Race, disadvantage, and violence: A spatial exploration of macrolevel covariates of police-involved homicides within and between US counties.

Efforts to explore the macrolevel determinants of police-involved homicides have expanded in recent years due in part to increased scrutiny and media attention to such events, and increased data availability of these events through crowdsourced databases. However, little empirical research has examined the spatial determinants of such events. The present study extends the extant macrolevel research on police-involved homicides by employing an underutilized spatial econometric model, the spatial Durbin model (SDM), to assess the direct and indirect county effects of racial threat, economic threat, social disorganization, and community violence on police killings within and between US counties from 2013 through 2020. Results indicate a direct inverse relationship between racial threat and police-involved homicides, no support for economic threat, and a direct positive association with two measures of social disorganization. Additionally, we find firearm availability exhibits significant direct and indirect spatial dependence on focal county police-involved homicides, reflecting spatial spillover processes. In essence, as firearm availability in neighboring counties increases, police-involved homicides within a focal county increase. The implications of these findings for racial threat, economic threat, social disorganization, and community violence are discussed.

Outpatient geriatric health care in the German federal state of Mecklenburg-Western Pomerania: a population-based spatial analysis of claims data.

BACKGROUND: Due to unidentified geriatric needs, elderly patients have a higher risk for developing chronic conditions and acute medical complications. Early geriatric screenings and assessments help to identify geriatric needs. Holistic and coordinated therapeutic approaches addressing those needs maintain the independence of elderly patients and avoid adverse effects. General practitioners are important for the timely identification of geriatric needs. The aims of this study are to examine the spatial distribution of the utilization of outpatient geriatric services in the very rural Federal State of Mecklenburg-Western Pomerania in the Northeast of Germany and to identify regional disparities. METHODS: Geographical analysis and cartographic visualization of the spatial distribution of outpatient geriatric services of patients who are eligible to receive basic geriatric care (BGC) or specialized geriatric care (SGC) were carried out. Claims data of the Association of Statutory Health Insurance Physicians in Mecklenburg-Western Pomerania were analysed on the level of postcode areas for the quarter periods between 01/2014 and 04/2017. A Moran's I analysis was carried out to identify clusters of utilization rates. RESULTS: Of all patients who were eligible for BGC in 2017, 58.3% (n = 129,283/221,654) received at least one BCG service. 77.2% (n = 73,442/95,171) of the patients who were eligible for SGC, received any geriatric service (BGC or SGC). 0.4% (n = 414/95,171) of the patients eligible for SGC, received SGC services. Among the postcode areas in the study region, the proportion of patients who received a basic geriatric assessment ranged from 3.4 to 86.7%. Several regions with statistically significant Clusters of utilization rates were identified. CONCLUSIONS: The widely varying utilization rates and the local segregation of high and low rates indicate that the provision of outpatient geriatric care may depend to a large extent on local structures (e.g., multiprofessional, integrated networks or innovative projects or initiatives). The great overall variation in the provision of BGC services implicates that the identification of geriatric needs in GPs' practices should be more standardized. In order to reduce regional disparities in the provision of BGC and SGC services, innovative solutions and a promotion of specialized geriatric networks or healthcare providers are necessary.

Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging.

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1high T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

From erosion to epidemics: Understanding the overlapping vulnerability of hydrogeomorphic hotspots, malaria affliction, and poverty in Nigeria.

Hydrogeomorphic changes, encompassing erosion, waterlogging, and siltation, disproportionately threaten impoverished rural communities. Yet, they are often marginalized in discussions of disasters. This oversight is especially concerning as vulnerable households with limited healthcare access are most susceptible to related diseases and displacement. However, our current understanding of how these risks intersect remains limited. We explore the complex relationships between hydrogeomorphic hazards, malaria incidence, and poverty in Nigeria. Through spatial analyses we expand traditional boundaries, incorporating factors such as healthcare access, migration patterns, dam locations, demographics, and wealth disparities into a unified framework. Our findings reveal a stark reality: most residents in hydrogeomorphic hotspots live in poverty (earnings per person ≤$1.25/day), face elevated malaria risks (80 % in malaria hotspots), reside near dams (59 %), and struggle with limited healthcare access. Moreover, exposure to hydrogeomorphic hotspots could double by 2080, affecting an estimated 5.8 million Nigerians. This forecast underscores the urgent need for increased support and targeted interventions to protect those living in poverty within these hazardous regions. In shedding light on these dynamics, we expose and emphasise the pressing urgency of the risks borne by the most vulnerable populations residing in these regions-communities often characterised by limited wealth and resilience.

