Record Linkage for Malaria Deaths Data Recovery and Surveillance in Brazil

被引:3
作者
Sabino Garcia, Klauss Kleydmann [1 ]
Xavier, Danielly Batista [2 ]
Soremekun, Seyi [3 ]
Abrahao, Amanda Amaral [4 ]
Drakeley, Chris [3 ]
Ramalho, Walter Massa [1 ]
Siqueira, Andre M. [5 ]
机构
[1] Univ Brasilia, Ctr Trop Med, BR-70904970 Brasilia, DF, Brazil
[2] Univ Sao Paulo, Escola Super Agr Luis de Queiroz, BR-13418900 Piracicaba, SP, Brazil
[3] Univ London, Fac Infect & Trop Dis, London Sch Hyg & Trop Med, Dept Infect Biol, London WC1E 7HT, England
[4] Univ Brasilia, Fac Hlth Sci, BR-70910900 Brasilia, DF, Brazil
[5] Fundacao Oswaldo Cruz, Evandro Chagas Natl Inst Infectol, BR-21040360 Rio De Janeiro, RJ, Brazil
基金
比尔及梅琳达.盖茨基金会;
关键词
malaria; epidemiology; public health; control; interrupted time series; Brazil;
D O I
10.3390/tropicalmed8120519
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Objective: The objective is to describe the results and the methodological processes of record linkage for matching deaths and malaria cases. Methods: A descriptive cross-sectional study was conducted with probabilistic record linkage of death and malaria cases data in Brazil from 2011 to 2020 using death records from the Mortality Information System (SIM) and epidemiological data from the Notifiable Diseases Information System (Sinan) and Epidemiological Surveillance Information Systems for malaria (Sivep-Malaria). Three matching keys were used: patient's name, date of birth, and mother's name, with an analysis of cosine and Levenshtein dissimilarity measures. Results: A total of 490 malaria deaths were recorded in Brazil between 2011 and 2020. The record linkage resulted in the pairing of 216 deaths (44.0%). Pairings where all three matching keys were identical accounted for 30.1% of the total matched deaths, 39.4% of the matched deaths had two identical variables, and 30.5% had only one of the three key variables identical. The distribution of the variables of the matched deaths (216) was similar to the distribution of all recorded deaths (490). Out of the 216 matched deaths, 80 (37.0%) had poorly specified causes of death in the SIM. Conclusions: The record linkage allowed for the detailing of the data with additional information from other epidemiological systems. Record linkage enables data linkage between information systems that lack interoperability and is an extremely useful tool for refining health situation analyses and improving malaria death surveillance in Brazil.
引用
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页数:13
相关论文
共 34 条
  • [1] Avoundjian Tigran, 2020, JMIR Public Health Surveill, V6, pe15917, DOI 10.2196/15917
  • [2] Brasil, Presidencia da Republica. Casa Civil, Subchefia para Assuntos Juridicos. Lei N 10.216, de 6 de abril de 2001. Dispoe Sobre a Protecao e os Direitos das Pessoas Portadoras de Transtornos Mentais e Redireciona o Modelo Assistencial em Saude Mental
  • [3] Brasil. Ministerio da Saude, Portal Sinan-Malaria: Ficha de Notificacao/Investigacao Individual Para Malaria
  • [4] Brasil. Ministerio da Saude, Ficha de Notificacao Sivep-Malaria Atualizado em 30 de jun 2022
  • [5] Camargo K R Jr, 2000, Cad Saude Publica, V16, P439
  • [6] Preparation of name and address data for record linkage using hidden Markov models
    Tim Churches
    Peter Christen
    Kim Lim
    Justin Xi Zhu
    [J]. BMC Medical Informatics and Decision Making, 2 (1)
  • [7] Sensitivity of the Dengue Surveillance System in Brazil for Detecting Hospitalized Cases
    Coelho, Giovanini Evelim
    Leal, Priscila Leite
    Cerroni, Matheus de Paula
    Rocha Simplicio, Ana Cristina
    Siqueira, Joao Bosco, Jr.
    [J]. PLOS NEGLECTED TROPICAL DISEASES, 2016, 10 (05):
  • [8] Neto GCC, 2021, CAD SAUDE PUBLICA, V37, DOI [10.1590/0102-311x00182119, 10.1590/0102-311X00182119]
  • [9] Record linkage under suboptimal conditions for data-intensive evaluation of primary care in Rio de Janeiro, Brazil
    Coeli, Claudia Medina
    Saraceni, Valeria
    Medeiros, Paulo Mota, Jr.
    da Silva Santos, Helena Pereira
    Guillen, Luis Carlos Torres
    Alves, Luis Guilherme Santos Buteri
    Hone, Thomas
    Millett, Christopher
    Trajman, Anete
    Durovni, Betina
    [J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2021, 21 (01)
  • [10] David R., 2020, FuzzyJoin