Project description:BackgroundMeasuring access to medicines has often been limited to assessing availability and affordability, while little is known regarding other dimensions of access including geographical accessibility. Our study aims to provide a systematic review of literature on the accessibility of medicines by studying the geographical distribution of pharmacies using Spatial Analytical methods.MethodsAs systematic review of scientific peer-reviewed literature between 2000 and 2018 was carried out using PubMed, Web of Science, Google Scholar, Google and the Preferred Reporting items for Systematic Reviews and Meta-Analyses (PRISMA). Data regarding pharmacy density, distance to pharmacies in relation of pharmacy to sociodemographic factors and pharmacy characteristics were extracted from studies that meet the inclusion criteria.FindingsTwenty papers fulfilled our inclusion criteria, of which only three were from middle income countries and rest from high-income economies. Pharmacy density per population was reported in 15 studies. Although geographical information was utilized in all studies, only 14 studies reported distance to pharmacies represented as Euclidean (straight line) distance. Disparities in accessibility was reported according to population income and rural or urban location. Seven studies described additional pharmacy characteristics including opening hours, presence of a pharmacist and delivery services.ConclusionsGeographical accessibility is a key dimension of access to medicines. Pharmacy density per population is a relevant indicator to assess geographical accessibility which should be complemented by an equity analysis using socio-demographic information and population perception of accessibility.
Project description:ImportanceCommunity pharmacies are crucial for public health, providing essential services such as medication dispensing, vaccinations, and point-of-care testing. Addressing disparities in pharmacy access, particularly in underserved rural and low-income areas, is critical for health equity.ObjectiveTo identify areas in the US at risk of becoming pharmacy deserts through the development of a novel pharmacy vulnerability index.Design, setting, and participantsThis population-based cross-sectional study in the contiguous 48 states performed geographic information systems analysis of pharmacy data from the National Council for Prescription Drug Programs (NCPDP) dataQ. Participants included all open-door pharmacies (community or retail pharmacies open to the general public without restrictions on who can access its services) in the US as of February 2024. Statistical analysis was performed from July to August 2024.ExposureThe primary exposure was travel time to pharmacies across the US.Main outcomes and measuresA pharmacy desert was defined as a census tract where the travel time to the nearest pharmacy exceeds the supermarket access time for that region and urbanicity level. Building on this definition, a pharmacy vulnerability index was developed, which indicates the number of pharmacies that would need to close for a census tract to become a pharmacy desert. Tracts with a pharmacy vulnerability index of 1, depending solely on a single pharmacy for access, were identified as at risk of becoming deserts. Subpopulation totals and percentages living in pharmacy deserts or relying on keystone pharmacies were computed, and then stratified by urbanicity and race.ResultsAmong 321.3 million individuals (39.7 million [12.3%] Black, 59.0 million [18.2%] Hispanic, 195.0 million [60.3%] White) in the contiguous US, 57.1 million (17.7%) were identified as living in pharmacy deserts, with 28.9 million (8.9%) additionally relying on a single pharmacy for access. Small rural areas were particularly affected, with a higher dependency on single pharmacies (4.1 million individuals [14.3%]).Conclusions and relevanceIn this cross-sectional study of pharmacy access in the US, significant disparities in pharmacy access were identified, especially pronounced in small rural areas. Targeted policy interventions, such as incremental reimbursement rates or other monetary incentives, are needed to ensure the financial sustainability of pharmacies that serve as the sole source of pharmacy services in at-risk areas.
Project description:ObjectivesLimited studies have investigated geographic accessibility to a nearby community pharmacy for elderly which is an essential determinant of the access to medications and pharmacy services. This research identified pharmacy deserts and investigated availability of different types of community pharmacies and their services for elderly enrolled in a State Pharmaceutical Assistance Program (SPAP).MethodsThe state of Pennsylvania in the US was used as a case to demonstrate the geographic accessibility to community pharmacy and services for elderly enrolled in SPAP. The locations of community pharmacies and households of elderly enrolled in SPAP were derived from Pharmaceutical Assistance Contract for the Elderly programs' database. The street addresses were geocoded and the distance to a nearby community pharmacy was calculated for study sample using the haversine formula. The demographic and geographic data were aggregated to Census Tracts and pharmacy deserts were identified using the predefined criteria. Descriptive statistical analysis was used to determine whether there are statistical differences in the socio-demographic profiles and distribution of different types of community pharmacies and their services in pharmacy deserts and non-deserts. This research used hot spot analyses at county level to identify clusters of pharmacy deserts, areas with high concentration of different racial/ethnic groups and clusters of high densities of chain and independent pharmacies.ResultsThe Spatial analysis revealed that 39% and 61% Census Tracts in Pennsylvania were pharmacy deserts and non-deserts respectively (p < 0.001). Pharmacy deserts were found to have significantly more females, married and white elderly and fewer blacks and Hispanics compared to pharmacy non-deserts. Pharmacy deserts had significantly fewer chain and independent pharmacies and less delivery and 24-hour services in pharmacies than pharmacy non-deserts. Hot spot analyses showed that clusters of pharmacy deserts were more concentrated in southcentral, northwest and northeast regions of the state which represent rural areas and overlapped with clusters of high concentration of white individuals.ConclusionsThe findings suggest that urban-rural inequality, racial/ethnic disparity and differences in availability of pharmacies and their services exist between pharmacy deserts and non-deserts. The methodological approach and analyses used in this study can also be applied to other public health programs to evaluate the coverage and breadth of public health services.