Spatiotemporal assessment of the nexus between urban sprawl and land surface temperature as microclimatic effect: implications for urban planning.

Rapid urbanisation has led to significant environmental and climatic changes worldwide, especially in urban heat islands where increased land surface temperature (LST) poses a major challenge to sustainable urban living. In the city of Abha in southwestern Saudi Arabia, a region experiencing rapid urban growth, the impact of such expansion on LST and the resulting microclimatic changes are still poorly understood. This study aims to explore the dynamics of urban sprawl and its direct impact on LST to provide important insights for urban planning and climate change mitigation strategies. Using the random forest (RF) algorithm optimised for land use and land cover (LULC) mapping, LULC models were derived that had an overall accuracy of 87.70%, 86.27% and 93.53% for 1990, 2000 and 2020, respectively. The mono-window algorithm facilitated the derivation of LST, while Markovian transition matrices and spatial linear regression models assessed LULC dynamics and LST trends. Notably, built-up areas grew from 69.40 km2 in 1990 to 338.74 km2 in 2020, while LST in urban areas showed a pronounced warming trend, with temperatures increasing from an average of 43.71 °C in 1990 to 50.46 °C in 2020. Six landscape fragmentation indices were then calculated for urban areas over three decades. The results show that the Largest Patch Index (LPI) increases from 22.78 in 1990 to 65.24 in 2020, and the number of patches (NP) escalates from 2,531 in 1990 to an impressive 10,710 in 2020. Further regression analyses highlighted the morphological changes in the cities and attributed almost 97% of the LST variability to these urban patch dynamics. In addition, water bodies showed a cooling trend with a temperature decrease from 33.76 °C in 2000 to 29.69 °C in 2020, suggesting an anthropogenic influence. The conclusion emphasises the urgent need for sustainable urban planning to counteract the warming trends associated with urban sprawl and promote climate resilience.

Climate change and land cover effects on water yield in a subtropical watershed spanning the yungas-chaco transition of Argentina.

The demand for mountain water resources is increasing, and their availability is threatened by climate change, emphasizing the urgency for effective protection and management. The upper Sali-Dulce watershed holds vital significance as it contributes the majority of the Sali-Dulce water resources, supporting a densely populated dry region in Northwestern Argentina, covering an area of 24,217 km2. However, the potential impact of climate change and land use/land cover change on water yield in this watershed remains uncertain. This study employs the InVEST Annual Water Yield model to analyze the average water yield in the watershed and evaluate its potential changes under future scenarios of climate and land use/land cover change. InVEST was calibrated using data from multiple river gauges located across the watershed, indicating satisfactory performance (R2 = 0.751, p-value = 0.0054). Precipitation and evapotranspiration were the most important variables explaining water yield in the area, followed by land use. Water yield showed a notable concentration in the montane area with 40% of the watershed accounting for 80% of the water yield, underscoring the importance of conserving natural land cover in this critical zone. Climate change scenarios project an increase in water yield ranging from 21 to 75%, while the effects of land cover change scenarios on water yield vary, with reforestation scenarios leading to reductions of up to 15% and expansions in non-irrigated agriculture resulting in increases of up to 40%. Additionally, water yield distribution may become more concentrated or dispersed, largely dependent on the type of land cover. The combined scenarios highlight the pivotal role of land cover in adapting to climate change. Our findings provide valuable insights for designing future studies and developing policies aimed at implementing effective adaptation strategies to climate change within the Salí-Dulce watershed.

'Nowhere and no one is safe': spatial analysis of damage to critical civilian infrastructure in the Gaza Strip during the first phase of the Israeli military campaign, 7 October to 22 November 2023.

