Seroprevalence of human leptospirosis in a rural community from Tandil, Argentina. Assessment of risk factors and spatial analysis.

Leptospirosis is a neglected zoonosis that is widely distributed in the world. Although it is endemic in Argentina, prevalence remains unknown. The aims of the study were: (i) to determine the prevalence of leptospirosis in humans from a rural community in Tandil Argentina, (ii) to identify infecting Leptospira spp. serogroups, (iii) to identify factors associated with the infection, (iv) to estimate the population attributable fraction (PAF) of the risk factors and (v) to determine the spatial patterns of disease presentation and related risk factors. Blood samples from 202 participants were collected. A survey was conducted to obtain clinical and epidemiological data. Serological testing was performed by the microscopic agglutination test (MAT). Univariate and multivariate methods were applied to evaluate associations. Spatial clusters were investigated for seroprevalence and risk factors. Antibodies were found in 32.2% of participants (95% CI: 25.8-39.1). The most prevalent serogroup was Hebdomadis followed by Sejroe; Icterohaemorrhagiae; Tarassovi and Canicola. Living at lower altitudes (OR: 13.04; 95% CI: 2.60-65.32); not having access to water supply network (OR: 2.95; 95% CI: 1.30-6.69); living close to flooded streets (OR: 2.94; 95% CI: 1.14-7.69) and practicing water sports (OR: 3.12; 95% CI: 1.12-8.33) were associated with seropositivity. Factors related with housing characteristics, services and infrastructure had the higher PAF (from 17% to 81%). A spatial cluster with higher rates of positivity and of the main risk factors was determined. This work contributes useful data for specific preventive measures that should be implemented for the control of the disease.

Epidemiology and Geographic Distribution of Generalized Pustular Psoriasis in Spain: A National Population-Based Study of Hospital Admissions from 2016 to 2020. / Epidemiología y distribución espacial de la psoriasis pustulosa generalizada en España: un análisis poblacional a nivel nacional basado en datos de ingresos hospitalarios (2016-2020).

INTRODUCTION: Little has been published on the epidemiology of generalized pustular psoriasis (GPP). The aim of this study was to describe and analyze the geographic distribution of hospital admissions for GPP in Spain. METHODS: We performed a cross-sectional study using the hospital discharge database of the Spanish Basic Minimum Data Set (CMBD), which is a mandatory data set of all admissions to public hospitals in the country. We included patients with a primary diagnosis of psoriasis or GPP at discharge for the period 2016 to 2020. We performed a descriptive analysis of clinical and sociodemographic characteristics of patients admitted with GPP, a spatial analysis at the province level assessing the presence of geographic heterogeneity and a GPP disease map. RESULTS: We detected 949 diagnoses of psoriasis and 744 primary diagnoses of GPP. Mean age of patients admitted with GPP was 62.2 years. Intensive care unit admissions were ordered for 6.1% of patients and 4.8% died. The overall incidence rate of GPP among newly hospitalized patients during the study period was 3.18 cases per 1,000,000 person-years. The geographic distribution varied widely, with higher rates observed in the north-west of the country. CONCLUSIONS: We describe the characteristics of GPP hospitalized patients in Spain and provide the first disease map for the country. The findings could help guide future research and suggest the possibility of genetic or environmental factors driving geographic differences.

Mapping social-ecological vulnerability to inform local decision making.

An overarching challenge of natural resource management and biodiversity conservation is that relationships between people and nature are difficult to integrate into tools that can effectively guide decision making. Social-ecological vulnerability offers a valuable framework for identifying and understanding important social-ecological linkages, and the implications of dependencies and other feedback loops in the system. Unfortunately, its implementation at local scales has hitherto been limited due at least in part to the lack of operational tools for spatial representation of social-ecological vulnerability. We developed a method to map social-ecological vulnerability based on information on human-nature dependencies and ecosystem services at local scales. We applied our method to the small-scale fishery of Moorea, French Polynesia, by combining spatially explicit indicators of exposure, sensitivity, and adaptive capacity of both the resource (i.e., vulnerability of reef fish assemblages to fishing) and resource users (i.e., vulnerability of fishing households to the loss of fishing opportunity). Our results revealed that both social and ecological vulnerabilities varied considerably through space and highlighted areas where sources of vulnerability were high for both social and ecological subsystems (i.e., social-ecological vulnerability hotspots) and thus of high priority for management intervention. Our approach can be used to inform decisions about where biodiversity conservation strategies are likely to be more effective and how social impacts from policy decisions can be minimized. It provides a new perspective on human-nature linkages that can help guide sustainability management at local scales; delivers insights distinct from those provided by emphasis on a single vulnerability component (e.g., exposure); and demonstrates the feasibility and value of operationalizing the social-ecological vulnerability framework for policy, planning, and participatory management decisions.

A spatial approach to combatting wildlife crime.

Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. We used data from an 8-year study in Savé Valley Conservancy, Zimbabwe, to show how geographic profiling-a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology-can be adapted for use in investigations of wildlife crime. The data set contained information on over 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. We used a subset of data for which the illegal hunters' identities were known. Our model identified the illegal hunters' home villages based on the spatial locations of the hunting incidences (e.g., snares). Identification of the villages was improved by manipulating the probability surface inside the conservancy to reflect the fact that although the illegal hunters mostly live outside the conservancy, the majority of hunting occurs inside the conservancy (in criminology terms, commuter crime). These results combined with rigorous simulations showed for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns, for example, where landscape heterogeneity means some parts of the study area are less likely to be used (e.g., aquatic areas for terrestrial animals) or where landscape permeability differs (e.g., forest bats tend not to fly over open areas). More broadly, these results show how geographic profiling can be used to target antipoaching interventions more effectively and more efficiently and to develop management strategies and conservation plans in a range of conservation scenarios.

