Getis-Ord Gi Research Articles

Spatial distribution of zero-dose children in Ethiopia: evidence for a targeted intervention from a large-scale cross-sectional evaluation survey.

Ethiopia is the fourth leading contributor to the global total of zero-dose children (those who lack the first dose of diphtheria-tetanus-pertussis containing vaccine) and has substantial regional variations in zero-dose children. This study explored the spatial pattern of zero-dose children aged 12-35 months in Ethiopia. A survey was conducted in pastoralist regions, developing regions, newly-established regions, conflict-affected areas, underserved urban populations, hard-to-reach areas, internally displaced populations, and refugees. Spatial autocorrelation was measured using the Global Moran'sIstatistic. Getis-Ord Gi* statistics was applied to calculate the spatial variability of the high and low prevalence rates of zero-dose children. The spatial interpolation technique was also applied to estimate unknown values that fall between known values. Inverse distance weighting interpolation method was used to predict the risk of zero-dose children. ArcGIS version 10.8 was used for the spatial analysis. A total of 3,646 children aged 12-35 months were included in the study. The spatial distribution of zero-dose children in Ethiopia was non-random (Global Moran'sI = 0.178971, p < 0.001). According to the hotspot analysis, western, eastern and northern parts of Somali and western and central parts of Afar regions had the highest load of zero-dose children (hotspot areas) followed by the Northeastern part of Amhara and southeastern part of Oromia regions. On the other hand, Southern Nations, Nationalities, and Peoples, Sidama, and the Eastern part of the Southwest Ethiopia peoples regions were identified as cold spot areas. The spatial interpolation analysis corresponded with the hotspot analysis results where western and central parts of Afar and western, eastern and northern parts of Somali regions were identified as high-risk areas for zero-dose children. However, Addis Ababa, Dire Dawa, Harari, Southern Nations, Nationalities, and Peoples, Sidama, Southwest Ethiopia Peoples, and parts of Oromia were found to be low-risk areas for zero-dose children. The spatial analysis identified that zero-dose children had a significant spatial variation across the study areas. High clusters of zero-dose children were detected in Afar and Somali regions. Implementing routine and mop-up vaccination campaigns in the identified hotspot areas will help Ethiopia to improve coverage and reduce immunization inequalities.

Identification of high lead exposure locations in Ohio at the census tract scale using a generalizable geospatial hotspot approach

BackgroundLead is a persistent, ubiquitous pollutant whose historical sources have been largely addressed through regulation and voluntary actions. The United States (U.S.) has achieved significant decreases in children’s blood lead levels (BLL) over the past 40 years; however, there is no known safe level of Pb exposure. Some communities continue to be disproportionately impacted by exposure to Pb, including Black children and families living in older homes.ObjectiveTo identify Ohio (OH) census tracts with children exposed to Pb and evaluate potential exposure determinants.MethodsWe obtained individual children’s blood Pb data from 2005–2018 in OH. The percent of children with elevated BLL (EBLL) was calculated for OH census tracts using three blood Pb reference values (3.5, 5, and 10 µg/dL). Getis-Ord Gi* geospatial hotspot or top 20th percentile methodologies were then applied to identify “hotspots.” Findings across multiple time periods and blood Pb reference values were evaluated and compared with existing Pb exposure indices and models.ResultsConsistency was observed across different blood Pb reference values, with the main hotspots identified at 3.5 µg/dL, also identified at 5 and 10 µg/dL. Substantial gains in public health were demonstrated, with the biggest decreases in the number of census tracts with EBLL observed between 2008–2010 and 2011–2013. Across OH, 355 census tracts (of 2850) were identified as hotspots across 17 locations, with the majority in the most populated cites. Generally, old housing and sociodemographic factors were indicators of these EBLL hotspots. A smaller number of hotspots were not associated with these exposure determinants. Variables of race, income, and education level were all strong predictors of hotspots.Impact statementThe Getis-Ord Gi* geospatial hotspot analysis can inform local investigations into potential Pb exposures for children living in OH. The successful application of a generalizable childhood blood Pb methodology at the census tract scale provides results that are more readily actionable. The moderate agreement of the measured blood Pb results with public Pb indices provide confidence that these indices can be used in the absence of available blood Pb surveillance data. While not a replacement for universal blood Pb testing, a consistent approach can be applied to identify areas where Pb exposure may be problematic.

