Gonorrhea cluster detection in Manitoba, Canada: Spatial, temporal, and spatio-temporal analysis.

In Canada, Gonorrhea infection ranks as the second most prevalent sexually transmitted infection. In 2018, Manitoba reported an incidence rate three times greater than the national average. This study aims to investigate the spatial, temporal, and spatio-temporal patterns of Gonorrhea infection in Manitoba, using individual-level laboratory-confirmed administrative data provided by Manitoba Health from 2000 to 2016. Age and sex patterns indicate that females are affected by infections at younger ages compared to males. Moreover, there is an increase in repeated infections in 2016, accounting for 16% of the total infections. Spatial analysis at the 96 Manitoba regional health authority districts highlights significant positive spatial autocorrelation, demonstrating a clustered distribution of the infection. Northern districts of Manitoba and central Winnipeg were identified as significant clusters. Temporal analysis shows seasonal patterns, with higher infections in late summer and fall. Additionally, spatio-temporal analysis reveals clusters during high-risk periods, with the most likely cluster in the northern districts of Manitoba from January 2006 to June 2014, and a secondary cluster in central Winnipeg from June 2004 to November 2012. This study identifies that Gonorrhea infection transmission in Manitoba has temporal, spatial, and spatio-temporal variations. The findings provide vital insights for public health and Manitoba Health by revealing high-risk clusters and emphasizing the need for focused and localized prevention, control measures, and resource allocation.

Spatiotemporal analysis of HPV vaccination and associated neighborhood-level disparities in Texas-an ecological study.

Background: HPV is responsible for most cervical, oropharyngeal, anal, vaginal, and vulvar cancers. The HPV vaccine has decreased cervical cancer incidence, but only 49% of Texas adolescents have initiated the vaccine. Texas shows great variation in HPV vaccination rates. We used geospatial analysis to identify areas with high and low vaccination rates and explored differences in neighborhood characteristics. Methods: Using Anselin's Local Moran's I statistic, we conducted an ecological analysis of hot and cold spots of adolescent HPV vaccination coverage in Texas from 2017 to 2021. Next, we utilized a Mann-Whitney U test to compare neighborhood characteristics of vaccination coverage in hot spots versus cold spots, leveraging data from the Child Opportunity Index (COI) and American Community Survey. Results: In Texas, there are 64 persistent vaccination coverage hotspots and 55 persistent vaccination coverage cold spots. The persistent vaccination coverage hot spots are characterized by ZIP codes with lower COI scores, higher percentages of Hispanic residents, higher poverty rates, and smaller populations per square mile compared to vaccine coverage cold spots. We found a more pronounced spatial clustering pattern for male adolescent vaccine coverage than we did for female adolescent vaccine coverage. Conclusion: In Texas, HPV vaccination coverage rates differ depending on the community's income level, with lower-income areas achieving higher success rates. Notably, there are also gender-based discrepancies in vaccination coverage rates, particularly among male adolescents. This knowledge can aid advocates in customizing their outreach initiatives to address these disparities.

The COVID-19 pandemic in Brazil: space-time approach of cases, deaths, and vaccination coverage (February 2020 - April 2024).

OBJECTIVE: To assess the evolution of the COVID-19 pandemic in Brazil and its macro-regions, considering disease incidence and mortality rates, as well as identifying territories with still rising disease indices and evaluating vaccine coverage and population adherence to COVID-19 immunization. METHODS: An ecological study conducted in Brazil with COVID-19 cases and deaths reported between February 2020 and April 2024, obtained through the Coronavirus Panel. Historical series were constructed from incidence and mortality rates to assess the pandemic's evolution, and temporal trends were estimated using the Seasonal Trend Decomposition using Loess (STL) method. The Spatial Variation in Temporal Trends (SVTT) technique was employed to identify clusters with significant variations in temporal trends. Vaccination was analyzed considering the percentage of vaccinated and unvaccinated population in each municipality of the country. RESULTS: Brazil recorded a total of 38,795,966 cases and 712,038 deaths from COVID-19 during the study period. Incidence and mortality rates showed three waves of the disease, with a fourth wave of smaller amplitude. Four clusters with significant case growth and two with increased deaths were identified. Vaccine coverage varied among municipalities, with some regions showing low vaccination rates and others with high immunization adherence. CONCLUSION: The study provided a comprehensive overview of coronavirus behavior in Brazil, and its results highlight the ongoing importance of vaccination and the need to direct efforts and resources to areas of higher risk.

