Spatial and Temporal Impacts of Socioeconomic and Environmental Factors on Healthcare Resources: A County-Level Bayesian Local Spatiotemporal Regression Modeling Study of Hospital Beds in Southwest China

The allocation and utilization efficiency of hospital beds in Sichuan Province, China

OBJECTIVE

To analyze the allocation and utilization efficiency of hospital beds in Sichuan Province, China, and to provide a scientific basis for improving the rational allocation and efficient utilization.

METHODS

The supply and demand balance method, health resource agglomeration degree (HRAD), bed efficiency index and bed utilization model were used to evaluate the allocation and utilization efficiency of hospital beds in Sichuan Province from 2017 to 2021.

RESULTS

The number of hospital beds per 1000 population in Sichuan Province increased from 4.97 in 2017 to 5.94 in 2021. The overall supply and demand ratio of hospital beds in Sichuan Province is between 0.85 and 1.01, and the supply and demand situation is a basically balanced situation. The HRAD of hospital beds in Ya'an, Aba, Ganzi and Liangshan is <1, indicating that the equity of hospital beds by geography in these regions is low. The difference between HRAD and population agglomeration degree (PAD) in 9 regions, including Deyang, Aba, Ganzi and Liangshan, is <0, indicating that there are insufficient hospital beds in these areas relative to the agglomerated population. The bed efficiency index of hospital beds in 17 regions, including Chengdu, Zigong, Aba and Ganzi, are all <1, which means that hospital beds are operating with low efficiency. The bed utilization model of Panzhihua is efficiency type, that of Zigong, Deyang and Ziyang is pressure bed type, and that of Nanchong and Ya'an is idle type.

CONCLUSION

The hospital bed allocation in Sichuan Province is relatively good, and the supply and demand situation is in a basically balanced situation. The hospital bed allocation in Aba, Ganzi and Liangshan is insufficient by geography and population. The overall operational efficiency of hospital beds is low, and there are more idle and pressure bed utilization models.

Knowledge, attitude, and practice towards bacterial multidrug-resistance and structural equation modeling analysis among intensive care unit nurses and physicians

BACKGROUND

The intensive care unit (ICU) is a department with a high risk of MDR bacteria, and ICU nurses and physicians play critical roles in bacterial multidrug resistance (MDR) prevention.

OBJECTIVES

To explore the knowledge, attitudes, and practice (KAP) towards bacterial MDR among ICU nurses and physicians.

METHODS

A self-designed questionnaire was administered to collect data. Structural equation modeling (SEM) was applied to assess the associations among study variables.

RESULTS

A total of 369 questionnaires were collected; 43 questionnaires were excluded due to self-contradictory on the trap question or the obviously repeated pattern. Finally, 326 (88.35%) valid questionnaires were included in the analysis. The knowledge, attitudes, and practice were 13.57 ± 1.69 (90.47%, possible range: 0-15), 38.75 ± 2.23 (96.88%, possible range: 8-40), and 47.40 ± 3.59 (94.80%, possible range: 10-50). The SEM showed that knowledge had a direct effect on attitude with a direct effect value of 0.61 (P < 0.001) and a direct negative effect on practice with a direct effect value of -0.30 (P = 0.009). The direct effect of attitude on practice was 0.89 (P < 0.001); the indirect effect of knowledge through attitude on practice was 0.52 (P < 0.001). Job satisfaction had a direct effect on attitude and practice, with an effect value of 0.52 (P = 0.030) and 0.75 (P = 0.040). Being a physician (OR = 0.354, 95%CI: 0.159-0.790, P = 0.011), 5-9.9 years of practice (OR = 4.534, 95%CI: 1.878-8.721, P < 0.001), and ≥ 10 years of practice (OR = 3.369, 95%CI: 1.301-8.721, P = 0.012) were independently associated with good knowledge. The attitude scores (OR = 1.499, 95%CI: 1.227-1.830, P < 0.001), male gender (OR = 0.390, 95%CI: 0.175-0.870, P = 0.022), and 5-9.9 years of experience (OR = 0.373, 95%CI: 0.177-0.787, P = 0.010) were independently associated with proactive practice.

