ABSTRACT
OBJECTIVE: To present a methodology for the empirical evaluation of primary health care (PHC) through the construction of digital representations of potential PHC coverage areas. METHODS: In this methodological study, potential areas were constructed by combinatorial analysis between census tracts and the location of basic health units with working PHC teams in Brazil. Six rules were used to parameterize the algorithm for the construction of potential areas. Thus, six restrictions were applied to enable the model: the selection of census tracts near the basic health unit; contiguous sectors; mutually exclusive sectors; sectors located in the same municipality of basic health units; sum of 4 500 users per health team in each unit; and volume of population ascribed proportional to the number of PHC teams allocated to the unit. Based on 316 594 census tracts and 39 758 basic health units, a neighborhood matrix was developed. To that matrix, a graph algorithm was applied to test combinations of sectors that simultaneously met the stipulated rules. RESULTS: A total of 1 901 114 arcs were defined, connecting 30 351 census tracts, allowing the construction of 26 907 potential areas. Based on these results, intra-municipal analyses can be performed to monitor PHC indicators. Customizable algorithm parameters can be adjusted to accommodate different sets of rules which may be adapted to different countries. CONCLUSIONS: The use of geoprocessing approaches creates conditions for the assessment of PHC impact, based on secondary databases at various levels, such as intra-municipal, basic health unit, and even at the team level.
OBJETIVO: Presentar una metodología para la evaluación empírica de la atención primaria de salud (APS) a través de la construcción de representaciones digitales de las áreas de cobertura potencial de los equipos de APS. MÉTODOS: Estudio de tipo metodológico. Las áreas potenciales se construyeron mediante un análisis combinatorio entre los sectores censales y la localización de las unidades básicas de salud con equipos de APS que trabajan en Brasil. Se utilizaron seis reglas para parametrizar el algoritmo de construcción de las áreas potenciales. Así, se estipularon seis restricciones que viabilizaron el modelo utilizado: selección de sectores censales cercanos a la unidad básica de salud; sectores contiguos; sectores mutuamente excluyentes; sectores ubicados en el mismo municipio de la unidad básica de salud; suma de 4 500 usuarios por equipo de salud en cada unidad básica de salud; y volumen de población adscrita proporcional al número de equipos de APS asignados en la unidad básica de salud. A partir de 316 574 sectores censales y 39 758 unidades básicas de salud se desarrolló una matriz de vecindad sobre la cual se aplicó un algoritmo gráfico que evaluaba las combinaciones de sectores que cumplían simultáneamente las reglas estipuladas. RESULTADOS: Se definieron en total 1 901 114 arcos, que conectaron 30 351 sectores censales, lo que permitió la construcción de 26 907 áreas potenciales. Sobre la base de estos resultados, se pueden realizar análisis intramunicipales para monitorear los indicadores de APS. Los parámetros modificables del algoritmo se pueden ajustar para adaptarse a diferentes conjuntos de reglas y a diferentes países. CONCLUSIONES: El uso de enfoques basados en geoprocesamiento puede crear condiciones para la evaluación del impacto de la APS conforme a bases de datos secundarias y a nivel intramunicipal, de la unidad básica de salud e incluso a nivel de equipo.
ABSTRACT
This paper compares the occupational structure of cities in Brazil and United States aiming to evaluate the extent to which the economic structure of these urban agglomerations is associated with the different stages of development, specifically when comparing a rich country with a developing one. Using a harmonized occupational database and microdata from the Brazilian 2010 Demographic Census and the U.S. American Community Survey (2008-2012), results show that Brazilian cities have a stronger connection between population size, both with occupational structure and human capital distribution, than the one found for cities in the United States. These findings suggest a stronger primacy of large cities in Brazil's urban network and a more unequal distribution of economic activity across cities when compared to USA, indicating a strong correlation between development and occupational structure.
Este artigo compara a estrutura ocupacional das cidades do Brasil e dos Estados Unidos, visando avaliar a extensão em que a estrutura econômica dessas aglomerações urbanas se associa aos diferentes estágios de desenvolvimento, especificamente quando se compara um país rico com um em desenvolvimento. Utilizando um banco de dados ocupacionais harmonizado e microdados do Censo Demográfico Brasileiro de 2010 e do US American Community Survey (2008-2012), os resultados mostram que as cidades brasileiras têm uma conexão mais forte do tamanho da população com a estrutura ocupacional e a distribuição de capital humano do que a observada em cidades nos Estados Unidos. Estes resultados sugerem uma primazia mais forte das grandes cidades na rede urbana do Brasil e uma distribuição mais desigual da atividade econômica entre as cidades quando comparadas aos EUA, indicando uma alta correlação entre desenvolvimento e estrutura ocupacional.
