carried out. Influence of these factors was obtained in quantitative terms using Information Value method in the GIS environment. It was found that built-up areas have highest influence and constitute the highest risk zones. Forest areas have no influence on DF/DHF epidemic. Agricultural areas have moderate risk in DF/DHF incidences. Finally the dengue risk map of the Sukhothai province was developed using Information Value method. Dengue risk map can be used by the Public Health Department as a base map for applying preventive measures to control the dengue outbreak. Public Health Department can initiate their effort once the ER-3 predicts a possibility of significant high dengue incidence. This will help in focussing the preventive measures being applied on priority in very high and high-risk zones and help in saving time and money.