CONCLUSION

Nurses and physicians in the ICU showed good knowledge, positive attitudes, and proactive practice toward bacterial MDR. Nurses and physicians' knowledge had a direct effect on their attitude, while attitude might directly influence the practice and also play a mediating role between knowledge and practice. Job satisfaction might directly support the positive attitude and practice toward bacterial MDR.

Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties

BACKGROUND

Ensuring universal health coverage and equitable access to health services requires a comprehensive understanding of spatiotemporal heterogeneity in healthcare resources, especially in small areas. The absence of a structured spatiotemporal evaluation framework in existing studies inspired us to propose a conceptual framework encompassing three perspectives: spatiotemporal inequalities, hotspots, and determinants.

METHODS

To demonstrate our three-perspective conceptual framework, we employed three state-of-the-art methods and analyzed 10 years' worth of Chinese county-level hospital bed data. First, we depicted spatial inequalities of hospital beds within provinces and their temporal inequalities through the spatial Gini coefficient. Next, we identified different types of spatiotemporal hotspots and coldspots at the county level using the emerging hot spot analysis (Getis-Ord Gi* statistics). Finally, we explored the spatiotemporally heterogeneous impacts of socioeconomic and environmental factors on hospital beds using the Bayesian spatiotemporally varying coefficients (STVC) model and quantified factors' spatiotemporal explainable percentages with the spatiotemporal variance partitioning index (STVPI).

RESULTS

Spatial inequalities map revealed significant disparities in hospital beds, with gradual improvements observed in 21 provinces over time. Seven types of hot and cold spots among 24.78% counties highlighted the persistent presence of the regional Matthew effect in both high- and low-level hospital bed counties. Socioeconomic factors contributed 36.85% (95% credible intervals [CIs]: 31.84-42.50%) of county-level hospital beds, while environmental factors accounted for 59.12% (53.80-63.83%). Factors' space-scale variation explained 75.71% (68.94-81.55%), whereas time-scale variation contributed 20.25% (14.14-27.36%). Additionally, six factors (GDP, first industrial output, local general budget revenue, road, river, and slope) were identified as the spatiotemporal determinants, collectively explaining over 84% of the variations.

CONCLUSIONS

Three-perspective framework enables global policymakers and stakeholders to identify health services disparities at the micro-level, pinpoint regions needing targeted interventions, and create differentiated strategies aligned with their unique spatiotemporal determinants, significantly aiding in achieving sustainable healthcare development.

Outpatient rehabilitation for an older couple in a repopulated village 10 years after the Fukushima nuclear disaster:An embedded case study

BackgroundLittle information is available on the role of community-based rehabilitation after a nuclear disaster. Here, we report the case of an older couple living in an area repopulated after the Fukushima nuclear disaster of 2011 who received outpatient rehabilitation.Case presentationAn 84-year-old woman underwent total hip arthroplasty (THA) after she fell and sustained a trochanteric fracture while caring for her husband with Alzheimer's disease. The 85-year-old husband experienced worsening behavioral and psychological symptoms of dementia (BPSD) following his wife's hospitalization. The couple received rehabilitation at an outpatient facility in a nearby village using a shuttle service. The woman's postoperative anxiety was relieved and her physical function improved. Moreover, the husband's BPSD symptoms decreased.ConclusionA wife and husband showed improvement in physical function after THA and alleviation of BPSD, respectively, following rehabilitation. In post-disaster, resource-scarce areas, older adults may benefit from utilizing the outpatient rehabilitation services available in the surrounding area.

Geodetector analysis of individual and joint impacts of natural and human factors on maternal and child health at the provincial scale

This ecological study examined the individual and joint impacts of natural-human factors on the spatial patterns of maternal and child health status in China at the provincial scale in 2020. We considered natural factors (forest coverage, average temperature, and total sulfur dioxide and particulate matter emissions) and human factors (economic development, urbanization, healthcare access, and education level). We combined maternal, infant, and under-five mortality rates into a composite maternal and child health index using the entropy method. The spatial autocorrelation analysis of this index highlighted distinct health patterns across provinces, whereas the geodetector method assessed the effects of natural-human factors on the patterns. A notable east-central-west stepwise decline in health status was observed. Global Moran's I showed positive spatial clustering, with high-high clustering areas in the Yangtze River Delta and low-low clustering areas in western regions. Factor detection identified eight significant natural-human factors impacting maternal and child health, with total sulfur dioxide emission density having the greatest impact. The interaction between average schooling years and total sulfur dioxide emission notably affected maternal and child health patterns. The study concludes that natural-human factors critically affect the spatial distribution of maternal and child health.

