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.

Nitrate contamination in groundwater is a worldwide problem especially in agricultural countries. Environmental factors, such as land-use pattern, type of aquifer, and soil-drainage capacity, affect the level of contamination. Exposure to high levels of nitrate in groundwater may contribute to adverse health effects among residents who use groundwater for consumption. This study aimed to determine the relationship between nitrate levels in groundwater with land-use pattern, type of aquifer, and soil-drainage capacity, in Photharam District, Ratchaburi Province, lower Mae Klong basin, Thailand. Health risk maps were created based on hazard quotient to quantify the potential health risk of the residents using US Environmental Protection Agency (U.S. EPA) health risk assessment model. The results showed the influence of land-use patterns, type of aquifer, and soil-drainage capacity on nitrate contamination. It was found that most of the residents in the studied area were not at risk; however, a groundwater nitrate monitoring system should be implemented.

Meteorological parameters play an important role in determining the prevalence of ambient particulate matter (PM) in the upper north of Thailand. Mae Hong Son is a province located in this region and which borders Myanmar. This study aimed to determine the relationships between meteorological parameters and ambient concentrations of particulate matter less than 10 µm in diameter (PM10) in Mae Hong Son. Parameters were measured at an air quality monitoring station, and consisted of PM10, carbon monoxide (CO), ozone (O3), and meteorological factors, including temperature, rainfall, pressure, wind speed, wind direction, and relative humidity (RH). Nine years (2009–2017) of pollution and climate data obtained from the Thai Pollution Control Department (PCD) were used for analysis. The results of this study indicate that PM10 is influenced by meteorological parameters; high concentration occurred during the dry season and northeastern monsoon seasons. Maximum concentrations were always observed in March. The PM10 concentrations were significantly related to CO and O3 concentrations and to RH, giving correlation coefficients of 0.73, 0.39, and −0.37, respectively (p-value < 0.001). Additionally, the hourly PM10 concentration fluctuated within each day. In general, it was found that the reporting of daily concentrations might be best suited to public announcements and presentations. Hourly concentrations are recommended for public declarations that might be useful for warning citizens and organizations about air pollution. Our findings could be used to improve the understanding of PM10 concentration patterns in Mae Hong Son and provide information to better air pollution measures and establish a warning system for the province.