The impact of COVID-19 national lockdowns on drug-resistant tuberculosis in KwaZulu-Natal, South Africa: A spatial analysis.

PURPOSE: We sought to understand the impact of the initial COVID-19 mitigation strategies in 2020 on drug-resistant (DR) TB diagnoses in KwaZulu-Natal province (KZN), South Africa. METHODS: We compared the number, spatial distribution, and characteristics of DR TB diagnoses before and after the initial COVID-19 lockdown on March 26th, 2020. Information on DR TB diagnoses was collected from the CONTEXT prospective cohort study and municipality characteristics were collected from Statistics South Africa. We used Bayesian conditional autoregressive models and relative-risk surface maps to examine spatial correlates and patterns of DR TB notifications. RESULTS: Between October 2018 and February 2022, there were 693 individuals diagnosed with DR TB in KZN, South Africa. The rate of diagnoses per year was 274 and 155 prior and after to the initial lockdowns, respectively, corresponding to a 43 % decrease in the notification rate of cases. Compared to cases diagnosed before the lockdown, cases diagnosed after were less likely to have a fuel source for heating, piped water, a flush toilet, or own a phone (p-values≤0.02). Changes in notifications were not homogenously distributed, with predominantly rural northeastern and southwestern municipalities having significantly greater relative-risks after the lockdown. CONCLUSIONS: We found a reduction in the rate of DR TB diagnoses after the COVID-19 pandemic lockdowns and observed that individuals diagnosed after the lockdowns had worse living conditions, fewer household resources, and more adults living in their household compared to before the pandemic.

A methodological framework to characterize the wildlife-livestock interface: The case of wild boar in mainland Spain.

BACKGROUND: The representation of wildlife-livestock interface (WLI) at an accurate spatial resolution poses several challenges. Furthermore, there is a lack of published material providing detailed descriptions of geospatial techniques for the purpose of producing visual results that are interpretable and contrastable for epidemiological analysis. OBJECTIVES: Our aim is to develop a standardized, applicable, and scalable methodological framework for describing and characterizing the WLI across a large spatial extent. Subsequently, we aim to employ this framework to depict specific WLI based on different epidemiological scenarios determined by the abundance of wild boar (Sus scrofa) and domestic ungulates as an illustrative case, specifically focusing on mainland Spain. METHODS: To establish a methodological framework, we merged data from both wild and domestic sources into a hexagonal grid. We utilized data on wild boar hunting and the locations of pig, cattle, sheep, and goat farms in mainland Spain. New variables were derived from this combined dataset to illustrate the overlapping abundance between wild boar and domestic species. Finally, a cluster analysis of the generated variables was carried out, with the aim of distinguishing and characterizing various scenarios of the wild boar-domestic ungulate interface in mainland Spain. RESULTS: The hexagonal grid proved appropriate to represent and evaluate the WLI at fine spatial resolution over such broad extent. Despite the inability to ascribe a dominant livestock type and production system to a specific region, we were able to identify fifteen main areas of interest in terms of overlap. As for extensive livestock, normally at the highest risk of interaction with wild boar, the primary regions in Spain were those with dehesa agroecosystem and the Atlantic areas. Certain scenarios were particularly relevant in terms of risk for interaction and subsequent transmission of disease, namely, the case of extensive pig production in south western Spain (dehesa agroecosystem), which is especially concerned about the potential introduction of African Swine fever (ASF) in the Country. DISCUSSION AND CONCLUSIONS: We provide a basis for visualizing and understanding of different WLI scenarios, which is extensible to other regions and interfaces, and automatable where precise source of data from wildlife and livestock are available. This spatial statistics framework enables the utilization of high-resolution data, ensuring consistency on uniform grids. This aligns with the needs of high-resolution disease dissemination models based on wildlife behaviour. Such aspects are crucial for developing risk assessment and improving strategies for the prevention, control, and eradication of shared priority emerging diseases at national and international levels, such as ASF.

