Adherence to a Mediterranean type of diet in the world: a geographical analysis based on a systematic review of 57 studies with 1,125,560 participants.

This systematic review aimed to assess the level and time-trends of adherence to Mediterranean-type diets (MTD) among the general population, globally. According to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, a comprehensive literature search of the MEDLINE and Scopus databases was carried out, until 04/09/2023, based on specific criteria. Fifty-seven studies with 1,125,560 apparently healthy adults from Europe (n = 37), US (n = 8), Asia (n = 8), Australia (n = 4) and Africa (n = 1) were included. Adherence to an MTD was moderate with a significant decline observed in the last decade. European countries, mainly driven by Mediterranean countries, showed higher adherence than other regions. Geographical analysis revealed that adherence to an MTD is related to both geographic location and socioeconomic status throughout the world.

Little Between-Region and Between-Country Variance When People Form Impressions of Others.

To what extent are perceivers' first impressions of other individuals dictated by cultural background rather than personal idiosyncrasies? To address this question, we analyzed a globally diverse data set containing 11,481 adult participants' ratings of 120 targets across 45 countries (2,597,624 total ratings). Across ratings of 13 traits, we found that perceivers' idiosyncratic differences accounted for approximately 29% of variance and impressions on their own and approximately 16% in conjunction with target characteristics. However, country- and region-level differences, here a proxy for culture, accounted for 3.2% on average (i.e., both alone and in conjunction with target characteristics). We replicated this pattern of effects in a preregistered analysis on an entirely novel data set containing 7,007 participants' ratings of 100 targets across 41 countries (24,886 total ratings). Together, these results suggest that perceivers' impressions of other people are largely dictated by their individual characteristics and local environment rather than their cultural background.

Spatial Epidemiology of Sporadic Creutzfeldt-Jakob Disease in Apulia, Italy.

BACKGROUND: Sporadic Creutzfeldt-Jakob disease (CJD) is a rare neurodegenerative disease caused by prions that is randomly distributed in all countries, with an overall yearly mortality rate of about 1-2 cases per million people. On a few occasions, however, sporadic CJD occurred with higher than expected rates, but further investigations failed to recognize any convincing causal link. In Italy, cluster analyses of sporadic CJD cases have not been performed previously. OBJECTIVE: To investigate the geographical distribution of sporadic CJD using municipality geographical data of Apulia with the aim of detecting spatial clusters of disease. PATIENTS AND METHODS: Patients included in this study were diagnosed as probable or definite sporadic CJD and were residents of the Apulia Region (Italy). Bayesian hierarchical models with spatially structured and unstructured random components were used to describe the spatial pattern of the disease and to assess the extent of heterogeneity among municipalities. The Kulldorff-Nagarwalla scan test and the flexible spatial scan statistic were used for detecting spatial clusters. RESULTS: Smoothed Bayesian relative risks above the null value were observed in a few adjacent municipalities in the north and middle areas of Apulia. However, both the circular scanning method and the flexible spatial scan statistic identified only a single cluster in the central part of the region. CONCLUSION: Geographical analyses and tests for spatial randomness identified a restricted area with an unusually high number of sporadic CJD cases in the Apulia region of Italy. Environmental and genetic risk factors other than mutations in the prion protein gene however, need to be investigated.

Spatial analysis of hypospadias cases in northern France: taking clinical data into account.

BACKGROUND: Strong evidence for a causal role of environmental factors in a congenital anomaly is still difficult to produce. The collection of statistical data is crucial for gaining a better understanding of the epidemiology and pathophysiology of these anomalies. We aimed to evaluate spatial variations in hypospadias within our region and it's association to socioeconomic and ecological factors, taking clinical data into account. METHODS: All boys with hypospadias born in northern France and seen in Lille University Medical Center (Lille, France) between 1999 and 2012 were included in the analysis. We retrospectively collected geographic data, clinical data (especially known confounding factors associated with an elevated risk of hypospadias), and demographic, socio-economic and ecological data. We analyzed the entire study population and subsequently the subset of boys lacking confounding factors. RESULTS: The study sample of 975 cases of hypospadias over the 13-year period resulted in an incidence of 25.4/10,000 male births, and was characterized by significant spatial heterogeneity (p < 0.005) and autocorrelation (p < 0.001). We detected two high-incidence clusters that differed with regard to their land use. After the exclusion of 221 patients with confounding factors, two high-incidence clusters with significant disease risks (1.65 and 1.75, respectively; p < 0.001) and a significant difference in land use (p < 0.001) again appeared. The first cluster contained a higher median [interquartile range] proportion of artificialized land (0.40 [0.22;0.47]) than the remaining "neutral areas" (0.19 [0.08;0.53]) did (p < 0.001). Conversely, the second cluster contained a higher median proportion of rural land (0.90 [0.78;0.96]) than the "neutral areas" (0.81 [0.47;0.92]) did (p < 0.001). The median deprivation index was significantly lower in the urban cluster (0.47 [0.42;0.55]) and significantly higher in the rural cluster (0.69 [0.56;0.73]) (p < 0.001). CONCLUSIONS: Our results evidenced the heterogeneous spatial distribution of cases of hypospadias in northern France. We identified two clusters with different environmental and social patterns - even after the exclusion of known confounding factors.

