Global Spatial Autocorrelation Research Articles

Epidemic features of coronavirus disease 2019 in Henan Province.

To analyze the regional epidemic features of coronavirus disease 2019 (COVID-19) in Henan Province, China. According to the data of COVID-19 patients and the resident population at the end of 2018 in Henan Province, statistical description and analysis of epidemiological characteristics of COVID-19 in Henan Province were conducted, including the time distribution, population distribution, and regional distribution. The cumulative incidence of COVID-19 in Henan Province was 1.32/100 000, the cure rate was 98.03%, and the fatality rate was 1.73% by March 9, 2020. The incidence curve showed that the epidemic peak reached from January 24 to January 28. The high-incidence area was Xinyang, with a standardized cumulative incidence rate of 4.36/100 000. There were 580 female COVID-19 patients (45.60%), 688 males (54.09%) in Henan Province. The incidence of males was 1.41/100 000, while the incidence of females was 1.23/100 000. The age with the highest incidence of COVID-19 in Henan Province was 20-69 years old (88.68%). The incidence rate was highest in men aged 30-39 (2.51/ 100 000), while the lowest rate in women aged 0-9 (0.16/100 000). There were 1 225 local patients (96.31%), and the rural patients (45.73%) were slightly higher than the urban patients (44.02%) in Henan Province. A total of 63.60% patients had traveled or lived in Hubei or contacted with people who came from Hubei to Henan. The proportion of patients whose family members suffered from COVID-19 was 32.70%. Global spatial autocorrelation analysis suggested that there was a statistically significant positive correlation in the spatial distribution of COVID-19 patients in Henan Province (Moran's I=0.248, Z=2.955, P<0.01). There are differences in the morbidity and mortality of COVID-19 patients in different areas of Henan Province, with epidemic peak reaching from January 24 to January 28. Henan is dominated by local patients, male patients, and patients with contact history in Hubei. The space appears to be moderately clustered.

Spatial Patterns and Spatial Autocorrelations of Wetland Changes in China During 2003-2013

Wetlands play an important role in maintaining ecosystem functions. Wetlands in China have suffered intensive human disturbance, especially before 2000, resulting in great losses and degradation. Therefore, two national wetland resource surveys were carried out by the Chinese government during 1998-2003 and 2008-2013 to determine the status of wetlands, understand their dynamics, and provide substantial data that can aid scientific wetland conservation. Based on the survey data, the spatial pattern and spatial autocorrelation were explored using the standard deviation ellipse as well as global and local spatial autocorrelation statistics. GIS mapping was employed to display the results via the visualization of the spatial patterns and relationships. Results indicate that:① Changes in the wetlands of China are significant and exhibit obvious regional differences. The center of the ellipse of the total wetlands has moved to the west, and the degree of spatial differentiation between natural wetlands and artificial wetlands is increasing. There is no significant spatial autocorrelation for changes in artificial wetlands. ② The changes in natural wetlands are significantly spatially autocorrelated and clustered, which are identified by global Moran's I and local Moran's I. The hotspots of natural wetland change are concentrated primarily in Qinghai, Tibet, and Sichuan. The individual hotspot is in Inner Mongolia and the cold spot is in Henan. The difference in spatial autocorrelation between natural and artificial wetland changes indicates that natural wetland changes have shown spatial continuity, while artificial wetland changes have shown strong spatial randomness. ③ Some useful spatial associations are used to delineate wetland conservation effects. Then, three major or five minor effective protection management regions are identified. Wetland conservation efforts should be continuously strengthened and improved, especially in the middle-lower Yangtze River region of central China. The use of Moran statistics helps to reveal spatial autocorrelation and identify the conservation effects in wetland changes, which can provide a basis for decision-making in regional wetland conservation and management systems.

Toward Establishing Internal Validity for Correlated Gene Expression Measures in Imaging Genomics of Functional Networks: Why Distance Corrections and External Face Validity Alone Fall Short. Reply to "Distance Is Not Everything in Imaging Genomics of Functional Networks: Reply to a Commentary on Correlated Gene Expression Supports Synchronous Activity in Brain Networks".

