An Epidemiologic Model of Severe Morbidity and Mortality Caused by Plasmodium Falciparum

Abstract

Abstract. The intensity of Plasmodium falciparum transmission has multifarious and sometimes counter-intuitive effects on age-specific rates of severe morbidity and mortality in endemic areas. This has led to conflicting speculations about the likely impact of malaria control interventions. We propose a quantitative framework to reconcile the various apparently contradictory observations relating morbidity and mortality rates to malaria transmission. Our model considers two sub-categories of severe malaria episodes. These comprise episodes with extremely high parasite densities in hosts with little previous exposure, and acute malaria episodes accompanied by co-morbidity or other risk factors enhancing susceptibility. In addition to direct malaria mortality from severe malaria episodes, the model also considers the enhanced risk of indirect mortality following acute episodes accompanied by co-morbidity after the parasites have been cleared. We fit this model to summaries of field data from endemic areas of Africa, and show that it can account for the observed age-and exposure-specific patterns of pediatric severe malaria and malaria-associated mortality in children. This model will allow us to make predictions of the long-term impact of potential malaria interventions. Predictions for children will be more reliable than those for older people because there is a paucity of epidemiologic studies of adults and adolescents.

An Approach to Model the Costs and Effects of Case Management of Plasmodium Falciparum Malaria in Sub-Saharan Africa

“…Simulated patterns of ageprevalence and age-incidence for the reference scenario (Figure 2) are similar to those for typical meso-endemic settings in Africa to which the models were fitted. 9,12,13 The direct cost per capita is stable over time. The predicted infectiousness of the host population, u (t), fluctuates seasonally around a value of approximately 3% (Figure 3a).…”

“…They have been determined by functions that have been fitted to field data across a wide range of transmission settings. [12][13][14] In addition, the prevalence of anemia (hemoglobin levels less than 8 g/dL) is assigned at the population rather than the individual level, as a function of simulated age and parasite prevalence.…”

“…Q h (a) varies with age a, taking values from 3% to 13%. Q c (a) takes values estimated previously using our model for severe malaria and mortality assuming the two risks to be related via a constant odds ratio, 1 , taking a value of 2.09, 12 i.e.,…”

“…12 Non-malaria death and out-migration correspond to events that occur independently of the parasitologic status of the host. These events are simulated to maintain the correct agestructure of the simulated population.…”

“…We consider these as equivalent to those events that would have led to an admission diagnosis of severe malaria, had the patient presented to a health facility. 12 The current model assumes that a severe malaria case can either be treated as an inpatient or not be treated at all. In the former case it is assumed that compliance is 100%.…”