Geographical variation in dementia prevalence across China: a geospatial analysis.

Background: Dementia poses great health and social challenges in China. Dementia prevalence may vary across geographic areas, while comparable estimations on provincial level is lacking. This study aims to estimate dementia prevalence by provinces across China, taking into account risk factors of individual level and potential spatial correlation of provinces. Methods: In this study, 17,176 adults aged 50 years or older were included from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS 2018), covering 28 provinces, autonomous regions and municipalities. To improve provincial representativeness, we constructed provincial survey weights based on China 7th census (2020). The prevalence of dementia and 95% Bayesian credible intervals (BCIs) were estimated using a Bayesian conditional autoregressive (CAR) model with spatially varying coefficients of covariates. Findings: The weighted prevalence of dementia at provincial level in China in 2018 ranged from 2.62% (95%BCI: 1.70%, 3.91%) to 13.53% (95%BCI: 8.82%, 20.93%). High dementia prevalence was concentrated in North China, with a prominent high-high cluster, while provinces of low prevalence were concentrated on East and South China, characterized by a low-low cluster. Ordered by the median estimation of prevalence, the top 10% of provinces, include Xinjiang, Jilin, and Beijing. Meanwhile, Fujian, Zhejiang, and Guangdong rank among the last. The association between dementia prevalence and drinking, smoking, social isolation, physical inactivity, hearing impairment, hypertension, and diabetes exhibits provincial variation. Interpretation: Our study identifies a geospatial disparity in dementia prevalence and risk factor effects across China's provinces, with high-high and low-low clusters in some northern and southern provinces, respectively. The findings emphasize the need for targeted strategies, such as addressing hypertension and hearing impairment, in specific regions for more effective dementia prevention and treatment. Funding: National Science Foundation of China/the Economic and Social Research Council, UK Research and Innovation joint call: Understanding and Addressing Health and Social Challenges for Ageing in the UK and China. UK-China Health And Social Challenges Ageing Project (UKCHASCAP): present and future burden of dementia, and policy responses (grant number 72061137003, ES/T014377/1).

Spatial distribution and geographical heterogeneity factors associated with households' enrollment level in community-based health insurance.

Background: Healthcare service utilization is unequal among different subpopulations in low-income countries. For healthcare access and utilization of healthcare services with partial or full support, households are recommended to be enrolled in a community-based health insurance system (CBHIS). However, many households in low-income countries incur catastrophic health expenditure. This study aimed to assess the spatial distribution and factors associated with households' enrollment level in CBHIS in Ethiopia. Methods: A cross-sectional study design with two-stage sampling techniques was used. The 2019 Ethiopian Mini Demographic and Health Survey (EMDHS) data were used. STATA 15 software and Microsoft Office Excel were used for data management. ArcMap 10.7 and SaTScan 9.5 software were used for geographically weighted regression analysis and mapping the results. A multilevel fixed-effect regression was used to assess the association of variables. A variable with a p < 0.05 was considered significant with a 95% confidence interval. Results: Nearly three out of 10 (28.6%) households were enrolled in a CBHIS. The spatial distribution of households' enrollment in the health insurance system was not random, and households in the Amhara and Tigray regions had good enrollment in community-based health insurance. A total of 126 significant clusters were detected, and households in the primary clusters were more likely to be enrolled in CBHIS. Primary education (AOR: 1.21, 95% CI: 1.05, 1.31), age of the head of the household >35 years (AOR: 2.47, 95% CI: 2.04, 3.02), poor wealth status (AOR: 0.31, 95% CI: 0.21, 1.31), media exposure (AOR: 1.35, 95% CI: 1.02, 2.27), and residing in Afar (AOR: 0.01, 95% CI: 0.003, 0.03), Gambela (AOR: 0.03, 95% CI: 0.01, 0.08), Harari (AOR: 0.06, 95% CI: 0.02, 0.18), and Dire Dawa (AOR: 0.02, 95% CI: 0.01, 0.06) regions were significant factors for households' enrollment in CBHIS. The secondary education status of household heads, poor wealth status, and media exposure had stationary significant positive and negative effects on the enrollment of households in CBHIS across the geographical areas of the country. Conclusion: The majority of households did not enroll in the CBHIS. Effective CBHIS frameworks and packages are required to improve the households' enrollment level. Financial support and subsidizing the premiums are also critical to enhancing households' enrollment in CBHIS.

