Modelling the Force of Infection for Hepatitis A in an Urban Population-Based Survey: A Comparison of Transmission Patterns in Brazilian Macro-Regions

摘要

Background:This study aimed to identify the transmission pattern of hepatitis A (HA) infection based on a primary datasetfrom the Brazilian National Hepatitis Survey in a pre-vaccination context. The national survey conducted in urban areasdisclosed two epidemiological scenarios with low and intermediate HA endemicity.Methods:A catalytic model of HA transmission was built based on a national seroprevalence survey (2005 to 2009). Theseroprevalence data from 7,062 individuals aged 5–69 years from all the Brazilian macro-regions were included. We built upthree models: fully homogeneous mixing model, with constant contact pattern; the highly assortative model and the highlyassortative model with the additional component accounting for contacts with infected food/water. Curves of prevalence,force of infection (FOI) and the number of new infections with 99% confidence intervals (CIs) were compared between theintermediate (North, Northeast, Midwest and Federal District) and low (South and Southeast) endemicity areas. A contourplot was also constructed.Results:The anti- HAV IgG seroprevalence was 68.8% (95% CI, 64.8%–72.5%) and 33.7% (95% CI, 32.4%–35.1%) for theintermediate and low endemicity areas, respectively, according to the field data analysis. The models showed that a higherforce of infection was identified in the 10- to 19-year-old age cohort (,9,000 infected individuals per year per 100,000susceptible persons) in the intermediate endemicity area, whereas a higher force of infection occurred in the 15- to 29-year-old age cohort (,6,000 infected individuals per year per 100,000 susceptible persons) for the other macro-regions.Conclusion:Our findings support the shift of Brazil toward intermediate and low endemicity levels with the shift of the riskof infection to older age groups. These estimates of HA force of infection stratified by age and endemicity levels are usefulinformation to characterize the pre-vaccination scenario in Brazil.