BACKGROUND: Since the Hamas attacks in Israel on 7 October 2023, the Israeli military has launched an assault in the Gaza Strip, which included over 12,000 targets struck and over 25,000 tons of incendiary munitions used by 2 November 2023. The objectives of this study include: (1) the descriptive and inferential spatial analysis of damage to critical civilian infrastructure (health, education, and water facilities) across the Gaza Strip during the first phase of the military campaign, defined as 7 October to 22 November 2023 and (2) the analysis of damage clustering around critical civilian infrastructure to explore broader questions about Israel's adherence to International Humanitarian Law (IHL). METHODS: We applied multi-temporal coherent change detection on Copernicus Sentinel 1-A Synthetic Aperture Radar (SAR) imagery to detect signals indicative of damage to the built environment through 22 November 2023. Specific locations of health, education, and water facilities were delineated using open-source building footprint and cross-checked with geocoded data from OCHA, OpenStreetMap, and Humanitarian OpenStreetMap Team. We then assessed the retrieval of damage at and with close proximity to sites of health, education, and water infrastructure in addition to designated evacuation corridors and civilian protection zones. The Global Moran's I autocorrelation inference statistic was used to determine whether health, education, and water facility infrastructure damage was spatially random or clustered. RESULTS: During the period under investigation, in the entire Gaza Strip, 60.8% (n = 59) of health, 68.2% (n = 324) of education, and 42.1% (n = 64) of water facilities sustained infrastructure damage. Furthermore, 35.1% (n = 34) of health, 40.2% (n = 191) of education, and 36.8% (n = 56) of water facilities were functionally destroyed. Applying the Global Moran's I spatial inference statistic to facilities demonstrated a high degree of damage clustering for all three types of critical civilian infrastructure, with Z-scores indicating < 1% likelihood of cluster damage occurring by random chance. CONCLUSION: Spatial statistical analysis suggests widespread damage to critical civilian infrastructure that should have been provided protection under IHL. These findings raise serious allegations about the violation of IHL, especially in light of Israeli officials' statements explicitly inciting violence and displacement and multiple widely reported acts of collective punishment.

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

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Is entrepreneurship a key factor in the development of European countries? A proposal for an innovation readiness environment (IRE) index.

This study investigates the complex interplay among innovation, research and development (R&D), and entrepreneurship within the context of European nations. The focus of the study is also on the contributory role of tertiary educational institutions in nurturing entrepreneurial activities. To deepen the understanding of these multifaceted relationships and their subsequent impact on regional economies, the research introduces a novel metric termed the Innovation Readiness Environment (IRE) index. This index combines various indicators such as R&D expenditure, patenting rates, firm size, and educational levels, thereby providing a framework for evaluating the innovative capabilities and entrepreneurial success of firms in a given region. Utilization of this index offers policymakers and stakeholders a nuanced understanding of the regional innovation ecosystem, facilitating the identification of both strengths and deficiencies. This, in turn, enables the formulation of targeted policy interventions to enhance both innovation and entrepreneurship. One salient conclusion drawn from this study is the pivotal role of tertiary education in catalysing entrepreneurial ventures. The findings posit that higher levels of entrepreneurial education significantly supplement an individual's likelihood of entrepreneurial success by imparting the requisite skills and knowledge indispensable in a competitive business milieu. Higher education institutions, by fostering an environment conducive to innovation, emerge as critical agents in the cultivation of entrepreneurial acumen and the stimulation of economic expansion. The study further incorporates a spatial analytical framework to elucidate the regional specificities of innovation at the pan-European scale.

The present research examines the interconnected roles of innovation, research and development, and entrepreneurship in European countries, particularly emphasising how higher education contributes to entrepreneurial activity. Through the introduction of the Innovation Readiness Environment (IRE) index, the study provides a structured way to measure various aspects like research spending, patent rates, and educational levels in a region. The IRE index is intended to guide policymakers and other key stakeholders. The index is a tool for comprehensively assessing regional strengths and weaknesses in innovation and entrepreneurship. Furthermore, the study underscores the crucial role of higher education in fostering entrepreneurial skills, thereby enhancing the probability of entrepreneurial success. As a result, it appears that universities are not just places for acquiring knowledge; they serve as incubators for new ideas and start-ups, contributing to broader economic growth.

Immune Cytolytic Activity and Strategies for Therapeutic Treatment.

