Spatial heterogeneity of the association between temperature and hand, foot, and mouth disease risk in metropolitan and other areas

The non-stationary and spatially varying associations between hand, foot and mouth disease and multiple environmental factors: A Bayesian spatiotemporal mapping model study

The transmission and prevalence of Hand, Foot and Mouth Disease (HFMD) are affected by a variety of natural and socio-economic environmental factors. This study aims to quantitatively investigate the non-stationary and spatially varying associations between various environmental factors and HFMD risk. We collected HFMD surveillance cases and a series of relevant environmental data from 2013 to 2021 in Xi'an, Northwest China. By controlling the spatial and temporal mixture effects of HFMD, we constructed a Bayesian spatiotemporal mapping model and characterized the impacts of different driving factors into global linear, non-stationary and spatially varying effects. The results showed that the impact of meteorological conditions on HFMD risk varies in both type and magnitude above certain thresholds (temperature: 30 °C, precipitation: 70 mm, solar radiation: 13000 kJ/m2, pressure: 945 hPa, humidity: 69%). Air pollutants (PM2.5, PM10, NO2) showed an inverted U-shaped relationship with the risk of HFMD, while other air pollutants (O3, SO2) showed nonlinear fluctuations. Moreover, the driving effect of increasing temperature on HFMD was significant in the 3-year period, while the inhibitory effect of increasing precipitation appeared evident in the 5-year period. In addition, the proportion of urban/suburban/rural area had a strong influence on HFMD, indicating that the incidence of HFMD firstly increased and then decreased during the rapid urbanization process. The influence of population density on HFMD was not only limited by spatial location, but also varied between high and low intervals. Higher road density inhibited the risk of HFMD, but higher night light index promoted the occurrence of HFMD. Our findings further demonstrated that both ecological and socioeconomic environmental factors can pose multiple driving effects on increasing the spatiotemporal risk of HFMD, which is of great significance for effectively responding to the changes in HFMD epidemic outbreaks.

Assessing habitat quality at Poyang Lake based on InVEST and Geodetector modeling

Poyang Lake is an essential natural wetland in the Yangtze River basin and plays a vital role in maintaining the ecosystem function and ecological security in the middle and lower reaches of the Yangtze River. However, the relative importance and spatial heterogeneity of the impacts of human activities and land use changes on ecological security needs to be further explored. Here, we analyzed the habitat quality level around Poyang Lake in 2022 and explored the factors of habitat quality change from a geographical perspective. The land use structure changes around the Poyang Lake basin from 2000 to 2022 were quantitatively analyzed, and then the relative importance and spatial heterogeneity of each factor on ecological security changes were investigated using geographic probes. The results show that (1) The worst quality habitat (0-0.1) consists mainly of construction land (1624.9 km2) with an area of 1634.64 km2; (2) Construction land continues to increase with the most significant change, and the dynamic land use attitude is 0.47. Grassland and mudflats have the greatest decrease. The increase in cultivated land in different periods is mainly due to the shift of water surface and forest land; (3) The drivers of habitat quality in Poyang Lake were significantly influenced by the interaction of socioeconomic factors. The explanatory power of population density interacting with the total year-end population and population density interacting with administrative area exceeded 0.84. These values were higher than the explanatory power of each individual factor, indicating that habitat quality was primarily associated with population density, total year-end population, and administrative area. These results suggest that human activities contribute to the degradation of wetlands around Poyang Lake. This study has significant reference value for coordinating human-land relationships in Poyang Lake, optimizing land management policy, and improving the sustainable development of cities.

Influence of social and meteorological factors on hand, foot, and mouth disease in Sichuan Province

BACKGROUND

Hand, foot and mouth disease (HFMD) caused by a variety of enteroviruses remains a major public health problem in China. Previous studies have found that social factors may contribute to the inconsistency of the relationship patterns between meteorological factors and HFMD, but the conclusions are inconsistent. The influence of social factors on the association between meteorology and HFMD is still less well understood. We aimed to analyze whether social factors affected the effect of meteorological factors on HFMD in Sichuan Province.