The Correlation between Economic Convergence and Health Indices in Developed Countries

Background

Economic convergence signifies diminishing income disparities among global or regional economies and their eventual disappearance. It is also linked to economic growth and key health indicators. We aimed to assess the association between economic convergence and key health indicators in developed countries called G7 (USA, UK, Germany, France, Italy, Japan, and Canada).

Methods

We examined G7 health and economic indicators from 2000 to 2021 using panel data analysis. We compared balanced and unbalanced panel datasets to address missing data and applied suitable methods to handle missing health indicators.

Results

Little's MCAR test (X 2 = 3.2872, P - value = 0.3494) confirmed random missing data in the unbalanced panel, enabling us to impute missing values as missing observations were below 5%. Unit root tests on balanced and unbalanced panel data validated the health convergence hypothesis, showing no unit roots in economic growth rate, current health expenditure, and female and male population indicators (P<0.05). Interestingly, the hypothesis for hospital bed counts in the unbalanced panel, differing from the balanced panel, offers new insights into addressing incomplete health data.

Conclusion

While G7 have economic similarities, their health indicators diverge (excluding hospital bed counts). Variations in health indicators stem from healthcare system structures, funding mechanisms, resource allocation, and health investments, even among economies of similar size. Therefore, G7 member states should develop tailored national health policies based on their specific circumstances and priorities, utilizing economic convergence data for effective health resource planning.

Spatiotemporal distribution of migraine in China: analyses based on baidu index

BACKGROUND

In recent years, innovative approaches utilizing Internet data have emerged in the field of syndromic surveillance. These novel methods aim to aid in the early prediction of epidemics across various scenarios and diseases. It has been observed that these systems demonstrate remarkable accuracy in monitoring outbreaks even before they become apparent in the general population. Therefore, they serve as valuable complementary tools to augment existing methodologies. In this study, we aimed to investigate the spatiotemporal distribution of migraine in China by leveraging Baidu Index (BI) data.

METHODS

Migraine-related BI data from January 2014 to December 2022 were leveraged, covering 301 city-level areas from 31 provincial-level regions by using the keyword "migraine ()". Prevalence data from the Global Burden of Disease study (GBD) were attracted to ensure the reliability of utilizing migraine-related BI data for research. Comprehensive analytical methods were then followed to investigate migraine's spatiotemporal distribution. The Seasonal-Trend decomposition procedure based on Loess (STL) was used to identify the temporal distribution. Spatial distribution was explored using the Getis-Ord Gi* statistic, standard deviation ellipse analysis, Moran's Index, and Ordinary Kriging. The top eight migraine-related search terms were analyzed through the Demand Graph feature in the Baidu Index platform to understand the public's concerns related to migraine.

RESULTS

A strong association was observed between migraine-related BI and the prevalence data of migraine from GBD with a Spearman correlation coefficient of 0.983 (P = 4.96 × 10- 5). The overall trend of migraine-related BI showed a gradual upward trend over the years with a sharp increase from 2017 to 2019. Seasonality was observed and the peak period occurred in spring nationwide. The middle-lower reaches of the Yangtze River were found to be hotspots, while the eastern coastal areas had the highest concentration of migraine-related BI, with a gradual decrease towards the west. The most common search term related to migraine was "How to treat migraine quickly and effectively ()".

CONCLUSIONS

This study reveals important findings on migraine distribution in China, underscoring the urgent need for effective prevention and management strategies.

Spatiotemporal analysis of the effect of global development indicators on child mortality

BACKGROUND

Child mortality continue to be a major public health issue in most developing countries; albeit there has been a decline in global under-five deaths. The differences in child mortality can best be explained by socioeconomic and environmental inequalities among countries. In this study, we explore the effect of country-level development indicators on under-five mortality rates. Specifically, we examine potential spatio-temporal heterogeneity in the association between major world development indicators on under-five mortality, as well as, visualize the global differential time trend of under-five mortality rates.

