BACKGROUND: Adverse social determinants of health have been shown to be associated with a greater chance of developing chronic conditions. Although there has been increased focus on screening for health-related social needs (HRSNs) in health care delivery systems, it is seldom examined if the provision of needed services to address HRSNs is sufficiently available in communities where patients reside.
METHODS: The authors used geospatial analysis to determine how well a newly formed health system and community-based organizations (CBOs) social care coordination network covered the areas in which a high number of patients experiencing HRSNs live. Geospatial clusters (hotspots) were constructed for Kaiser Permanente Northwest members experiencing any of the following 4 HRSNs: transportation needs, housing instability, food insecurity, or financial strain. Next, a geospatial polygon was calculated indicating whether a member could reach a social care provider within 30 minutes of travel time.
RESULTS: A total of 185,535 Kaiser Permanente Northwest members completed a HRSN screener between April 2022 and April 2023. Overall, the authors found that among Kaiser Permanente Northwest members experiencing any of the 4 HRSNs, 97% to 98% of them were within 30 minutes of a social care provider. A small percentage of members who lived greater than 30 minutes to a social care provider were primarily located in rural areas.
CONCLUSIONS: This study demonstrates the importance of health system and community-based organization partnerships and investment in community resources to develop social care coordination networks, as well as how patient-level HRSN can be used to assess the coverage and representativeness of the network.

This study employs comprehensive clustering analysis to examine COVID-19 vaccine hesitancy and related socio-demographic factors across U.S. counties, using the collected and curated data from Johns Hopkins University. Utilizing K-Means and hierarchical clustering, we identify five distinct clusters characterized by varying levels of vaccine hesitancy, MMR vaccination coverage, population demographics, and political affiliations. Principal Component Analysis (PCA) was conducted to reduce dimensionality, and key variables were selected based on their contribution to cumulative explained variance. Our analysis reveals significant geographic and demographic patterns in vaccine hesitancy, providing valuable insights for public health strategies and future pandemic responses. Geospatial analysis highlights the distribution of clusters across the United States, indicating areas with high and low vaccine hesitancy. In addition, multiple regression analyses within each cluster identify key predictors of vaccine hesitancy in corresponding U.S. county clusters, emphasizing the importance of socio-economic and demographic factors. The findings underscore the need for targeted public health interventions and tailored communication strategies to address vaccine hesitancy across the United States and, potentially, across the globe.

This study focusses on ground and surface water resources in the northern parts of the Indo-Gangetic Plains. The study aims to identify potential contaminants, analyse their distribution, trace their origins, and evaluate associated health risk. Samples from 80 locations; groundwater (n = 69) and surface water (n = 11) were analysed for nineteen trace and toxic elements using ICP-MS. Eight elements in groundwater (Mn, Fe, Ni, Zn, As, Tl, U and Se) and six in surface water (Al, Mn, Fe, Ni, Zn, and Tl) exceeded WHO (2011) and BIS (2012) limits in certain areas. The geospatial analysis reveals hotspots of trace and toxic element concentration, with higher levels detected in the southeast and western regions of the study area. Correlation matrices revealed a robust correlation (∼>0.75-0.99, p < 0.01) among all trace and toxic elements (excluding Li, Be, As, Ag, and U) in surface water samples when compared to groundwater samples. Cluster analysis and principal component analysis (PCA) (explains 70.09 cumulative percent for total 6 of factors) of groundwater chemistry indicates that Zn, Ni and Tl contamination may originate from industrial activities (metallurgical processes and manufacturing). The potential sources of Mn may be both geological and human-induced, while Fe, Se, As and U can originate from specific geological formations or human-related activities like over-extraction and leaching of excess fertilizers into aquifers. For surface water, PCA (explains 92.92 cumulative percent for total 5 of factors) identifies industrial activities as the main source of Mn, Fe, Tl, Ni, and Zn, while Al originates from both geological and anthropogenic sources. The water quality index indicated poor to very poor water quality in the western and central regions, whereas the northern and eastern regions exhibited excellent water quality. Health risk assessment reveals HI values for groundwater water: 3.85 (adults), 7.70 (children); surface water: 1.52 (adults), 3.05 (children), emphasizing the urgent need for remediation measures.