County Town Comprehensive Service Functions in China: Measurement, Spatio-Temporal Divergence Evolution, and Heterogeneity of Influencing Factors

Strengthening the service function of small towns, using its fundamental role in the urban system to drive rural development, is the main issue that needs to be addressed urgently in numerous developing countries. County towns are unique types of small towns in China. Analyzing the spatial-temporal patterns and differentiation mechanisms of comprehensive service functions of county towns in China from a geographic point of view can not only provide a basis for the macro-control of county towns but also provide typical regional research results for the study of urban systems and urban–rural coordination in developing countries. Based on Point of Interest (POI) data of 1788 county towns in China, this study analyzes the evolution of spatial and temporal differentiation of comprehensive service functions and influencing factors by using modeling methods such as Getis-Ord Gi* analysis, the random forest model, and Multiscale Geographically Weighted Regression (MGWR). The obtained results show that (1) from 2012 to 2021, the average value of the comprehensive service function index (CSFI) of county towns in China shows a significant increase, and the proportion of county towns with medium–high service levels and above increases from 3.41% to 54.50%; (2) spatially, the comprehensive service function of county towns is characterized by the basic pattern of “high east, low west; high south, low north”, which keeps getting stronger. During the study period, eastern China has always been a high-level region, northwestern and southwestern China have always been low-level regions, and northeastern China has been a stagnant region, while central, northern, and southern China have been fast-growing regions; (3) county general public budget revenues, value added of secondary industry, GDP per capita, county town resident population, altitude, and GDP per capita of affiliated prefecture-level cities to which it belongs are the key factors influencing the comprehensive service function of county towns in China. The county general public budget revenue indicator, which represents the governmental capacity, has the strongest influence; and (4) the results of the MGWR analysis indicate that there is spatial and temporal heterogeneity in the intensity of the above-mentioned key influencing factors on the development of comprehensive service functions of county towns in China. Based on this finding, differentiated strategies should be proposed to policy makers and urban planners in different regions in order to effectively enhance the level of comprehensive service functions of county towns in China.

Individual and Geospatial Determinants of Health Associated With School-Based Human Papillomavirus Immunization in Alberta: Population-Based Cohort Study.

Human papillomavirus (HPV) infection causes nearly all cervical cancer cases and is a cause of anogenital and oropharyngeal cancers. The incidence of HPV-associated cancers is inequitable, with an increased burden on marginalized groups in high-income countries. Understanding how immunization status varies by material and social deprivation, health system, and geospatial factors is valuable for prioritizing and planning HPV immunization interventions. The objective of this study was to describe school-based HPV immunization rates by individual and geospatial determinants of health in Alberta, Canada. Health administrative data for male and female individuals born in 2004 in Alberta were used to determine HPV immunization status based on age and the number of doses administered in schools during the 2014/2015-2018/2019 school years. Immunization status and its relationship with material and social deprivation and health system factors were assessed by a logistic regression model. Geospatial clustering was assessed using Getis-Ord Gi* hot spot analysis. Mean scores of material and social deprivation and health system factors were compared between hot and cold spots without full HPV immunization using independent samples t tests. A multidisciplinary team comprising researchers and knowledge users formed a co-design team to design the study protocol and review the study results. The cohort consisted of 45,207 youths. In the adjusted model, the odds of those who did not see their general practitioner (GP) within 3 years before turning 10 years old and not being fully immunized were 1.965 times higher (95% CI 1.855-2.080) than those who did see their GP. The odds of health system users with health conditions and health system nonusers not being fully immunized were 1.092 (95% CI 1.006-1.185) and 1.831 (95% CI 1.678-1.998) times higher, respectively, than health system users without health conditions. The odds of those who lived in areas with the most material and social deprivation not being fully immunized were 1.287 (95% CI 1.200-1.381) and 1.099 (95% CI 1.029-1.174) times higher, respectively, than those who lived in areas with the least deprivation. The odds of those who lived in rural areas not being fully immunized were 1.428 times higher (95% CI 1.359-1.501) than those who lived in urban areas. Significant hot spot clusters of individuals without full HPV immunization exist in rural locations on the northern and eastern regions of Alberta. Hot spots had significantly worse mean material deprivation scores (P=.008) and fewer GP visits (P=.001) than cold spots. Findings suggest that material and social deprivation, health system access, and rural residency impact HPV immunization. Such factors should be considered by public health professionals in other jurisdictions and will be used by the Alberta co-design team when tailoring programs to increase HPV vaccine uptake in priority populations and regions.