Spatial and Temporal Dynamics of Chikungunya Incidence in Brazil and the Impact of Social Vulnerability: A Population-Based and Ecological Study.

To assess the temporal and spatial dynamics of chikungunya incidence and its association with social vulnerability indicators in Brazil, an ecological and population-based study was conducted herein, with confirmed cases of chikungunya and based on clinical and clinical-epidemiological criteria from 2017 to 2023. Data were obtained from the Notifiable Diseases Information System and social vulnerability indicators were extracted from the official platform of the United Nations Development Program and the Social Vulnerability Atlas. Temporal, spatial, and global spatial regression models were employed. The temporal trend showed that in 2017, the incidence increased by 1.9%, and this trend decreased from 2020 to 2021 (-0.93%). The spatial distribution showed heterogeneity and positive spatial autocorrelation (I: 0.71; p < 0.001) in chikungunya cases in Brazil. Also, the high-risk areas for the disease were concentrated in the northeast and north regions. The social vulnerability indicators associated with the outcome were those related to income, education, and housing conditions. Our analyses demonstrate that chikungunya continues to be a serious health concern in Brazil, but specially in the northeast and north regions. Lastly, mapping risk areas can provide evidence for the development of public health strategies and disease control in endemic regions.

Spatial patterns of Mental Health Act apprehensions in Toronto, Canada, 2014-2022.

OBJECTIVES: This research examines the temporal rates and spatial patterns of police-involved Mental Health Act (MHA) apprehensions in Toronto, Canada, from 2014 to 2022. Building from the work of Toronto Police Services (TPS), the goal of this research is to deepen our understanding of MHA apprehensions and provide insights which may be used to guide local mental health reform efforts. METHODS: Using data collected by TPS, an exploratory, descriptive analysis of spatial patterns of MHA apprehension events between 2014 and 2022 at the neighbourhood level was conducted. To identify high-rate clusters, we used a discrete Poisson model in SaTScan, with a circular moving window. Primary and secondary clusters with a relative risk of 1.5 or greater are reported. RESULTS: From 2014 to 2022, 93,932 MHA apprehensions occurred in Toronto. Apprehension rates were found to vary substantially between neighbourhoods, with approximately 91% of Toronto's 140 neighbourhoods experiencing a net positive increase in rates during the study period after adjusting for population growth. Repeated spatial cluster analysis for each year revealed a range of 4 to 7 clusters annually, with the downtown core consistently emerging as an area of elevated risk (RR range 1.58-1.99). CONCLUSION: Rising MHA apprehensions within Toronto highlight the pressing need to confront the city's intensifying mental health needs. These findings offer valuable insights into the patterns and nature of police-involved MHA apprehensions, outline reproducible analysis methods that can be used by others, and support targeted evaluation, expansion, and implementation of downstream initiatives to improve mental health responses.

RéSUMé: OBJECTIFS: Cette recherche examine les taux temporels et les variations spatiales des appréhensions impliquant la police en vertu de la Loi sur la santé mentale (LSM) à Toronto, Canada, de 2014 à 2022. S'appuyant sur le travail du Service de police de Toronto (SPT), l'objectif de cette recherche est d'approfondir notre compréhension des appréhensions LSM afin d'identifier les tendances et les variations géographiques pour guider les efforts de réforme du système de santé mentale locaux. MéTHODES: En utilisant les données collectées par les SPT, une analyse exploratoire et descriptive des variations spatiales des appréhensions LSM entre 2014 et 2022 au niveau du quartier a été réalisée. Pour identifier les agrégats à taux augmenté, le logiciel SatScan a été utilisé avec un modèle de Poisson discret, couplé avec une fenêtre mobile circulaire. Les agrégats primaires et secondaires avec un risque relatif de 1,5 ou plus sont signalées. RéSULTATS: De 2014 à 2022, 93 932 appréhensions en vertu de la LSM ont eu lieu à Toronto. Les taux d'appréhension variaient considérablement entre les quartiers, environ 91 % des 140 quartiers de Toronto ayant connu une augmentation nette des taux pendant la période d'étude, après ajustement pour la croissance démographique. L'analyse répétée des agrégats spatiaux pour chaque année a révélé 4 à 7 agrégats annuels, le centre-ville émergeant systématiquement comme une zone à risque élevé (risque relatif 1,58­1,99). CONCLUSION: L'augmentation des appréhensions en vertu de la LSM à Toronto souligne le besoin urgent de faire face aux besoins croissants en santé mentale de la ville. Ces résultats offrent des informations précieuses sur les variations et la nature des appréhensions en vertu de la LSM impliquant la police, décrivent des méthodes d'analyse reproductibles qui peuvent être utilisées par d'autres, et soutiennent l'évaluation ciblée, l'expansion et la mise en œuvre d'initiatives en aval pour améliorer les réponses en matière de santé mentale.