OBJECTIVE: The ability to apply results from a study to a broader population remains a primary objective in translational science. Distinct from intrinsic elements of scientific rigor, the extrinsic concept of generalization requires there be alignment between a study cohort and population in which results are expected to be applied. Widespread efforts have been made to quantify representativeness of study cohorts. These techniques, however, often consider the study and target cohorts as monolithic collections that can be directly compared. Overlooking known impacts to health from socio-demographic and environmental factors tied to individual\'s geographical location, and potentially obfuscating misalignment in underrepresented population subgroups. This manuscript introduces several measures to account for geographic information in the assessment of cohort representation.
METHODS: Metrics were defined across two themes: First, measures of recruitment, to assess if a study cohort is drawn at an expected rate and in an expected geographical pattern with respect to individuals in a reference cohort. Second, measures of individual characteristics, to assess if the individuals in the study cohort accurately reflect the sociodemographic, clinical, and geographic diversity observed across a reference cohort while accounting for the geospatial proximity of individuals.
RESULTS: As an empirical demonstration, methods are applied to an active clinical study examining asthma in Black/African American patients at a US Midwestern pediatric hospital. Results illustrate how areas of over- and under-recruitment can be identified and contextualized in light of study recruitment patterns at an individual-level, highlighting the ability to identify a subset of features for which the study cohort closely resembled the broader population. In addition they provide an opportunity to dive deeper into misalignments, to identify study cohort members that are in some way distinct from the communities for which they are expected to represent.
CONCLUSIONS: Together, these metrics provide a comprehensive spatial assessment of a study cohort with respect to a broader target population. Such an approach offers researchers a toolset by which to target expected generalization of results derived from a given study.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

BACKGROUND: Along the southern shoreline of Lake Malawi, the incidence of schistosomiasis is increasing with snails of the genera Bulinus and Biomphalaria transmitting urogenital and intestinal schistosomiasis, respectively. Since the underlying distribution of snails is partially known, often being focal, developing pragmatic spatial models that interpolate snail information across under-sampled regions is required to understand and assess current and future risk of schistosomiasis.
METHODS: A secondary geospatial analysis of recently collected malacological and environmental survey data was undertaken. Using a Bayesian Poisson latent Gaussian process model, abundance data were fitted for Bulinus and Biomphalaria. Interpolating the abundance of snails along the shoreline (given their relative distance along the shoreline) was achieved by smoothing, using extracted environmental rainfall, land surface temperature (LST), evapotranspiration, normalised difference vegetation index (NDVI) and soil type covariate data for all predicted locations. Our adopted model used a combination of two-dimensional (2D) and one dimensional (1D) mapping.
RESULTS: A significant association between normalised difference vegetation index (NDVI) and abundance of Bulinus spp. was detected (log risk ratio - 0.83, 95% CrI - 1.57, - 0.09). A qualitatively similar association was found between NDVI and Biomphalaria sp. but was not statistically significant (log risk ratio - 1.42, 95% CrI - 3.09, 0.10). Analyses of all other environmental data were considered non-significant.
CONCLUSIONS: The spatial range in which interpolation of snail distributions is possible appears < 10km owing to fine-scale biotic and abiotic heterogeneities. The forthcoming challenge is to refine geospatial sampling frameworks with future opportunities to map schistosomiasis within actual or predicted snail distributions. In so doing, this would better reveal local environmental transmission possibilities.

BACKGROUND: Few studies have examined county-level hotspots of veteran suicide and associated place-based contributors, limiting development of targeted community-level prevention strategies. The objectives of this national spatial analysis of all veteran suicides were to identify areas of the United States with higher-than-expected veteran suicide rates and determine county-level social and economic characteristics associated with areas of higher risk.
METHODS: Using Bayesian hierarchical modeling, county-level standardized mortality ratios for veteran suicide deaths were estimated for time periods 2011-2018, 2011-2014, and 2015-2018. Adjusted relative risk, accounting for community characteristics, for each county was then estimated and associations between community characteristics and veteran suicide risk were examined. Analyses were conducted in 2023-2024.
RESULTS: Risk of veteran suicide is predominantly concentrated in the Mountain West and West. Significant predictors of risk across all time periods were per capita number of firearm retailers (2011-2018 relative risk [RR]=1.065 [95% credible interval [CI] 1.030-1.102]), the proportion of residents who moved in the past year (2011-2018 RR=1.060 [95% CI 1.039-1.081]), the proportion of residents who live alone (2011-2018 RR=1.067 [95% CI 1.046-1.089]), the proportion of residents in rental housing (2011-2018 RR=1.041 [95% CI 1.018-1.065]), and the proportion of married residents (2011-2018 RR=0.915 [95% CI 0.890-0.941]).
CONCLUSIONS: This study contributes to a comprehensive public health approach to veteran suicide prevention by identifying where resources are needed most, and which place-based intervention targets have the largest potential for impact. Findings suggest that public health efforts to address suicide among veterans should address community-level firearm access and identify ways to alleviate deleterious effects of social fragmentation.