Este documento compara la estructura ocupacional de ciudades de Brasil y Estados Unidos de Norteamérica con el objetivo de evaluar la extensión a la cual la estructura económica de estas aglomeraciones urbanas se asocia en las diferentes etapas de desarrollo, específicamente cuando se compara un país rico con un país en desarrollo. Utilizando una base de datos ocupacional armonizada y microdatos del censo demográfico brasileño de 2010 y de la Encuesta de la Comunidad Estadounidense (2008-2012), los resultados muestran una conexión más fuerte en las ciudades brasileñas entre el tamaño de la población y la estructura ocupacional y la distribución del capital humano que la encontrada para ciudades de los Estados Unidos. Estos hallazgos sugieren una mayor primacía de las grandes ciudades en la red urbana de Brasil y una distribución más desigual de la actividad económica entre las ciudades en comparación con las de Estados Unidos, lo que indica una fuerte correlación entre el desarrollo y la estructura ocupacional.
Subject(s)
Humans , Male , Female , Adult , Middle Aged , Aged , Developed Countries , Urban Area , Developing Countries , Economics , United States , Urban Population , Brazil , Population Density , Agglomeration, Urban , Principal Component Analysis , Educational Status , EmploymentABSTRACT
OBJECTIVE: to describe a solution enabling geolocation of hospital admissions (AIH), processed on the Brazilian National Health System's Hospital Information System. METHODS: in order to spatialize AIHs an R language script was written, based on the microdatasus and CepR packages; the script was applied to identify all AIHs in Goiás state in the year 2015; after downloading and pre-processing the data, the procedure for AIH spatialization was detailed. RESULTS: of the 361,213 AIHs processed, we were able to retrieve 24,220 different ZIP codes (CEPs); from this set of ZIP codes, 23,910 (98.7%) were geolocated; these geolocated ZIP codes enabled spatialization of 97.7% of AIHs processed for the state of Goiás. CONCLUSION: it is possible to spatialize AIHs with a high success rate; the method detailed in this paper opens a new range of possibilities for the design of evaluation studies, formulation of policies and planning of health care actions.
Subject(s)
Geographic Information Systems , Hospital Information Systems/statistics & numerical data , Hospitalization/statistics & numerical data , National Health Programs , Brazil , Humans , SoftwareABSTRACT
BACKGROUND: Although the Zika virus (ZIKV) epidemic ceased to be a public health emergency by the end of 2016, studies to improve knowledge about this emerging disease are still needed, especially those investigating a causal relationship between ZIKV in pregnant women and microcephaly in neonates. However, there are still many challenges in describing the relationship between ZIKV and microcephaly. The few studies focusing on the epidemiological profile of ZIKV and its changes over time are largely limited to systematic reviews of case reports and dispersal mapping of ZIKV spread over time without quantitative methods to analyze patterns and their covariates. Since Brazil has been at the epicenter of the ZIKV epidemic, this study examines the geospatial association between ZIKV and microcephaly in Brazil. METHODS: Our study is categorized as a retrospective, ecological study based on secondary databases. Data were obtained from January to December 2016, from the following data sources: Brazilian System for Epidemiological Surveillance, Disease Notification System, System for Specialized Management Support, and Brazilian Institute of Geography and Statistics. Data were aggregated by municipality. Incidence rates were estimated per 100,000 inhabitants. Analyses consisted of mapping the aggregated incidence rates of ZIKV and microcephaly, followed by a Getis-Ord-Gi spatial cluster analysis and a Bivariate Local Moran's I analysis. RESULTS: The incidence of ZIKV cases is changing the virus's spatial pattern, shifting from Brazil's Northeast region to the Midwest and North regions. The number of municipalities in clusters of microcephaly incidence is also shifting from the Northeast region to the Midwest and North, after a time lag is considered. Our findings suggest an increase in microcephaly incidence in the Midwest and North regions, associated with high levels of ZIKV infection months before. CONCLUSION: The greatest burden of microcephaly shifted from the Northeast to other Brazilian regions at the beginning of 2016. Brazil's Midwest region experienced an increase in microcephaly incidence associated with ZIKV incidence. This finding highlights an association between an increase in ZIKV infection with a rise in microcephaly cases after approximately three months.