Spatial analysis of American cutaneous leishmaniasis in the state of Amazonas.

To evaluate, using spatial analysis, the occurrence of American Cutaneous Leishmaniasis (ACL) and analyze its association with the municipal human development index (MHDI) and deforestation in the state of Amazonas, Brazil, from 2016 to 2020. This ecological study, carried out from January 2016 to December 2020, included the 62 municipalities of the state of Amazonas. The incidence rate of ACL was determined in space and time. Using Multiple Linear Regression by Ordinary Least Squares (OLS) and Spatial Autoregressive Regression (SAR) models, the relationship between incidence rates and Human Development Index (HDI) and deforestation was analyzed., The high- and low-risk clusters were identified by employing the Getis-Ord Gi* statistic. A total of 7,499 cases of ACL were registered in all 62 municipalities in the state. Most cases were in male (n=5,924; 79.24%), with the greatest frequency in the population aged from 20 to 39 years (n=3,356; 44.7%). The incidence rate in the state of Amazonas was 7.34 cases per 100,000 inhabitants-year, with the municipalities of Rio Preto da Eva and Presidente Figueiredo showing the highest rates (1,377.5 and 817.5 cases per 100,000 population-year, respectively). The ACL cases were clustered into specific areas related to those municipalities with the highest incidence rates. The SAR model revealed a positive relationship between ACL and deforestation. The occurrence of ACL was evident in a variety of patterns in the state of Amazonas; the high incidence rates and persistence of this disease in this state were linked to deforestation. The temporal distribution showed variations in the incidence rates during each year. Our results can help optimize the measures needed to prevent and control this disease in the state.

Low Measles Vaccination Coverage and Spatial Analysis of High Measles Vaccination Dropout in Ethiopia's Underprivileged Areas.

(1) Background: Measles remains a major cause of disease and death worldwide, especially in the World Health Organization African Region. This study aimed to estimate the coverage of measles vaccinations and map the spatial distribution of measles vaccination dropout in Ethiopia; (2) Methods: A cross-sectional survey was conducted in Ethiopia's underprivileged areas. The study included 3646 mothers/caregivers of children. ArcGIS for the spatial analysis, Global Moran's I statistic for spatial autocorrelation, and Getis-Ord Gi* statistics for hot spot analysis were applied; (3) Results: Overall, coverages of measles-containing-vaccine first- and second-doses were 67% and 35%, respectively. Developing regions had the lowest coverages of measles-containing-vaccine first- and second-doses, 46.4% and 21.2%, respectively. On average, the measles vaccination dropout estimate was 48.3%. Refugees had the highest measles vaccination dropout estimate (56.4%). The hot spot analysis detected the highest burden of measles vaccination dropout mainly in the northeastern parts of Ethiopia, such as the Afar Region's zones 1 and 5, the Amhara Region's North Gondar Zone, and peripheral areas in the Benishangul Gumuz Region's Assosa Zone; (4) Conclusions: The overall measles vaccination coverages were relatively low, and measles vaccination dropout estimates were high. Measles vaccination dropout hot spot areas were detected in the northeastern parts of Ethiopia.