Quantifying the extent of protected-area downgrading, downsizing, and degazettement in Australia.

The use of total area protected as the predominant indicator of progress in building protected area (PA) networks is receiving growing criticism. Documenting the full dynamics of PA networks, both in terms of the gains and losses in protection, provides a much more informative approach to tracking progress. To this end, documentation of PA downgrading, downsizing, and degazettement (PADDD) has increased. Studies of PADDD events generally fail to place these losses in the context of gains in protection; therefore, they omit important elements of PA network dynamics. To address this limitation, we used a spatially explicit approach to identify every parcel of land added to and excised from the Australian terrestrial PA network and PAs that had their level of protection changed over 17 years (1997-2014). By quantifying changes in the spatial configuration of the PA network with time-series data (spatial layers for nine separate time steps), ours is the first assessment of the dynamics (increases and decreases in area and level of protection) of a PA network and the first comprehensive assessment of PADDD in a developed country. We found that the Australian network was highly dynamic; there were 5233 changes in area or level of protection over 17 years. Against a background of enormous increases in area protected, we identified over 1500 PADDD events, which affected over one-third of the network, which were largely the result of widespread downgrading of protection. We believe our approach provides a mechanism for robust tracking of trends in the world's PAs through the use of data from the World Database on Protected Areas. However, this will require greater transparency and improved data standards in reporting changes to PAs.

Restoration planning to guide Aichi targets in a megadiverse country.

Ecological restoration has become an important strategy to conserve biodiversity and ecosystems services. To restore 15% of degraded ecosystems as stipulated by the Convention on Biological Diversity Aichi target 15, we developed a prioritization framework to identify potential priority sites for restoration in Mexico, a megadiverse country. We used the most current biological and environmental data on Mexico to assess areas of biological importance and restoration feasibility at national scale and engaged stakeholders and experts throughout the process. We integrated 8 criteria into 2 components (i.e., biological importance and restoration feasibility) in a spatial multicriteria analysis and generated 11 scenarios to test the effect of assigning different component weights. The priority restoration sites were distributed across all terrestrial ecosystems of Mexico; 64.1% were in degraded natural vegetation and 6% were in protected areas. Our results provide a spatial guide to where restoration could enhance the persistence of species of conservation concern and vulnerable ecosystems while maximizing the likelihood of restoration success. Such spatial prioritization is a first step in informing policy makers and restoration planners where to focus local and large-scale restoration efforts, which should additionally incorporate social and monetary cost-benefit considerations.

Disease mapping for informing targeted health interventions: childhood pneumonia in Bohol, Philippines.

BACKGROUND: Acute lower respiratory tract infections (ALRI) are the leading cause of childhood mortality worldwide. Currently, most developing countries assign resources at a district level, and yet District Medical Officers have few tools for directing targeted interventions to high mortality or morbidity areas. Mapping of ALRI at the local level can guide more efficient allocation of resources, coordination of efforts and targeted interventions, which are particularly relevant for health management in resource-scarce settings. METHODS: An efficacy study of 11-valent pneumococcal vaccine was conducted in six municipalities in the Bohol Province of central Philippines from July 2000 to December 2004. Geocoded under-five pneumonia cases (using WHO classifications) were mapped to create spatial patterns of pneumonia at the local health unit (barangay) level. RESULTS: There were 2951 children with WHO-defined clinical pneumonia, of whom 1074 were severe or very severely ill, 278 were radiographic, and 219 were hypoxaemic. While most children with pneumonia were from urban barangays, there was a disproportionately higher distribution of severe/very severe pneumonia in rural barangays and the most severe hypoxaemic children were concentrated in the northern barangays most distant from the regional hospital. CONCLUSIONS: Mapping of ALRI at the local administrative health level can be performed relatively simply. If these principles are applied to routinely collected IMCI classification of disease at the district level in developing countries, such efforts can form the basis for directing public health and healthcare delivery efforts in a targeted manner.

Spatial analysis of under-5 mortality and potential risk factors in the Basse Health and Demographic Surveillance System, the Gambia.

OBJECTIVES: To describe the spatial pattern in under-5 mortality rates in the Basse Health and Demographic Surveillance System (BHDSS) and to test for associations between under-5 deaths and biodemographic and socio-economic risk factors. METHODS: Using data on child survival from 2007 to 2011 in the BHDSS, we mapped under-5 mortality by km(2) . We tested for spatial clustering of high or low death rates using Kulldorff's spatial scan statistic. Associations between child death and a variety of biodemographic and socio-economic factors were assessed with Cox proportional hazards models, and deviance residuals from the best-fitting model were tested for spatial clustering. RESULTS: The overall death rate among children under 5 was 0.0195 deaths per child-year. We found two spatial clusters of high death rates and one spatial cluster of low death rates; children in the two high clusters died at a rate of 0.0264 and 0.0292 deaths per child-year, while in the low cluster, the rate was 0.0144 deaths per child-year. We also found that children born to Fula mothers experienced, on average, a higher hazard of death, whereas children born in the households in the upper two quintiles of asset ownership experienced, on average, a lower hazard of death. After accounting for the spatial distribution of biodemographic and socio-economic characteristics, we found no residual spatial pattern in child mortality risk. CONCLUSION: This study demonstrates that significant inequality in under-5 death rates can occur within a relatively small area (1100 km(2) ). Risks of under-5 mortality were associated with mother's ethnicity and household wealth. If high mortality clusters persist, then equity concerns may require additional public health efforts in those areas.

