The spatiotemporal evolution of rural landscape patterns in Chinese metropolises under rapid urbanization.

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided.

Study on the development characteristics and spatial and temporal patterns of population ageing in 31 central cities in China.

Background: Population ageing is inseparable from technological innovation, social progress and the development of human civilization, and constitutes a new element in the development of contemporary human history. Objective: To dynamically analyses the developmental, structural and growth characteristics of population ageing in 31 provincial capitals and municipalities in China, using the data of the fifth national census in 2000 and the seventh national census in 2020. Methods: The development characteristics and spatial and temporal patterns of population aging in the 31 cities were measured using the population aging index growth model, Theil's index, coefficient of variation, population aging index and other analytical methods. Results: (1) From 2000 to 2020, the population aging rate of the 31 central cities generally increased, and the population aging level of the cities showed the characteristics of "East-Central-Northeast-West" to "Northeast-East-Central-West" decreasing. (2) Regional differences in the ratio of old to young are relatively high, while regional differences in the level of population ageing are relatively small. The level of population ageing is classified with the indicators of size structure, family structure and age structure in the first and third quadrants, and with the geographic concentration rate in the second and fourth quadrants. (3) China's population ageing has a T-shaped spatial distribution characteristic pointing along the coast - along the Yangtze Rivers. Conclusion: The 31 central cities are the center of gravity of China's economy and have strong economic power in dealing with the challenges of population ageing, but how to make population ageing compatible with the economy and society, and then promote sustainable population development, is a topic that needs further attention in the study.

Spatial distribution of arboviruses and its association with a social development index and the waste disposal in São Luís, state of Maranhão, Brazil, 2015 to 2019.

OBJECTIVE: To detect spatial and spatiotemporal clusters of urban arboviruses and to investigate whether the social development index (SDI) and irregular waste disposal are related to the coefficient of urban arboviruses detection in São Luís, state of Maranhão, Brazil. METHODS: The confirmed cases of Dengue, Zika and Chikungunya in São Luís, from 2015 to 2019, were georeferenced to the census tract of residence. The Bayesian Conditional Autoregressive regression model was used to identify the association between SDI and irregular waste disposal sites and the coefficient of urban arboviruses detection. RESULTS: The spatial pattern of arboviruses pointed to the predominance of a low-incidence cluster, except 2016. For the years 2015, 2016, 2017, and 2019, an increase of one unit of waste disposal site increased the coefficient of arboviruses detection in 1.25, 1.09, 1.23, and 1.13 cases of arboviruses per 100 thousand inhabitants, respectively. The SDI was not associated with the coefficient of arboviruses detection. CONCLUSION: In São Luís, spatiotemporal risk clusters for the occurrence of arboviruses and a positive association between the coefficient of arbovirus detection and sites of irregular waste disposal were identified.

Global arthropod beta-diversity is spatially and temporally structured by latitude.

Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

Revealing climatic and groundwater impacts on the spatiotemporal variations in vegetation coverage in marine sedimentary basins of the North China Plain, China.

The North China Plain (NCP) is one of the three great plains in China and also serves as a vital region for grain, cotton, and oil production. Under the influence of regional hydrothermal changes, groundwater overexploitation, and seawater intrusion, the vegetation coverage is undergoing continuous alterations. However, a comprehensive assessment of impacts of precipitation, temperature, and groundwater on vegetation in marine sedimentary regions of the NCP is lacking. Heilonggang Basin (HB) is located in the low-lying plain area in the east of NCP, which is part of the NCP. In this study, the HB was chosen as a typical area of interest. We collected a series of data, including the Normalized Difference Vegetation Index (NDVI), precipitation, temperature, groundwater depth, and Total Dissolved Solids (TDS) from 2001 to 2020. Then the spatiotemporal variation in vegetation was analyzed, and the underlying driving mechanisms of vegetation variation were explored in this paper. The results show that NDVI experiences a rapid increase from 2001 to 2004, followed by stable fluctuations from 2004 to 2020. The vegetation in the HB has achieved an overall improvement in the past two decades, with 76% showing improvement, mainly in the central and eastern areas, and 24% exhibiting deterioration in other areas. From 2001 to 2020, NDVI correlates positively with precipitation, whereas its relationship with temperature fluctuates between positive and negative, and is not statistically significant. There is a threshold for the synergistic change of NDVI and groundwater depth. When the groundwater depth is lower than 3.8 m, NDVI increases sharply with groundwater depth. However, beyond this threshold, NDVI tends to stabilize and fluctuate. In the eastern coastal areas, NDVI exhibits a strong positive correlation with groundwater depth, influenced by the surface soil TDS controlled by groundwater depth. In the central regions, a strong negative correlation is observed, where NDVI is primarily impacted by soil moisture under the control of groundwater. In the west and south, a strong positive correlation exists, with NDVI primarily influenced by the intensity of groundwater exploitation. Thus, precipitation and groundwater are the primary driving forces behind the spatiotemporal variability of vegetation in the HB, while in contrast, the influence of temperature is uncertain. This study has elucidated the mechanism of vegetation response, providing a theoretical basis for mitigating adverse factors affecting vegetation growth and formulating rational water usage regulations in the NCP.

