Publications

Count data are very common in health services research, and very commonly the basic Poisson regression model has to be extended in several ways to accommodate several sources of heterogeneity: (i) an excess number of zeros relative to a Poisson distribution, (ii) hierarchical structures, and correlated data, (iii) remaining “unexplained” sources of overdispersion. In this paper, we propose hierarchical zero-inflated and overdispersed models with independent, correlated, and shared random effects for both components of the mixture model. We show that all different extensions of the Poisson model can be based on the concept of mixture models, and that they can be combined to account for all different sources of heterogeneity. Expressions for the first two moments are derived and discussed. The models are applied to data on maternal deaths and related risk factors within health facilities in Mozambique. The final model shows that the maternal mortality rate mainly depends on the geographical location of the health facility, the percentage of women admitted with HIV and the percentage of referrals from the health facility.

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Background: The follow-up of HIV-exposed infants remains a public health challenge in many Sub-Saharan countries. Just as integrated antenatal and maternity services have contributed to improved care for HIV-positive pregnant women, so too could integrated care for mother and infant after birth improve follow-up of HIV-exposed infants. We present results of a study testing the viability of such integrated care, and its effects on follow-up of HIV-exposed infants, in Tete Province, Mozambique.

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There is little information about the prevalence of sexually transmitted infections (STIs) in pregnant women in Mozambique. In Tete, a province in the country's northwest, recent data are not available. However, the province's Directorate of Health reported an antenatal clinic (ANC) attendance rate of nearly 100%. This study set out to assess the prevalence of Chlamydia trachomatis (CT), Neisseria gonorrhoeae (G) and syphilis in pregnant women attending urban health centres.
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