The Application of Geographic Information System in Analysing the Voting Patterns among Dayak Voters in the Sarawak State Elections of 2016 and 2021

Geographic information system (GIS) and election-related research focuses on the geographical characteristics of election boundaries, the election information management system and the application of GIS analysis to election boundaries. This article aims to acquire a deeper understanding of the issues affecting Dayak voters during the state elections of 2016 and 2021, geographically. This study employs three spatial analyses: Thematic Map-Density, Spatial Autocorrelation Moran’s I Index and Hot Spot Analysis (Getis-Ord Gi*). In select constituencies with a Dayak-majority, interviews and observations supplemented the spatial data. This article examines Dayak-majority constituencies’ geographical distribution and spatial concentration in the 2016 and 2021 elections. It demonstrates that there are significant differences in the density of voter participation, majorities obtained by candidates, and total votes cast by the electorate across the state in both state elections, confirming the assertion made by researchers of electoral politics in Sarawak that election issues are primarily location-specific and that understanding the problems faced by communities at the local level is essential. It is anticipated that the outcome of this study will aid in providing a spatial overview and projection of state election results and in strategising the future management of state elections.

Analysis of maritime piracy trends and patterns using spatial autocorrelation in Africa

ABSTRACT Many studies have analyzed causation factors for piracy, but failed to quantitatively examine how piracy trends in regions have changed. The research aimed to establish the changing patterns of maritime piracy in Africa. The study utilized world piracy data from the National Geospatial Intelligence Agency, which was analyzed using spatial auto-correlation tools. Getis-Ord Gi* statistic identified piracy clusters and hot spot comparison tool compared the hot spot layers in East and West Africa. Autocorrelation analysis results suggest changing frequency of piracy incidents in the study areas before and after 2012. The mean Getis-Ord Gi* values for East Africa were 0.35946 and 0.07839 before and after 2012, illustrating agreater change. However, West Africa mean values were 0.60917 and 0.43408 pre and post 2012, suggesting minimal change. The comparison analysis results generated a smaller similarity value for East Africa (0.43350) and a larger index for West Africa (0.9867). West Africa recorded many incidents in the study period; hence, piracy intensity was almost similar. The study revealed high similarities in piracy events in West Africa, and low similarities in East Africa pre and post 2012. These have implications for understanding the changing dynamics of maritime piracy in Africa, and asserting spatial analysis.

Spatial Heterogeneity of Nontuberculous Mycobacterial Pulmonary Disease in Shanghai: Insights from a Ten-Year Population-Based Study

ObjectiveTo investigate the spatial heterogeneity of nontuberculous mycobacterial pulmonary disease (NTM-PD) in Shanghai. MethodsA population-based retrospective study was conducted using presumptive pulmonary tuberculosis surveillance data of Shanghai between 2010 and 2019. The study described the spatial distribution of NTM-PD notification rates, employing hierarchical Bayesian mapping for high-risk areas and the Getis-Ord Gi* statistic to identify hot spots and explore associated factors. ResultsOf 1652 NTM-PD cases, the most common species was Mycobacterium kansasii complex (MKC) (41.9%), followed by Mycobacterium avium complex (MAC) (27.1%) and Mycobacterium abscessus complex (MABC) (16.2%). MKC-PD patients were generally younger males with a higher incidence of pulmonary cavities, while MAC-PD patients were more often farmers or had a history of tuberculosis treatment. MKC-PD hot spots were primarily located in the areas alongside the Huangpu River, while MAC-PD hot spots were mainly in the western agricultural areas. Patients with MKC-PD and MAC-PD exhibited a higher risk of spatial clustering compared to those with MABC-PD. ConclusionsDifferent types of NTM-PD exhibit distinct patterns of spatial clustering and are associated with various factors. These findings underscore the importance of environmental and host factors in the epidemic of NTM-PD.