Is there a casual relation between air pollution and dementia?

Dementia has been cited as a critical public health risk in the contemporary world, while few empirical researchers try to reveal the casual relationship between air pollutant concentrations (APCs) and dementia, especially given the increasing prevalence of air pollution on a global scale. Accordingly, this paper tries to infer the causal relationship between APCs and dementia. The 59,605 valid data was compiled through a combination of the statistic from the China Family Panel Study, China Environmental Statistics Yearbook, World Meteorological Association and China National Bureau of Statistics. The RD design of this study utilizes the discontinuous variation in APCs and dementia as one crosses the Huai River boundary, which is an arbitrary heating policy that causes the significant difference in APCs between the north and south of China. We used stata17.0 to analyze the data. The results of the RD regression indicated that a 100 µ g/m3 rise in APCs led to an increase of 42.4% in the hazard ratio of suffering dementia (Coeff=-0.58, SD= 0.23, P < 0.05). Meanwhile, heterogeneous models revealed that the hazard ratio of suffering dementia by APCs was more significant in the older compared to younger (coeff= 1.35 vs coeff= 1.55, P < 0.05), male compared to female (coeff= 1.62 vs coeff= 0.71, P < 0.05), smoking compared to non-smoke (coeff= 2.12 vs coeff= 0.93, P < 0.05), and thin groups compared to medium and obesity (coeff= 2.05 vs coeff= 1.22, coeff= 1.28, P < 0.05). In addition, the O3 and SO2 were the air pollutants with the highest (coeff= 1.54, P < 0.05) and lowest effects (coeff= 0.81, P < 0.05) on the hazard ratio of suffering dementia among the five APCs, respectively. And the robustness of the results was ensured by changing the RD bandwidth, polynomial order. The results indicated that APCs significantly induced the hazard ratio of suffering dementia of Chinese residents, which provides empirical evidence in supporting the Chinese government to invest more in combating air pollution and ensure the public health of Chinese residents.

Beyond the numbers: An in-depth look at Cameroon's fifth national COVID-19 vaccination campaign through geographical and gender lenses.

BACKGROUND: Cameroon has been struggling with low Covid-19 vaccination coverage, with only 4.5 % of the population receiving the primary series as of November 2022. The COVID-19 Vaccine Delivery Partnership (CoVDP) conducted a high-level mission to Cameroon to assess progress and advocate for actions to address bottlenecks. The objective of the mission was to administer at least 3,000,000 doses of vaccines during the 5th Mass vaccination campaign. This study examines the factors contributing to the success of the campaign and uses a geographical and gender lens to assess the results. METHODS: The study is a secondary analysis of data from the DHIS2 collected during the 5th mass vaccination campaign for Covid-19. Descriptive statistics were used to assess coverages per location and gender expressed in OR. sccess factors, and chi-squared tests were used to assess differences in vaccine distribution across regions and by gender. RESULTS: This 5th vaccination campaign benefitted from a strong political commitment facilitated by CoVDP's mission, international support, collaboration, planning, supervision, and demand generation. The campaign recorded 2 019 118 administered vaccine doses, a staggering 46-fold increase in vaccinated individuals relative to the first round, with vaccination coverage reaching 10.1 % of the general population. However, the study reveals regional and gender disparities in vaccination coverage. Men had higher odds of being vaccinated than women in the three Sahel regions. Among individuals with comorbidities, the national coverage rate was only 14 %, and the Far North and East regions exhibited the lowest coverage rates. Janssen was the most used vaccine, and the total AEFI cases reported were 2 per 1000 vaccine doses. CONCLUSION: The 5th COVID-19 vaccination campaign in Cameroon saw a strong political commitment and was the most successful so far. Despite the gains, there was gender disparity in coverage in some regions. It is important to continue the established momentum, ensure equitable access in the Sahel regions, and reach high-priority groups with primary series and booster doses.

