Detection of risk clusters for deaths due to tuberculosis specifically in areas of southern Brazil where the disease was supposedly a non-problem.

Autor: Alves LS; Nursing Graduate Program in Public Health Nursing, University of São Paulo at Ribeirão Preto Nursing College, 3900 Avenida dos Bandeirantes, São Paulo, Brazil. lu.selesrp@gmail.com.; Maternal-Infant and Public Health Nursing Department, University of São Paulo at Ribeirão Preto College of Nursing, Av dos Bandeirantes 3900, Ribeirão Preto, São Paulo, 14040-902, Brazil. lu.selesrp@gmail.com., Dos Santos DT; Inter-institutions Doctoral Program in Nursing, University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., Arcoverde MAM; Nursing Graduate Program in Public Health Nursing, University of São Paulo at Ribeirão Preto Nursing College, 3900 Avenida dos Bandeirantes, São Paulo, Brazil., Berra TZ; Nursing Graduate Program in Public Health Nursing, University of São Paulo at Ribeirão Preto Nursing College, 3900 Avenida dos Bandeirantes, São Paulo, Brazil., Arroyo LH; Inter-institutions Doctoral Program in Nursing, University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., Ramos ACV; Nursing Graduate Program in Public Health Nursing, University of São Paulo at Ribeirão Preto Nursing College, 3900 Avenida dos Bandeirantes, São Paulo, Brazil., de Assis IS; Nursing Graduate Program in Public Health Nursing, University of São Paulo at Ribeirão Preto Nursing College, 3900 Avenida dos Bandeirantes, São Paulo, Brazil., de Queiroz AAR; Public Health, Natal, Rio Grande do Norte, Brazil., Alonso JB; University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., Alves JD; Inter-institutions Doctoral Program in Nursing, University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., Popolin MP; Department of Nursing, Fasipe School, Mato Grosso, Brazil., Yamamura M; Inter-institutions Doctoral Program in Nursing, University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., de Almeida Crispim J; Inter-institutions Doctoral Program in Nursing, University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., Dessunti EM; Department of Nursing, Londrina State University, Londrina, Paraná, Brazil., Palha PF; University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil., Chiaraval-Neto F; Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, São Paulo, Brazil., Nunes C; National School of Public Health, Nova University of Lisbon, Lisboa, Portugal., Arcêncio RA; University of São Paulo at Ribeirão Preto Nursing College, São Paulo, Brazil.
Jazyk: angličtina
Zdroj: BMC infectious diseases [BMC Infect Dis] 2019 Jul 17; Vol. 19 (1), pp. 628. Date of Electronic Publication: 2019 Jul 17.
DOI: 10.1186/s12879-019-4263-1
Abstrakt: Background: Tuberculosis (TB) is the infectious disease that kills the most people worldwide. The use of geoepidemiological techniques to demonstrate the dynamics of the disease in vulnerable communities is essential for its control. Thus, this study aimed to identify risk clusters for TB deaths and their variation over time.
Methods: This ecological study considered cases of TB deaths in residents of Londrina, Brazil between 2008 and 2015. We used standard, isotonic scan statistics for the detection of spatial risk clusters. The Poisson discrete model was adopted with the high and low rates option used for 10, 30 and 50% of the population at risk, with circular format windows and 999 replications considered the maximum cluster size. Getis-Ord Gi* (Gi*) statistics were used to diagnose hotspot areas for TB mortality. Kernel density was used to identify whether the clusters changed over time.
Results: For the standard version, spatial risk clusters for 10, 30 and 50% of the exposed population were 4.9 (95% CI 2.6-9.4), 3.2 (95% CI: 2.1-5.7) and 3.2 (95% CI: 2.1-5.7), respectively. For the isotonic spatial statistics, the risk clusters for 10, 30 and 50% of the exposed population were 2.8 (95% CI: 1.5-5.1), 2.7 (95% CI: 1.6-4.4), 2.2 (95% CI: 1.4-3.9), respectively. All risk clusters were located in the eastern and northern regions of the municipality. Additionally, through Gi*, hotspot areas were identified in the eastern and western regions.
Conclusions: There were important risk areas for tuberculosis mortality in the eastern and northern regions of the municipality. Risk clusters for tuberculosis deaths were observed in areas where TB mortality was supposedly a non-problem. The isotonic and Gi* statistics were more sensitive for the detection of clusters in areas with a low number of cases; however, their applicability in public health is still restricted.
Databáze: MEDLINE
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