RESUMO
OBJECTIVE: To analyse the spatial distribution of the incidence of leprosy and identify areas at risk for occurrences of hyper-endemic disease in Northeastern Brazil. METHODS: Ecological study using municipalities as the analysis unit. Data on new cases of leprosy came from the Health Hazard Notification System (SINAN). This study focused on Pernambuco and covered the years 2005 to 2014. Indicators for monitoring were calculated per 100 000 inhabitants. The local empirical Bayes method was used to minimise rate variance, and spatial autocorrelation maps were used for spatial pattern analysis (box maps and Moran maps). RESULTS: A total of 28 895 new cases were registered in the study period. The average incidence was 21.88/100 000; the global Moran's I index was 0.36 (P < 0.01), thus indicating the existence of spatial dependence; and the Moran map identified 20 municipalities with high priority for attention. The average incidence rate among individuals under 15 years of age was 8.78/100 000; the global Moran's I index showed the presence of positive spatial autocorrelation (0.43; P < 0.01), and the Moran map showed a main cluster of 15 hyper-endemic municipalities. The average rate of grade 2 physical disability at the time of diagnosis was 1.12/100 000; the global Moran index presented a positive spatial association (0.17; P < 0.01); and the Moran map located clusters of municipalities (high-high) in three mesoregions. CONCLUSION: Application of different spatial analysis methods made it possible to locate areas that would not have been identified by epidemiological indicators alone.
Assuntos
Doenças Endêmicas , Hanseníase/epidemiologia , Adolescente , Brasil/epidemiologia , Criança , Pré-Escolar , Feminino , Humanos , Incidência , Lactente , Recém-Nascido , Hanseníase/etiologia , Masculino , Fatores de Risco , Análise Espaço-TemporalRESUMO
BACKGROUND: Since the introduction of the national notifiable diseases information system (SINAN) in Pernambuco State, Brazil, in 1994, many problems have been encountered. The aim of this study was to evaluate the SINAN software, quality of data input, the transfer of the computerised data from the municipality to state levels, human resources and other factors associated with the health information system infrastructure (HIS). METHODS: A cross-sectional study was carried out in Pernambuco state, North-eastern Brazil, in 2005. A sample of health regions and municipalities was chosen. SINAN forms from those municipalities were analysed and the flow of notifications followed from municipal level to the regional and finally to the state. Professionals from health units, district, municipal and regional Hansen's Disease Control Programme (HDCP) and Epidemiological Surveillance System (ESS) coordinators, health secretaries and managers of the municipalities and health regions selected were interviewed. RESULTS: SINAN software is functioning up to expectation. However, at all levels of the health system, serious weaknesses not related to the SINAN software were found, varying from lack of human resources (limited number of staff and staff development), lack of infrastructure (office space, computers, supplies, etc.) to an absence of effective coordination, management and supervision of the HIS. CONCLUSIONS: Lack of reliable, complete and timely information, and especially the lack of widespread analysis and use of available information in planning and management of health services were the main weaknesses found. Many areas need urgent attention: the quality of patient examination, recording and reporting, the timely processing of quality data, the coordination and management of disease control programmes, and the use of HIS reports by the health services and health managers. Regular feedback, supportive supervision visits and annual reviews are essential to monitor the system and make sure that essential information is decentralised and used by the primary health services and HDCP coordination. Assessing the quality of services from a client perspective would give additional information for the identification of strengths and weaknesses of the Hansen's disease (leprosy) services.