Enhancing resilience: Integrating future flood modeling and socio-economic analysis in the face of climate change impacts.

As climate change intensifies, future floods will become more severe in some areas with geographic variation, necessitating that local and regional governments implement systems to provide information for climate adaptation, particularly for vulnerable populations. Therefore, we aimed to develop a methodology to identify areas that are at an increased risk from future floods and independently socially vulnerable. In this study, 100-year recurrence interval flood extents and depths were estimated using an ensemble of six independent Coupled Model Intercomparison Project Phase 6 climate models for a past and future period under the highest-emissions climate scenario. The flood inundation results were related to social vulnerability for two selected study areas in the Mississippi River Basin. The range of flood extents and depths for both time periods were estimated, and differences were evaluated to determine the effects from climate change. To identify at-risk areas, the relationship between the spatial distribution of flood depths and vulnerability was then assessed. Finally, an analysis of the current and future damages on infrastructure from flooding on residential housing was performed to determine whether damages are correlated with higher vulnerability areas. Results show in every flooding scenario, flood extents and depths are increasing in the future compared with the past, ranging from an increase of 6 to 76 km2 in extent across both locations. A statistically significant relationship between spatial clusters of flooding and of vulnerability was found. The infrastructure analysis found that residential structures in the most vulnerable census tracts are 6 to 59 times more likely to experience moderate damage compared with the least vulnerable tracts depending on scenario. Overall, a framework was established to holistically understand the hydrologic and socioeconomic impacts of climate change, and a methodology was developed to use for allocating resources at the local scale.

Epidemiology of Q fever in humans in four selected regions, Spain, 2016 to 2022.

BackgroundQ fever is a bacterial zoonosis caused by Coxiella burnetii. Spain has the highest number of notified human cases in Europe. Small ruminants are a key reservoir for the pathogen, transmission from animals to humans is usually airborne.AimWe aimed at exploring temporal and spatial epidemiological patterns of sporadic and outbreak cases of Q fever in four Spanish regions with the highest number of notified cases.MethodsWe extracted data on Q fever cases in the Canary Islands, Basque Country, La Rioja and Navarre between 2016 and 2022 from the Spanish National Epidemiological Surveillance Network. We calculated standardised incidence ratios (SIR), spatial relative risks (sRR) and posterior probabilities (PP) utilising Besag-York-Mollié models.ResultsThere were 1,059 notifications, with a predominance of males aged 30-60 years. In Basque Country, La Rioja and Navarre area, 11 outbreaks were reported, while no in the Canary Islands. A seasonal increase in incidence rates was observed between March and June. In the Canary Islands, elevated sRR was seen in La Palma, Gran Canaria, Lanzarote and Fuerteventura. In Basque Country, La Rioja and Navarre area, the highest sRR was identified in the south of Biscay province.ConclusionGoats were the main source for humans in outbreaks reported in the literature. Seasonal increase may be related to the parturition season of small ruminants and specific environmental conditions. Local variations in sRR within these regions likely result from diverse environmental factors. Future One Health-oriented studies are essential to deepen our understanding of Q fever epidemiology.

Spatial colocalization and combined survival benefit of natural killer and CD8 T cells despite profound MHC class I loss in non-small cell lung cancer.