Anaemia remains a major nutritional-related health concern for women under reproductive age (WRA) in developing nations like India as well as the Indian EAG states. According to NFHS round-5, EAG states constitute 57% of WRA having any form of anaemia, higher than many other states of India and other developed and developing nations. This study aimed to assess the frequency of anaemia among the WRA in India\'s eight EAG states. Also, it attempts to analyse the causes associated with anaemia by the women\'s background characteristics with spatial correlation with its co-variates across 291 districts of the EAG states. One of the most current Demographic and Health Survey\'s (DHS) cross-sectional data is the NFHS-5th (2019-21) round taken, conducted by the IIPS under the administration of MoHFW, India. This study only included 315,069 women under reproductive age (WRA). The variables related to anaemia among women\'s (WRA) background socio-demographic characteristics were assessed using bivariate statistics and multinominal logistic regression analysis to comprehend the spatial correlation between women and their determinant factors. Among the EAG states, the overall prevalence of anaemia was 57%, varying from 42.6% in Uttarakhand to 65.3% in Jharkhand. Multinominal logistic regression analyses reveal that the chances of anaemia are remarkably more prevalent in younger women (15-19 years of age), women living in rural areas, no educated and primary level educated women, women belonging to the middle to poorest wealth quintile, women no longer living together, women of the Christian religion, women who are not exposed to reading newspapers, underweight BMI women, and scheduled tribe women. Mainly, the prevalence is observed in the North-eastern and southeastern states of Bihar, Jharkhand, Odisha, Chhattisgarh, some parts of Madhya Pradesh, Uttar Pradesh, and Rajasthan, which is shown by the hotspot map. According to the findings of this study, numerous factors like family, socioeconomic, educational, awareness, and individual characteristics such as caste and domicile all lead to a risk of anaemia. The WRA suffers from anaemia as a result of their socioeconomic background and awareness, which leads to a lack of nourishment, and they seek nutrient deficiencies. To overcome this anaemia, multiple discipline policies and initiatives need to be taken targeting women\'s wellness and nutritional status by increasing women\'s education and socioeconomic status.

BACKGROUND: Pediatric scald burns account for 12% of all U.S. burn center admissions and are the most common type of burn in children. We hypothesized that geospatial analysis of burn registry data could identify specific geographic areas and risk factors to focus injury prevention efforts.
METHODS: The burn registry of a U.S. regional burn center was used to retrospectively identify pediatric scald burn patients ages 0-17, from January 2018 to June 2023. Geocoding of patient home addresses with census tract data was performed. Area Deprivation Index (ADI) was assigned to patients at the census block group level. Burn incident hot spot analysis to identify statistically significant burn incident clusters was done using the Getis Ord Gi∗ statistic.
RESULTS: There were 950 pediatric scald burn patients meeting study criteria. The cohort was 52% male and 36% White, with median age of 3 y and median total body surface area of 1.5%; 23.8% required hospital admission. On multivariable logistic regression, increased child poverty levels (P = 0.004) and children living in single-parent households (P = 0.009) were associated with increased scald burn incidence. Geospatial analysis identified burn hot spots, which were associated with higher ADI (P < 0.001). Black patients were more likely to undergo admission compared to White patients.
CONCLUSIONS: Geospatial analysis of burn registry data identified geographic areas at high risk of pediatric scald burn. ADI, poverty, and children in single-parent households were the greatest predictors of injury. Addressing these inequalities requires targeted injury prevention education, enhanced outpatient support systems and more robust community resources.

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