METHOD

We collected daily data on HFMD, meteorological factors and social factors in Sichuan Province from 2011 to 2017. First, we used a Bayesian spatiotemporal model combined with a distributed lag nonlinear model to evaluate the exposure-lag-response association between meteorological factors and HFMD. Second, by constructing the interaction of meteorological factors and social factors in the above model, the changes in the relative risk (RR) under different levels of social factors were evaluated.

RESULTS

The cumulative exposure curves for average temperature, relative humidity, and HFMD were shaped like an inverted "V" and a "U" shape. As the average temperature increased, the RR increased and peaked at 19 °C (RR 1.020 [95% confidence interval CI 1.004-1.050]). The urbanization rate, per capita gross domestic product (GDP), population density, birth rate, number of beds in health care centers and number of kindergartens interacted with relative humidity. With the increase in social factors, the correlation curve between relative humidity and HFMD changed from an "S" shape to a "U" shape.

CONCLUSIONS

Relative humidity and average temperature increased the risk of HFMD within a certain range, and social factors enhanced the impact of high relative humidity. These results could provide insights into the combined role of environmental factors in HFMD and useful information for regional interventions.

Study on the interaction between different pathogens of Hand, foot and mouth disease in five regions of China

Objectives

This study aims to explore the interaction of different pathogens in Hand, foot and mouth disease (HFMD) by using a mathematical epidemiological model and the reported data in five regions of China.

Methods

A cross-regional dataset of reported HFMD cases was built from four provinces (Fujian Province, Jiangsu province, Hunan Province, and Jilin Province) and one municipality (Chongqing Municipality) in China. The subtypes of the pathogens of HFMD, including Coxsackievirus A16 (CV-A16), enteroviruses A71 (EV-A71), and other enteroviruses (Others), were included in the data. A mathematical model was developed to fit the data. The effective reproduction number (R _eff ) was calculated to quantify the transmissibility of the pathogens.

Results

In total, 3,336,482 HFMD cases were collected in the five regions. In Fujian Province, the R _eff between CV-A16 and EV-A71&CV-A16, and between CV-A16 and CV-A16&Others showed statistically significant differences (P < 0.05). In Jiangsu Province, there was a significant difference in R _eff (P < 0.05) between the CV-A16 and Total. In Hunan Province, the R _eff between CV-A16 and EV-A71&CV-A16, between CV-A16 and Total were significant (P < 0.05). In Chongqing Municipality, we found significant differences of the R _eff (P < 0.05) between CV-A16 and CV-A16&Others, and between Others and CV-A16&Others. In Jilin Province, significant differences of the R _eff (P < 0.05) were found between EV-A71 and Total, and between Others and Total.

Conclusion

The major pathogens of HFMD have changed annually, and the incidence of HFMD caused by others and CV-A16 has surpassed that of EV-A71 in recent years. Cross-regional differences were observed in the interactions between the pathogens.

Assessing the impact of ambient temperature on the risk of hand, foot, and mouth disease in Guangdong, China: New insight from the disease severity and burden

Background

The association between the incidence of hand, foot, and mouth disease (HFMD) and ambient temperature has been well documented. Although the severity of symptoms is an important indicator of disease burden and varies significantly across cases, it usually was ignored in previous studies, potentially leading to biased estimates of the health impact of temperature.

Methods

We estimated the disability-adjusted life year (DALY) by considering the severity of symptoms for each HFMD case reported during 2010–2012 in Guangdong and used distributed lag-nonlinear models to estimate the association between the daily average temperature and daily DALY of HFMD cases at the city-level. We investigated the potential effect modifiers on the pathway between temperature and DALY and pooled city-specific estimates to a provincial association using a meta-regression. The overall impact of temperature was further evaluated by estimates of DALYs that could be attributed to HFMD.

Results

The overall cumulative effect of daily mean temperature on the DALY of HFMD showed an inverse-U shape, with the maximum effect estimated to be β = 0.0331 (95%CI: 0.0199–0.0463) DALY at 23.8°C. Overall, a total of 6.432 (95%CI: 3.942–8.885) DALYs (attributable fraction = 2.721%, 95%CI: 1.660–3.759%) could be attributed to temperature exposure. All the demographic subgroups had a similar trend as the main analysis, while the magnitude of the peak of the temperature impact tended to be higher among the males, those aged ≥3yrs or from the Pear-River Delta region. Additionally, the impact of temperature on DALY elevated significantly with the increasing population density, per capita GDP, and per capita green space in parks.

