ESTIMATION OF ATTRIBUTABLE FRACTION FOR MALARIA IN PREGNANT WOMEN

Abstract

 This study applied the estimation of logit model of fever risk as a disease function of parasite density, age and season to give a more precise estimate. The data used for this study was obtained from the University College Hospital (UCH). Asymptomatic carriage of malaria parasites occurs frequently in endemic areas and the detection of parasites in a blood film from a febrile individual which does not necessarily indicate clinical malaria. In areas of very high transmission such estimates of the attributable fraction may be imprecise because very few individual pregnant women are without parasites. Furthermore, non-malaria fevers appear to suppress low levels of parasitaemia resulting in biased estimates of attributable fraction. We therefore, propose a qualitative response regression model for obtaining precise estimates of the probabilities of pregnant women with different level of parasitaemia having fever due to malaria. Logistic regression methods which model fever risk as a continuous function of parasite density, age, and season to give a more precise estimates than simple analyses of parasite prevalence and overcome problems of bias caused by the effects of non-malaria fevers. The result indicate that age is not a predicting factor affecting the pregnant women living in endemic areas, and also season has a slight effect while the parasite level is a major factor.