The 3-5year epidemic cycle of dengue fever in Thailand makes it a major re-emerging public health problem resulting in being a burden in endemic areas. Although the Thai Ministry of Public Health adopted the WHO dengue control strategy, all dengue virus serotypes continue to circulate. Health officers and village health volunteers implement some intervention options but there is a need to ascertain most appropriate (or a combination of) interventions regarding the environment and contextual factors that may undermine the effectiveness of such interventions. This study aims to understand the dengue-climate relationship patterns at the district level in the southern region of Thailand from 2002 to 2018 by examining the statistical association between dengue incidence rate and eight environmental patterns, testing the hypothesis of equal incidence of these. Data on environmental variables and dengue reported cases in Nakhon Si Thammarat province situated in the south of Thailand from 2002 to 2018 were analysed to (1) detect the environmental factors that affect the risk of dengue infectious disease; to (2) determine if disease risk is increasing or decreasing over time; and to (3) identify the high-risk district areas for dengue cases that need to be targeted for interventions. To identify the predictors that have a high and significant impact on reported dengue infection, three steps of analysis were used. First, we used Partial Least Squares (PLS) Regression and Poisson Regression, a variant of the Generalized Linear Model (GLM). Negative co-efficient in correspondence with the PLS components suggests that sea-level pressure, wind speed, and pan evaporation are associated with dengue occurrence rate, while other variables were positively associated. Using the Akaike information criterion in the stepwise GLM, the filtered predictors were temperature, precipitation, cloudiness, and sea level pressure with the standardized coefficients showing that the most influential variable is cloud cover (three times more than temperature and precipitation). Also, dengue occurrence showed a constant negative response to the average increase in sea-level pressure values. In southern Thailand, the predictors that have been locally determined to drive dengue occurrence are temperature, rainfall, cloud cover, and sea-level pressure. These explanatory variables should have important future implications for epidemiological studies of mosquito-borne diseases, particularly at the district level. Predictive indicators guide effective and dynamic risk assessments, targeting pre-emptive interventions.

Clean water and sanitation are essential for human development. Governments, international and national aid organizations have implemented water, sanitation, and hygiene (WASH) projects worldwide, notably in low- and middle-income countries. However, the majority of such projects experience failure. As a result, 2.4 billion people worldwide are deprived of improved WASH services. Research revealing how WASH projects can be sustained and which factors need to be considered is crucial. Despite the gap and its importance, existing studies on the sustainability assessment of WASH projects are limited. This study attempted to assess and compare the sustainability of WASH projects in Myanmar that used the Community Led Total Sanitation (CLTS) and Participatory Hygiene and Sanitation Transformation (PHAST) approaches with the “Sustainability Check” developed by The United Nations Children’s Fund (UNICEF). This research also evaluated the extent to which WASH projects contributed to the Myanmar National WASH Strategy. The study results show that both CLTS and PHAST project operations fully met the sustainability standards regarding accessibility and intra-village equity. Other sustainability indicators, such as water quality, use of sanitation facilities, and handwashing facilities, were at or above 85% and had already met the 2025 national targets. In contrast, handwashing practices have reached the 2030 national targets. The findings revealed that technical factors, institutional factors (at the community level), social, financial, and sanitation factors contributed to WASH project sustainability. The results also highlight the need for strengthening collaboration with local government to ensure that communities receive post-implementation support from local authorities, to encourage community participation and foster sense of ownership, to empower community-based bodies for O&M and monitoring of water and sanitation facilities, to integrate appropriate behavioral change activities, and to align with the National WASH Strategy. This study would be beneficial for WASH practitioners to ensure the inclusion of factors that support sustainability in the execution of future WASH projects. Graphical abstract

This study aims to analyse the potential environmental impact of natural rubber (NR) condoms over its entire life cycle. The environmental performance of the production process of NR condoms is also compared to that of synthetic polyisoprene (PI) condoms. Options to reduce the environmental impact of condom production are proposed and evaluated. The potential environmental impacts are quantified by life cycle assessment (LCA). The study takes a cradle-to-grave approach, and considers six phases: 1) fresh latex production, 2) concentrated latex production, 3) condom production, 4) condom use, 5) condom transportation, and 6) condom disposal. The comparative analysis of NR and PI condom production takes a gate-to-gate scope. The functional unit is one gross condom. The results indicate that the condom production phase has the largest share (34–73%) in the environmental impact during the life cycle of NR condoms, followed by the disposal phase (20–60%). Comparing the production of NR and PI condoms reveals that the production of PI condoms results in a 1.5–2.5 times higher environmental impacts than the NR condom production, due to higher electricity consumption, especially for the compounding, dipping, and leaching processes. Reduction of electricity use is a key measure to reduce the environmental impact. Combining natural gas with electricity for the dipping process is a promising option to reduce the electricity use; it results in ~10–17% reduction in environmental impacts.

