A time series analysis of detection and mortality of hepatitis C in Brazil, 2008-2018

BMC Infect Dis. 2022 Jan 24;22(1):81. doi: 10.1186/s12879-022-07063-5.

Abstract

Background: The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030. In Brazil, efforts have been undertaken to achieve this goal; there are, however, great challenges. It is important to understand the disease profile in different regions of the country in order to design strategies to fight the disease nationwide. The objective of this study was to analyse the time trend of the incidence and mortality of hepatitis C in Brazil during the period from 2008 to 2018 according to sociodemographic and clinical characteristics.

Methods: All newly diagnosed cases of hepatitis C reported between 2008 and 2018, in all regions of Brazil, were included. The indicators were obtained from the databases of the Brazilian Ministry of Health. For the time series analysis, a joinpoint regression model was used.

Results: Between 2008 and 2018, 136,759 newly diagnosed cases of hepatitis C were reported considering anti-HCV and HCV RNA positivity, and 271,624 newly diagnosed cases were reported considering one or another positive test. The majority of the records were concentrated in the Southeast (61%) and South (26.2%) Regions. The joinpoint regression model indicated an increasing trend in the detection rate of hepatitis C in Brazil, but there was a decreasing trend in the mortality rate during the period analysed.

Conclusions: Differences were observed in the time trend of hepatitis C and in the sociodemographic and clinical characteristics in different regions of Brazil. These data can provide support to design strategies for the elimination of hepatitis C in Brazil, according to regional particularities.

Keywords: Epidemiology; HCV; Hepatitis C; Incidence; Mortality.

MeSH terms

  • Brazil / epidemiology
  • Hepacivirus* / genetics
  • Hepatitis C* / diagnosis
  • Hepatitis C* / epidemiology
  • Humans
  • Incidence
  • Time Factors