Analysis of spatial and temporal changes in vegetation cover and its drivers in the Aksu River Basin, China.

Exploring vegetation dynamics in arid areas and their responses to different natural and anthropogenic factors is critical for understanding ecosystems. Based on the monthly MOD13Q1 (250 m) remote sensing data from 2000 to 2019, this study analyzed spatio-temporal changes in vegetation cover in the Aksu River Basin and predicted future change trends using one-dimensional linear regression, the Mann-Kendall test, and the Hurst index. Quantitative assessment of the magnitude of anthropogenic and natural drivers was performed using the Geodetector model. Eleven natural and anthropogenic factors were quantified and analyzed within five time periods. The influence of the driving factors on the changes in the normalized difference vegetation index (NDVI) in each period was calculated and analyzed. Four main results were found. (1) The overall vegetation cover in the region significantly grew from 2000 to 2019. The vegetation cover changes were dominated by expected future improvements, with a Hurst index average of 0.45. (2) Land use type, soil moisture, surface temperature, and potential vapor dispersion were the main drivers of NDVI changes, with annual average q-values above 0.2. (3) The driving effect of two-factor interactions was significantly greater than that of single factors, especially land use type interacts with other factors to a greater extent on vegetation cover. (4) The magnitude of the interaction between soil moisture and potential vapor dispersion and the magnitude of the interaction between anthropogenic factors and other factors showed an obvious increasing trend. Current soil moisture and human activities had a positive influence on the growth of vegetation in the area. The findings of this study are important for ecological monitoring and security as well as land desertification control.

A Bayesian spatio-temporal model of COVID-19 spread in England.

Exploring the spatio-temporal variations of COVID-19 transmission and its potential determinants could provide a deeper understanding of the dynamics of disease spread. This study aimed to investigate the spatio-temporal spread of COVID-19 infections in England, and examine its associations with socioeconomic, demographic and environmental risk factors. We obtained weekly reported COVID-19 cases from 7 March 2020 to 26 March 2022 at Middle Layer Super Output Area (MSOA) level in mainland England from publicly available datasets. With these data, we conducted an ecological study to predict the COVID-19 infection risk and identify its associations with socioeconomic, demographic and environmental risk factors using a Bayesian hierarchical spatio-temporal model. The Bayesian model outperformed the ordinary least squares model and geographically weighted regression model in terms of prediction accuracy. The spread of COVID-19 infections over space and time was heterogeneous. Hotspots of infection risk exhibited inconsistent clustering patterns over time. Risk factors found to be positively associated with COVID-19 infection risk were: annual household income [relative risk (RR) = 1.0008, 95% Credible Interval (CI) 1.0005-1.0012], unemployment rate [RR = 1.0027, 95% CI 1.0024-1.0030], population density on the log scale [RR = 1.0146, 95% CI 1.0129-1.0164], percentage of Caribbean population [RR = 1.0022, 95% CI 1.0009-1.0036], percentage of adults aged 45-64 years old [RR = 1.0031, 95% CI 1.0024-1.0039], and particulate matter ( PM 2.5 ) concentrations [RR = 1.0126, 95% CI 1.0083-1.0167]. The study highlights the importance of considering socioeconomic, demographic, and environmental factors in analysing the spatio-temporal variations of COVID-19 infections in England. The findings could assist policymakers in developing tailored public health interventions at a localised level.