Benefits to poorly studied taxa of conservation of bird and mammal diversity on islands.

Protected area delineation and conservation action are urgently needed on marine islands, but the potential biodiversity benefits of these activities can be difficult to assess due to lack of species diversity information for lesser known taxa. We used linear mixed effects modeling and simple spatial analyses to investigate whether conservation activities based on the diversity of well-known insular taxa (birds and mammals) are likely to also capture the diversity of lesser known taxa (reptiles, amphibians, vascular land plants, ants, land snails, butterflies, and tenebrionid beetles). We assembled total, threatened, and endemic diversity data for both well-known and lesser known taxa and combined these with physical island biogeography characteristics for 1190 islands from 109 archipelagos. Among physical island biogeography factors, island area was the best indicator of diversity of both well-known and little-known taxa. Among taxonomic factors, total mammal species richness was the best indicator of total diversity of lesser known taxa, and the combination of threatened mammal and threatened bird diversity was the best indicator of lesser known endemic richness. The results of other intertaxon diversity comparisons were highly variable, however. Based on our results, we suggest that protecting islands above a certain minimum threshold area may be the most efficient use of conservation resources. For example, using our island database, if the threshold were set at 10 km(2) and the smallest 10% of islands greater than this threshold were protected, 119 islands would be protected. The islands would range in size from 10 to 29 km(2) and would include 268 lesser known species endemic to a single island, along with 11 bird and mammal species endemic to a single island. Our results suggest that for islands of equivalent size, prioritization based on total or threatened bird and mammal diversity may also capture opportunities to protect lesser known species endemic to islands.

Spatiotemporal trends of illegal activities from ranger-collected data in a Ugandan national park.

Within protected areas, biodiversity loss is often a consequence of illegal resource use. Understanding the patterns and extent of illegal activities is therefore essential for effective law enforcement and prevention of biodiversity declines. We used extensive data, commonly collected by ranger patrols in many protected areas, and Bayesian hierarchical models to identify drivers, trends, and distribution of multiple illegal activities within the Queen Elizabeth Conservation Area (QECA), Uganda. Encroachment (e.g., by pastoralists with cattle) and poaching of noncommercial animals (e.g., snaring bushmeat) were the most prevalent illegal activities within the QECA. Illegal activities occurred in different areas of the QECA. Poaching of noncommercial animals was most widely distributed within the national park. Overall, ecological covariates, although significant, were not useful predictors for occurrence of illegal activities. Instead, the location of illegal activities in previous years was more important. There were significant increases in encroachment and noncommercial plant harvesting (nontimber products) during the study period (1999-2012). We also found significant spatiotemporal variation in the occurrence of all activities. Our results show the need to explicitly model ranger patrol effort to reduce biases from existing uncorrected or capture per unit effort analyses. Prioritization of ranger patrol strategies is needed to target illegal activities; these strategies are determined by protected area managers, and therefore changes at a site-level can be implemented quickly. These strategies should also be informed by the location of past occurrences of illegal activity: the most useful predictor of future events. However, because spatial and temporal changes in illegal activities occurred, regular patrols throughout the protected area, even in areas of low occurrence, are also required.

Leprosy in Brazil and its association with characteristics of municipalities: ecological study, 2009-2011.

OBJECTIVE: To analyse the ecological association between the demographic and socio-economic characteristics of the Brazilian municipalities and average leprosy incidence rate in the period 2009-2011. METHODS: An ecological study taking the Brazilian municipalities as its units of analysis. The local empirical Bayes estimation method was used to obtain smoothed incidence rates (SIR) for leprosy. The mean, median, first quartile (Q1) and third quartile (Q3) of the SIR were calculated per 100 000 inhabitants. Hierarchical log-linear negative binomial regression models were used to estimate the incidence rate ratios (IRR). RESULTS: In the period 2009-2011, the average SIR of leprosy in Brazil was 20.2 per 100 000 inhabitants, and the median incidence rate among municipalities was 9.1 per 100 000 inhabitants. Significantly higher adjusted IRR were identified for large municipalities (IRR = 1.67) compared to small municipalities, as well as in municipalities with higher illiteracy rates (IRR = 2.15), more urbanised municipalities (IRR = 1.53), those with greater social inequality as per the Gini index (IRR = 1.26), high percentage of households with inadequate sanitation (IRR = 1.63), higher average number of people per room (IRR = 1.41), high proportions of Family Health Programme coverage (IRR = 1.29), high percentage of household contacts investigated (IRR = 2.30) and those with percentage of cases with grade 2 disability considered to be the medium (IRR = 1.26). CONCLUSIONS: In this study, SIR was significantly associated with municipalities with low socio-economic status. Disease control activities need to be focused on these municipalities, and investments need to be made in improving the population's living conditions.

Socio-economic and environmental effects influencing the development of leprosy in Bahia, north-eastern Brazil.