Background: MHC class I (MHC-I) loss is frequent in non-small cell lung cancer (NSCLC) rendering tumor cells resistant to T cell lysis. NK cells kill MHC-I-deficient tumor cells, and although previous work indicated their presence at NSCLC margins, they were functionally impaired. Within, we evaluated whether NK cell and CD8 T cell infiltration and activation vary with MHC-I expression. Methods: We used single-stain immunohistochemistry (IHC) and Kaplan-Meier analysis to test the effect of NK cell and CD8 T cell infiltration on overall and disease-free survival. To delineate immune covariates of MHC-I-disparate lung cancers, we used multiplexed immunofluorescence (mIF) imaging followed by multivariate statistical modeling. To identify differences in infiltration and intercellular communication between IFNγ-activated and non-activated lymphocytes, we developed a computational pipeline to enumerate single cell neighborhoods from mIF images followed by multivariate discriminant analysis. Results: Spatial quantitation of tumor cell MHC-I expression revealed intra- and inter-tumoral heterogeneity, which was associated with the local lymphocyte landscape. IHC analysis revealed that high CD56+ cell numbers in patient tumors were positively associated with disease-free survival (DFS) (HR=0.58, p=0.064) and overall survival (OS) (HR=0.496, p=0.041). The OS association strengthened with high counts of both CD56+ and CD8+ cells (HR=0.199, p<1×10-3). mIF imaging and multivariate discriminant analysis revealed enrichment of both CD3+CD8+ T cells and CD3-CD56+ NK cells in MHC-I-bearing tumors (p<0.05). To infer associations of functional cell states and local cell-cell communication, we analyzed spatial single cell neighborhood profiles to delineate the cellular environments of IFNγ+/- NK cells and T cells. We discovered that both IFNγ+ NK and CD8 T cells were more frequently associated with other IFNγ+ lymphocytes in comparison to IFNγ- NK cells and CD8 T cells (p<1×10-30). Moreover, IFNγ+ lymphocytes were most often found clustered near MHC-I+ tumor cells. Conclusions: Tumor-infiltrating NK cells and CD8 T cells jointly affected control of NSCLC tumor progression. Co-association of NK and CD8 T cells was most evident in MHC-I-bearing tumors, especially in the presence of IFNγ. Frequent co-localization of IFNγ+ NK cells with other IFNγ+ lymphocytes in near-neighbor analysis suggests NSCLC lymphocyte activation is coordinately regulated.

Mechanisms of lymphoma-stromal interactions focusing on tumor-associated macrophages, fibroblastic reticular cells, and follicular dendritic cells.

The interaction between cancer cells and stromal cells contributes to the pathogenesis of various types of tumors in the tumor microenvironment (TME). Macrophages (Mφs), a type of stromal cell, are transformed into tumor-associated Mφs (TAMs) after integrating within solid tumors. TAMs are known to interact with cancer cells and induce tumor progression. Thus, the cancer cells construct an organ-specific TME, which is advantageous for the survival of cancer cells in the TME. The density of stromal cells is known to be involved in the prognosis of patients with lymphomas. A higher density of stromal cells increases the interaction between lymphoma cells and stromal cells, promoting lymphoma progression. This review focuses on stromal cells in lymphoid tissues, such as TAMs, fibroblastic reticular cells (FRCs), and follicular dendritic cells (FDCs). This review also focuses on the signal transduction caused by stromal cells and tumor cells via factors such as cytokines. IL-10 and other cytokines secreted by TAMs activate the JAK/STAT pathway in lymphoma cells of follicular lymphoma, classic Hodgkin lymphoma, and diffuse large B-cell lymphoma. FRCs play roles in tumor promotion in follicular lymphoma and diffuse large B-cell lymphoma. Cytokines/chemokines secreted by FDCs play essential roles in lymphoma cell survival, proliferation, invasion, and migration in follicular lymphoma. In conclusion, TAMs, FRCs, and FDCs play crucial roles in the TME of lymphomas. Furthermore, histological spatial analysis revealing the positional relationship of each cell could highlight lymphoma-stromal interactions.