The long-term spatio-temporal trends in burden and attributable risk factors of major depressive disorder at global, regional and national levels during 1990-2019: a systematic analysis for GBD 2019.

AIMS: Caused by multiple risk factors, heavy burden of major depressive disorder (MDD) poses serious challenges to public health worldwide over the past 30 years. Yet the burden and attributable risk factors of MDD were not systematically known. We aimed to reveal the long-term spatio-temporal trends in the burden and attributable risk factors of MDD at global, regional and national levels during 1990-2019. METHODS: We obtained MDD and attributable risk factors data from Global Burden of Disease Study 2019. We used joinpoint regression model to assess the temporal trend in MDD burden, and age-period-cohort model to measure the effects of age, period and birth cohort on MDD incidence rate. We utilized population attributable fractions (PAFs) to estimate the specific proportions of MDD burden attributed to given risk factors. RESULTS: During 1990-2019, the global number of MDD incident cases, prevalent cases and disability-adjusted life years (DALYs) increased by 59.10%, 59.57% and 58.57%, respectively. Whereas the global age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized DALYs rate (ASDR) of MDD decreased during 1990-2019. The ASIR, ASPR and ASDR in women were 1.62, 1.62 and 1.60 times as that in men in 2019, respectively. The highest age-specific incidence, prevalence and DALYs rate occurred at the age of 60-64 in women, and at the age of 75-84 in men, but the maximum increasing trends in these age-specific rates occurred at the age of 5-9. Population living during 2000-2004 had higher risk of MDD. MDD burden varied by socio-demographic index (SDI), regions and nations. In 2019, low-SDI region, Central sub-Saharan Africa and Uganda had the highest ASIR, ASPR and ASDR. The global PAFs of intimate partner violence (IPV), childhood sexual abuse (CSA) and bullying victimization (BV) were 8.43%, 5.46% and 4.86% in 2019, respectively. CONCLUSIONS: Over the past 30 years, the global ASIR, ASPR and ASDR of MDD had decreased trends, while the burden of MDD was still serious, and multiple disparities in MDD burden remarkably existed. Women, elderly and populations living during 2000-2004 and in low-SDI regions, had more severe burden of MDD. Children were more susceptible to MDD. Up to 18.75% of global MDD burden would be eliminated through early preventing against IPV, CSA and BV. Tailored strategies-and-measures in different regions and demographic groups based on findings in this studywould be urgently needed to eliminate the impacts of modifiable risk factors on MDD, and then mitigate the burden of MDD.

Spatio-Temporal distribution characteristics and driving factors of traditional villages in the Yellow River Basin.

Currently, research on traditional villages mainly focuses on the current development status and evolutionary trends in specific regions, with relatively limited studies from a macroscopic and holistic perspective on the spatiotemporal evolution of traditional villages. Therefore, this study selects traditional villages in the Yellow River Basin (YRB) as the research object. By analyzing the spatiotemporal distribution characteristics and driving factors of traditional villages (TVs) in the basin, it aims to further promote high-quality development in the YRB and protect traditional cultural resources. Based on data from 892 village points of the first to sixth batches of TVs in the YRB, ArcGIS 10.8 spatial analysis techniques were employed to analyze the overall spatial pattern of TVs in the YRB. The results indicate: (1) In the basin, TVs are more numerous in the east than the west and more in the south than the north, forming clusters and contiguous distributions, with dense areas primarily in the upstream regions dominated by Qinghai Province and the midstream areas along the Shanxi-Shaanxi coast. (2) The number and scale of TVs in the basin generally exhibit an increasing trend, with imbalanced provincial distribution. More recent years show a more balanced distribution of villages and proportions, with a higher number of villages in the mountainous and plateau regions of the basin. (3) The layout center of TVs within the basin evolves with each batch, showing a migration pattern from north to south, back to north, and finally east to west. (4) The interaction of natural and social factors plays a synergistic role in driving the spatiotemporal distribution pattern of TVs. Among these, natural geographical factors are the primary factors. TVs are more commonly found in regions with low altitude sunny slopes, mild climate, abundant precipitation, proximity to ancient roads and rivers, gentle slopes, and soil predominantly comprising loess, brown earth, and alluvial soils. The cultural environment is a secondary factor, with TVs often located in areas with larger populations, developed economies, and rich cultural heritage.