Conclusions

Temperature exposure was associated with increased burden of HFMD nonlinearly, with certain groups such as boys and those from areas with greater population density being more vulnerable.

Hand, foot, and mouth disease (HFMD) is a contagious viral infection common in young children. Although the association between ambient temperature and the risk of HFMD has been well documented, existing studies were solely based on the reported number of cases, failing to differentiate cases of different severity. This study improves the estimation of disease burden by additionally accounting for the severity of symptoms. Our major findings included that (1) we identified an inverse-U shaped association between the ambient temperature and the daily DALY (i.e. an established indicator for disease burden) associated with HFMD, with 2.7% DALY could be attributed to the temperature exposure; (2) the peak impact of temperature on DALY was estimated to be β = 0.0331 (95%CI: 0.0199–0.0463) DALY and identified at 23.8°C; (3) the trends were generally consistent across different demographic and geographic subgroups, with the peak effect identified to be greater among the males, those aged ≥3yrs or from the Pear-River Delta region; (4) the impact of temperature on DALY elevated more apparently in areas with a greater population density, per capita GDP, or per capita green space in parks.

Temporal and Spatial Heterogeneity of PM2.5 Related to Meteorological and Socioeconomic Factors across China during 2000-2018

In recent years, air pollution caused by PM_2.5 in China has become increasingly severe. This study applied a Bayesian space-time hierarchy model to reveal the spatiotemporal heterogeneity of the PM_2.5 concentrations in China. In addition, the relationship between meteorological and socioeconomic factors and their interaction with PM_2.5 during 2000-2018 was investigated based on the GeoDetector model. Results suggested that the concentration of PM_2.5 across China first increased and then decreased between 2000 and 2018. Geographically, the North China Plain and the Yangtze River Delta were high PM_2.5 pollution areas, while Northeast and Southwest China are regarded as low-risk areas for PM_2.5 pollution. Meanwhile, in Northern and Southern China, the population density was the most important socioeconomic factor affecting PM_2.5 with q values of 0.62 and 0.66, respectively; the main meteorological factors affecting PM_2.5 were air temperature and vapor pressure, with q values of 0.64 and 0.68, respectively. These results are conducive to our in-depth understanding of the status of PM_2.5 pollution in China and provide an important reference for the future direction of PM_2.5 pollution control.

Daily mean temperature and HFMD: risk assessment and attributable fraction identification in Ningbo China

BACKGROUND

Hand, foot, and mouth disease (HFMD) remains a significant public health issue, especially in developing countries. Many studies have reported the association between environmental temperature and HFMD. However, the results are highly heterogeneous in different regions. In addition, there are few studies on the attributable risk of HFMD due to temperature.

OBJECTIVES

The study aimed to assess the association between temperature and HFMD incidence and to evaluate the attributable burden of HFMD due to temperature in Ningbo China.

METHODS

The research used daily incidence of HFMD from 2014 to 2017 and distributed lag non-linear model (DLNM) to investigate the effects of daily mean temperature (Tmean) on HFMD incidence from lag 0 to 30 days, after controlling potential confounders. The lag effects and cumulative relative risk (CRR) were analyzed. Attributable fraction (AF) of HFMD incidence due to temperature was calculated. Stratified analysis by gender and age were also conducted.

RESULTS

The significant associations between Tmean and HFMD incidence were observed in Ningbo for lag 0-30. Two peaks were observed at both low (5-11 °C) and high (16-29 °C) temperature scales. For low temperature scale, the highest CRR was 2.22 (95% CI: 1.61-3.07) at 7 °C on lag 0-30. For high temperature scale, the highest CRR was 3.54 (95% CI: 2.58-4.88) at 24 °C on lag 0-30. The AF due to low and high temperature was 5.23% (95% CI: 3.10-7.14%) and 39.55% (95% CI: 30.91-45.51%), respectively. There was no significant difference between gender- and age-specific AFs, even though the school-age and female children had slightly higher AF values.

CONCLUSIONS

The result indicates that both high and low temperatures were associated with daily incidence of HFMD, and more burdens were caused by heat in Ningbo.