Spatial Variation and Determinants of Inadequate Minimum Meal Frequency among Children Aged 6-23 Months in Ethiopia: Spatial and multilevel analysis using Ethiopian Mini Demographic and Health Survey (EMDHS) 2019.

Introduction: Minimum meal frequency is the number of times children eat in a day. Without adequate meal frequency, infants and young children are prone to malnutrition. There is little information on the spatial distribution and determinants of inadequate meal frequency at the national level. Therefore, we aimed to investigate the spatial distribution and determinants of inadequate meal frequency among young children in Ethiopia. Methods: The most recent Ethiopian demographic and health survey data was used. The analysis was conducted using a weighted sample of 1,610 children aged 6-23 months old. The Global Moran's I was estimated to assess the regional variation in minimum meal frequency. Further, a multivariable multilevel logistic regression model was fitted to identify factors associated with inadequate meal frequency. The AOR (adjusted odds ratio) at 95% CI (confidence interval) was computed to assess the strength and significance of the relationship between explanatory variables and the outcome variable. Factors with a p-value of <0.05 are declared statistically significant. Results: This study revealed that the prevalence of inadequate meal frequency was found to be 30.56% (95% CI: 28.33-32.88). We identified statistically significant clusters of high inadequate meal frequency, notably observed in Somalia, northern Amhara, the eastern part of southern nations and nationalities, and the southwestern Oromia regions. Child age, antenatal care (ANC) visit, marital status, and community level illiteracy were significant factors that were associated with inadequate meal frequency. Conclusion: According to the study findings, the proportion of inadequate meal frequency among young children in Ethiopia was higher and also distributed non-randomly across Ethiopian regions. As a result, policymakers and other concerned bodies should prioritize risky areas in designing intervention. Thus, special attention should be given to the Somalia region, the northern part of Amhara, the eastern part of Southern nations and nationalities, and southwestern Oromia.

Socioeconomic risk and the longitudinal child lifetime prevalence of child protection involvement.

BACKGROUND: North American studies find that geographic indicators of disadvantage, such as concentrated poverty, significantly increase the risk of child protection involvement. Despite having one of the most extensive family support systems and progressive income redistribution policies in North America, the Canadian province of Québec still faces geographic variations in socioeconomic conditions that remain a major risk factor for child protection involvement. OBJECTIVE: This study asks how child protection involvement is distributed across socioeconomically distinct geographic areas of the province. Drawing from prior literature, we hypothesize that the highest level of child protection involvement across childhood (age 0-17) is found in the lowest socioeconomic areas. PARTICIPANTS & SETTING: This is a population-based prevalence study using administrative child protection data spanning the years 2000 to 2017 across Québec. METHODS: We constructed cumulative risk life tables of first instances of child protection events (report confirmation, compromised security or development, and out-of-home placement). Prevalence rates were mapped onto 10,650 Census dissemination areas divided into three tiers according to a validated socioeconomic status (SES) index. RESULTS: The highest childhood prevalence of confirmed child protection reports, finding of compromised security or development, and out-of-home placement was found in the lowest SES areas. Rates in low SES areas can be over twice the rates in high SES areas. CONCLUSIONS: Area-level socioeconomic vulnerability remains a robust predictor of child protection involvement even in a socially progressive context. Our findings underscore that without targeted pediatric and family services, as well as poverty-alleviation programs for high-need families in high-need areas, even well-intentioned systems may fall short of reaching the families most in need.

Hidden leprosy in a low-endemic area in southern Brazil: changes in endemicity following an active search.

BACKGROUND: Leprosy, a neglected tropical disease, is reported in over 120 countries, with upwards of 200,000 new cases annually. This Cross-Sectional Cohort Study aimed to delineate the epidemiological profile of leprosy in a low-endemic area in southern Brazil, both before and after implementing an active search strategy. METHODS: The study examined two surveillance periods in Caçador, Santa Catarina, Brazil. The active search strategy was carried out through the application of the LSQ by the community health workers as a screening and detection tool for new cases of leprosy and this was compared with passive case detection. The first spanned from 2014 to 2020, and the second from January 2021 to August 2023. FINDINGS: 48 leprosy cases were reported throughout the study, 83.3 % of which were diagnosed as multibacillary. The first period had an average detection rate of 0.38 cases per 10,000 inhabitants, increasing to 1.19 cases per 10,000 inhabitants in the second period. Notably, there was a substantial shift in the degree of physical disability (GD), with more Grade 0 and Grade 1 disabilities observed post-active search. MAIN CONCLUSIONS: The study underscores the efficacy of active search strategies in early diagnosis, highlighting a 300 % increase in the annual average of diagnosed cases. This large number of detected cases demonstrates the high sensitivity of the LSQ. This approach significantly aids in uncovering hidden cases of leprosy, enhancing disease management and control in low-endemic areas indicating that the Ministry of Health should intensify leprosy control activities in these regions.