OBJECTIVES: To investigate spatial clusters and possible associations between relative risks of leprosy with socio-economic and environmental factors, taking into account diagnosed cases in children under 15 years old. METHODS: An ecological study was conceived using data aggregated by municipality to identify possible spatial clusters of leprosy from 2005 to 2011. Relative risks were calculated accounting for the respective covariate gender. The second stage of the analysis consisted of verifying possible associations between the relative risks of leprosy as a dependent variable, and socio-economic and environmental variables as independent. This was performed using a multivariate regression analysis according to a previously defined conceptual framework. RESULTS: Overall rates have decreased from 0.88/10 000 in 2005 to 0.52 in 2011. Spatial scan statistics identified 4 high-risk and 6 low-risk clusters. In the regression model, after allowing for spatial dependence, relative risks were associated with higher percentage of water bodies, higher Gini index, higher percentage of urban population, larger average number of dwellers by permanent residence and smaller percentage of residents born in Bahia. CONCLUSIONS: Although relative risks of leprosy in Bahia have been decreasing, they remain very high. The association between relative risks of leprosy and water bodies in the proposed geographic scale indicates that hypothesis linking M. leprae and humid environments cannot be discarded. Socio-economic conditions such as inequality, a greater number of dwellers by residence and migration are derived from the urbanisation process carried out in this State. Precarious settlements and poor living conditions in the cities would favour the continuity of leprosy transmission.

National spatial and temporal patterns of notified dengue cases, Colombia 2007-2010.

OBJECTIVES: To explore the variation in the spatial distribution of notified dengue cases in Colombia from January 2007 to December 2010 and examine associations between the disease and selected environmental risk factors. METHODS: Data on the number of notified dengue cases in Colombia were obtained from the National Institute of Health (Instituto Nacional de Salud - INS) for the period 1 January 2007 through 31 December 2010. Data on environmental factors were collected from the Worldclim website. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between monthly dengue cases and temperature, precipitation and elevation. RESULTS: Monthly dengue counts decreased by 18% (95% credible interval (CrI): 17-19%) in 2008 and increased by 30% (95% CrI: 28-31%) and 326% (95% CrI: 322-331%) in 2009 and 2010, respectively, compared to 2007. Additionally, there was a significant, nonlinear effect of monthly average precipitation. CONCLUSIONS: The results highlight the role of environmental risk factors in determining the spatial of dengue and show how these factors can be used to develop and refine preventive approaches for dengue in Colombia.

[Effect of the population in collective dwellings on small-area mortality risk estimation in the Basque Country region (Spain)]. / Efecto producido por la población institucionalizada en la estimación del riesgo de mortalidad en áreas pequeñas de Euskadi (España).

OBJECTIVE: To quantify the effect of the inclusion of the population in collective dwellings on the estimation of mortality risk in the census areas of the Basque Country (Spain) for the main causes of mortality in the period 1996-2003. METHOD: Small-area ecological cross-sectional study. The main causes of mortality by sex were analyzed. RESULTS: When the general effect on all areas with a a population in collective dwellings was analyzed, hardly any noticeable effect was seen on either men or women. On the other hand, an effect was found when selecting the areas where the population in collective dwellings is more than 10% of the area's population. CONCLUSIONS: The effect of the inclusion of the population in collective dwellings clearly seen in causes of mortality, such as dementia and Alzheimer's disease, and in chronic obstructive pulmonary disease, related to greater dependence or frailty, and therefore related to being in a nursing or elderly persons' home, over-estimating the risk of mortality by approximately 8% and 4%, respectively, in these geographical areas.

Factores socioambientales relacionados con la leishmaniasis a nivel cantonal, Costa Rica, 2018-2021 / Socio-environmental factors related to leishmaniasis at the cantonal level, Costa Rica, 2018-2021

Resumen Objetivo: Analizar factores socioambientales relacionados con la incidencia acumulada de leishmaniasis a nivel cantonal en Costa Rica del año 2018 al 2021. Materiales y métodos: Estudio de tipo observacional, ecológico, a nivel cantonal, descriptivo-analítico. Se realiza un análisis espacial por medio de mapas coropléticos, Índice de Moran e Índice Local de Asociación Espacial. Se llevan a cabo modelos de regresión binomial negativa bivariado y multivariado. Resultados: Se desarrollan dos modelos multivariados: Modelo multivariado A, las variables dimensión educativa y acceso a información se comportan como factores protectores. Modelo B, el porcentaje de hogares con carencia de albergue digno, razón de masculinidad, porcentaje de población afrodescendiente y porcentaje de hogares pobres, actúan como factores de riesgo. Conclusiones: Se observa que los cantones con mayor incidencia acumulada de leishmaniasis fueron los localizados principalmente en el caribe y zona sur. Se identifican factores socioambientales relacionados con la incidencia acumulada estandarizada cantonal de leishmaniasis en Costa Rica del año 2018 al 2021. Es posible determinar clústeres de autocorrelación espacial alta entre las variables identificadas en esta pesquisa como factores protectores, dimensión educativa, acceso a la información y de riesgo, porcentaje de hogares con carencia de albergue digno, razón de masculinidad, porcentaje de población afrodescendiente, y porcentaje de hogares pobres principalmente en cantones ubicados en la zona del caribe y zona sur del país, así como clústeres de autocorrelación espacial baja en cantones del centro del país.

