Geohealth最新文献

The flooded soil conditions under which rice is typically grown are beneficial for boosting yield and decreasing herbicide inputs but may pose a food safety and environmental health risk. Flooded soils lead to reducing conditions and anaerobic metabolisms of soil microorganisms, which mobilizes arsenic from soil into soil solution, where it can be absorbed by rice roots and transported to grain. These conditions also promote the production and emission of methane (CH₄)—a potent greenhouse gas. To evaluate how water management affects metal(loid) grain concentrations and CH₄ emissions, we conducted a 2-year field study in which rice paddy water was managed under a range of soil redox conditions that spanned from flooded to non-flooded. We observed that growing rice under less flooded conditions decreased CH₄ emissions and concentrations of grain total As, grain inorganic As, grain total Hg, and grain inorganic Hg relative to flooded conditions, with more reductions observed as conditions were drier; grain organic As and Hg (MeHg) species also decreased with drier conditions particularly in Year 1. However, the driest conditions tested led to a 50%–97% increase in grain Cd concentrations that exceeded the CODEX limit and grain yield reductions as high as 25% and 40% in Year 1 and 2, respectively. While concentrations of toxic metal(loid)s could be manipulated by water management, micronutrient concentrations were similar or decreased with drier conditions, potentially increasing grain Cd bioaccessibility to humans. Because practices for rice water management are gaining momentum, more research should monitor grain Cd levels along with micronutrients.

Highly pathogenic avian influenza (HPAI) virus presents a serious threat to poultry and public health worldwide, with transmission dynamics shaped by avian migration patterns and environmental conditions. Recent outbreaks in the Philippines highlight the urgent need for effective control measures. While previous studies have shown the importance of waterfowl-to-poultry transmission and farm-to-farm spread, the spillover risk to local avian species remains underexplored. This study aimed to examine H5N1-HPAI outbreaks in poultry in relation to environmental factors and local avian species in the Philippines. We applied a two-step ecological niche modelling approach using maximum entropy algorithms. First, environmental variables from remote sensing images were used to predict the distribution of 10 common avian species based on citizen science data from the eBird platform. Next, these avian distribution data were combined with environmental variables to create a risk map for H5N1-HPAI outbreaks in the Philippines. The H5N1-HPAI risk model demonstrated strong predictive performance, with an AUCROC value of 0.936 ± 0.026. Key factors contributing to predicted H5N1-HPAI risk included precipitation levels, population density, and avian species such as the Eurasian Tree Sparrow and Zebra Dove. The higher risk of spillover for the two local avian species may be due to their shared similar environmental signatures with outbreak poultries. The risk map highlighted Metro Manila and Central Luzon as high-risk regions of H5N1-HPAI. This study identified the main clusters and environmental factors associated with avian influenza outbreaks in poultry in the Philippines. Additionally, the transmission risk may threaten the local avian population.

Communities and ecosystems of northern Utah, USA receive particulate pollution from anthropogenic activity and dust emissions from sources including the Great Salt Lake (“the Lake”) playa. In addition to affecting communities, anthropogenic pollution is delivered to the Lake's playa sediments, which are eroded during dust events. Yet, spatial variability in dust flux and composition and their risks to human health are poorly understood. We analyzed dust in 17 passive samplers proximal to the Lake during fall 2022 for dust flux, the dust fraction of particulate matter, ⁸⁷Sr/⁸⁶Sr, and elemental geochemistry. We evaluated spatial patterns of 11 priority pollutant metals and estimated the hypothetical non-cancer dust and soil ingestion health hazard for six age cohorts. We observed the highest dust fluxes proximal to the Lake's playa. The highest concentrations of and greatest number of metals occurred in and south of Ogden, UT. Sites to the northeast of Farmington Bay had the highest fluxes. Metal concentrations and ⁸⁷Sr/⁸⁶Sr suggest that the dust composition near Bountiful represents contributions from anthropogenic sources, whereas the dust composition to the northeast of Farmington Bay reflects the Lake's playa emissions. Evaluations of potential health hazards from dust ingestion suggest that children between birth and 6 years are vulnerable at higher ingestion rates. Thallium, As, Pb, Co and Cr contributed most to the estimated hazard. Among these, As and sometimes Pb are likely derived from the Lake's playa emissions. Thus, suppression of dust emissions from the Lake's playa may decrease possible health risks for children in northern Utah.

Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne zoonotic disease, which are classified by the World Health Organization as a priority disease for research and development in emergency situations due to the high mortality rate. Previous studies indicated that the complex nonlinear and delayed association was observed between meteorological factors and SFTS. However, these did not consider the short-term effect of meteorological factors on the incidence of SFTS. In this study, we used generalized additive models (GAM) and distributed lag nonlinear models (DLNM) to investigate the short-term correlation between meteorological factors and SFTS incidence. From 1 January 2013 to 31 December 2023 a total of 6,601 cases of SFTS were reported in Xinyang. Females constituted the majority with a male-to-female ratio of 0.68 and the average age of cases being approximately at around 61.52 years old. The multivariate GAM analysis revealed that mean temperature exerted the greatest influence on the incidence of SFTS compared to other meteorological factors and interacted with these factors. After accounting for lag period of 0–14 days, the DLNM analysis indicated that specific range of temperature (18–23°C), a certain range atmospheric pressure (1,006–1,017 hPa), extreme high wind speed (>11.6 m/s), and prolonged sunshine duration (>9h) were associated with SFTS, while there was no significant correlation between relative humidity and the incidence of SFTS. This study investigates the non-linear trend and lagged exposure effect of various meteorological factors on short-term SFTS incidence, thereby enhancing our comprehensive understanding of the effect of meteorological factors on SFTS.

Tuberculosis (TB) remains a critical public health issue, particularly in regions with significant socio-economic disparities. This study provides a comprehensive spatial analysis of TB dynamics in Şanlıurfa, Türkiye, covering the period from 2016 to 2023. Utilizing Geographic Information Systems, epidemiological data, and advanced statistical techniques, the research examines the spatial distribution and temporal trends of TB cases within this region. By integrating patient data with demographic, environmental, and socio-economic variables, the study assesses the complex factors influencing TB incidence and prevalence. The results indicate significant spatial clustering of TB cases, with the highest concentrations in areas characterized by high population density, lower socio-economic status, limited healthcare accessibility, and poor environmental conditions. Temporal trends reveal a gradual decline in TB incidence over the study period; however, certain hotspots persist, underscoring the need for sustained and targeted interventions. Furthermore, the study identifies a correlation between TB prevalence and inadequate living conditions, emphasizing the role of socio-economic improvement in disease control. These findings provide crucial insights for policymakers and public health officials, facilitating the development of more effective, evidence-based TB control strategies tailored to the unique socio-economic and geographical landscape of Şanlıurfa.

Air pollution, particularly fine particulate matter, poses significant health and environmental risks, with exposure levels exhibiting considerable spatial inequality. However, few studies have comprehensively examined how urban form and environmental factors influence air pollution exposure and its spatial inequality. This study investigates how urban and environmental factors affect particulate matter pollution (PM₁, PM_2.5, and PM₁₀) and its spatial inequality across 85 counties in Fujian, China. Twelve indicators across urban form, socio-economic, and environmental domains were analyzed using principal component analysis and partial correlation networks. Our results show that while overall air pollution levels exhibit substantial variability, spatial inequality in exposure does not always correlate directly with these levels. Notably, while urbanized counties display higher pollution exposure, significant disparities in pollution distribution are observed within regions of similar pollution levels. Urban and socio-economic features such as population density and road density are strongly correlated with higher pollution exposure, especially in more urbanized areas. In contrast, environmental factors, such as vegetation coverage and precipitation, significantly mitigate pollution levels. Principal component analysis reveals that development density and environmental changes primarily drive overall pollution levels, while economic activity and segregation contribute to the spatial inequality of exposure. Network analysis further corroborates that high-density urban development exacerbates pollution exposure, while socio-economic segregation contributes to uneven distribution across the population. Our findings underscore the need for integrated urban planning strategies that address these urban and environmental factors to reduce air pollution inequality and promote more equitable urban environments.

We conducted a pilot study to explore methods of incorporating qualitative community knowledge into quantitative assessment of temporal and spatial air quality patterns in a neighborhood in Vancouver, British Columbia. We deployed a low-cost sensor network measuring NO, NO₂, and PM_2.5. We used a variety of sources of community knowledge to complement a timeseries analysis and spatial model: a survey by the residents' association; odor reports from a citizen science project; and data from a community mapping event. Community knowledge highlighted, among other sources, areas where cars and heavy-duty vehicles idle, locations of construction, and locations of wood stoves. When creating a “traditional” land use regression (LUR) using easily accessible, and publicly available data sources, and a “community” LUR that uses community-reported air pollution sources, model fit was improved in the community LURs for NO₂ and NO_x. This suggests that community knowledge can provide insight into sources that are not well captured in commonly used, publicly available data sets due to their transient and informal nature. Not all community-reported short-term events corresponded to peaks in monitor data, which could reflect that reports were more correlated with unmeasured pollutants. We suggest that future studies collecting community knowledge on short-term pollution events through community mapping lower barriers to participation (i.e., through hosting a series of drop-in events, providing childcare, or timing any event to coincide with neighborhood-wide events). With these examples, we showcased ways to include community knowledge in quantitative air pollution studies and highlight opportunities to expand on these methods.

