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Published on: February 20, 2020
[Analysis of visceral leishmaniasis reports by the capture-recapture method]
Ana Nilce Silveira Maia-Elkhoury1, Eduardo Hage Carmo, Marcia Leite Sousa-Gomes
1Departamento de Vigilância Epidemiológica, Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília, DF, Brasil. ana.elkhoury@saude.gov.br
Objective:
To analyze the number of cases, deaths, incidence and fatality rate due to visceral leishmaniasis, and to estimate its underreporting, as well as the coverage of the national information systems.
Methods:
Confirmed cases of visceral leishmaniasis were analyzed, based on the following systems: the Sistema de Informação de Agravos de Notificação (SINAN - Information System on Disease Notification), the Sistema de Informações sobre Mortalidade (SIM - Mortality Information System) and the Sistema de Informações Hospitalares (SIH - Hospital Information System), between 2002 and 2003. The variables utilized in relationship for pair identification were: patient's name, mother's name, date of birth, gender, city of residence, and mailing address. The capture-recapture method was applied to calculate the estimates, by means of the Chapman formula.
Results:
The estimated underreporting of visceral leishmaniasis in the SINAN, in relation to the SIH and the SIM, was 42.2% and 45.0% respectively. The estimated underreporting of deaths was 53% and 46.5%, when compared to SINAN-deaths and SIH-deaths respectively. The estimated incidence was 2.9 per 100,000 inhabitants, from the comparison between the SINAN and the SIH, 70.5% higher than the one found when SINAN's data were the only ones utilized. Furthermore, when comparing data from SIM and SINAN-deaths, an estimated fatality rate of 8% was observed, representing an increase in 16% from the one initially registered in the SINAN-deaths.
Conclusions:
The results show high estimated underreporting of cases and deaths due to visceral leishmaniasis in Brazil. The relationship between information systems and the capture-recapture method application enabled to know and improve the epidemiological estimates, making its utilization in health services feasible.
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