Abstract Objective: Analyze socio-environmental factors related to the cumulative incidence of leishmaniasis at the cantonal level in Costa Rica from 2018 to 2021. Materials and methods: Observational, ecological, cantonal, descriptive-analytical study. A spatial analysis is carried out through choropleth maps, Moran Index and Local Spatial Association Index. Bivariate and multivariate negative binomial regression models are carried out. Results: Two multivariate models are developed: Multivariate model A: the variables educational dimension and access to information behave as protective factors. Model B: the percentage of households lacking decent shelter, sex ratio, percentage of Afro-descendant population and percentage of poor households act as risk factors. Conclusions: It is observed that the cantons with the highest cumulative incidence of leishmaniasis were those located mainly in the Caribbean and southern areas. Socioenvironmental factors related to the cantonal standardized cumulative incidence of leishmaniasis in Costa Rica from 2018 to 2021 are identified. It is possible to determine the presence of clusters of high spatial autocorrelation between the variables identified in this research as protective factors educational dimension, access to information and risk factors percentage of households lacking decent shelter, sex ratio, percentage of population Afrodescendant, and percentage of poor households mainly in cantons located in the Caribbean area and southern part of the country, as well as clusters of low spatial autocorrelation in cantons in the center of the country.

Mortalidad por COVID-19: desigualdades educativas y contexto socio-espacial en dos provincias de Argentina / Mortality from COVID-19: educational inequalities and socio-spatial context in two provinces of Argentina

Con el objetivo de describir la asociación entre las características sociodemográficas y factores contex-tuales con la mortalidad por COVID-19, durante 2020-2021 en las provincias de Mendoza y San Juan en Argentina se realizó un estudio de tipo ecológico, donde los factores sociodemográficos fueron la edad, el sexo y el nivel educativo y contextuales la pobreza y la urbanización a nivel departamental. Los análisis se estimaron mediante modelos jerárquicos bayesianos binomial negativos.Existieron desigualdades edu-cacionales independientemente del contexto socioeconómico y el nivel de urbanización. La excepción fue el grupo etario de 65 a más años durante 2021 que, independientemente del nivel educativo, mostró un riesgo de muerte por COVID-19 mayor en departamentos con niveles altos de pobreza estructural. En conclusión, la desigualdad educativa es un indicador de desigualdad social que aumenta la vulnera-bilidad para la mortalidad por COVID-19.

Recognize the epidemiological and geospatial profile of the Mobile Emergency Care Service: a strategy to optimize response time

Epidemiological, cross-sectional, descriptive, retrospective study of a quantitative nature, to trace the epidemiological and geospatial profile of the occurrences assisted by the Mobile Emergency Care Service. For that purpose, secondary data from the documents of the Mobile Emergency Care Service of a city in the interior of Rio Grande do Norte were used, considering the frequency of the variables: sex, age group, nature of occurrences, days of the week, ambulance sent, removal inter-hospital care and patient destination. Of the 363 occurrences, most were due to clinical causes, followed by traumatic, psychiatric, and gynecological/obstetric causes, with an emphasis on cardiovascular diseases and transport accidents. aged 19 to 59 years and over 60 years, with the Basic Support Unit providing the majority of care. Among the calls for clinical causes, women stood out, while for traumatic and psychiatric causes, men. The information contributes to the organization and planning of the service and the understanding of the morbidity profile. The geographic distribution highlights the need for integration between health agencies, for the institution of preventive actions, and the redirection of human and financial resources(AU)

Estudio epidemiológico, transversal, descriptivo, retrospectivo, de carácter cuantitativo que tiene como objetivo trazar el perfil epidemiológico y geoespacial de los incidentes atendidos por el Servicio Móvil de Atención de Urgencias. Para ello se utilizan datos secundarios de dos documentos del Servicio Móvil de Atención de Emergencias de un municipio del interior de Rio Grande do Norte; considera la frecuencia de las variables: sexo, edad, naturaleza de los eventos, días de la semana, ambulancia enviada, retiro interhospitalario y destino del paciente. De los 363 sucesos, la mayoría se debió a causas clínicas, seguidas de causas traumáticas, psiquiátricas y ginecológicas/obstétricas, incluidas las enfermedades cardiovasculares y los accidentes de transporte. La frecuencia de ocurrencia fue ligeramente mayor en individuos masculinos con predominio de mujeres y edades entre los 19 y 59 años y mayores de 60 años; la Unidad Básica de Apoyo fue la responsable de la mayoría de los servicios. Entre los lesionados por causas clínicas destacan las mujeres, mientras que los hombres tienen causas traumáticas y psiquiátricas. Esta información contribuye a la organización y planificación de los servicios y a la comprensión del perfil de morbilidad. La distribución geográfica resalta la necesidad de integración entre las organizaciones de salud para implementar acciones preventivas y redireccionar recursos humanos y financieros(AU)

Dinâmica espaço-temporal e fatores associados à mortalidade neonatal / Space-temporal dynamics and factors associated with newborn mortality / Dinámica Espacio-temporal y factores asociados a la mortalidad del recién nacido

Objetivo:analisar a distribuição espacial e temporal da mortalidade neonatal e fatores associados no Piauí de 2007 a 2017. Método: foi utilizado o método Joinpoint, estatística bayesiana e a técnica de varredura Scan. A análise multivariada dos indicadores foi realizada através do modelo Ordinary Least Squares Estimation, considerando-se p<0,05. Resultados: a mortalidade neonatal reduziu de forma linear e significativa ao longo do período estudado. As maiores taxas bayesianas variaram de 16,34 a 18,38 óbitos por 1.000 nascidos vivos, especialmente no Sudeste piauiense. Houve associação negativa entre a mortalidade neonatal e as variáveis: Taxa de analfabetismo (ß = -0,60; p= 0,027), Cobertura da Estratégia Saúde da Família (ß = -2,80; p= 0,023) e Índice de Desenvolvimento Humano Municipal (ß = -0,60; p= 0,003). Conclusão: a mortalidade neonatal segue decrescente e sua distribuição no território mostrou-se irregular. Indicadores socioeconômicos e de saúde influenciam a mortalidade neonatal no Piauí