Spatial pattern of the population casualty rate caused by super typhoon Lekima and quantification of the interactive effects of potential impact factors

BACKGROUND

Typhoons greatly threaten human life and property, especially in China. Therefore, it is important to make effective policy decisions to minimize losses associated with typhoons.

METHODS

In this study, the GeoDetector method was used to quantify the determinant powers of natural and socioeconomic factors, and their interactions, on the population casualty rate of super typhoon Lekima. The local indicator of spatial association (LISA) method was followed to explore the spatial pattern of the population casualty rate under the influence of the identified dominant factors.

RESULTS

Both natural and socioeconomic factors were found to have significantly impacted the population casualty rate due to super typhoon Lekima. Among the selected factors, maximum precipitation was dominant factor (q = 0.56), followed by maximum wind speed (q = 0.45). In addition, number of health technicians (q = 0.35) and number of health beds (q = 0.27) have a strong influence on the population casualty rate. Among the interactive effects of 12 influencing factors, the combined effects of maximum precipitation and ratio of brick-wood houses, the maximum precipitation and ratio of steel-concrete houses, maximum precipitation and number of health technicians were highest (q = 0.72). Furthermore, high-risk areas with very high casualty rates were concentrated in the southeastern part of Zhejiang and northern Shandong Provinces, while lower-risk areas were mainly distributed in northern Liaoning and eastern Jiangsu provinces.

CONCLUSIONS

These results contribute to the development of more specific policies aimed at safety and successful property protection according to the regional differences during typhoons.

Determinant Powers of Socioeconomic Factors and Their Interactive Impacts on Particulate Matter Pollution in North China

Severe air pollution has significantly impacted climate and human health worldwide. In this study, global and local Moran’s I was used to examine the spatial autocorrelation of PM_2.5 pollution in North China from 2000–2017, using data obtained from Atmospheric Composition Analysis Group of Dalhousie University. The determinant powers and their interactive effects of socioeconomic factors on this pollutant are then quantified using a non-linear model, GeoDetector. Our experiments show that between 2000 and 2017, PM_2.5 pollution globally increased and exhibited a significant positive global and local autocorrelation. The greatest factor affecting PM_2.5 pollution was population density. Population density, road density, and urbanization showed a tendency to first increase and then decrease, while the number of industries and industrial output revealed a tendency to increase continuously. From a long-term perspective, the interactive effects of road density and industrial output, road density, and the number of industries were amongst the highest. These findings can be used to develop the effective policy to reduce PM_2.5 pollution, such as, due to the significant spatial autocorrelation between regions, the government should pay attention to the importance of regional joint management of PM_2.5 pollution.

A Quantitative Analysis of Factors Influencing Organic Matter Concentration in the Topsoil of Black Soil in Northeast China Based on Spatial Heterogeneous Patterns

Black soil is fertile, abundant with organic matter (OM) and is exceptional for farming. The black soil zone in northeast China is the third-largest black soil zone globally and produces a quarter of China’s commodity grain. However, the soil organic matter (SOM) in this zone is declining, and the quality of cultivated land is falling off rapidly due to overexploitation and unsustainable management practices. To help develop an integrated protection strategy for black soil, this study aimed to identify the primary factors contributing to SOM degradation. The geographic detector, which can detect both linear and nonlinear relationships and the interactions based on spatial heterogeneous patterns, was used to quantitatively analyze the natural and anthropogenic factors affecting SOM concentration in northeast China. In descending order, the nine factors affecting SOM are temperature, gross domestic product (GDP), elevation, population, soil type, precipitation, soil erosion, land use, and geomorphology. The influence of all factors is significant, and the interaction of any two factors enhances their impact. The SOM concentration decreases with increased temperature, population, soil erosion, elevation and terrain undulation. SOM rises with increased precipitation, initially decreases with increasing GDP but then increases, and varies by soil type and land use. Conclusions about detailed impacts are presented in this paper. For example, wind erosion has a more significant effect than water erosion, and irrigated land has a lower SOM content than dry land. Based on the study results, protection measures, including conservation tillage, farmland shelterbelts, cross-slope ridges, terraces, and rainfed farming are recommended. The conversion of high-quality farmland to non-farm uses should be prohibited.