The tropical climate of Thailand encourages very high mosquito densities in certain areas and is ideal for dengue transmission, especially in the southern region where the province Nakhon Si Thammarat is located. It has the longest dengue fever transmission duration that is affected by some important climate predictors, such as rainfall, number of rainy days, temperature and humidity. We aimed to explore the relationship between weather variables and dengue and to analyse transmission hotspots and coldspots at the district-level. Poisson probability distribution of the generalized linear model (GLM) was used to examine the association between the monthly weather variable data and the reported number of dengue cases from January 2002 to December 2018 and geographic information system (GIS) for dengue hotspot analysis. Results showed a significant association between the environmental variables and dengue incidence when comparing the seasons. Temperature, sea-level pressure and wind speed had the highest coefficients, i.e. β=0.17, β= –0.12 and β= –0.11 (P<0.001), respectively. The risk of dengue incidence occurring during the rainy season was almost twice as high as that during monsoon. Statistically significant spatial clusters of dengue cases were observed all through the province in different years. Nabon was identified as a hotspot, while Pak Phanang was a coldspot for dengue fever incidence, explained by the fact that the former is a rubber-plantation hub, while the agricultural plains of the latter lend themselves to the practice of pisciculture combined with rice farming. This information is imminently important for planning apt sustainable control measures for dengue epidemics.

Background: More than half of the global population is predicted to be living in areas susceptible to dengue transmission with the vast majority in Asia. Dengue fever is of public health concern, particularly in the southern region of Thailand due to favourable environmental factors for its spread. The risk of dengue infection at the population level varies in time and space among sub-populations thus, it is important to study the risk of infection considering spatio-temporal variation. Methods: This study presents a joint spatio-temporal epidemiological model in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation with the CARBayesST package of R software. For this purpose, monthly dengue records by district from 2002 to 2018 from the southern region of Thailand provided by the Ministry of Public Health of Thailand and eight environmental variables were used. Results: Results show that an increasing level of temperature, number of rainy days and sea level pressure are associated with a higher occurrence of dengue fever and consequently higher incidence risk, while an increasing level of wind speed seems to suggest a protective factor. Likewise, we found that the elevated risks of dengue in the immediate future are in the districts of Phipun, Phrom Kili, Lan Saka, Phra Phrom and Chaloem Phakiat. The resulting estimates provide insights into the effects of covariate risk factors, spatio-temporal trends and dengue-related health inequalities at the district level in southern Thailand. Conclusion: Possible implications are discussed considering some anthropogenic factors that could inhibit or enhance dengue occurrence. Risk maps indicated which districts are above and below baseline risk, allowing for the identification of local anomalies and high-risk boundaries. In the event of near future, the threat of elevated disease risk needs to be prevented and controlled considering the factors underlying the spread of mosquitoes in the Southeast Asian region.

Access to improved water, sanitation, and hygiene (WASH) services is crucial in recognizing human rights to water and sanitation and due to their impacts on education, livelihoods, and human health. However, these services are often inadequate in non-household settings such as prisons, refugee camps, schools, and healthcare facilities. Progress in monitoring to ensure sustainable services in these settings has been limited. Although several tools are available to assess WASH services in both household and non-household settings, they have limitations, and none has taken a holistic approach to evaluate WASH performance in all non-household settings. Furthermore, the impacts of climate change on WASH services are rarely considered in these evaluations, making the inadequacies of WASH services worse. To address these gaps, an integrated tool was developed to assess WASH performance in non-household settings, incorporating financial, institutional, environmental impact, technical, social, and climate change factors. The tool provides scores for indicators to solve the problem of a lack of final aggregated data to enable decision-makers to determine the level of WASH performance in a setting. Moreover, it provides qualitative explanations for each score, allowing decision-makers to identify areas for improvement. This tool offers valuable and insightful data for improving WASH facilities and ensuring sustainable services in non-household settings, particularly for WASH service providers and local governments.