Exploring Spatial Accessibility to Urban Activities Based on the Transit-Oriented Development Concept in Pathum Thani, Thailand

Transit-oriented development (TOD) serves as a model for sustainable urban planning, integrating land use and transport planning. Successful implementation varies across specific geographic locations and has yet to be fully realized in the suburban areas of Thailand. This study empirically examined and searched for understanding of the enhanced accessibility to urban activities through the TOD concept by focusing on bus stops and rail mass transit. The study utilized a network buffer zone approach around transit areas as TOD measurement units, examining distances of 500 m, 1000 m, and 2000 m. Spatial analysis was applied to examine and understand the enhanced accessibility to urban activities through TOD by using network analysis, Getis-Ord Gi* hotspot analysis, and bivariate local Moran’s I. The results revealed that this area still has limited access to activities via public transport, particularly in the areas where activities are concentrated, especially in commercial, mixed-use, and residential zones. However, upon examining the relationship between access distance and the intensity of land use activities, it became apparent that within the network buffer zone encircling the transit areas, designated as transit-oriented development (TOD) measurement units, there exists a notable concentration and diversity of land use activities. Specifically, enhanced accessibility to the transportation system corresponded to increased activity density. Nonetheless, this correlation was predominantly observed at stations situated in more central areas, whereas stations located at greater distances exhibited a lower intensity and diversity of activities within the TOD zone.

Response of ecosystem service values to land use change, 2002–2021

Ecosystems in inland river basins are crucial for maintaining socioeconomic stability in arid regions. As a result, an essential tool for tracking ecosystem changes is the measurement of ecosystem service value (ESV). Using land use changes in the Aksu River Basin (ARB) from 2002 to 2021 as an example, the response of land use variations to the ESV in the basin was examined. Using the equivalency coefficients of ecosystem service values adapted for the specific Chinese context, nine different types of ecosystem service values were assessed using the Getis-Ord Gi* statistical technique and Spearman rank correlation analysis. The findings revealed that (1) the pattern of land use change in the ARB has changed significantly over the past 20 years, with grassland and unused land being the dominant land types in the ARB, both accounting for more than 74 % of the total area of the study area. Changes in dynamics were more pronounced for each land use type, with all land use types exhibiting positive dynamics, except for grassland and unused land, which exhibited negative dynamics. (2) The total ESV in the study area increased from 48.06 billion yuan in 2002 to 52.59 billion yuan in 2011 and then decreased to 49.37 billion yuan in 2021. Grassland was the main ecological land type, and the total ESV showed an increasing and then a decreasing trend. (3) There was clear geographical and temporal variation in the ESV distribution, with hotspots primarily located in the northern section of the ARB and coldspots primarily dispersed in the east-central region. (4) Each land use type's sensitivity index was less than 1, showing that the ecological value coefficient (VC) had a small impact on ESV. Policymakers should be aware of the significant effects that land use changes have on ESV as a result, and they should take steps to modify the land use structure, particularly to encourage ecological goals. The above discussion will support the sustainable development of ARB in a variety of ways.

Spatial Cluster Change of Schistosoma japonicum Transmission Foci in Indonesia During the Schistosomiasis Elimination Program.

The Government of Indonesia committed to eliminating schistosomiasis by 2025. Collaboratively snail control became one of the crucial strategies to ensure that the prevalence ofSchistosoma japonicuminOncomelania hupensis lindoensisreaches zero by the end of the program. This research investigated the spatial cluster change ofS. japonicumtransmission foci in Indonesia between 2017 and 2021. We mapped the snail foci, collected the snails, and calculated the snail density. We also conducted laboratory tests to detect the existence of cercariae in the snails. Identified infected snails were used to calculate the infection rate (IR) or snails' prevalence of schistosome cercariae among freshwater snails. We then analysed the spatial cluster using the Getis-Ord Gi* statistic to identify the hot and cold spots. The 5-year schistosomiasis elimination program successfully declined 18.84% of the snail foci and reduced 40.37% of the infected snail foci. Local spatial autocorrelation of snail density and infection rate identified that in 2017 and 2021, the number of cold spots decreased by 53.91% and 0%, while hot spots increased by 2.63% and 56.1%. The presence of more hotspots suggests a rise in the number of foci with high snail density and infection rates. The implementation of snail control was not optimal, and the parasite transmission through domestic animals still existed, causing the spatial cluster of hot spots to change during this period. Most hotspots have been observed near settlements, primarily in cocoa plantations, developed and deserted rice fields, grassland, and bush wetlands. During the schistosomiasis elimination program, the number of hot spots increased while cold spots decreased, and there were notable changes in the geographical distribution of hot spots, indicating a shift in the clustering pattern of schistosomiasis cases. The findings become essential for policymakers, particularly in selecting priority areas for intervention. In the Discussion section, we demonstrated the selection process based on the existence of hot and cold spots. Furthermore, we proposed that enhancing cross-sector integration is crucial, particularly in connection with the management of S. japonicum transmission through domestic animals.