METHODS

The data from 195 countries were curated from the World Bank's World Development Indicators (WDI) spanning from 2000 to 2017 and national estimates for under-five mortality from the UN Inter-agency Group for Child Mortality Estimation (UN IGME).We built parametric and non-parametric Bayesian space-time interaction models to examine the effect of development indicators on under-five mortality rates. We also used employed Bayesian spatio-temporal varying coefficient models to assess the spatial and temporal variations in the effect of development indicators on under-five mortality rates.

RESULTS

In both parametric and non-parametric models, the results show indicators of good socioeconomic development were associated with a reduction in under-five mortality rates while poor indicators were associated with an increase in under-five mortality rates. For instance, the parametric model shows that gross domestic product (GDP) (β = - 1.26, [CI - 1.51; - 1.01]), current healthcare expenditure (β = - 0.40, [CI - 0.55; - 0.26]) and access to basic sanitation (β = - 0.03, [CI - 0.05; - 0.01]) were associated with a reduction under-five mortality. An increase in the proportion practising open defecation (β = 0.14, [CI 0.08; 0.20]) an increase under-five mortality rate. The result of the spatial components spatial variation in the effect of the development indicators on under-five mortality rates. The spatial patterns of the effect also change over time for some indicators, such as PM2.5.

CONCLUSION

The findings show that the burden of under-five mortality rates was considerably higher among sub-Saharan African countries and some southern Asian countries. The findings also reveal the trend in reduction in the sub-Saharan African region has been slower than the global trend.

The impact of health resource enhancement and its spatiotemporal relationship with population health

Objective

This study investigated the impact of health resource enhancement on health and spatiotemporal variation characteristics from 2000 to 2010 at the county level.

Methods

Multiscale Geographically Weighted Regression and curve fitting were used to explore the characteristics of spatiotemporal impact and divergence mechanism of health resource enhancement on population health.

Results

From 2000 to 2010, China's population health continued to rise steadily, and health resource allocation improved. Population health demonstrated the significant spatial autocorrelation, and its spatial clustering patterns were relatively fixed. Health resource allocation was relatively equal. Health technicians per 1,000 persons had a significant positive effect on population health in 2000 and 2010. Meanwhile, its impact tends to be consistent across regions, and the impact scale has been continuously expanding. A quantitative relationship exists between population health and health resource inputs. When life expectancy ranged from 73.68 to 84.08 years, the death rate ranged from 6.27 to 9.00%, and the infant mortality rate ranged from 0.00 to 6.33%, investments in health resources, especially related to health technicians, were beneficial for population health.

Conclusions

The government should improve the science and rationality of health resource planning. Planning meets regional realities by combining the impacts of economy and geography. The influence of health resources on population health depends on the overall allocation of health technicians. The number of health technicians needs to be further increased to improve the health resources' effective allocation between regions.

Spatiotemporal disparities in regional public risk perception of COVID-19 using Bayesian Spatiotemporally Varying Coefficients (STVC) series models across Chinese cities

Regional public attention has been critical during the COVID-19 pandemic, impacting the effectiveness of sub-national non-pharmaceutical interventions. While studies have focused on public attention at the national level, sub-national public attention has not been well investigated. Understanding sub-national public attention can aid local governments in designing regional scientific guidelines, especially in large countries with substantial spatiotemporal disparities in the spread of infections. Here, we evaluated the online public attention to the COVID-19 pandemic using internet search data and developed a regional public risk perception index (PRPI) that depicts heterogeneous associations between local pandemic risk and public attention across 366 Chinese cities. We used the Bayesian Spatiotemporally Varying Coefficients (STVC) model, a full-map local regression for estimating spatiotemporal heterogeneous relationships of variables, and improved it to the Bayesian Spatiotemporally Interacting Varying Coefficients (STIVC) model to incorporate space-time interaction non-stationarity at spatial or temporal stratified scales. COVID-19 daily cases (median contribution 82.6%) was the most critical factor affecting public attention, followed by urban socioeconomic conditions (16.7%) and daily population mobility (0.7%). After adjusting national and provincial impacts, city-level influence factors accounted for 89.4% and 58.6% in spatiotemporal variations of public attention. Spatiotemporal disparities were substantial among cities and provinces, suggesting that observing national-level public dynamics alone was insufficient. Multi-period PRPI maps revealed clusters and outlier cities with potential public panic and low health literacy. Bayesian STVC series models are systematically proposed and provide a multi-level spatiotemporal heterogeneous analytical framework for understanding collective human responses to major public health emergencies and disasters.