The primary claim of the Richiardi et al. (2015) Science article is that a measure of correlated gene expression, significant strength fraction (SSF), is related to resting state fMRI (rsfMRI) networks. However, there is still debate about this claim and whether spatial proximity, in the form of contiguous clusters, accounts entirely, or only partially, for SSF (Pantazatos and Li, 2017; Richiardi et al., 2017). Here, 13 distributed networks were simulated by combining 34 contiguous clusters randomly placed throughout cortex, with resulting edge distance distributions similar to rsfMRI networks. Cluster size was modulated (6–15 mm radius) to test its influence on SSF false positive rate (SSF-FPR) among the simulated “noise” networks. The contribution of rsfMRI networks on SSF-FPR was examined by comparing simulated networks whose clusters were sampled from: (1) all 1,777 cortical tissue samples, (2) all samples, but with non-rsfMRI cluster centers, and (3) only 1,276 non-rsfMRI samples. Results show that SSF-FPR is influenced only by cluster size (r > 0.9, p < 0.001), not by rsfMRI samples. Simulations using 14 mm radius clusters most resembled rsfMRI networks. When thresholding at p < 10–4, the SSF-FPR was 0.47. Genes that maximize SF have high global spatial autocorrelation. In conclusion, SSF is unrelated to rsfMRI networks. The main conclusion of Richiardi et al. (2015) is based on a finding that is ∼50% likely to be a false positive, not <0.01% as originally reported in the article (Richiardi et al., 2015). We discuss why distance corrections alone and external face validity are insufficient to establish a trustworthy relationship between correlated gene expression measures and rsfMRI networks, and propose more rigorous approaches to preclude common pitfalls in related studies.

CO2 emission in transportation sector across 51 countries along the Belt and Road from 2000 to 2014

The transportation sector is a key economic sector and an important source of CO2 emissions. Due to these environmental implications and a desire to reduce emission levels, the number of empirical analyses on the transportation sector have increased significantly in recent times. Given this pretext, our study examines the heterogeneity and spatial autocorrelation CO2 emissions of the transportation sector for 51 belt and road economies from 2000 to 2014. As part of analysis, we examine the heterogeneity of CO2 emissions in the transportation sector through the use of the Theil index and semi-variogram analysis. Furthermore, our study also analyzed the global and local spatial autocorrelation of transport sector CO2 emissions using the Moran index for participating countries. From the analysis, this study found that the transportation CO2 emission intensity of Central and Western Asia and North Africa is significantly higher than that of other regions along the belt and road, and there is a strong spatial correlation in Southeast Asian countries. Our research provides a key reference point for governments by proposing carbon-reduction policies and the promotion of greener developmental initiatives within the transportation sector.

Epigenetic Patterns and Geographical Parthenogenesis in the Alpine Plant Species Ranunculus kuepferi (Ranunculaceae).

Polyploidization and the shift to apomictic reproduction are connected to changes in DNA cytosine-methylation. Cytosine-methylation is further sensitive to environmental conditions. We, therefore, hypothesize that DNA methylation patterns would differentiate within species with geographical parthenogenesis, i.e., when diploid sexual and polyploid apomictic populations exhibit different spatial distributions. On natural populations of the alpine plant Ranunculus kuepferi, we tested differences in methylation patterns across two cytotypes (diploid, tetraploid) and three reproduction modes (sexual, mixed, apomictic), and their correlation to environmental data and geographical distributions. We used methylation-sensitive amplified fragment-length polymorphism (methylation-sensitive AFLPs) and scored three types of epiloci. Methylation patterns differed independently between cytotypes versus modes of reproduction and separated three distinct combined groups (2x sexual + mixed, 4x mixed, and 4x apomictic), with differentiation of 4x apomicts in all epiloci. We found no global spatial autocorrelation, but instead correlations to elevation and temperature gradients in 22 and 36 epiloci, respectively. Results suggest that methylation patterns in R. kuepferi were altered by cold conditions during postglacial recolonization of the Alps, and by the concomitant shift to facultative apomixis, and by polyploidization. Obligate apomictic tetraploids at the highest elevations established a distinct methylation profile. Methylation patterns reflect an ecological gradient rather than the geographical differentiation.