A data-driven approach to analyse the co-evolution of urban systems through a resilience lens: A Helsinki case study

Urban areas are dynamic systems, in which different infrastructural, social and economic subsystems continuously co-evolve. As such, disruptions in one system can propagate to another. However, open challenges remain in (i) assessing the long-term implications of change for resilience and (ii) understanding how resilience propagates throughout urban systems over time. Despite the increasing reliance on data in smart cities, few studies empirically investigate long-term urban co-evolution using data-driven methods, leading to a gap in urban resilience assessments. This paper presents an approach that combines Getis-ord Gi* statistical and correlation analyses to investigate how cities recover from crises and adapt by analysing how the spatial patterns of urban characteristics and their relationships changed over time. We illustrate our approach through a study on Helsinki’s road infrastructure, socioeconomic system and built-up area from 1991 to 2016, a period marked by a major socioeconomic crisis. By analysing this case study, we provide insights into the co-evolution over more than two decades, thereby addressing the lack of longitudinal studies on urban resilience.

Spatiotemporal Patterns of Reptile and Amphibian Road Fatalities in a Natura 2000 Area: A 12-Year Monitoring of the Lake Karla Mediterranean Wetland.

The pervasive expansion of human-engineered infrastructure, particularly roads, has fundamentally reshaped landscapes, profoundly affecting wildlife interactions. Wildlife-vehicle collisions, a common consequence of this intricate interplay, frequently result in fatalities, extending their detrimental impact within Protected Areas (PAs). Among the faunal groups most susceptible to road mortality, reptiles and amphibians stand at the forefront, highlighting the urgent need for global comprehensive mitigation strategies. In Greece, where road infrastructure expansion has encroached upon a significant portion of the nation's PAs, the plight of these road-vulnerable species demands immediate attention. To address this critical issue, we present a multifaceted and holistic approach to investigating and assessing the complex phenomenon of herpetofauna road mortality within the unique ecological context of the Lake Karla plain, a rehabilitated wetland complex within a PA. To unravel the intricacies of herpetofauna road mortality in the Lake Karla plain, we conducted a comprehensive 12-year investigation from 2008 to 2019. Employing a combination of statistical modeling and spatial analysis techniques, we aimed to identify the species most susceptible to these encounters, their temporal and seasonal variations, and the ecological determinants of their roadkill patterns. We documented a total of 340 roadkill incidents involving 14 herpetofauna species in the Lake Karla's plain, with reptiles, particularly snakes, being more susceptible, accounting for over 60% of roadkill occurrences. Moreover, we found that environmental and road-related factors play a crucial role in influencing roadkill incidents, while spatial analysis techniques, including Kernel Density Estimation, the Getis-Ord Gi*, and the Kernel Density Estimation plus methods revealed critical areas, particularly in the south-eastern region of Lake Karla's plain, offering guidance for targeted interventions to address both individual and collective risks associated with roadkill incidents.