An External Patient Healthcare Index (EPHI) for Simulating Spatial Tendencies in Healthcare Seeking Behavior

Background

Healthcare resources are always more limited compared with demand, but better matching supply with demand can improve overall resource efficiency. In countries like China where patients are free to choose healthcare facilities, over-utilization and under-utilization of healthcare resources co-exist because of unreasonable healthcare seeking behavior. However, scholarship regarding the spatial distribution of utilization for healthcare resources, resulting from unreasonable spatial tendencies in healthcare seeking, is rare.

Methods

In this article, we propose a new External Patient Healthcare Index (EPHI) to simulate the spatial distribution of utilization for healthcare resources, based on the Two-Step Floating Catchment Area (2SFCA) method, which is widely used to assess potential spatial accessibility. Instead of using individual-level healthcare utilization data which is difficult to obtain, the EPHI uses institution-level aggregated data, including numbers of inpatient/outpatient visits. By comparing the estimated utilization (based on local healthcare institution services provision) with the expected utilization (based on local population morbidity), guest patients (e.g., patients flowing in for treatment) and bypass patients (patients flowing out) can be identified. To test the applicability of this index, a case study was carried out on China's Hainan Island. The spatial tendencies of patients for inpatient and outpatient services were simulated, then incorporated with spatial access to healthcare resources to evaluate overall resource allocation efficiency, thus guiding future resource allocations and investment for policy makers and healthcare providers.

Results

The EPHI revealed that bypass activities widely exist on Hainan Island in both inpatient and outpatient care, with patients tending to travel from less developed regions with fewer healthcare resources to more highly developed regions with more healthcare resources to receive healthcare. Comparison with spatial accessibility demonstrated how bypass activities on Hainan produced an under-utilization of doctors in less developed regions and over-utilization of doctors in more developed coastal regions.

Conclusions

This case study on Hainan Island demonstrates that this new index can very clearly identify both the sources and sinks of patient spatial tendencies. Combining these results with spatial accessibility of healthcare resources, how efficiently the available supply matches the utilization can be revealed, indicating wide-ranging applicability for local governments and policymakers.

Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China

Previous Studies, such as the evaluation of the supply of and demand for regional medical resources and carrying capacity assessments, require further development. This paper aims to evaluate the carrying capacity and spatial distribution of medical resources in Shenzhen from the perspective of supply and demand, and to conduct a time-series variation of the coupling coordination degree from 1986 to 2019. The two-step floating catchment area method was employed to quantify the carrying capacity and coupling coordination degree method and spatial autocorrelation analysis were applied to analyze spatial distribution between supply and demand. The results were as follows. (1) The carrying capacity index in more than 50% of the districts was classified as low-grade. The percentage of regions with good grades was 8.27%. The regions with a high carrying capacity were distributed in the central and southeastern areas. (2) The coupling coordination continued to rise, increasing from 0.03397 in 1986 to 0.33627 in 2019. (3) The level of supply and demand for medical resources in Shenzhen increased from 1986 to 2019, and the highest degree of compatibility between the supply and the population size was largely concentrated in the western and eastern regions. This research can provide a theoretical reference for Shenzhen to rationally plan medical resources and improve the carrying capacity of medical resources.

Ten years of China's new healthcare reform: a longitudinal study on changes in health resources

BACKGROUND

China launched a new round of healthcare-system reform in 2009 and proposed the goal of equal and guaranteed essential medical and health services for all by 2020. We aimed to investigate the changes in China's health resources over the past ten years after the healthcare reform.

METHODS

Data were collected from the China Statistical Yearbook and China Health Statistics Yearbook from 2009 to 2018. Four categories and ten indicators of health resources were analyzed. A descriptive analysis was used to present the overall condition. The Health Resource Density Index was applied to showcase health-resource distribution in demographic and geographic dimensions. The global and local Moran's I were used to assess the spatial autocorrelation of health resources. Concentration Index (CI) was used to quantify the equity of health-resource distribution. A Geo-Detector model and Geographic Weighted Regression (GWR) were applied to assess the association between gross domestic product (GDP) per capita and health resources.