Prediction and Spatial Correlation Analysis of Standard Grain Theoretical Capacity for Land Improvement Based on GIS Technology

China has a large population and a limited area of arable land. In recent years, society has developed rapidly, the area of arable land has gradually decreased, and the issue of food has become a highly regarded issue. With the promulgation of a national policy to adhere to the red line of 1.8 billion acres of arable land, the rational management and improvement of unused and degraded lands will be improved, and the problems will be solved in terms of both arable land area and arable land quality. To sum up, the issue of grain is the issue of yield. The fluctuation of grain yield is the most critical factor. Therefore, the use of GIS technology to analyze and monitor the change in grain yield from cultivated land resources has become a new management of cultivated land resources. And powerful means of optimal use. In this paper, the correlation coefficients of spatial autocorrelation are used to characterize, through the global spatial autocorrelation and local spatial autocorrelation, with the help of statistical yearbook data processing, the theoretical capacity of Shaanxi Province standard grain unit theoretical capacity is predicted and spatial autocorrelation analysis is performed.

A Study on the Factors Affecting Optimal Site of Offshore Wind Farm from the Perspective of Maritime Traffic using Spatial Analysis

At present, interest and technology development in offshore wind generation is rapidly progressing worldwide. Offshore wind farm to be set up on the ocean should be selected in a comprehensive perspective, including wind conditions, economic efficiency, environmental issues and maritime traffic. In this study, spatial analysis was performed based on AIS(Automatic Identification System) data collected in donghae gas plant to select the optimal site for maritime traffic safety in consideration of the intentional relationship between maritime traffic and ship accident. In order to perform the spatial analysis, the safety distance of ships near the plant was analyzed, also ship density and traffic patterns were analyzed through KDE(Kernel Density Estimation) analysis in the study area. To quantify this, ship density and mean speed density are totaled on a grid cell base. A spatial autocorrelation showing correlation between a grid cell including a ship accident and an adjacent grid cell is analyzed by Moran s I. As a result, the global spatial autocorrelation between the ship density and the mean speed density has shown clustered. In addition, local spatial autocorrelation values of grid cells in which ship accidents occurred are analyzed to have occurred frequently in areas where &#57352;&#57581; values of ship density is 26.47 and mean speed density is 4.89, while &#57369;&#57417;&#57352; &#57581; &#57418; values of ship density is 34.46 and mean speed density is 17.06.

Temporal-spatial distribution of tuberculosis in China, 2004-2016

Objective: To analyze the spatial distribution pattern and the cluster spots of tuberculosis (TB) patients in China from 2004 to 2016, so as to provide evidence for prevention and control of the disease. Methods: Using ArcGIS 10.0 software as a platform for data management and presentation, a TB spatial analysis database from 2004 to 2016 was established, and spatial autocorrelation analysis was performed based on the TB epidemics. SaTScan 9.6 software was used for spatiotemporal scanning analysis. Results: From 2004 to 2016, a total of 13 157 794 cases of pulmonary tuberculosis were registered in China, with the mean annual registered incidence rate as 75.90/100 000 (range: 27.95/100 000-180.82/100 000). Through Global spatial autocorrelation studies, the results showed that the distribution of TB incidence was somehow clustered. The result of local Moran's I autocorrelation analysis showed that Xinjiang, Tibet, Guizhou, Guangxi, Hainan provinces were high-high cluster areas, and Beijing, Hebei, Tianjin, Shandong, Jiangsu, and Shanghai provinces were low-low cluster areas. Result from the Getis-Ord General G spatial autocorrelation analysis showed the existence of fifteen "hot spot" regions, of which three "positive hot spots" were Xinjiang, Tibet, and Hainan provinces, and twelve "negative hot spots" were Beijing, Tianjin, Liaoning, Inner Mongolia, Hebei, Shandong, Jiangsu, Anhui, Shanghai, Shanxi, Henan, Jilin provinces. Using the SaTScan 9.6 software, results from the Phased spatial-temporal analysis identified twelve cluster areas, with statistical significances (P<0.05) among them. Conclusions: From 2004 to 2016, tuberculosis epidemics showed an annual downward trend in China. The average annual rates of notification among provinces were not randomly distributed, showing the existence of obvious spatial aggregation. Numbers of areas with clustering nature that noticed through the temporal and spatial scanning technics had gradually decreased. At the same time, progress had been made in TB control programs, despite the existence of high-risk areas. Development of more strict and targeted prevention and control measures are called for.