Environmental forensic approach towards unraveling contamination sources with receptor models: A case study in Nakdong River, South Korea.

The upstream of Nakdong River is contaminated by heavy metals such as Cd, Cu, Zn, As, and Pb. Although the origin of the contamination is unequivocal, it is suspected that the heavy metals have been leached from several mine tailings and a refinery. Here, receptor models, absolute principal component score (APCS) and positive matrix factorization (PMF), were used to identify the contamination sources. Source markers representing each source (factor) were investigated using correlation analysis for five major contaminants (Cd, Zn, As, Pb, and Cu) and identified as following: Cd and Zn for the refinery (factor 1), As for mine tailings (factor 2). The categorization of sources into two factors was statistically validated via the cumulative proportion and APCS-based KMO test score with the values >90 % and > 0.7 (p < 0.001), respectively. High R2 values of linear regressions between the predicted data from receptor models and observed data indicate the reliability of the model prediction; moreover, the predicted initial concentrations of contaminants were validated using a sediment sample collected from near the refinery (chi-test: p > 0.200). Concentration distribution and source contribution using GIS revealed the heavy metal contaminated zones affected by the precipitation.

American Indian and Alaskan Native Access to Obstetrics and Gynecology Subspecialists: Findings From a National Mystery Caller Study in the United States.

Background A significant disparity exists for American Indian and Alaska Native populations in accessing obstetric and gynecology (OBGYN) subspecialty care, as nearly 43% of individuals do not reside in areas where the Indian Health Service (IHS) provides care. Geographical separation from IHS facilities exacerbates healthcare disparities, particularly regarding access to specialized services. This study aims to create a map illustrating the average driving time from an IHS clinic to OBGYN subspecialists (e.g., gynecologic oncology, maternal-fetal medicine, family planning, urogynecology, pediatric and adolescent gynecology, and reproductive endocrinology and infertility [REI]) and determine the average wait time for appointments with these specialists. Study design A cross-sectional and mystery caller study was conducted using hospital-level data from the IHS and data on women from the 2010 United States Census provided by the US Census Bureau. All US OBGYN subspecialists were identified and mapped. The local distribution of clinics near IHS hospitals was determined, and the nearest OBGYN subspecialist was mapped to IHS hospitals providing women's care services. Thirty-seven OBGYN subspecialists closest to IHS hospitals were contacted to calculate the mean wait time for subspecialty care appointments. Results The median driving time to the closest gynecologic oncology, maternal-fetal medicine, family planning, urogynecology, pediatric and adolescent gynecology, and reproductive endocrinology and infertility OBGYN subspecialist was 214 minutes (interquartile range [IQR] 107-290). The longest drive to see a subspecialist for urogynecology services was over 240 minutes. From the 2010 US Census, we identified 583,574 American Indian and Alaska Native (AI/AN) pediatric, adolescent, and women within a 60-minute drive of an IHS hospital. The mean wait time for a new patient appointment was 13.6 business days (SD ± 2). Conclusions Geographical disparities significantly impact the ability of American Indian and Alaska Native populations to access OBGYN subspecialty care. There was no difference in wait times compared to the national average, though there were significantly longer drive times.

Mind the gap. How job task distributions of health professional developers constitute evidence-based practice.

BACKGROUND: Development of clinical practice at a Danish neurorehabilitation centre was delegated to a group of health professional developers. Their job function lacked conceptual foundation, and it was unclear how their working tasks contributed to evidence-based practice. OBJECTIVE: Conceptual clarification of the job function and pattern analysis of activity distributions for health professional developers. METHODS: Health professional developers kept continuous time geographical diaries for two weeks. Meaningful categories were subtracted through content analysis. Patterns were analysed within activity distributions with regards to evidence-based practice. RESULTS: A total of 213 diaries were collected from 21 health professional developers of three professions (physiotherapists, occupational therapists and nurses). Each participant reported 6-13 workdays (median 10 days). Eleven main categories of work tasks emerged with 42 subcategories. Overall, 7% of total time reported was spent on external knowledge, with minimal variation between professions and contractual time allocation. CONCLUSION: Conceptual clarification of work tasks was established for health professional developers. Their work activity distributions contributed mainly to maintenance of existing level of professional knowledge rather than to implementation of new knowledge, which did not fulfil the intended responsibility for development of evidence-based practice. Educational competence boost and data-driven change of organisation structure was recommended.