RESULTS

Health resources have increased over the past ten years. The global and local Moran's I suggested spatial aggregation in the distribution of health resources. Hospital beds were concentrated in wealthier areas, but this inequity decreased yearly (from CI=0.0587 in 2009 to CI=0.0021 in 2018). Primary medical and health institutions (PMHI) and their beds were concentrated in poorer areas (CI remained negative). Healthcare employees were concentrated in wealthier areas (CI remained positive). In 2017, the q-statistics indicated that the explanatory power of GDP per capita to beds, health personnel, and health expenditure was 40.7%, 50.3%, and 42.5%, respectively. The coefficients of GWR remained positive with statistical significance, indicating the positive association between GDP per capita and health resources.

CONCLUSIONS

From 2009 to 2018, the total amount of health resources in China has increased substantially. Spatial aggregation existed in the health-resources distribution. Health resources tended to be concentrated in wealthier areas. When allocating health resources, the governments should take economic factors into account.

What resources do elderly people choose for managing their symptoms? Clarification of rural older people's choices of help-seeking behaviors in Japan

Background

Appropriate help-seeking behavior (HSB) that involves lay and professional care may moderate the usage of medical resources and promote good health, especially among the rural elderly. However, there is little evidence regarding the rural elderly’s HSB choices for mild symptoms. Therefore, this study attempts to bridge this gap.

Methods

The participants were patients living in rural areas and over the age of 65, who attended Japanese clinics and general hospitals. In Phase 1, monthly diaries and one-on-one interviews about their mild symptoms and HSB were used to establish HSB items and assess its content validity. Content analysis helped determine the items. In Phase 2, participants were asked to complete the list to measure HSB. The answers to the list and HSB mentioned in the diaries were compared to evaluate concurrent validity. Retests were conducted to examine the content’s reliability and test-retest reliability.

Results

Phase 1 included 267 participants (average age = 75.1 years, standard deviation [SD] = 4.3; 50.1% male). The diary collection rate was 97.6%. Of the participants, 70.4% used lay care and 25.4% used professional care. Content analysis identified eight types of lay care and four types of professional care. Phase 2 included 315 participants (average age = 77.7 years, SD = 8.27; 46.0% male). In terms of validity, the results of the list and the diaries were correlated (Spearman r 0.704; p < 0.001). The most common behavior with mild symptoms was consulting with primary care physicians, followed by self-care and using home medicine. The test-retest reliability for mild symptoms found kappa values of 0.836 for lay care and 0.808 for professional care.

Conclusions

The choices of HSB for mild symptoms clarified identified in this study have high validity and reliability. Therefore, it can be used to assess the relationships between HSB and health conditions and the effectiveness of health promotion on rural older people’s HSB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06684-x.

Socioeconomic and Environmental Impacts on Regional Tourism across Chinese Cities: A Spatiotemporal Heterogeneous Perspective

Understanding geospatial impacts of multi-sourced drivers on the tourism industry is of great significance for formulating tourism development policies tailored to regional-specific needs. To date, no research in China has explored the combined impacts of socioeconomic and environmental drivers on city-level tourism from a spatiotemporal heterogeneous perspective. We collected the total tourism revenue indicator and 30 potential influencing factors from 343 cities across China during 2008–2017. Three mainstream regressions and an emerging local spatiotemporal regression named the Bayesian spatiotemporally varying coefficients (Bayesian STVC) model were constructed to investigate the global-scale stationary and local-scale spatiotemporal nonstationary relationships between city-level tourism and various vital drivers. The Bayesian STVC model achieved the best model performance. Globally, eight socioeconomic and environmental factors, average wage (coefficient: 0.47, 95% credible intervals: 0.43–0.51), employed population (−0.14, −0.17–−0.11), GDP per capita (0.47, 0.42–0.52), population density (0.21, 0.16–0.27), night-time light index (−0.01, −0.08–0.05), slope (0.10, 0.06–0.14), vegetation index (0.66, 0.63–0.70), and road network density (0.34, 0.29–0.38), were identified to have nonlinear effects on tourism. Temporally, the main drivers might have gradually changed from the local macro-economic level, population density, and natural environment conditions to the individual economic level over the last decade. Spatially, city-specific dynamic maps of tourism development and geographically clustered influencing maps for eight drivers were produced. In 2017, China formed four significant city-level tourism industry clusters (hot spots, 90% confidence), the locations of which coincide with China’s top four urban agglomerations. Our local spatiotemporal analysis framework for geographical tourism data is expected to provide insights into adjusting regional measures to local conditions and temporal variations in broader social and natural sciences.