Project description:MotivationFederated Learning (FL) is gaining traction in various fields as it enables integrative data analysis without sharing sensitive data, such as in healthcare. However, the risk of data leakage caused by malicious attacks must be considered. In this study, we introduce a novel attack algorithm that relies on being able to compute sample means, sample covariances, and construct known linearly independent vectors on the data owner side.ResultsWe show that these basic functionalities, which are available in several established FL frameworks, are sufficient to reconstruct privacy-protected data. Additionally, the attack algorithm is robust to defense strategies that involve adding random noise. We demonstrate the limitations of existing frameworks and propose potential defense strategies analyzing the implications of using differential privacy. The novel insights presented in this study will aid in the improvement of FL frameworks.Availability and implementationThe code examples are provided at GitHub (https://github.com/manuhuth/Data-Leakage-From-Covariances.git). The CNSIM1 dataset, which we used in the manuscript, is available within the DSData R package (https://github.com/datashield/DSData/tree/main/data).
Project description:Non-technical summaryOur analysis shows that the framing of social vulnerability is shaped by a narrow definition of resilience, focusing on post-disaster return and recovery responses. This perspective does not account for the dynamism and non-stationarity of social-ecological systems (SES) which is becoming increasingly important in the face of accelerating environmental change. Incorporating social-ecological resilience into social vulnerability analysis can improve coastal governance by accounting for adaptation and transformation, as well as scale and cross-scale interactions.Technical summarySocial vulnerability analysis has been unable to deliver outcomes that reflect the reality of vulnerability and its consequences in an era characterised by accelerating environmental change. In this work, we used critical discourse analysis and key informant interviews to understand different framings of social vulnerability in coastal governance and management, globally and in New Zealand. We found that the framing of system vulnerability could vary depending on the definition of resilience adopted, which has critical ramifications for coastal governance of linked systems of humans and nature. We found that the framing of social vulnerability in coastal governance is mainly influenced by engineering, community and disaster resilience, focusing on return and recovery governance responses to environmental change (e.g. hurricanes, wildfires). Instead, we suggest a novel perspective based on social-ecological resilience, which more accurately reflects the dynamics of linked systems of humans and nature (SES). This revised perspective, general vulnerability, accounts for the dynamics of Earth's systems across various spatial and temporal scales in the face of accelerating environmental change. Accounting for social-ecological resilience and its core aspects (i.e. panarchy, adaptation and transformation) is essential for informing coastal governance of SES (Do we adapt? or Do we transform the SES?).Social media summarySocial-ecological resilience is essential for social vulnerability analysis in the face of accelerating environmental change.
Project description:With the increasing likelihood of agricultural production failures under a warmer global climate, the importance of markets in providing access to nutrient-dense foods (NDFs) through trade is predicted to grow. However, regions with relatively poor access to markets and supporting infrastructures (e.g. roads and storage facilities) are potentially ill-equipped to deal with both short-term hydrometeorological hazards such as droughts and floods, and longer-term shifts in agricultural productivity. Despite the increasing focus upon markets within academic and policymaking circles, a regional-scale assessment of these potentially coexisting hotspots of vulnerability has not been conducted. We conduct a two-stage geospatial analysis integrating three publicly available datasets across the Indian states of Bihar, Chhattisgarh, Jharkhand, and Odisha. Combining the 2011 national census with the new PMGSY-GeoSadak database, we conduct nearest neighbour analysis to measure multidimensional market inaccessibility by: (i) distance from a settlement to its nearest village, town or city with a market, (ii) distance from a settlement to its nearest major road, and (iii) distance from a settlement to its subdistrict headquarters. We then correlate these measures with India's only district-wise assessment of climate vulnerability to identify hotspots of market inaccessibility and climate hazards. We find that the three market access measures are spatially autocorrelated and positively interrelated at the settlement (n = 129 555) and district (n = 107) levels, meaning that settlements located further from their nearest market tend to experience poorer road connectivity and access to the subdistrict economic hub. Approximately 18.5-million people live in districts with relatively high climate vulnerability and relatively high and multidimensional market inaccessibility. Hotspots of coexisting vulnerabilities are also disproportionately populated by 'Schedule Castes and Schedule Tribes' (SC/ST) communities. The identification of coexisting hotspots has important implications for the development of equitable and resilient markets that bolster NDF access for climate vulnerable and nutritionally insecure populations.