Using Geospatial Analysis to Inform Development of a Place-Based Integrated Care Initiative: The Healthy Homes and Neighbourhoods Experience.

INTRODUCTION: Disadvantaged families experience many barriers to accessing health and social care. The Healthy Homes and Neighbourhoods (HHAN) Integrated Care Initiative was developed to address these barriers, and ensure families have their complex needs met and are kept safe and connected to society. DESCRIPTION: A spatial epidemiology approach was taken, as part of the HHAN feasibility phase, to identify the geographical distribution of the "most vulnerable" families in Sydney Local Health District (SLHD). A literature review was conducted to identify indicators of family stress and disadvantage, and cluster and hotspot analyses were undertaken. Hotspots of family stress and disadvantage were mapped for SLHD and used to identify areas for HHAN place-based delivery, and for collaborative co-design. DISCUSSION: The HHAN initiative called for consideration of context and the undertaking of collaborative design with communities. The spatial analysis provided a more accurate picture of family stress and disadvantage than previously available and provided a tool that could be used during consultation and planning activities. CONCLUSION: When planning place-based integrated care initiatives, spatial analysis of small geographic scales can allow identification of areas of concentrated or complex disadvantage that may be masked when analysis is performed on larger areas, allowing for targeted, place-based delivery of programs to those most in need.

Discrete versus continuous domain models for disease mapping.

The main goal of disease mapping is to estimate disease risk and identify high-risk areas. Such analyses are hampered by the limited geographical resolution of the available data. Typically the available data are counts per spatial unit and the common approach is the Besag-York-Mollié (BYM) model. When precise geocodes are available, it is more natural to use Log-Gaussian Cox processes (LGCPs). In a simulation study mimicking childhood leukaemia incidence using actual residential locations of all children in the canton of Zürich, Switzerland, we compare the ability of these models to recover risk surfaces and identify high-risk areas. We then apply both approaches to actual data on childhood leukaemia incidence in the canton of Zürich during 1985-2015. We found that LGCPs outperform BYM models in almost all scenarios considered. Our findings suggest that there are important gains to be made from the use of LGCPs in spatial epidemiology.

Emerging Natural Focal Infectious Diseases in Russia: A Medical-Geographical Study.

In Russia, as in other countries, the problem of emerging natural focal infectious diseases (EIDs) became more acute toward the end of the 20th century. However, the situation in Russia is unknown to foreign readers, while the prevention and control of these diseases require international collaboration. The aim of the study is to provide a medical-geographical assessment of the distribution of the main natural focal EIDs in Russia, as well as to present the approaches used in the country to create aggregate maps of risk assessment. To consider its current status, we determined the most important natural focal EIDs for Russia (tick-borne encephalitis, ixodid tick-borne borrelioses, hemorrhagic fever with renal syndrome, Crimean-Congo hemorrhagic fever, West Nile fever, Astrakhan spotted fever, leptospiroses, and tularemia) and analyzed the patterns of their epidemic manifestation. As a result, a working classification of such infections and a series of maps showing the current situation of EID morbidity in Russia were created. To design an aggregated risk map, we developed an original mapping methodology and recalculated the model disease incidence by taking data from administrative units and adjusting them for natural geographical boundaries (biomes) for European Russia, and then evaluated the risk of infection for separate model diseases and for a set of them. The highest risk rates are confined to the northwest regions of European Russia, the Cis-Urals and the Volga region, which are naturally related to forest biomes, as well as to the southern steppe regions of the interfluves between the Volga and the Don, and the foothills of the North Caucasus.

Recent Incidence of Human Malaria Caused by Plasmodium knowlesi in the Villages in Kudat Peninsula, Sabah, Malaysia: Mapping of The Infection Risk Using Remote Sensing Data.