Is Urbanization Good for the Health of Middle-Aged and Elderly People in China?—Based on CHARLS Data

The purpose of this paper is to test whether improved healthcare services can mitigate health hazards resulting from environmental pollution in the urbanization process. Specifically, using China Health and Retirement Longitudinal Study (CHARLS) data and official statistics, this paper constructs comprehensive urbanization indicators and healthcare service indicators by applying the fully arrayed polygonal graphical indication method. Then, we introduce healthcare service indicators, urbanization indicators, environmental pollution indicators, and the interaction term between environmental pollution and healthcare into an ordered-logistics regression model. Our results indicate that improvement in health conditions can decrease the health risks from multiplied emissions of industrial sulfur dioxide, industrial soot and dust, and industrial effluents, but it cannot counteract the adverse health effects of PM2.5. Furthermore, heterogeneity tests show that, when considering the multidimensionality of urbanization, the positive influence of healthcare is the greatest in residential surroundings urbanization and economic urbanization, which reduces the prevalence of chronic diseases by 18.4% and 14.9%, respectively. Among the diverse city types, mixed-economy cities have the most obvious positive effects, where healthcare has the greatest mitigating effect on the health damage caused by industrial sulfur dioxide and industrial soot and dust, decreasing the prevalence of chronic diseases among the middle-aged and elderly by 27.3% and 16.4%, respectively. When considering the regional impacts of urbanization, there is a large difference in the positive effects brought about by medical care, which is reflected mainly in eastern and western China. In eastern China, although healthcare does not offset the health damage of PM2.5, the increase in chronic diseases among the middle-aged and elderly is only 0.5%, while in western China, the increase rises to 22.4%.

Modeling of daily confirmed Saudi COVID-19 cases using inverted exponential regression

The coronavirus disease 2019 (COVID-19) pandemic caused by the coronavirus strain has had massive global impact, and has interrupted economic and social activity. The daily confirmed COVID-19 cases in Saudi Arabia are shown to be affected by some explanatory variables that are recorded daily: recovered COVID-19 cases, critical cases, daily active cases, tests per million, curfew hours, maximal temperatures, maximal relative humidity, maximal wind speed, and maximal pressure. Restrictions applied by the Saudi Arabia government due to the COVID-19 outbreak, from the suspension of Umrah and flights, and the lockdown of some cities with a curfew are based on information about COVID-15. The aim of the paper is to propose some predictive regression models similar to generalized linear models (GLMs) for fitting COVID-19 data in Saudi Arabia to analyze, forecast, and extract meaningful information that helps decision makers. In this direction, we propose some regression models on the basis of inverted exponential distribution (IE-Reg), Bayesian (BReg) and empirical Bayesian regression (EBReg) models for use in conjunction with inverted exponential distribution (IE-BReg and IE-EBReg). In all approaches, we use the logarithm (log) link function, gamma prior and two loss functions in the Bayesian approach, namely, the zero-one and LINEX loss functions. To deal with the outliers in the proposed models, we apply Huber and Tukey's bisquare (biweight) functions. In addition, we use the iteratively reweighted least squares (IRLS) algorithm to estimate Bayesian regression coefficients. Further, we compare IE-Reg, IE-BReg, and IE-EBReg using some criteria, such as Akaike's information criterion (AIC), Bayesian information criterion (BIC), deviance (D), and mean squared error (MSE). Finally, we apply the collected data of the daily confirmed from March 23 - June 21, 2020 with the corresponding explanatory variables to the theoretical findings. IE-EBReg shows good model for the COVID-19 cases in Saudi Arabia compared with the other models.