The impact of foreign direct investment on urban PM2.5 pollution in China

The hypothesis of “Pollution Heaven” or “Pollution Halo” has, for some time, been one of the central issues in environmental economics. There is a controversy in the conclusions with regards to China, it thus needs further empirical testing. Based on 2003 to 2016 statistical data on 285 Chinese cities, this paper uses a dynamic spatial panel model to empirically analyze the impact of foreign direct investment (FDI) on PM2.5 pollution. The results demonstrate that urban PM2.5 pollution shows both significant global spatial autocorrelation and local spatial agglomeration effects. Overall, FDI significantly aggravates China's urban PM2.5 pollution, thus confirming the “Pollution Heaven” hypothesis. This effect, however, depends on the stage of urban economic development. Although FDI has no significant effect on urban PM2.5 pollution in the initial stage of industrialization, it does aggravate urban PM2.5 pollution in the midterm stage. In the later period of industrialization, FDI actually improves urban PM2.5 pollution, but the effect of this improvement is relatively weak. Furthermore, PM2.5 pollution shows significant spatial spillover and dynamic effects. It follows that both joint prevention and control and continuous efforts must be made to control PM2.5 pollution.

Epidemic cystic and alveolar echinococcosis in Kyrgyzstan: an analysis of national surveillance data

Human cystic and alveolar echinococcosis are among the priority neglected zoonotic diseases for which WHO advocates control. The incidence of both cystic echinococcosis and alveolar echinococcosis has increased substantially in the past 30 years in Kyrgyzstan. Given the scarcity of adequate data on the local geographical variation of these focal diseases, we aimed to investigate within-country incidence and geographical variation of cystic echinococcosis and alveolar echinococcosis at a high spatial resolution in Kyrgyzstan. We mapped all confirmed surgical cases of cystic echinococcosis and alveolar echinococcosis reported through the national echinococcosis surveillance system in Kyrgyzstan between Jan 1, 2014, and Dec 31, 2016, from nine regional databases. We then estimated crude surgical incidence, standardised incidence, and standardised incidence ratios (SIRs) of primary cases (ie, excluding relapses) based on age and sex at country, region, district, and local community levels. Finally, we tested the SIRs for global and local spatial autocorrelation to identify disease hotspots at the local community level. All incidence estimates were calculated per 100 000 population and averaged across the 3-year study period to obtain annual estimates. The surveillance system reported 2359 primary surgical cases of cystic echinococcosis and 546 primary surgical cases of alveolar echinococcosis. Country-level crude surgical incidence was 13·1 per 100 000 population per year for cystic echinococcosis and 3·02 per 100 000 population per year for alveolar echinococcosis. At the local community level, we found annual crude surgical incidences up to 176 per 100 000 population in Sary-Kamysh (Jalal-Abad region) for cystic echinococcosis and 246 per 100 000 population in Uch-Dobo (Alay district, Osh region) for alveolar echinococcosis. Significant hotspots of cystic echinococcosis were found in four regions: Osh (five local communities in Uzgen district and four in Alay district), Naryn (three local communities in Jumgal district and one in Naryn district), Talas (three local communities in Talas district), and Chuy (one local community in Jayyl district). Significant alveolar echinococcosis hotspots were detected in the Osh region (11 communities in Alay district, including the local community of Sary Mogol, and one in Chong-Alay district) and in the Naryn region (five communities in Jumgal district and three in At-Bashy district), in the southwest and centre of the country. Our analyses reveal remarkable within-country variation in the surgical incidence of cystic echinococcosis and alveolar echinococcosis in Kyrgyzstan. These high-resolution maps identify precise locations where interventions and epidemiological research should be targeted to reduce the burden of human cystic echinococcosis and alveolar echinococcosis. Swiss National Science Foundation.