Plasmodium knowlesi (Pk) is a malaria parasite that naturally infects macaque monkeys in Southeast Asia. Pk malaria, the zoonosis transmitted from the infected monkeys to the humans by Anopheles mosquito vectors, is now a serious health problem in Malaysian Borneo. To create a strategic plan to control Pk malaria, it is important to estimate the occurrence of the disease correctly. The rise of Pk malaria has been explained as being due to ecological changes, especially deforestation. In this research, we analysed the time-series satellite images of MODIS (MODerate-resolution Imaging Spectroradiometer) of the Kudat Peninsula in Sabah and created the "Pk risk map" on which the Land-Use and Land-Cover (LULC) information was visualised. The case number of Pk malaria of a village appeared to have a correlation with the quantity of two specific LULC classes, the mosaic landscape of oil palm groves and the nearby land-use patches of dense forest, surrounding the village. Applying a Poisson multivariate regression with a generalised linear mixture model (GLMM), the occurrence of Pk malaria cases was estimated from the population and the quantified LULC distribution on the map. The obtained estimations explained the real case numbers well, when the contribution of another risk factor, possibly the occupation of the villagers, is considered. This implies that the occurrence of the Pk malaria cases of a village can be predictable from the population of the village and the LULC distribution shown around it on the map. The Pk risk map will help to assess the Pk malaria risk distributions quantitatively and to discover the hidden key factors behind the spread of this zoonosis.

A Nationwide Registry-Based Study on Mortality Due to Rare Congenital Anomalies.

This study aimed to analyse population-based mortality attributed to rare congenital anomalies (CAs) and assess the associated time trends and geographical differences in Spain. Data on CA-related deaths were sourced from annual mortality databases kept by the National Statistics Institute of Spain (1999⁻2013). Based on the ICD-10, only CAs corresponding to rare diseases definition were included in this study. Annual age-adjusted mortality rates were calculated and time trends were evaluated by joinpoint regression analysis. Geographical differences were assessed using standardised mortality ratios and cluster detection. A total of 13,660 rare-CA-related deaths (53.4% males) were identified in the study period. Annual age-adjusted mortality rates decreased by an average of -5.2% (-5.5% males, -4.8% females, p < 0.001). Geographical analysis showed a higher risk of rare-CA-related mortality in regions largely located in the south of the country. Despite their limitations, mortality statistics are essential and useful tools for enhancing knowledge of rare disease epidemiology and, by extension, for designing and targeting public health actions. Monitoring rare-CA-related mortality in Spain has shown a 15-year decline and geographical differences in the risk of death, all of which might well be taken into account by the health authorities in order to ensure equality and equity, and to adopt appropriate preventive measures.

Geographic Analysis of Motor Neuron Disease Mortality and Heavy Metals Released to Rivers in Spain.

The etiology of motor neuron disease (MND) is still unknown. The aims of this study were to: (1) analyze MND mortality at a fine-grained level; and (2) explore associations of MND and heavy metals released into Spanish river basins. MND deaths were extracted from the Spanish nationwide mortality registry (2007⁻2016). Standardized mortality ratios (SMRs) for MND were estimated at a municipal level. Sites that emitted quantities of heavy metals above the regulatory thresholds were obtained from the European Pollutant Release and Transfer Register database (2007⁻2015). The relative risks for non-exposed and exposed municipalities (considering a downstream 20 km river section) by type of heavy metal were analyzed using a log-linear model. SMRs were significantly higher in central and northern municipalities. SMRs were 1.14 (1.10⁻1.17) higher in areas exposed to heavy metals than in non-exposed areas: 0.95 (0.92⁻0.96). Considering the different metals, we found the following increased MND death risks in exposed areas: 20.9% higher risk for lead, 20.0% for zinc, 16.7% for arsenic, 15.7% for chromium, 15.4% for cadmium, 12.7% for copper, and 12.4% for mercury. This study provides associations between MND death risk and heavy metals in exposed municipalities. Further studies investigating heavy metal exposure are needed to progress in MND understanding.

Revealing geographical and population heterogeneity in HIV incidence, undiagnosed HIV prevalence and time to diagnosis to improve prevention and care: estimates for France.