Bayesian spatio-temporal analysis of malaria prevalence in children between 2 and 10 years of age in Gabon

BackgroundGabon still bears significant malaria burden despite numerous efforts. To reduce this burden, policy-makers need strategies to design effective interventions. Besides, malaria distribution is well known to be related to the meteorological conditions. In Gabon, there is limited knowledge of the spatio-temporal effect or the environmental factors on this distribution. This study aimed to investigate on the spatio-temporal effects and environmental factors on the distribution of malaria prevalence among children 2–10 years of age in Gabon.MethodsThe study used cross-sectional data from the Demographic Health Survey (DHS) carried out in 2000, 2005, 2010, and 2015. The malaria prevalence was obtained by considering the weighting scheme and using the space–time smoothing model. Spatial autocorrelation was inferred using the Moran’s I index, and hotspots were identified with the local statistic Getis-Ord General Gi. For the effect of covariates on the prevalence, several spatial methods implemented in the Integrated Nested Laplace Approximation (INLA) approach using Stochastic Partial Differential Equations (SPDE) were compared.ResultsThe study considered 336 clusters, with 153 (46%) in rural and 183 (54%) in urban areas. The prevalence was highest in the Estuaire province in 2000, reaching 46%. It decreased until 2010, exhibiting strong spatial correlation (P < 0.001), decreasing slowly with distance. Hotspots were identified in north-western and western Gabon. Using the Spatial Durbin Error Model (SDEM), the relationship between the prevalence and insecticide-treated bed nets (ITNs) coverage was decreasing after 20% of coverage. The prevalence in a cluster decreased significantly with the increase per percentage of ITNs coverage in the nearby clusters, and per degree Celsius of day land surface temperature in the same cluster. It slightly increased with the number of wet days and mean temperature per month in neighbouring clusters.ConclusionsIn summary, this study showed evidence of strong spatial effect influencing malaria prevalence in household clusters. Increasing ITN coverage by 20% and prioritizing hotspots are essential policy recommendations. The effects of environmental factors should be considered, and collaboration with the national meteorological department (DGM) for early warning systems is needed.

A Methodological Approach for Gap Filling of WFV Gaofen-1 Images from Spatial Autocorrelation and Enhanced Weighting

Clouds and cloud shadow cover cause missing data in some images captured by the Gaofen-1 Wide Field of View (GF-1 WFV) cameras, limiting the extraction and analysis of the image information and further applications. Therefore, this study proposes a methodology to fill GF-1 WFV images using the spatial autocorrelation and improved weighting (SAIW) method. Specifically, the search window size is adaptively determined using Getis-Ord Gi* as a metric. The spatial and spectral weights of the pixels are computed using the Chebyshev distance and spectral angle mapper to better filter the suitable similar pixels. Each missing pixel is predicted using linear regression with similar pixels on the reference image and the corresponding similar pixel located in the non-missing region of the cloudy image. Simulation experiments showed that the average correlation coefficient of the proposed method in this study is 0.966 in heterogeneous areas, 0.983 in homogeneous farmland, and 0.948 in complex urban areas. It suggests that SAIW can reduce the spread of errors in the gap-filling process to significantly improve the accuracy of the filling results and can produce satisfactory qualitative and quantitative fill results in a wide range of typical land cover types and has extensive application potential.

Otiorhynchus aurifer Boheman, 1842, O. pseudonothus Apfelbeck, 1897 and Pachyrhinus lethierryi Desbrochers des Loges, 1875: Three new non-native weevils (Coleoptera: Curculionidae: Entiminae) in Romania

The first documented occurrences of Otiorhynchus aurifer, O. pseudonothus, and Pachyrhinus lethierryi in Romania are given. The hotspot analysis (occurrence density, Getis-Ord Gi* statistic, and Kernel density estimation) indicates global bilateral clustering of Otiorhynchus aurifer in Western Europe + Great Britain Island and the Black Sea region and local clustering in Marseille and Burgas + Istanbul, suggesting that these locations are likely the main gateways for further expansion. The major local clustering of O. pseudonothus is in Vienna, and secondary clusters are in Bruges, Amsterdam, and Denmark. This species reached East Europe including Russia, Ukraine, and Romania in the early 2020s. The analysis identifies Paris as a crucial gateway for the westward expansion of Pachyrhinus lethierryi. Potential vectors for O. auriferinclude various Lauraceae and Oleaceae, with a preference for wild privet (Ligustrum vulgare), shared with O. pseudonothus. Northern white-cedar (Thuja occidentalis) emerges as a potent coniferous vector in the spread of O. pseudonothus and P. lethierryi. The trade of potted conifers, particularly Christmas trees, is believed to contribute to the long-distance transportation of O. pseudonothus. While the establishment of O. pseudonothus and P. lethierryi remains unconfirmed, O. aurifer is likely established in Agigea. O. aurifer, a non-native inhabitant of Western European urban areas, demonstrates adaptability to both urban and disturbed natural biotopes in the Black Sea region.