Geographic Association Between Incidence of Acute Appendicitis and Socioeconomic Status

Some studies based on proportions of patients with perforated appendicitis (PA) among all patients with acute appendicitis (AA) have found an association between socioeconomic status (SES) and risk of perforation. A potential limitation is their use of proportions, which assumes that incidence of AA is evenly distributed across populations at risk. This assumption may be invalid, and SES may have a more complex association with both AA and PA. To generate population-based incidences of AA and PA and to examine geographic patterns of incidence alongside geographic patterns of SES. Retrospective study of data from Washington's Comprehensive Hospital Abstract Reporting System and the 2010 US census. Geographic methods were used to identify patterns of age- and sex-standardized incidence in Washington State between 2008 and 2012. The study included all patients discharged with International Classification of Diseases, Ninth Revision codes for AA or PA. Data were analyzed between November 2016 and December 2018. Location of primary residence. Age- and sex-standardized incidence for AA and PA was generated for each census tract (CT). Global spatial autocorrelation was examined using Moran index (0.0 = completely random incidence; 1.0 = fully dependent on location). Clusters of low-incidence CTs (cold spots) and high-incidence CTs (hot spots) were identified for AA. Census-based SES data were aggregated for hot spots and cold spots and then compared. Statewide, over the 5-year study period, there were 35 730 patients with AA (including 9780 cases of PA), of whom 16 574 were women (46.4%). Median age of the cohort was 29 years (IQR, 16-48 years). Statewide incidence of AA and PA was 106 and 29 per 100 000 person-years (PY), respectively. Crude incidence was higher within the male population and peaked at age 10 to 19 years. Age- and sex-standardized incidence of AA demonstrated significant positive spatial autocorrelation (Moran index, 0.30; P < .001), but autocorrelation for PA was only half as strong (0.16; P < .001). Median incidence of AA was 118.1 per 100 000 PY among hot spots vs 86.2 per 100 000 PY among cold spots (P < .001). Socioeconomic status was higher in cold spots vs hot spots: mean proportion of college-educated adults was 56% vs 26% (P < .001), and mean per capita income was $44 691 vs $30 027 (P < .001). Age- and sex-standardized incidence of appendicitis is not randomly distributed across geographic subunits, and geographic clustering of AA is twice as strong as PA. Socioeconomic advantages, such as higher income and secondary education, are strongly associated with lower incidence of AA. These findings challenge conventional views that AA occurs randomly and has no predisposing characteristics beyond age/sex. Socioeconomic status, and likely other geographically circumscribed factors, are associated with incidence of AA.

The association between internal migration and pulmonary tuberculosis in China, 2005\u20132015: a spatial analysis

BackgroundInternal migration places individuals at high risk of contracting tuberculosis (TB). However, there is a scarcity of national-level spatial analyses regarding the association between TB and internal migration in China. In our research, we aimed to explore the spatial variation in cases of sputum smear-positive pulmonary TB (SS + PTB) in China; and the associations between SS + PTB, internal migration, socioeconomic factors, and demographic factors in the country between 2005 and 2015.MethodsReported cases of SS + PTB were obtained from the national PTB surveillance system database; cases were obtained at the provincial level. Internal migration data were extracted from the national population sampling survey and the census. Spatial autocorrelations were explored using the global Moran’s statistic and local indicators of spatial association. The spatial temporal analysis was performed using Kulldorff’s scan statistic. Fixed effects regression was used to explore the association between SS + PTB and internal migration.ResultsA total of 4 708 563 SS + PTB cases were reported in China between 2005 and 2015, of which 3 376 011 (71.7%) were male and 1 332 552 (28.3%) were female. There was a trend towards decreasing rates of SS + PTB notifications between 2005 and 2015. The result of global spatial autocorrelation indicated that there were significant spatial correlations between SS + PTB rate and internal migration each year (2005–2015). Spatial clustering of SS + PTB cases was mainly located in central and southern China and overlapped with the clusters of emigration. The proportions of emigrants and immigrants were significantly associated with SS + PTB. Per capita GDP and education level were negatively associated with SS + PTB. The internal migration flow maps indicated that migrants preferred neighboring provinces, with most migrating for work or business.ConclusionsThis study found a significant spatial autocorrelation between SS + PTB and internal migration. Both emigration and immigration were statistically associated with SS + PTB, and the association with emigration was stronger than that for immigration. Further, we found that SS + PTB clusters overlapped with emigration clusters, and the internal migration flow maps suggested that migrants from SS + PTB clusters may influence the TB epidemic characteristics of neighboring provinces. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migrants.

