Purpose of Review: A large body of epidemiological evidence demonstrates that exposure to particulate matter (PM) is associated with increased morbidity and mortality. Many epidemiology studies have investigated the health effects of PM in Europe and North America and focussed on traffic derived PM. However, elevated levels of PM are a global problem and the impacts of other sources of PM on health should be assessed. Biomass burning can increase PM levels in urban and rural indoor and outdoor environments in developed and developing countries. We aim to identify whether the health effects of traffic and biomass burning derived PM are similar by performing a narrative literature review. We focus on Thailand as haze episodes from agricultural biomass burning can substantially increase PM levels. Recent Findings: Existing epidemiology, in vitro and in vivo studies suggest that biomass burning derived PM elicits toxicity via stimulation of oxidative stress, inflammation and genotoxicity. Thus, it is likely to cause similar adverse health outcomes to traffic PM, which causes toxicity via similar mechanisms. However, there is conflicting evidence regarding whether traffic or biomass burning derived PM is most hazardous. Also, there is evidence that PM released from different biomass sources varies in its toxic potency. Summary: We recommend that epidemiology studies are performed in Thailand to better understand the impacts of PM emitted from specific biomass sources (e.g. agricultural burning). Further, experimental studies should assess the toxicity of PM emitted from more diverse biomass sources. This will fill knowledge gaps and inform evidence-based interventions that protect human health.

Aim A novel corona virus disease 2019 (COVID-19) was declared as pandemic by WHO as global level and local levels in many countries. The movement of people might be one influencing factor, this paper aims to report the situation COVID-19 and spreading in Thailand, including influencing factors of spreading and control. Subject and method Infected, confirmed COVID-19 data were obtained from the official website of the Department of Disease Control, Ministry of Public Health. Tourist data was downloaded from Ministry of Tourism and Sports. Researchers analyzed the situation from the first found case in Thailand until 15 April 2020 with the timeline of important influencing factors. Correlation coefficients of tourist data and infected case was calculated by person correlation coefficient. Results The number of infected cases was significant associated (correlation coefficient > 0.7) with economic factor, namely; number of visitors, generated income from both Thai and foreigner tourist (p value <0.01). The influencing factors of slow increased rate were the enforcement and implementation of both central and local government regulation, the strength of the Thai health care system, the culture and social relation, the partnership among various governmental and private sectors. Conclusion We found that the number of tourist and their activities were significant associated with number of infected, confirmed COVID-19 cases. The public education and social supporting were the key roles for regulation enforcement and implementation.

Background: Exposure to particulate matter (PM) emitted from biomass burning is an increasing concern, particularly in Southeast Asia. It is not yet clear how the source of PM influences the risk of an adverse health outcome. The objective of this study was to quantify and compare health risks of PM from biomass burning and non-biomass burning sources in northern Thailand. Methods: We collected ambient air pollutant data (PM with a diameter of < 10 μm [PM₁₀], PM_2.5, Carbon Monoxide [CO], Ozone [O₃], and Nitrogen Dioxide [NO₂]) from ground-based monitors and daily outpatient hospital visits in Thailand during 2014–2017. Outpatient data included chronic lower respiratory disease (CLRD), ischaemic heart disease (IHD), and cerebrovascular disease (CBVD). We performed an ecological time series analysis to evaluate the association between daily air pollutants and outpatient visits. We used the 90th and 95th percentiles of PM₁₀ concentrations to determine days of exposure to PM predominantly from biomass burning. Results: There was significant intra annual variation in PM₁₀ levels, with the highest concentrations occurring during March, coinciding with peak biomass burning. Incidence Rate Ratios (IRRs) between daily PM₁₀ and outpatient visits were elevated most on the same day as exposure for CLRD = 1.020 (95% CI: 1.012 to 1.028) and CBVD = 1.020 (95% CI: 1.004 to 1.035), with no association with IHD = 0.994 (95% CI: 0.974 to 1.014). Adjusting for CO tended to increase effect estimates. We did not find evidence of an exposure response relationship with levels of PM₁₀ on days of biomass burning. Conclusions: We found same-day exposures of PM₁₀ to be associated with certain respiratory and cardiovascular outpatient visits. We advise implementing measures to reduce population exposures to PM wherever possible, and to improve understanding of health effects associated with burning specific types of biomass in areas where such large-scale activities occur.

The change of temperature and weather parameters is a major concern affecting sustainable development and impacting various sectors, such as agriculture, tourism, and industry. Changing weather patterns and their impact on water resources are important climatic factors that society is facing. In Thailand, climatological features such as ambient temperature, relative humidity, and precipitation play a substantial role in affecting extreme weather events, which cause damage to the economy, agriculture, tourism, and livelihood of people. To investigate recent serious changes in annual trends of temperature, relative humidity, and precipitation in Thailand, this study used the Mann–Kendall (MK) test and innovative trend analysis (ITA) methods. The MK test showed that all six regions had an upward trend in temperature and humidity index (humidex, how hot the weather feels to the average person), while relative humidity and precipitation showed both upward and downward trends across different regions. The ITA method further confirmed the upward trend in temperature and humidex and showed that most data points fell above the 1:1 line. However, the upward trend in most variables was not significant at the 5% level. The southern and eastern regions showed a significant upward trend in relative humidity and humidex at a 5% level of significance according to the MK test. The output of this study can help in the understanding of weather variations and predict future situations and can be used for adaptation strategies.

Particulate air pollution causes a spectrum of adverse health effects affecting the respiratory, cardiovascular, neurological, and metabolic systems that are hypothesised to be driven by inflammation and oxidative stress. Millions of premature deaths each year are attributed to exposure to ambient particulate matter (PM). We quantified health and economic impacts from long-term exposure to ambient PM_2.5 in the population of Thailand for 2016. We collected data on ambient PM_2.5 concentrations from automatic monitoring stations across Thailand over 1996–2016. We used historic exposure to PM_2.5 to estimate the mortality in each province from lower respiratory infections (LRIs), stroke, chronic obstructive pulmonary disease, lung cancer, and ischaemic heart disease, and also assessed diabetes mortality, as well as incident cases of dementia and Parkinson’s disease, in supplementary analyses. We applied risk estimates from the Global Exposure Mortality Model to calculate attributable mortality and quantify disability-adjusted life years (DALYs); we based economic costs on the value of a statistical life (VSL). We calculated 50 019 (95% confidence interval [CI]: 42 189–57 849) deaths and 508 918 (95% CI: 438 345–579 492) DALYs in 2016 attributed to long-term PM_2.5 exposure in Thailand. Population attributable fractions ranged from 20% (95% CI: 10% to 29%) for stroke to 48% (95% CI: 27% to 63%) for LRIs. Based on the VSL, we calculated a cost of US$ 60.9 billion (95% CI: US$ 51.3–70.4 billion), which represents nearly 15% of Thailand’s gross domestic product in 2016. While progress has been made to reduce exposure to ambient PM_2.5 in Thailand, continued reductions based on stricter regulatory limits for PM_2.5 and other air pollutants would help prolong life, and delay, or prevent, onset of cardiorespiratory and other diseases.