Case Definitions of Clinical Malaria in Children from Three Health Districts in the North Region of Cameroon

Abstract

Malaria endemicity in Cameroon greatly varies according to ecological environment. In such conditions, parasitaemia, which is associated with fever, may not always suffice to define an episode of clinical malaria. The evaluation of malaria control intervention strategies mostly consists of identifying cases of clinical malaria and is crucial to promote better diagnosis for accurate measurement of the impact of the intervention. We sought out to define and quantify clinical malaria cases in children from three health districts in the Northern region of Cameroon. A cohort study of 6,195 children aged between 6 and 120 months was carried out during the raining season (July to October) between 2013 and 2014. Differential diagnosis of clinical malaria was performed using the parasite density and axillary temperature. At recruitment, patients with malaria-related symptoms (fever [axillary temperature ≥ 37.5°C], chills, severe malaise, headache, or vomiting) and a malaria positive blood smear were classified under clinical malaria group. The malaria attributable fraction was calculated using logistic regression models. Plasmodium falciparum was responsible for over 91% of infections. Children from Pitoa health district had the highest number of asymptomatic infections (45.60%) compared to those from Garoua and Mayo Oulo. The most suitable cut-off for the association between parasite densities and fever was found among children less than 24 months. Overall, parasite densities that ranged above 3,200 parasites per μl of blood could be used to define the malaria attributable fever cases. In groups of children aged between 24 and 59 months and 60 and 94 months, the optimum cut-off parasite density was 6,400 parasites per μl of blood, while children aged between 95 and 120 months had a cut-off of 800 parasites per μl of blood. In the same ecoepidemiological zone, clinical malaria case definitions are influenced by age and location (health district) and this could be considered when evaluating malaria intervention strategies in endemic areas.