Using a general practice research database to assess the spatio-temporal COVID-19 risk.

BACKGROUND: In Flanders, general practitioners (GPs) were among the first ones to collect data regarding COVID-19 cases. Intego is a GPs' morbidity registry in primary care with data collected from the electronic medical records from a sample of general practices. The Intego database contain elaborate information regarding patient characteristics, such as comorbidities. At the national level, the Belgian Public Health Institute (Sciensano) recorded all test-confirmed COVID-19 cases, but without other patient characteristics. METHODS: Spatio and spatio-temporal analyses were used to analyse the spread of COVID-19 incidence at two levels of spatial aggregation: the municipality and the health sector levels. Our study goal was to compare spatio-temporal modelling results based on the Intego and Sciensano data, in order to see whether the Intego database is capable of detecting epidemiological trends similar to those in the Sciensano data. Comparable results would allow researchers to use these Intego data, and their wealth of patient information, to model COVID-19-related processes. RESULTS: The two data sources provided comparable results. Being a male decreased the odds of having COVID-19 disease. The odds for the age categories (17,35], (35,65] and (65,110] of being a confirmed COVID-19 case were significantly higher than the odds for the age category [0,17]. In the Intego data, having one of the following comorbidities, i.e., chronic kidney disease, heart and vascular disease, and diabetes, was significantly associated with being a COVID-19 case, increasing the odds of being diagnosed with COVID-19. CONCLUSION: We were able to show how an alternative data source, the Intego data, can be used in a pandemic situation. We consider our findings useful for public health officials who plan intervention strategies aimed at monitor and control disease outbreaks such as that of COVID-19.

The coupling coordination between health service supply and regional economy in China: spatio-temporal evolution and convergence.

Background: The coordination of health service supply and regional economy is an integral path to promote China's prosperity. Methods: Based on the coupling mechanism of health service supply and regional economy, we sampled the data from 30 provinces in China from 2009 to 2021 in this study and constructed the evaluation index system. Additionally, we calculated the coupling coordination degree (HED) of the two through the coupling coordination degree model. We further used the kernel density estimation, Moran's I index, and spatial ß convergence model to assess the dynamic evolution trends, spatial aggregation effect, and spatial convergence characteristics of coupling coordination. Conclusion: (1) HED in China showed a rising trend during the study period but with large regional differences, forming a gradient distribution pattern of "high in the east and low in the west." (2) The results of Kernel density estimation show that HED has formed a gradient differentiation phenomenon within each region in China. (3) HED has modeled spatial clustering characteristics during the study period, with high-value clusters mainly appearing in the eastern region and low-value clusters appearing in the northwestern region. (4) There are absolute ß-convergence and conditional ß-convergence trends in HED in China and the three major regions during the study period, but there is an obvious regional heterogeneity in the control factors. The research provides a reference for accurately implementing policies according to different levels of health service supply and economic development, in addition to narrowing the regional differences of the coupling coordination between the regional economy and health service supply.

Spatiotemporal differentiation and driving mechanisms of high-level Grade A tourist attractions in the Yangtze River Delta City Cluster.

Herein, the spatial evolution characteristics of high-level Grade A tourist attractions in the Yangtze River Delta (YRD) urban agglomeration, from 2001 to 2021, are studied by comprehensively applying the nearest neighbor index, kernel density analysis, standard deviation ellipse, and spatial autocorrelation. High-level Grade A tourist attractions are investigated using the random forest model as the driving mechanism of the spatial pattern. Results show that 1) the spatial distribution of high-level Class A tourist attractions in the YRD city cluster has grown to be an agglomeration, and the high-density areas have evolved from "point-like dispersion to regiment-like combination," gradually forming a B-shaped core density structure. 2) The spatial distribution comprises an overall "northwest-southeast" direction, a small counterclockwise rotation, the distribution of the center of gravity to the southwest migration, and the center of gravity from the territory of Suzhou City to the territory of Huzhou City. 3) The high-level Class A tourist attractions in the YRD city cluster as a whole show a strong positive spatial correlation, and the significantly clustered areas include three types: high-high (H-H), low-low (L-L), and low-high (L-H). 4) The spatial distribution of high, A-level tourist attractions in the YRD city cluster results from the combined action of the natural environment, resource endowment, socioeconomy, and policy background. Each element has a nonlinear and complex influence on the distribution of scenic spots.