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

Spatial Pattern Analysis using Closest Events (SPACE)-A Nearest Neighbor Point Pattern Analysis Framework for Assessing Spatial Relationships from Digital Images.

The quantitative description of biological structures is a valuable yet difficult task in the life sciences. This is commonly accomplished by imaging samples using fluorescence microscopy and analyzing resulting images using Pearson's correlation or Manders' co-occurrence intensity-based colocalization paradigms. Though conceptually and computationally simple, these approaches are critically flawed due to their reliance on signal overlap, sensitivity to cursory signal qualities, and inability to differentiate true and incidental colocalization. Point pattern analysis provides a framework for quantitative characterization of spatial relationships between spatial patterns using the distances between observations rather than their overlap, thus overcoming these issues. Here we introduce an image analysis tool called Spatial Pattern Analysis using Closest Events (SPACE) that leverages nearest neighbor-based point pattern analysis to characterize the spatial relationship of fluorescence microscopy signals from image data. The utility of SPACE is demonstrated by assessing the spatial association between mRNA and cell nuclei from confocal images of cardiac myocytes. Additionally, we use synthetic and empirical images to characterize the sensitivity of SPACE to image segmentation parameters and cursory image qualities such as signal abundance and image resolution. Ultimately, SPACE delivers performance superior to traditional colocalization methods and offers a valuable addition to the microscopist's toolbox.

Neighboring macrophage-induced alteration in the phenotype of colorectal cancer cells in the tumor budding area.

BACKGROUND: A higher number of tumor buds in the invasive front of colorectal cancer (CRC) specimens has been shown to contribute to a poor prognosis in CRC patients. Because macrophages (Mφs) have been demonstrated to alter the phenotype of cancer cells, we hypothesized that the phenotype of CRC cells in the tumor budding (TB) area might be changed by the interaction between CRC cells and Mφs. METHODS: We assessed the expression of topoisomerase 1 in CRC cells to estimate the acquisition of chemoresistance in CRC. To demonstrate the tumor-stromal interaction between CRC cells and Mφs, we assessed two histological findings, the number of Mφs per single CRC cell and the proximity between CRC cells and Mφs by histological spatial analysis using HALO software. RESULTS: The expression levels of topoisomerase 1 in CRC cells were decreased in deeper areas, especially in the TB area, compared to the surface area. Our histological spatial analysis revealed that 2.6 Mφs located within 60 µm of a single CRC cell were required to alter the phenotype of the CRC cell. Double-immunofluorescence staining revealed that higher Mφs were positive for interleukin-6 (IL-6) in the TB area and that AE1/AE3-positive CRC cells were also positive for phospho-STAT3 (pSTAT3) in the TB area; thus, the IL-6 receptor (IL-6R)/STAT3 signaling pathway in CRC cells was upregulated by IL-6 derived from neighboring Mφs. CONCLUSION: IL-6 secreted from the neighboring Mφs would alter the phenotype of CRC cells via IL-6R/STAT3 signaling pathway.

Injury-severity analysis of crashes involving defective vehicles and accounting for the underlying socioeconomic mediators.

Crashes occur from a combination of factors related to the driver, roadway, and vehicle factors. The impact of vehicles on road crashes is a critical consideration within road safety analysis, even though not much studies have been conducted in this area. This study assessed how various vehicle and other crash factors are significantly associated with crash outcomes. To do this, historical vehicle defect-related crashes were obtained for the state of Alabama from 2016 to 2020. After data cleaning, a crash injury severity model was developed using the random parameters multinomial logit with heterogeneity in means approach to account for possible unobserved heterogeneity in the data. A spatial analysis was further conducted to better understand vehicle defect crashes as a broader societal issue and potentially explore their connection with the socio-demographic characteristics of the drivers of these vehicles. The preliminary data analysis showed that brake and tire defects accounted for about 65% of the vehicle defects associated with the crashes. The model estimation results revealed that improper tread depth and headlight defects were associated with major injury outcomes, while brake defects were more associated with minor injuries. Also, crashes associated with speeding, drunk driving, failure to use seatbelts, and those that occurred on curved roads left with downgrades were likely to result in major injuries. Findings from the spatial analysis showed that postal codes with higher median incomes are more likely to record lower vehicle defect-related crashes, unlike those that have higher proportions of females and African Americans. The study's findings provide data-driven evidence for sustained safety campaigns, workshops, and training on basic vehicle maintenance practices in the low-income communities in the state.