INTRODUCTION: To close gaps in HIV prevention and care, knowledge about locations and populations most affected by HIV is essential. Here, we provide subnational and sub-population estimates of three key HIV epidemiological indicators, which have been unavailable for most settings. METHODS: We used surveillance data on newly diagnosed HIV cases from 2004 to 2014 and back-calculation modelling to estimate in France, at national and subnational levels, by exposure group and country of birth: the numbers of new HIV infections, the times to diagnosis, the numbers of undiagnosed HIV infections. The denominators used for rate calculations at national and subnational levels were based on population size (aged 18 to 64) estimates produced by the French National Institute of Statistics and Economic Studies and the latest national surveys on sexual behaviour and drug use. RESULTS: We estimated that, in 2014, national HIV incidence was 0.17‰ (95% confidence intervals (CI): 0.16 to 0.18) or 6607 (95% CI: 6057 to 7196) adults, undiagnosed HIV prevalence was 0.64‰ (95% CI: 0.57 to 0.70) or 24,197 (95% CI: 22,296 to 25,944) adults and median time to diagnosis over the 2011 to 2014 period was 3.3 years (interquartile range: 1.2 to 5.7). Three mainland regions, including the Paris region, out of the 27 French regions accounted for 56% of the total number of new and undiagnosed infections. Incidence and undiagnosed prevalence rates were 2- to 10-fold higher than the national rates in three overseas regions and in the Paris region (p-values < 0.001). Rates of incidence and undiagnosed prevalence were higher than the national rates for the following populations (p-values < 0.001): born-abroad men who have sex with men (MSM) (respectively, 108- and 78-fold), French-born MSM (62- and 44-fold), born-abroad persons who inject drugs (14- and 18-fold), sub-Saharan African-born heterosexuals (women 15- and 15-fold, men 11- and 13-fold). Importantly, affected populations varied from one region to another, and in regions apparently less impacted by HIV, some populations could be as impacted as those living in most impacted regions. CONCLUSIONS: In France, some regions and populations have been most impacted by HIV. Subnational and sub-population estimates of key indicators are not only essential to adapt, design implement and evaluate tailored HIV interventions in France, but also elsewhere where similar heterogeneity is likely to exist.

Mapping pediatric injuries to target prevention, education, and outreach.

BACKGROUND: Initiatives exist to prevent pediatric injuries, but targeting these interventions to specific populations is challenging. We hypothesized that mapping pediatric injuries by zip code could be used to identify regions requiring more interventions and resources. METHODS: We queried the trauma registries of two level I trauma centers for children 0-17years of age injured between 2009 and 2013 with home zip codes in our state. Maps were created to identify outlier zip codes. Multivariate linear regression analysis identified predictors within these zip codes. RESULTS: There were 5380 children who resided in the state and were admitted for traumatic injuries during the study period, with hospital costs totaling more than 200 million dollars. Choropleth mapping of patient addresses identified outlier zip codes in our metro area with higher incidences of specific mechanisms of injury and greater hospital charges. Multivariate analysis identified demographic features associated with higher rates of pediatric injuries and hospital charges, to further target interventions. CONCLUSIONS: We identified outlier zip codes in our metro area with higher frequencies of pediatric injuries and higher costs for treatment. These data have helped obtain funding for prevention and education efforts. Techniques such as those presented here are becoming more important as evidence based public health initiatives expand. LEVEL OF EVIDENCE: Type of Study: Cost Effectiveness, II.

Caracterização genética e distribuição geográfica do vírus rábico isolado de bovinos no estado de Mato Grosso, Brasil / Genetic characterization and geographic distribution of rabies virus isolates from cattle in Mato Grosso, Brazil

Foram caracterizados, geneticamente e geograficamente, o sequenciamento parcial da nucleoproteína (gene N) de 53 isolados do vírus da raiva (VR) originários do Estado de Mato Grosso, Brasil. Os isolados de bovinos, que se encontravam no grupo do VR relacionado a morcegos hematófagos, foram posteriormente subdivididos em sete subgrupos genéticos. Estes subgrupos foram distribuídos em regiões de terras planas, com alguns subgrupos separados por formações de pequenas montanhas e hidrografia. Estes resultados indicam que a raiva em bovinos é derivada de diversas variantes regionalmente definidas, o que sugere que sua distribuição geográfica está relacionada as populações de morcegos hematófagos.

A total of 53 rabies virus (RV) isolates originating from cattle in the state of Mato Grosso, Brazil, were genetically characterized. Partial nucleoprotein gene sequences of these isolates were phylogenetically and geographically analyzed. Cattle isolates, which clustered with the vampire bat related RV group, were further subdivided into 7 subgroups. These subgroups were distributed widely in lowland regions, with some subgroups separated from each other by small mountains and hydrographical features. These results indicate that cattle rabies is derived from several regionally-defined variants, which suggests that its geographical distribution is related to that of the vampire bat population.