Objective: to analyze the spatial and temporal distribution of neonatal mortality and associated factors in Piauí from 2007 to 2017. Method: the Joinpoint method, Bayesian statistics and the Scan technique were used. The multivariate analysis of the indicators was performed using the Ordinary Least Squares Estimation model, considering p<0.05. Results: neonatal mortality decreased linearly and significantly over the period studied. The highest Bayesian rates ranged from 16.34 to 18.38 deaths per 1,000 live births, especially in Southeast Piauí. There was a negative association between neonatal mortality and the variables: Illiteracy rate (ß = -0.60; p= 0.027), Family Health Strategy Coverage (ß = -2.80; p= 0.023) and Human Development Index Municipal (ß = -0.60; p= 0.003). Conclusion: neonatal mortality continues to decrease and its distribution in the territory proved to be irregular. Socioeconomic and health indicators influence neonatal mortality in Piauí

Objetivos: analizar la distribución espacial y temporal de la mortalidad neonatal y factores asociados en Piauí de 2007 a 2017. Método: se utilizó el método Joinpoint, la estadística bayesiana y la técnica Scan. El análisis multivariado de los indicadores se realizó mediante el modelo de Estimación por Mínimos Cuadrados Ordinarios, considerando p<0,05. Resultados: la mortalidad neonatal disminuyó lineal y significativamente durante el período estudiado. Las tasas bayesianas más altas oscilaron entre 16,34 y 18,38 muertes por 1.000 nacidos vivos, especialmente en el Sudeste de Piauí. Hubo asociación negativa entre la mortalidad neonatal y las variables: Tasa de Analfabetismo (ß = -0,60; p= 0,027), Cobertura de la Estrategia de Salud de la Familia (ß = -2,80; p= 0,023) e Índice de Desarrollo Humano Municipal (ß = -0,60; p= 0,003). Conclusión: la mortalidad neonatal continúa en descenso y su distribución en el territorio resultó ser irregular. Indicadores socioeconómicos y de salud influyen en la mortalidad neonatal en Piauí

Space-time analysis of work-related musculoskeletal disorders in Brazil: an ecological study / Análise espaço-temporal dos distúrbios osteomusculares relacionados ao trabalho no Brasil: um estudo ecológico / Análisis espacio-temporal de los trastornos musculoesqueléticos relacionados con el trabajo en Brasil: un estudio ecológico

Abstract: This study aimed to analyze the incidence of work-related musculoskeletal disorders (WMSD) in Brazil from 2007 to 2019, examining the spatial, temporal, and spatiotemporal patterns of their occurrence. An ecological time series study was conducted using spatial analysis techniques. WMSD morbidity data from 2007 to 2019 were collected from the Brazilian Information System for Notificable Diseases of the Brazilian Health Informatics Department. Incidence rates were standardized and smoothed using the local empirical Bayes' theorem. Time trends were analyzed by segmented linear regression. Spatial analysis was performed using Moran's univariate global (I) and local (LISA) indexes. The spatiotemporal scan statistic was used to identify high-risk spatiotemporal clusters for WMSD. A total of 93,387 cases of WMSD were recorded in Brazil. Temporal trends showed an increase in all regions except the Northeast, which remained stable. The incidence of WMSD showed a spatial dependence, with spatial and space-time clusters identified, especially in the Southeast region, overlapping the largest economic-industrial center of the country. The spatiotemporal clustering observed in one region suggests the highest level of industrial and economic development. Our findings highlight the need to implement intersectoral surveillance policies, inspect working conditions, and invest in the prevention and promotion of workers' health.

Resumo: O objetivo foi analisar a incidência de distúrbios osteomusculares relacionados ao trabalho (DORT) no Brasil de 2007 a 2019, examinando os padrões espaciais, temporais e espaço-temporais de sua ocorrência. Foi realizado um estudo ecológico de séries temporais utilizando técnicas de análise espacial. Os dados de morbidade por DORT de 2007 a 2019 foram coletados do Sistema de Informação de Agravos de Notificação do Departamento de Informática do SUS. As taxas de incidência foram padronizadas e suavizadas pelo método de Bayes empírico local. As tendências temporais foram examinadas por meio de regressão linear segmentada. A análise espacial foi realizada utilizando-se os índices univariados de Moran global (I) e índice de Moran local (LISA). A estatística de varredura espaço-temporal foi aplicada para identificar aglomerados espaço-temporais de DORT de alto risco. Foram registrados 93.387 casos de DORT no Brasil. A tendência temporal mostrou aumento em todas as regiões, exceto no Nordeste, que se manteve estável. A incidência de DORT apresentou dependência espacial e foram identificados aglomerados espaciais e espaço-temporais, particularmente na Região Sudeste, sobrepondo-se ao maior centro econômico-industrial do país. A aglomeração espaço-temporal observada em uma região sugere maior nível de desenvolvimento industrial e econômico. Os achados evidenciam a necessidade de implementação de políticas intersetoriais de vigilância, fiscalização das condições de trabalho e investimentos na prevenção e promoção da saúde do trabalhador.

