Search

Background: As most data on hepatitis in resource-poor countries relate to urban communities, surveys in the rural environment are necessary to determine the 'true' prevalence of these viral infections. We undertook a survey to determine the prevalence of hepatitis B virus (HBV) infection in an apparently healthy rural population in the Central African Republic (CAR). Methods: The cross-sectional study was based on dried blood spots (DBS) from 273 people recruited in four prefectures (Lobaye, Nana-Mambéré, Ouham and Ouaka). Eluates from DBS were tested with commercial ELISA kits to detect markers of HBV infection. DBS were directly used for DNA extraction, followed by PCR and genotyping based on preS/S gene sequences. Results: The overall prevalence of HBc antibodies was 27.1% (Lobaye 29%, Nana-Mambéré 28%, Ouaka 29% and Ouham 23%) and that of HBsAg was 10.6% (Lobaye 9%, Nana-Mambéré 9%, Ouaka 19% and Ouham 8%), with no statistically significant difference among the surveyed communities. Nineteen sequences obtained from 74 anti-HBc-positive patients all belonged to genotype E. Risk factor analysis of HBV infection pointed to sexual transmission of the virus. Conclusion: The prevalence of HBV is high in rural communities in the CAR and comparable to that observed in urban areas. In addition, genotype E is prevalent in these areas. These findings underline the importance of instituting a programme of active HBV surveillance and vaccination of the population. [ABSTRACT FROM AUTHOR]

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improvement of the surveillance system for these diseases. Biomedical ontologies are a growing field that can improve health information systems. Indeed biomedical ontologies allow semantic support, data integration, automated reasoning. We are building a meningitis ontology to assist filtering messages relevant to meningitis domain on social media in order to predict a possible epidemic. Indeed, the messages filtered are used for data and event extraction that serve as input for a meningitis surveillance system. In this paper we focused on the modeling and formalization of different perspectives of the meningitis disease such as biological perspective, clinical perspective, epidemiological and public health perspective. This paper presents the three modules in the global Infection Disease Ontology for Meningitis (IDOMEN) and at the end, we illustrate a case of reasoning with our ontology.