Project description:BackgroundSocial vulnerability occurs when the disadvantage conveyed by poor social conditions determines the degree to which one's life and livelihood are at risk from a particular and identifiable event in health, nature, or society. A common way to estimate social vulnerability is through an index aggregating social factors. This scoping review broadly aimed to map the literature on social vulnerability indices. Our main objectives were to characterize social vulnerability indices, understand the composition of social vulnerability indices, and describe how these indices are utilized in the literature.MethodsA scoping review was conducted in six electronic databases to identify original research, published in English, French, Dutch, Spanish or Portuguese, and which addressed the development or use of a social vulnerability index (SVI). Titles, abstracts, and full texts were screened and assessed for eligibility. Data were extracted on the indices and simple descriptive statistics and counts were used to produce a narrative summary.ResultsIn total, 292 studies were included, of which 126 studies came from environmental, climate change or disaster planning fields of study and 156 studies were from the fields of health or medicine. The mean number of items per index was 19 (SD 10.5) and the most common source of data was from censuses. There were 122 distinct items in the composition of these indices, categorized into 29 domains. The top three domains included in the SVIs were: at risk populations (e.g., % older adults, children or dependents), education, and socioeconomic status. SVIs were used to predict outcomes in 47.9% of studies, and rate of Covid-19 infection or mortality was the most common outcome measured.ConclusionsWe provide an overview of SVIs in the literature up to December 2021, providing a novel summary of commonly used variables for social vulnerability indices. We also demonstrate that SVIs are commonly used in several fields of research, especially since 2010. Whether in the field of disaster planning, environmental science or health sciences, the SVIs are composed of similar items and domains. SVIs can be used to predict diverse outcomes, with implications for future use as tools in interdisciplinary collaborations.
Project description:Despite the rapid progress in dissecting neural circuits for social behaviors, it remains unknown whether specific neural cell types are selectively vulnerable in social dysfunction cases often associated with neurodevelopmental disorders. Here, employing a single-cell transcriptome analysis in mice, we show that an embryonic disturbance known to induce social dysfunction preferentially impairs gene expressions crucial for neural functions in parvocellular oxytocin (OT) neurons—a subtype linked to social rewards—while neighboring cell types experience a lesser impact. Chemogenetic stimulation of OT neurons at the neonatal stage ameliorated social deficits, concomitant with a cell-type-specific sustained recovery of the pivotal gene expressions. Our data illuminates the transcriptomic selective vulnerability within the hypothalamic social behavioral center, offering a potential therapeutic target through specific neonatal neurostimulation.
Project description:We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate the Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, and United States as an example, the study reveals that equitably mitigating urban overheat is achievable by considering the city's demographic composition and physical structure. The study results show that while urban trees may yield less cooling impact (0.27 K of Universal Thermal Climate Index in daytime) relative to cool roofs (0.30 K), the urban trees strategy can emerge as an effective approach for enhancing community resilience in heat stress-related outcomes. Social vulnerability-based heat mitigation was reviewed as vulnerability-weighted daily cumulative heat stress change. The results underscore: (i) importance of considering the community resilience when evaluating heat mitigation impact and (ii) the need to assess planting spaces for urban trees, rooftop areas, and neighborhood vulnerability when designing community-oriented urban overheating mitigation strategies.
Project description:Trust attitude is a social personality trait linked with the estimation of others' trustworthiness. Trusting others, however, can have substantial negative effects on mental health, such as the development of depression. Despite significant progress in understanding the neurobiology of trust, whether the neuroanatomy of trust is linked with depression vulnerability remains unknown. To investigate a link between the neuroanatomy of trust and depression vulnerability, we assessed trust and depressive symptoms and employed neuroimaging to acquire brain structure data of healthy participants. A high depressive symptom score was used as an indicator of depression vulnerability. The neuroanatomical results observed with the healthy sample were validated in a sample of clinically diagnosed depressive patients. We found significantly higher depressive symptoms among low trusters than among high trusters. Neuroanatomically, low trusters and depressive patients showed similar volume reduction in brain regions implicated in social cognition, including the dorsolateral prefrontal cortex (DLPFC), dorsomedial PFC, posterior cingulate, precuneus, and angular gyrus. Furthermore, the reduced volume of the DLPFC and precuneus mediated the relationship between trust and depressive symptoms. These findings contribute to understanding social- and neural-markers of depression vulnerability and may inform the development of social interventions to prevent pathological depression.