Spatial autocorrelation of breast cancer mortality in the Metropolitan Region, Chile: an ecological study

Breast cancer is the most common malignancy in women worldwide and Chile, being the leading cause of female cancer death. A wide variation in mortality has been reported, with geographic clusters of higher risk. To spatially analyze mortality from breast cancer in women in the Metropolitan Region in 2015. Ecological study of location. We used death records in 2015 (C50 according to ICD10) and population projections of the Statistics Institute to estimate mortality rates. We calculated crude breast cancer mortality rates and standardized mortality ratios and performed a spatial epidemiological analysis of breast cancer mortality in women, estimating the global and local Moran I index to assess spatial autocorrelation. We present the results in maps according to the 2016 pre-census cartography. There were 622 deaths from breast cancer in the Metropolitan Region in 2015. The mean age was 66 years (SD: 15.5). 92.4% of deaths were registered in urban or central areas. However, the highest mortality rates were observed in peripherical districts. No global spatial autocorrelation was observed in the region (Morans I 0.007 p = 0.134). However, at the local level, four districts differ significantly from their neighbors. The risk of dying from breast cancer in the Metropolitan Region of Chile is concentrated in women from peripherical communes. Four districts in the region present different risks from their neighboring districts. It is necessary to investigate local realities to prevent deaths from this pathology.

Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge

Dispersal and nesting philopatry are two processes that affect the connectivity, evolution, and long-term viability of populations, and thus have important conservation implications for threatened and endangered species. Here we investigate dispersal, relatedness, and the fine-scale spatial genetic structure of Eastern Box Turtles (Terrapene carolina carolina) at the northern extreme of their geographic range in northwestern Michigan. We analyzed georeferenced microsatellite genotypes (n = 165) using global, sex-specific, and two-dimensional local spatial autocorrelation (2D LSA), as well as spatial principal components analysis (sPCA). Genetic diversity was low relative to Eastern Box Turtle populations in the middle of the range. We found dispersal was male-biased, as only females showed significant positive spatial genetic autocorrelation at distances less than 2 km. 2D LSA showed local genetic “hotspots” of related turtles that tended to correspond with known nesting areas. We found evidence for global genetic structure using sPCA, which we attribute to genetic clustering rather than clinal variation. Our results suggest that restricted female dispersal and fidelity to limited open-canopy nest sites result in fine-scale spatial genetic structuring in this population. We stress the importance of maintaining high quality nesting habitat and habitat corridors for transient males, which appear to be critical for functional connectivity of Eastern Box Turtles.

Geographical Disparities in HIV Prevalence Among Men Who Have Sex with Men and People Who Inject Drugs in Nigeria

Background: Assessment of geographical heterogeneity of HIV among men who have sex with men (MSM) and people who inject drugs (PWID) can usefully inform targeted HIV prevention and care strategies. We aimed to measure HIV prevalence and identify hotspots of HIV infection among MSM and PWID in Nigeria. Methods: We included all MSM and PWID accessing HIV testing services across seven prioritized states (Lagos, Nasarawa, Akwa Ibom, Cross Rivers, Rivers, Benue and the Federal Capital Territory) in three geographic regions (North Central, South South, South West) between Oct 1, 2016 and Sept 30, 2017. We extracted data from national testing registers, georeferenced all HIV test results aggregated at the level of Local Government Areas (LGAs), and calculated HIV prevalence. We calculated and compared HIV prevalence from our study to the integrated biological and behavioral surveillance survey (IBBSS) 2014 and used global spatial autocorrelation and hotspot analysis to highlight patterns of HIV infection, and to identify areas of significant clustering of HIV cases. Findings: A positive HIV test was reported in 12.1% (95%CI 9.7-13.1) and 11.8% (95%CI 9.3-12.7) of the 26,423 MSMs and 9,474 PWIDs, respectively. Global spatial autocorrelation Moran's I statistics revealed a clustered distribution of HIV infection among MSMs and PWIDs with a <5% and <1% likelihood that this clustered pattern could be due to chance respectively. Significant clusters of HIV infection (Getis-Ord-Gi* statistics) confined to the North Central, South-South regions were identified among MSM and PWID. Compared to the 2014 IBBSS our results suggest an increased HIV prevalence among PWID and a substantial decrease among MSM. Interpretation: This study identified geographical areas to prioritize for control of HIV infection among MSM and PWID, thus demonstrating that geographical information system technology is a useful tool to inform public health planning for interventions for epidemic control of HIV infection. Funding Statement: Data used for this study was collected from Key Population program in Nigeria through PEPFAR/USAID. OK was funded by the Swiss National Science Foundation (grant no 163878). Declaration of Interests: The authors report no financial or non-financial competing interests. Ethics Approval Statement: Informed consent was obtained for all clients who were tested for HIV in line with the Nigeria HTS policy. Ethical approval was obtained from the Federal Capital Territory, Health Research Ethics Committee, Nigeria (Approval Number: FHREC/2019/01/122/23-12-19). This study only analyzed anonymized and de-identified data.

