Hepatitis A incidence rate estimates from a pilot seroprevalence survey inRio de Janeiro, Brazil

Citation
Cj. Struchiner et al., Hepatitis A incidence rate estimates from a pilot seroprevalence survey inRio de Janeiro, Brazil, INT J EPID, 28(4), 1999, pp. 776-781
Citations number
34
Categorie Soggetti
Envirnomentale Medicine & Public Health","Medical Research General Topics
Journal title
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
ISSN journal
03005771 → ACNP
Volume
28
Issue
4
Year of publication
1999
Pages
776 - 781
Database
ISI
SICI code
0300-5771(199908)28:4<776:HAIREF>2.0.ZU;2-0
Abstract
Background To assess the impact of water sanitation and sewage disposal, pa rt of a major environmental control programme In Rio de Janeiro, we carried out seroprevalence studies for Hepatitis A virus (HAV) in three micro-regi ons in Rio de Janeiro. Each region varied with regard to level of sanitatio n. We are interested in assessing the discriminating power of age-specific prevalence curves for HAV as a proxy for improvement in sanitation. These c urves will serve as baseline information to future planned surveys as the s anitation programme progresses. Methods Incidence rate curves from prevalence data are estimated parametric ally via a Weibull-like survival function, and non-parametrically via maxim um likelihood and monotonic splines. Sera collected from children and adult s in the three areas are used to detect antibodies against HAV through ELIS A. Results We compare baseline incidence curves at the three sites estimated b y the three methods. We observe a strong negative correlation between level of sanitation and incidence rates for HAV infection. Incidence estimates y ielded by the parametric and non-parametric approaches tend to agree at ear ly ages in the microregion showing the best level of sanitation and to incr easingly disagree in the other two. Conclusion Our results support the choice of HAV as a sentinel disease that is associated with level of sanitation. We also introduce monotonic spline s as a novel non-parametric approach to estimate incidence from prevalence data. This approach outperforms current estimating procedures.