Spatial patterns of suicide in Texas: The potential confounding effect of race and ethnicity composition

In the United States, suicide rates are much higher among non-Hispanic Whites than any other racial or ethnic group. However, the impact of this pattern for spatial analysis remains unclear. This article explores the relationship among race and ethnicity, suicide mortality, and space in Texas. We compare traditional age-adjusted mortality rates with standardized mortality ratios created using indirect race or ethnicity rate adjustment. Both measurements are compared in three different contexts: choropleth maps, Getis–Ord Gi* hot spot analysis, and location-allocation modeling. Results show dramatic changes across all three methods after race or ethnicity adjustment. Regions of higher-than-expected suicide mortality shift from the non-Hispanic White-dominated north to the majority-Hispanic south. Accordingly, the p-median location-allocation model moves selected service sites closer to minority strongholds in large urban areas and along the Texas–Mexico border. A closer look at individual counties shows that minority-majority counties may have suicide rates two to three times the state average (given the population composition) yet remain hidden by traditional rate calculation methods. Failing to account for race and ethnicity effects will inevitably draw attention and resources to non-Hispanic White communities. At a time when governments are making investments in both mental health and diversity initiatives, this hidden bias must be addressed.

Unsuccessful tuberculosis treatment outcomes across Brazil's geographical landscape before and during the COVID-19 pandemic: are we truly advancing toward the sustainable development/end TB goal?

BackgroundTuberculosis is one of the most significant infectious diseases for global public health. The reallocation of healthcare resources and the restrictions imposed by the COVID-19 pandemic have hindered access to TB diagnosis and treatment. Increases in unfavorable outcomes of the disease have been observed in Brazil. The objective of this study was to analyze the spatial distribution of unfavorable TB treatment outcomes in Brazil before and during the pandemic.MethodsAn ecological study with spatial analysis was conducted with all 5569 municipalities in Brazil. All reported cases of tuberculosis between January 2010 and December 2021, as well as reported cases of COVID-19 from February 2020 to December 2021, were included. The outcomes studied encompass loss to follow-up, drug-resistant tuberculosis, and death. The Getis Ord GI* technique was employed to assess spatial association, and the Kernel density estimator was used to identify areas with concentrated increases or decreases in outcomes. Bivariate Local Moran's I was used to examine the spatial association between outcomes and COVID-19 incidence. The study was approved by the Research Ethics Committee of Ribeirão Preto Nursing School, University of São Paulo.ResultsThere were 134,394 cases of loss to follow-up, 10,270 cases of drug resistance, and 37,863 deaths. Clusters of high and low values were identified for all three outcomes, indicating significant changes in the spatial distribution patterns. Increases in concentrations were observed for lost to follow-up cases in the Southeast, while reductions occurred in the Northeast, South, and Midwest. Drug-resistant tuberculosis experienced an increase in the Southern and Southeastern regions and a decrease in the Northeast and South. TB-related deaths showed notable concentrations in the Midwest, Northeast, South, and Southeast. There was an increase in high occurrence clusters for deaths after 2020 and 2021 in the Northeast.ConclusionsThe pandemic has brought additional challenges, emphasizing the importance of enhancing efforts and disease control strategies, prioritizing early identification, treatment adherence, and follow-up. This commitment is vital for achieving the goal of tuberculosis elimination.

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

BackgroundEnsuring 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.MethodsTo 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).ResultsSpatial 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.ConclusionsThree-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.