Linking ecological efficiency and the economic agglomeration of China based on the ecological footprint and nighttime light data

Abstract As natural resources are becoming one of the factors hindering economic development, the utilization efficiency of natural resources should be improved and ecological stress should be reduced to ensure sustainable economic development. In this study, the ecological stress index and ecological efficiency were quantified using the ecological footprint model to describe the current status of sustainability and utilization efficiency of natural resources. The economic agglomeration was determined by conducting global spatial autocorrelation analysis using Defense Meteorological Program/Operational Line-Scan System (DMSP/OLS) nighttime light data. The relationship between economic agglomeration and ecological efficiency of China was then illustrated in a four-partite graph, and the results show that (1) the per-capita ecological footprints vary between the different provinces; however, the composition of the ecological footprint is similar between the provinces, and demonstrates the demand for fossil energy land is highest, while that for fishing ground is lowest. (2) All provinces are facing ecological overload, excluding Qinghai, and Shanghai, Tianjin, and Beijing are enduring the most severe ecological overload. (3) The ecological efficiency differs greatly between the different provinces of China, and the ecological efficiency values tend to decrease from the eastern coast to the inland region. (4) The economic activities in every province of China are spatially agglomerated, and the degree of agglomeration differs significantly. (5) There is a positive correlation between economic agglomeration and ecological efficiency, indicating that promoting economic agglomeration is an effective method of improving the utilization efficiency of natural resources. The relationship between economic agglomeration and ecological efficiency observed in this paper will provide a reference for optimizing the spatial distribution of economic activities and a theoretical basis for synchronizing environmental protection with economic development in China.

The role of interregional relationships in research talent development

The relevance of research. Workforce quality is paramount to the development of innovative economy and socio-economic development of territorial systems. Not all regions, however, are able to train sufficient R&amp;D personnel to meet the needs of their innovative economies. The lack of research talent can be compensated by establishing cooperative relationships with other territorial systems. Therefore, it is important to study the existing interregional interconnections in the development of research talent and to identify the key priorities in this sphere. The aim of the study is to demonstrate the relationship between the indicators of development of research talent in different regions and their innovative activity. Data and Methods. The study uses spatial econometric modeling tools and methods for calculating global and local spatial autocorrelation indices of Moran P. and their dispersion diagrams. The spatial autocorrelation was calculated by using a standardized matrix of distances along the roads between the regional administrative centers. As a result of the analysis, a close relationship was found between the indicators of development of research talent in Russian regions and their innovative activity. The constructed regression model based on spatial data lead us to the conclusion that efficient innovative development requires a pool of STEM talent in the regions, which means that it is necessary to provide sufficient opportunities for training and education in this sphere. Conclusions. The study of the interconnections between the regions using the improved method of spatial autocorrelation of P. Moran revealed a cluster of closely interconnected regions (Moscow - St. Petersburg - Moscow region - Nizhny Novgorod region - Ryazan region - Ivanovo region - Tver region - Kostroma region - Tula region) and three potential clusters: ‘Volga’, ‘Ural’, and ‘Siberia’.