Resumen: El objetivo fue analizar la incidencia de los trastornos musculoesqueléticos relacionados con el trabajo (TMERT) en Brasil del 2007 al 2019, examinando los patrones espaciales, temporales y espacio-temporales de su incidencia. Se realizó un estudio ecológico de series temporales usando técnicas de análisis espacial. Los datos de morbilidad por TMERT del 2007 al 2019 se recolectaron del Sistema de Información de Enfermedades de Notificación Obligatoria del Departamento de Informática del Sistema Único de Salud. Las tasas de incidencia se estandarizaron y se suavizaron usando el método de Bayes empírico local. Las tendencias temporales se examinaron mediante regresión lineal segmentada. El análisis espacial se realizó utilizando los índices univariados de Moran global (I) y el índice de Moran local (LISA). Se aplicó la estadística de análisis espacio-temporal para identificar aglomerados espacio-temporales de TMERT de alto riesgo. En Brasil se registraron 93.387 casos de TMERT. La tendencia temporal mostró aumento en todas las regiones, salvo en el Nordeste, que se mantuvo estable. La incidencia de TMERT presentó dependencia espacial y se identificaron aglomerados espaciales y espacio-temporales, particularmente en la región Sudeste, superponiéndose al centro económico-industrial más grande del país. La aglomeración espacio-temporal observada en una región sugiere un mayor nivel de desarrollo industrial y económico. Los hallazgos resaltan la necesidad de implementar políticas intersectoriales de vigilancia, inspección de las condiciones de trabajo e inversiones en la prevención y promoción de la salud del trabajador.

Análise dos feminicídios no estado de Pernambuco: violência de gênero e invisibilidade / Analysis of femicides in the state of Pernambuco: gender-based violence and invisibility / Análisis de los feminicidios en el estado de Pernambuco: violencia de género e invisibilidad

O feminicídio é um fenômeno decorrente da herança patriarcal machista e de estruturas sociais historicamente permeadas por relações desiguais de gênero. O objetivo desta dissertação, que é um estudo ecológico, foi analisar os aspectos epidemiológicos dos feminicídios registrados em Pernambuco, entre 2016 e 2019. Como proxy dos eventos de feminicídio, foi admitido como referência o registro de homicídios e de mortes por causas indeterminadas de mulheres no Sistema de Informações sobre Mortalidade. Foram estabelecidas etapas de buscas com o linkage probabilístico em bases de dados da saúde e, de forma complementar, de revisões manuais em plataforma do Tribunal de Justiça de Pernambuco (TJPE) e mídias noticiosas online. Realizou-se a descrição dos dados mediante a distribuição de frequências, medidas de tendência central e dispersão. Para analisar o padrão espacial das taxas de feminicídio, foram utilizados o método bayesiano empírico local e o índice de autocorrelação de Moran. Aplicou-se a regressão logística hierarquizada para verificar a associação entre o feminicídio e a violência interpessoal e estimar a razão de chances (Odds Ratio) com intervalos de confiança de 95% (IC95%). Assim, foram localizados 490 feminicídios, o que correspondeu a uma taxa de 2,5 por 100.000 mulheres. A maior proporção de feminicídios foi identificada pela busca manual em mídias noticiosas online e na base processual do TJPE (n = 247; 50,41%). As características principais das vítimas são: idade entre 20 e 39 anos (n = 286; 58,37%); raça/cor negra (n = 400; 81,63%); sem companheiro(a) (n = 407; 83,06%); e escolaridade superior a oito anos de estudo (n = 303; 61,84%). A autocorrelação espacial do evento foi confirmada pelo índice global de Moran das taxas suavizadas (I = 0,3; p = 0,001); a autocorrelação local reforça a interiorização do evento ao apontar área crítica (Q1) formada por municípios localizados na macrorregião do Vale do São Francisco e Araripe. No nível de determinação distal, identificou-se que as seguintes variáveis elevam as chances de ocorrência do feminicídio: residir em município de pequeno porte (OR = 2,10); indisponibilidade de delegacias especializadas no atendimento à mulher (OR = 1,11); e ausência de encaminhamentos para rede assistencial e protetiva na oportunidade de agressão anterior (OR = 1,32). Nos determinantes intermediários, destacou-se que, quanto maior é a intensidade do meio de ação empregado na prática da violência, maior é a chance do desfecho fatal, ressaltando-se o uso de objeto perfurocortante (OR = 3,93) e arma de fogo (OR = 11,14). E, acerca dos determinantes proximais, as vítimas inseridas na faixa etária entre 10 e 19 anos apresentaram menor chance quanto à ocorrência de feminicídio (OR = 0,51). A caracterização da população de estudo pode proporcionar a ampliação dos conhecimentos sobre violência estrutural contra as mulheres, aspectos da notificação e da rede assistencial e protetiva. A análise espacial identificou a interiorização do evento e áreas de transição em Pernambuco, as quais requerem priorização de intervenções. E a modelagem evidenciou que as mulheres estão expostas a múltiplos fatores de risco para a ocorrência de feminicídio, de forma que a discussão, de modo particularizado a todos os níveis de determinação, faz-se ainda mais necessária.