Spatial distribution characteristics and source apportionment of heavy metal(loid)s in park dust in the Mianyang urban area, China.

Park dust is a carrier of heavy metal pollutants and could potentially harm the health of urban residents. The concentrations of 10 heavy metal(loid)s (HMs) in park dust from the Mianyang urban area were analysed via X-ray fluorescence spectrometry. Based on ArcGIS spatial analysis, Spearman correlation analysis, spatial autocorrelation analysis, and the positive matrix factorization (PMF) model, the spatial distribution and sources of HMs in park dust were studied. The average contents of Zn, Co, Cu, Cr, Pb, and Ba in park dust were 185.0, 33.7, 38.7, 178.7, 51.0, and 662.1 mg/kg, respectively, which are higher than the reference values. The 10 HMs exhibited obvious spatial distribution and local spatial agglomeration patterns. High concentrations of As and Pb were primarily concentrated in the eastern part of the Mianyang urban area. High concentrations of Zn, Cr, and Cu were largely distributed in parks near the Changjiang River and Fujiang River. A high concentration of Co was concentrated in the northern region. The high-value areas of Mn, Ba, V, and Ni occurred far from the city centre and were located in the southwestern region. We found that Pb and As primarily originated from mixed traffic and natural sources; Zn, Cr, and Cu mainly originated from industrial activities; Co largely originated from building sources; and Ba, Ni, Mn, and V were mostly derived from natural sources. Mixed, industrial, building, and natural sources accounted for 24.5%, 24.8%, 24.7%, and 26.0%, respectively, of the HM sources. Co, Cu, Cr, and Zn in the Mianyang urban area were obviously influenced by human activities and should receive close attention.

Corrigendum: Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China.

[This corrects the article DOI: 10.3389/fpubh.2024.1354515.].

"Characterization of residential proximity to sources of environmental carcinogens in clusters of Acute Lymphoblastic Leukemia in San Luis Potosi, Mexico".

BACKGROUND: Acute Lymphoblastic Leukemia (ALL) is the most prevalent neoplasia in children and teenagers in Mexico. Although epidemiological data supports that children's residence close to emissions from vehicular traffic or industrial processes increases the risk of ALL; and the IARC states that benzene, PAHs, and PM 2.5 are well-known environmental carcinogens, there is a gap in linking these carcinogenic hazards with the sources and their distribution from scenario perspective. AIM: To identify ALL clusters in the population under 19 years of age and characterize the environment at the neighborhood level by integrating information on sources of carcinogenic exposure using spatial analysis techniques in the Metropolitan Area of San Luis Potosi, Mexico. METHODS: Using the Kernel Density test, we designed an ecological study to identify ALL clusters from incident cases in the population under 19 years of age. A multicriteria analysis was conducted to characterize the risk at the community level from carcinogenic sources. A hierarchical cluster analysis was performed to characterize risk at the individual level based on carcinogenic source count within 1 km for each ALL case. RESULTS: Eight clusters of carcinogenic sources were located within the five identified ALL clusters. The multicriteria analysis showed high-risk areas (by density of carcinogenic source) within ALL clusters. CONCLUSIONS: This study has a limited source and amount of available data on ALL cases, so selection bias is present as well as the inability to rule out residual confounding factors, since covariates were not included. However, in this study, children living in environments with high vehicular density, gas stations, brick kilns, incinerators, commercial establishments burning biomass, or near industrial zones may be at higher risk for ALL.

Big Cities, Big Impacts? A spatial analysis of 3,335 ecological offsets in France since 2012.