Human Development Dynamics across Districts of Indonesia: A Study of Regional Convergence and Spatial Approach

Indonesia is an archipelago country which comprises of two main parts, western and eastern regions and spread into over 500 districts. Each district has their own characteristics, especially in development aspect. Some districts have been growing faster on economic and social development, yet others still fall behind. Using Human Development Index and its components on education, health and economic variables over 2010- 2018 period, this study aims to examine convergence on the regional human growth process and investigate the speed of convergence across districts. The result reveals convergence occurred on human development process and its determinants across districts during 2010-2018. Education variables are assumed as the main contributor for boosting the speed of convergence of human development. Spatial dependences are detected among districts, followed by the spatial clusters and spatial outliers through global and local spatial autocorrelation. Applying two spatial autoregressive models, spatial autoregressive lag model (SAR) and spatial autoregressive error model (SEM), confirmed that there is significant spatial spill-overs.The speed of convergence for all variables are much declining after the inclusion of spatial lag and error model. As the policy implication, since regional inequality in term of human development is still a major issue, it will be a call for better coordination and cooperation within and between regions.

The role of interregional relationships in research talent development

The relevance of research. Workforce quality is paramount to the development of innovative economy and socio-economic development of territorial systems. Not all regions, however, are able to train sufficient R&amp;D personnel to meet the needs of their innovative economies. The lack of research talent can be compensated by establishing cooperative relationships with other territorial systems. Therefore, it is important to study the existing interregional interconnections in the development of research talent and to identify the key priorities in this sphere. The aim of the study is to demonstrate the relationship between the indicators of development of research talent in different regions and their innovative activity. Data and Methods. The study uses spatial econometric modeling tools and methods for calculating global and local spatial autocorrelation indices of Moran P. and their dispersion diagrams. The spatial autocorrelation was calculated by using a standardized matrix of distances along the roads between the regional administrative centers. As a result of the analysis , a close relationship was found between the indicators of development of research talent in Russian regions and their innovative activity. The constructed regression model based on spatial data lead us to the conclusion that efficient innovative development requires a pool of STEM talent in the regions, which means that it is necessary to provide sufficient opportunities for training and education in this sphere. Conclusions. The study of the interconnections between the regions using the improved method of spatial autocorrelation of P. Moran revealed a cluster of closely interconnected regions (Moscow - St. Petersburg - Moscow region - Nizhny Novgorod region - Ryazan region - Ivanovo region - Tver region - Kostroma region - Tula region) and three potential clusters: ‘Volga’, ‘Ural’, and ‘Siberia’.

Spatial Analysis and Risk Assessment Model Research of Arthritis Based on Risk Factors: China, 2011, 2013 and 2015

Arthritis is a public health issue that is of global concern. Arthritis is one of the chronic diseases with a high incidence of middle-aged and older adults. The patients have paid a heavy price for this and caused a substantial economic burden on society. In this study, we used spatial autocorrelation, spatial cluster analysis, multiple logistic regression, and random forest models to analyze the spatial distribution and possible risk factors for arthritis in elderly Chinese and assess arthritis risk. Global spatial autocorrelation analysis and significance test results show that Moran's I of arthritis spatial autocorrelation in 2011, 2013, and 2015 are statistically significant, so there is significant spatial autocorrelation three years. The results of local spatial autocorrelation and spatial clustering analysis show that the aggregation areas of arthritis patients are mainly in the southwest, northwest, and central China. Multivariate logistic regression analysis showed that gender, age, education level, Body Mass Index (BMI), Center for Epidemiologic Studies Depression Scale score (CES-D), altitude, region, weather temperature, hypertension, lung, liver, heart, stroke, digestive, and kidney disease were all arthritis affects factors (P <; 0.05). Compared with the multi-factor Logistic regression model, the random forest model better assesses performance and higher fit. The fitting accuracy is 82.2% in the random forest model, which is better than the multi-factor Logistic regression model (66.6%). According to the assessment risk map generated by the random forest model, Northeast, Southwest, Northwest, South, and Central are high-risk areas for arthritis. These results provide benchmark data for the control and prevention of arthritis diseases.