The impact of COVID-19 on tuberculosis in most populated state of India: A geospatial meta-analysis.

Background: Tuberculosis is one of the major burdens to developing nations. India is among the countries categorized by the World Health Organization (WHO) as experiencing a significant burden of TB, HIV-associated TB, and MDR/RR-TB within the context of low- and middle-income nations. Globally South East Asian and African region alone accounted for 82% of death (HIV negative), where India accounts for 36% of TB fatalities. Materials and Methods: The data was extracted from NIKSHAY web portal on TB notification cases in UP, India. The random effects meta-analysis was performed to estimate pooled proportion of TB cases in public and private notified during both the periods. Spatial analysis was used to display the spread of TB cases across the state, during both the periods. Results: A total 75 districts data on TB notified cases were available for current investigation. The pooled proportion of TB cases were 0.24 (0.21, 0.27) and 0.76 (0.73, 0.79) during COVID-19 period for private and public hospitals, respectively. Similarly, the pooled proportion of TB cases were 0.26 (0.23, 0.29) and 0.74 (0.71, 0.77) post-COVID-19 for private and public hospitals, respectively. Conclusion: The proportion of TB cases were more in public hospital as compared to private hospitals during COVID-19 period. Similarly, result was obtained in post-COVID-19 period.

Development and validation of a community risk score for sexual and reproductive health in the United States.

Equitable access to sexual and reproductive health (SRH) care is key to reducing inequities in SRH outcomes. Publicly funded family-planning services are an important source of SRH care for people with social risk factors that impede their access. This study aimed to create a new index (Local Social Inequity in SRH [LSI-SRH]) to measure community-level risk of adverse SRH outcomes based on social determinants of health (SDoH). We evaluated the validity of the LSI-SRH scores in predicting adverse SRH outcomes and the need for publicly funded services. The data were drawn from more than 200 publicly available SDoH and SRH measures, including availability and potential need for publicly supported family planning from the Guttmacher Institute. The sample included 72 999 Census tracts (99.9%) in the 50 states and the District of Columbia. We used random forest regression to predict the LSI-SRH scores; 42 indicators were retained in the final model. The LSI-SRH model explained 81% of variance in the composite SRH outcome, outperforming 3 general SDoH indices. LSI-SRH scores could be a useful for measuring community-level SRH risk and guiding site placement and resource allocation.

Trace metal pollution gradients in a tropical seagrass ecosystem.

Trace metals are one of the most serious pollutants in tropical seagrass meadows given their persistence and toxicity. Whereas quantity is frequently measured, there is no information on the spatial extent of metal pollution in these systems. Here, we use an island in Indonesia (Barang Lompo) as a model system to study the impact radius of two major and eight trace metals in sediment and seagrass leaves. We provide evidence for exponential decay in both the metal pollution index and concentrations of most metals with increasing distance from the island (k = -0.01 to -0.08 m-1). Consequently, there is an impact radius of approximately 100 m around the island. The comparative analysis of both seagrass species further revealed interspecific differences in metal loads. This study highlights the importance of assessing the spatial extent of metal pollution in addition to its quantity.

GIS-based methodology for tracking the grazing cattle site use.