Transient Propagation of the Invasion Front in the Homogeneous Landscape and in the Presence of a Road.

Understanding the propagation of invasive plants at the beginning of invasive spread is important as it can help practitioners eradicate harmful species more efficiently. In our work the propagation regime of the invasive plant species is studied at the short-time scale before a travelling wave is established and advances into space at a constant speed. The integro-difference framework has been employed to deal with a stage-structured population, and a short-distance dispersal mode has been considered in the homogeneous environment and when a road presents in the landscape. It is explained in the paper how nonlinear spatio-temporal dynamics arise in a transient regime where the propagation speed depends on the detection threshold population density. Furthermore, we investigate the question of whether the transient dynamics become different when the homogeneous landscape is transformed into the heterogeneous one. It is shown in the paper how invasion slows down in a transient regime in the presence of a road.

Spatiotemporal dynamics of the proton motive force on single bacterial cells.

Electrochemical gradients across biological membranes are vital for cellular bioenergetics. In bacteria, the proton motive force (PMF) drives essential processes like adenosine triphosphate production and motility. Traditionally viewed as temporally and spatially stable, recent research reveals a dynamic PMF behavior at both single-cell and community levels. Moreover, the observed lateral segregation of respiratory complexes could suggest a spatial heterogeneity of the PMF. Using a light-activated proton pump and detecting the activity of the bacterial flagellar motor, we perturb and probe the PMF of single cells. Spatially homogeneous PMF perturbations reveal millisecond-scale temporal dynamics and an asymmetrical capacitive response. Localized perturbations show a rapid lateral PMF homogenization, faster than proton diffusion, akin to the electrotonic potential spread observed in passive neurons, explained by cable theory. These observations imply a global coupling between PMF sources and consumers along the membrane, precluding sustained PMF spatial heterogeneity but allowing for rapid temporal changes.

Analysing the outbreaks of leptospirosis after floods in Kerala, India.

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.

Spatio-temporal characterization of earthquake sequence parameters and forecasting of strong aftershocks in Xinjiang based on the ETAS model.

In this paper, the Integrated Nested Laplace Algorithm (INLA) is applied to the Epidemic Type Aftershock Sequence (ETAS) model, and the parameters of the ETAS model are obtained for the earthquake sequences active in different regions of Xinjiang. By analyzing the characteristics of the model parameters over time, the changes in each earthquake sequence are studied in more detail. The estimated values of the ETAS model parameters are used as inputs to forecast strong aftershocks in the next period. We find that there are significant differences in the aftershock triggering capacity and aftershock attenuation capacity of earthquake sequences in different seismic regions of Xinjiang. With different cutoff dates set, we observe the characteristics of the earthquake sequence parameters changing with time after the mainshock occurs, and the model parameters of the Ms7.3 earthquake sequence in Hotan region change significantly with time within 15 days after the earthquake. Compared with the MCMC algorithm, the ETAS model fitted with the INLA algorithm can forecast the number of earthquakes in the early period after the occurrence of strong aftershocks more effectively and can forecast the sudden occurrence time of earthquakes more accurately.

Research on the spatial and temporal patterns of ozone concentration and population health effects in the Central Plains Urban Agglomeration from 2017 to 2020.