Since its introduction to North America in 1999, West Nile virus (WNV) has become the most widespread mosquito-borne disease in the United States. Climatic conditions significantly influence transmission dynamics. While temperature, precipitation, and humidity are known to affect mosquito populations and virus replication, wind speed is often neglected in transmission models despite its potential to alter mosquito behavior and facilitate mosquito dispersal. This study incorporates wind speed into climate-based WNV models to compare its effects in Louisiana and South Dakota, two U.S. states with contrasting climates, land cover, and vector and host species. From 2004 to 2022, we analyzed weekly WNV human case data in relation to daily meteorological data. The relationships were modeled using logistic regression with distributed lag effects. Incorporating wind speed consistently enhanced the fit of climate-based models across both states, as evidenced by the Akaike Information Criterion. Higher-than-normal wind speeds were associated with decreased WNV cases over specific lag periods, suggesting that increased wind speed may inhibit mosquito activity and reduce virus transmission. Differences in how temperature and moisture-related variables influenced the two regions highlight the importance of considering regional climatic contexts. These findings demonstrate that incorporating wind speed can enhance meteorological models of mosquito-borne diseases and reinforce the importance of considering a broader range of climatic factors beyond temperature and precipitation. Understanding these regional variations is essential for predicting local climatic influences on disease transmission, which can support the implementation of more targeted and effective public health strategies.

Phenological shifts due to climate change have been extensively studied in plants and animals. Yet, the responses of fungal spores—organisms important to ecosystems and major airborne allergens—remain understudied. This knowledge gap limits our understanding of their ecological and public health implications. To address this, we analyzed a long-term (2003–2022), large-scale (the continental US) data set of airborne fungal spores collected by the US National Allergy Bureau. We first pre-processed the spore data by gap-filling and smoothing. Afterward, we extracted 10 metrics describing the phenology (e.g., start and end of season) and intensity (e.g., peak concentration and integral) of fungal spore seasons. These metrics were derived using two complementary but not mutually exclusive approaches—ecological and public health approaches, defined as percentiles of total spore concentration and allergenic thresholds of spore concentration, respectively. Using linear mixed-effects models, we quantified annual shifts in these metrics across the continental US. We revealed a significant advancement in the onset of the spore seasons defined in both ecological (11 days, 95% confidence interval: 0.4–23 days) and public health (22 days, 6–38 days) approaches over two decades. Meanwhile, total spore concentrations in an annual cycle and in a spore allergy season tended to decrease over time. The earlier start of the spore season was significantly correlated with climatic variables, such as warmer temperatures and altered precipitations. Overall, our findings suggest possible climate-driven advanced fungal spore seasons, highlighting the importance of climate change mitigation and adaptation in public health decision-making.

Extreme heat is worsening due to climate change, and, in combination with increasing urban growth, is an escalating public health concern. In the Arabian Peninsula, the wet-bulb temperature is projected to surpass theoretical human tolerance limits during the 21st century. Yet, heat research in the region has generally not focused on health impacts, and it is unclear how epidemiologic literature has investigated this. We performed a scoping review to examine the existing literature that assessed the relationship between extreme heat and health outcomes in the Arabian Peninsula, collecting papers published from 2010 to 2024 from three databases. We identified and extracted detailed information from a limited number of studies (n = 12). The greatest number of studies were conducted in Kuwait (n = 8), with others in Saudi Arabia (n = 4), and Qatar, Oman, Yemen, and the United Arab Emirates (n = 1 each). Average temperature was the most used exposure (n = 9) assessed at the daily level (n = 10), using one or several meteorological stations (n = 9) from a single city (n = 8). The outcome was predominantly daily-level (n = 10) mortality (n = 9) assessed at an ecological scale (n = 10) as opposed to the individual scale. While most studies included confounders (n = 10), their selection was not always consistent with best practices. Most papers did not assess effect modification (n = 8), and none investigated modification by land-cover and land-use change on the heat-health relationship. We provide future research recommendations based on our findings. Additional studies are critical to better understand the heat-health relationship in the Arabian Peninsula, which can aid intervention implementation.