Feminicide results from the sexist patriarchal heritage and social structures historically permeated by unequal gender relations. This ecological study analyzes the epidemiological aspects of feminicides recorded in Pernambuco between 2016 and 2019. Records of homicides and undetermined causes of death of women available in the Mortality Information System were the proxy for feminicide events and accepted as reference. Search steps were established with probabilistic linkage in health databases, as well as manual reviews on the Pernambuco Court of Justice (TJPE) platform and online news media as a complement. Data were described by the distribution of frequencies, measures of central tendency and dispersion. Local empirical Bayesian method and Moran's autocorrelation index were used in the spatial pattern analysis of femicide rates. Hierarchical logistic regression was applied to verify the association between femicide and interpersonal violence and to estimate the Odds Ratio with 95% confidence intervals (95%CI). Search returned a total of 490 feminicides, corresponding to a rate of 2.5 per 100,000 women. The highest proportion of feminicides was identified by manual search in online news media and in the TJPE database (n = 247; 50.41%). Most victims were aged between 20 and 39 years (n = 286; 58.37%), black (n = 400; 81.63%), had no partner (n = 407; 83.06%) and with over eight years of schooling (n = 303; 61.84%). Spatial autocorrelation of the event was confirmed by the Global Moran Index of smoothed rates (I = 0.3; p = 0.001). Local autocorrelation reinforces the interiorization of the phenomenon by pointing to a critical area (Q1) formed by municipalities located in the Vale do São Francisco and Araripe macroregion. At the distal level, the following variables increase the chances of feminicide: living in a small city (OR = 2.10); unavailability of specialized police stations (OR = 1.11); and absence of referrals to the care and protection network in the event of a previous aggression (OR = 1.32). Regarding intermediate determinants, the greater the violence inflicted the greater the chance of a fatal outcome, emphasizing the use of sharp objects (OR = 3.93) and firearms (OR = 11.14). Regarding proximal determinants, victims in the age group 10-19 years old were less likely to be a victim of femicide (OR = 0.51). Characterizing the study population can further knowledge about structural violence against women, and aspects of the notification and the care and protection network. Spatial analysis pointed to the interiorization of the phenomenon and transition areas in Pernambuco, requiring prioritization of interventions. The modeling showed that women are exposed to multiple risk factors for feminicide and further discussions at all levels of determination are necessary.

El feminicidio es un fenómeno derivado de la herencia patriarcal machista y de estructuras sociales históricamente permeadas por relaciones desiguales de género. Este estudio de tipo ecológico tuvo por objetivo analizar los aspectos epidemiológicos de los feminicidios registrados en Pernambuco, en el período entre 2016 y 2019. Como proxy de los eventos de feminicidio, se utilizó como referencia el registro de homicidios y de causas indeterminadas de muertes de mujeres en el Sistema de Informaciones sobre Mortalidad. Se establecieron etapas de búsquedas con vinculación probabilística en las bases de datos de salud y, de forma complementaria, búsquedas manuales en la plataforma del Tribunal de Justicia de Pernambuco (TJPE) y medios en línea. Para describir los datos se utilizaron la distribución de frecuencias, medidas de tendencia central y dispersión. Para analizar el padrón espacial de las tasas de feminicidio se emplearon el método bayesiano empírico local y el índice de autocorrelación de Moran. Se aplicó la regresión logística jerarquizada para constatar la asociación entre el feminicidio y la violencia interpersonal, y estimar la razón de posibilidades (Odds Ratio) con intervalos de confianza del 95% (IC95%). Los resultados apuntaron a 490 feminicidios, lo que correspondió a una tasa de 2,5 por 100.000 mujeres. La mayor proporción de feminicidios se identificó mediante la búsqueda manual en prensa en línea y en la base procesal del TJPE (n = 247; 50,41%). Las principales características de las víctimas fueron edad entre 20 y 39 años (n = 286; 58,37%), raza/color negro (n = 400; 81,63%), sin compañero(a) (n = 407; 83,06%) y nivel de estudios superior a ocho años de estudio (n = 303; 61,84%). La autocorrelación espacial del evento se confirmó mediante el índice de Moran global de las tasas suavizadas (I = 0,3, p = 0,001); la autocorrelación local refuerza la interiorización del evento al señalar área crítica (Q1) formada por municipios situados en la macrorregión del Valle de São Francisco y Araripe. En el nivel de determinación distal se identificó que las siguientes variables aumentan las posibilidades de feminicidio: residir en municipio de pequeño tamaño, (OR = 2,10); indisponibilidad de comisarías especializadas en la atención a la mujer (OR = 1,1); y ausencia de remisiones a la red asistencial y protectora en la ocasión de agresión anterior (OR = 1,32). En los determinantes intermediarios, se destacó que cuanto mayor es la intensidad del medio de acción empleado en la práctica de la violencia, mayor es la posibilidad de desenlace fatal, destacándose el empleo de objeto cortopunzante (OR = 3,93) y arma de fuego (OR = 11,14). En cuanto a los determinantes proximales, las víctimas comprendidas en el tramo de edad comprendido entre los 10 y los 19 años presentaron menos posibilidad de incidencia de feminicidio (OR = 0,51). La caracterización de la población de estudio puede proporcionar la ampliación de los conocimientos sobre violencia estructural contra la mujer, aspectos de la notificación y de la red asistencial protectora. El análisis espacial identificó la interiorización del evento y áreas de transición en Pernambuco, las cuales requieren priorización de las intervenciones. Y el modelaje reveló que las mujeres están expuestas a múltiples factores de riesgo para la incidencia de feminicidio y el debate, de modo particularizado de todos los niveles de determinación, se hace todavía más necesario.