Fine particulate matter (PM2.5) and near-surface ozone (O3) are the main atmospheric pollutants in China. Long-term exposure to high ozone concentrations adversely affects human health. It is of great significance to systematically analyze the spatiotemporal evolution mechanism and health effects of ozone pollution. Based on the ozone data of 91 monitoring stations in the Central Plains Urban Agglomeration from 2017 to 2020, the research used Kriging method and spatial autocorrelation analysis to investigate the spatiotemporal variations of ozone concentration. Additionally, the study assessed the health effects of ozone on the population using the population exposure risk model and exposure-response relationship model. The results indicated that: (1) The number of premature deaths caused by ozone pollution in the warm season were 37,053 at 95% confidence interval (95% CI: 28,190-45,930) in 2017, 37,685 (95% CI: 28,669-46,713) in 2018, and 37,655 (95% CI: 28,647-46,676) in 2019. (2) The ozone concentration of the Central Plains urban agglomeration showed a decreasing trend throughout the year and during the warm season from 2017 to 2020, there are two peaks monthly, one is June, and the other is September. (3) In the warm season, the high-risk areas of population exposure to ozone in the Central Plains Urban Agglomeration were mainly concentrated in urban areas. In general, the population exposure risk of the south is lower than that of the north. The number of premature deaths attributed to ozone concentration during the warm season has decreased, but some southern cities such as Xinyang and Zhumadian have also seen an increase in premature deaths. China has achieved significant results in air pollution control, but in areas with high ozone concentrations and high population density, the health burden caused by air pollution remains heavy, and stricter air pollution control policies need to be implemented.

The spatio-temporal pattern and its influencing factors of production efficiency of health resources in China.

There is always a contradiction between the limited health resources and the unlimited demand of the population for health services, and only by improving the productivity of health resources can the health level of the population be improved as much as possible. Using prefecture-level administrative regions as spatial units, the paper analyzes the spatial pattern and changes of health productivity of health resources in China from 2000 to 2010, and uses a spatial panel Tobit model to examine the effects of factors such as technical level of health institutions, health service accessibility, public health policies and ecological environment quality on health productivity of health resources. The results show that with the Hu Huanyong line as the dividing line, the spatial heterogeneity of "high in the southeast and low in the northwest" in the health productivity of China's health resources is clear; as the regional differences narrow, the spatial correlation increases, and the spatial pattern of "overall dispersion and partial agglomeration" becomes more obvious. The fitting results of the spatial Durbin model reveal the direction and degree of influence of local and adjacent factors on the production efficiency of health resources. The positive influence of technical level of local health institutions and the accessibility of health services, the literacy level and the ability to pay for health services of residents in adjacent areas, the degree of urbanization of regional health resource allocation, climate suitability and the quality of the atmospheric environment are significant. And the negative influence of local residents' literacy and ability to pay for health services, the technical level of health institutions in adjacent areas and the degree of medicalization of health resource allocation are also significant. The influence of the degree of medicalization of local health resource allocation and the accessibility of health services in adjacent areas are significantly spatial-heterogeneous.

Spatial-temporal transmission dynamics of HIV-1 CRF01_AE in Indonesia.

Human immunodeficiency virus type 1 (HIV-1) remains a serious health threat in Indonesia. In particular, the CRF01_AE viruses were the predominant HIV-1 strains in various cities in Indonesia. However, information on the dynamic transmission characteristics and spatial-temporal transmission of HIV-1 CRF01_AE in Indonesia is limited. Therefore, the present study examined the spatial-temporal transmission networks and evolutionary characteristics of HIV-1 CRF01_AE in Indonesia. To clarify the epidemiological connection between CRF01_AE outbreaks in Indonesia and the rest of the world, we performed phylogenetic studies on nearly full genomes of CRF01_AE viruses isolated in Indonesia. Our results showed that five epidemic clades, namely, IDN clades 1-5, of CRF01_AE were found in Indonesia. To determine the potential source and mode of transmission of CRF01_AE, we performed Bayesian analysis and built maximum clade credibility trees for each clade. Our study revealed that CRF01_AE viruses were commonly introduced into Indonesia from Southeast Asia, particularly Thailand. The CRF01_AE viruses might have spread through major pandemics in Asian countries, such as China, Vietnam, and Laos, rather than being introduced directly from Africa in the early 1980s. This study has major implications for public health practice and policy development in Indonesia. The contributions of this study include understanding the dynamics of HIV-1 transmission that is important for the implementation of HIV disease control and prevention strategies in Indonesia.