Spatiotemporal heterogeneity of PM2.5 and its relationship with urbanization in North China from 2000 to 2017

Fine particulate matter (PM_2.5) pollution is becoming an increasing global concern due to rapid urbanization and socioeconomic development, especially in North China. Although North China experiences poor air quality and high PM_2.5 concentrations, their spatial heterogeneity and relationship with the relative spatial risks of air pollution have not been explored. Therefore, in this study, the temporal variation trends (slope values) of the PM_2.5 concentrations in North China from 2000 to 2017 were first quantified using the unitary linear regression model, and the Bayesian space-time hierarchy model was introduced to characterize their spatiotemporal heterogeneity. The spatial lag model was then used to examine the determinant power of urbanization and other socioeconomic factors. Additionally, the correlation between the spatial relative risks (probability of a region becoming more/less polluted relative to the average PM_2.5 concentrations of the study area), and the temporal variation trends of the PM_2.5 concentrations were quantified using the bivariate local indicators of spatial association model. The results showed that the PM_2.5 concentrations increased during 2000-2017, and peaked in 2007 and 2013. Spatially, the cities at high risk of PM_2.5 pollution were mainly clustered in southeastern Hebei, northern Henan, and western Shandong where the slope values were low, as demonstrated by the value of Moran's I (-0.56). Moreover, urbanization and road density were both positively correlated with PM_2.5 pollution, while the proportion of tertiary industry was negatively correlated. Furthermore, a notable increasing trend was observed in some cities, such as Tianjin, Zaozhuang, Qingdao, and Xinyang. These findings can contribute to the development of effective policies from the perspective of rapid urbanization to relieve and reduce PM_2.5 pollution.

Nonlinear effect of temperature on hand, foot, and mouth disease in Lanzhou, China

To examine the effects of temperature on the daily cases of hand, foot, and mouth disease (HFMD).Data on the daily cases of HFMD in Lanzhou from 2008 to 2015 were obtained, and meteorological data from the same period were collected. A distributed lag nonlinear model was fitted to reveal the relationship between the daily mean temperature and the daily cases of HFMD.From 2008 to 2015, 25,644 cases were reported, of which children under 5 years of age accounted for 78.68% of cases. The highest peak of HFMD cases was usually reported between April to July each year. An inverse V-shaped relationship was observed between daily mean temperature and HFMD cases; a temperature of 18°C was associated with a maximum risk of HFMD. The relative risk (RR) was 1.57 (95% confidence interval: 1.23-1.23), and boys and children aged 3 to 5 years were populations with the highest risk. The cumulative risks of high temperature (20.2°C and 25.2°C) in the total, age-specific, and gender-specific groups peaked on lag 14 days; RR was higher in girls than in boys and in children aged 1 to 2 years than in other age groups. However, the effects of low temperature (-5.3°C, 2.0°C, and 12.8°C) were not significant for both gender-specific and age-specific patients.High temperature may increase the risk of HFMD, and boys and children aged 3 to 5 years were at higher risks on lag 0 day; however, the cumulative risks in girls and children aged 1 to 2 years increased with the increasing number of lag days.

Spatial distribution, risk assessment and influence factors of terrestrial gamma radiation dose in China

The current spatial distribution of the risk of terrestrial gamma radiation in China were investigated by using spatial interpolation. And the driving factors influence on the terrestrial gamma radiation dose (TGRD) distribution were identified using the geographic detector, a new statistical method based on the nonlinear hypothesis. The results showed that the values of TGRD were range from 60 to 195 nGy h^-1 with the average of 86.5 nGy h^-1, and the higher values were recorded in Qingahi-Tibet Plateau, which were all within the range of background value in China. In addition, the radiological indices, ELCR (Excess Lifetime Cancer Risk), TGRD and AEDE (Annual Effective Dose Equivalent) were also within the acceptable range of values by risk assessment. The results by use of the geographic detector showed that sunshine duration, atmosphere pressure, altitude, and rainfall condition have closely related to the TGRD distribution. In addition, these meteorological factors and altitude had more impact on TGRD than the air pollution-related factors. Our study can provide useful information on studying the influence mechanism of the TGRD distribution, the variability of the natural terrestrial gamma radiation in China, and exposure data for risk assessment from low dose chronic exposures.