Interest in tracking and monitoring animals in livestock farming using wearable sensors has been steadily increasing. The use of these devices is particularly crucial in extensive livestock systems where direct interaction between animals and farmers is infrequent, necessitating strenuous efforts in long-distance herd monitoring. Internet of Things (IoT) technologies offer a promising solution to address the challenges posed by vast distances, enabling real-time and remote animal monitoring. In this study, an experimental trial was conducted using a custom-designed device, located in a Polyvinyl Chloride (PVC) case, specifically tailored to fit onto a collar. This case incorporates an integrated SigFox communication system, i.e., a Low Power Global Positioning System (LP-GPS) omnidirectional system, and a power supply. The trial took place in two grazing areas located in different territorial zones, designated as Case Study I and II. A LP-GPS collar was provided for each selected animal, and the data were recorded at 20-min intervals for Case Study I and 10-min intervals for Case Study II. The acquired data were then imported and analysed using Geographical Information Systems (GIS) software. Information was collected through a purpose-built web application (AppWeb). The objective was to analyze those territorial areas mostly occupied by animals within the two considered grazing areas by developing a GIS-based methodology. Specifically, customized algorithms such as Heatmap and Kernel Density Estimation (KDE) plugins were employed to conduct spatial analyses. The maps obtained through Heatmap plugin, showed the temporal-spatial distribution of animals within their grazing areas. Additionally, the KDE tool was used to classify preferred territorial areas, generating tailored charts for each animal in the sample. The individual Core Areas, determined through KDE evaluation for each animal, were overlaid to provide a comprehensive analysis of the monitored animals.The results achieved applying the GIS-based methodology facilitated the identification of animal positions and could be adopted to provide insights into feeding behavior and soil erosion, thereby aiding in the prevention of environmental issues.

Evaluation of Brain Function Recovery After Traumatic Brain Injury Treatment in a Porcine Model by Cross-Group Temporal-Spatial Correlation Analysis.

Traumatic brain injury (TBI), a significant global health issue, is affecting ∼69 million annually. To better understand TBI's impact on brain function and assess the efficacy of treatments, this study uses a novel temporal-spatial cross-group approach with a porcine model, integrating resting-state functional magnetic resonance imaging (rs-fMRI) for temporal and arterial spin labeling for spatial information. Our research used 18 four-week-old pigs divided into three groups: TBI treated with saline (SLN, n = 6), TBI treated with fecal microbial transplant (FMT, n = 6), and a sham group (sham, n = 6) with only craniectomy surgery as the baseline. By applying machine learning techniques-specifically, independent component analysis and sparse dictionary learning-across seven identified resting-state networks, we assessed the temporal and spatial correlations indicative of treatment efficacy. Both temporal and spatial analyses revealed a consistent increase of correlation between the FMT and sham groups in the executive control and salience networks. Our results are further evidenced by a simulation study designed to mimic the progression of TBI severity through the introduction of variable Gaussian noise to an independent rs-fMRI dataset. The results demonstrate a decreasing temporal correlation between the sham and TBI groups with increasing injury severity, consistent with the experimental results. This study underscores the effectiveness of the methodology in evaluating post-TBI treatments such as the FMT. By presenting comprehensive experimental and simulated data, our research contributes significantly to the field and opens new paths for future investigations into TBI treatment evaluations.

Mapping lock-ins and enabling environments for agri-food sustainability transitions in Europe.

European agri-food systems must overcome structural lock-ins to achieve more sustainable modes of production and consumption. Yet European regions are highly diverse, and we lack understanding of how different regional characteristics may enable or inhibit sustainability transitions. This hinders the development of context-tailored governance strategies. In this paper, we identify and apply sets of spatial indicators to map the regional potentials for agri-food transitions. We first analyse the strength of lock-in to the incumbent agro-industrial paradigm. We then map the enabling environments for two alternative agri-food networks-multifunctional value chains and civic food networks-that each embed distinct social-ecological qualities of agriculture and food. Results demonstrate a large spatial diversity in transition potential, with stronger lock-ins throughout North and Western Europe and stronger enabling environments for agri-food transitions in Italy, France, Switzerland, and Southwest Germany. We find that lock-ins are strongest in livestock-dominated regions and are associated with higher GHG emissions and excess nitrogen levels. Our study demonstrates the need for coordinated public policies that (1) leverage region-specific transition potentials and (2) enable complementary innovations in market-based and community-led networks. Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-024-01480-y.