This paper assesses the French policy of mitigation hierarchy, with the aim of no net loss of biodiversity, by studying the geographical aspects of the application of the concept of ecological offsets in equivalence between losses and gains using spatialized data. We seek to know whether the dynamics of urban and interurban development (notably built-up and transport infrastructures) lead to a spatially integrated implementation of biodiversity offsets taking into account local characteristics and areas under pressure from land artificialization. Our main finding reveals that the majority of ecological offsets are generated by projects related to transport infrastructures (38%) and urban planning and construction projects (23%). However, if there are fewer, the ecological offsets of projects such as waste storage or energy development are mostly located in natural preserved areas, revealing a potential risk of non additionnality of offset measures and a risk that the private sector (through ecological offsets) will gradually replace the state in the protection of biodiversity. Our analysis also points out that despite the diversity of projects, habitats and protected species across France, there is a typical spatial layout profile of ecological offsets, pleading for a "one size fits all" offsetting in the French policy context of tenuous regulators' availability in time and competence level due to weakness of refresh training and downsizing of public services in the environment. This last result argues for a stronger control from environmental agencies between two tremendously tricky concepts of offsetting, the equivalence valuation methods and the adjustments coefficients (time delay and ecological risk), to drive ecological offsetting future decisions at local but above all regional- and national-level planning documents.

Healthcare equity in focus: bridging gaps through a spatial analysis of healthcare facilities in Irbid, Jordan.

In the Irbid Governorate, Jordan, equitable healthcare facility distribution is vital to ensuring healthcare accessibility and improving public health outcomes. This study investigated the spatial distribution, accessibility, and conformity of healthcare facilities to the Ministry of Health standards to identify areas requiring improvement. Using geographic information systems (GIS), three spatial analyses were conducted: nearest neighbor analysis, buffer analysis, and service area analysis. These analyses comprehensively assessed the healthcare landscape, revealing a random spatial distribution pattern of healthcare facilities; and indicating an absence of structured organization. The buffer analysis revealed concentrations in specific regions, while others were underserved. The Service Area Analysis revealed significant healthcare access challenges, especially in remote areas. The healthcare resource distribution of the Irbid governorate fell short of national and international standards, emphasizing the need for improvements. To address these disparities, policymakers and healthcare authorities should focus on equitably redistributing resources, tailoring allocation to local needs, improving remote area infrastructure, and refining government policies. Continuous monitoring and evaluation are imperative to ensure alignment with international standards and achieve healthcare equity. The insights from this case study provide valuable guidance for regions facing similar healthcare distribution challenges.

Spatial pattern of isoniazid-resistant tuberculosis and its associated factors among a population with migrants in China: a retrospective population-based study.

Background: Isoniazid-resistant, rifampicin-susceptible tuberculosis (Hr-TB) globally exhibits a high prevalence and serves as a potential precursor to multidrug-resistant tuberculosis (MDR-TB). Recognizing the spatial distribution of Hr-TB and identifying associated factors can provide strategic entry points for interventions aimed at early detection of Hr-TB and prevention of its progression to MDR-TB. This study aims to analyze spatial patterns and identify socioeconomic, demographic, and healthcare factors associated with Hr-TB in Shanghai at the county level. Method: We conducted a retrospective study utilizing data from TB patients with available Drug Susceptible Test (DST) results in Shanghai from 2010 to 2016. Spatial autocorrelation was explored using Global Moran's I and Getis-Ord Gi∗ statistics. A Bayesian hierarchical model with spatial effects was developed using the INLA package in R software to identify potential factors associated with Hr-TB at the county level. Results: A total of 8,865 TB patients with DST were included in this analysis. Among 758 Hr-TB patients, 622 (82.06%) were new cases without any previous treatment history. The drug-resistant rate of Hr-TB among new TB cases in Shanghai stood at 7.20% (622/8014), while for previously treated cases, the rate was 15.98% (136/851). Hotspot areas of Hr-TB were predominantly situated in southwestern Shanghai. Factors positively associated with Hr-TB included the percentage of older adult individuals (RR = 3.93, 95% Crl:1.93-8.03), the percentage of internal migrants (RR = 1.35, 95% Crl:1.15-1.35), and the number of healthcare institutions per 100 population (RR = 1.17, 95% Crl:1.02-1.34). Conclusion: We observed a spatial heterogeneity of Hr-TB in Shanghai, with hotspots in the Songjiang and Minhang districts. Based on the results of the models, the internal migrant population and older adult individuals in Shanghai may be contributing factors to the emergence of areas with high Hr-TB notification rates. Given these insights, we advocate for targeted interventions, especially in identified high-risk hotspots and high-risk areas.