Research

Mapping the distribution of Loa loa in Cameroon in support of the African Programme for Onchocerciasis Control

Madeleine C Thomson¹, Valérie Obsomer¹, Joseph Kamgno², Jacques Gardon², Samuel Wanji³, Innocent Takougang⁴, Peter Enyong⁵, Jan H Remme⁶, David H Molyneux¹ and Michel Boussinesq²

¹  Liverpool School of Tropical Medicine, Liverpool, UK, L3 5QA

²  Laboratoire mixte Institut de Recherche pour le Développement (IRD) – Centre Pasteur du Cameroun d'Epidémiologie et de Santé publique, Centre Pasteur du Cameroun, BP 1274 Yaoundé, Cameroon

³  Department of Life Sciences, Faculty of Science, University of Buea, P.O. Box 63, Buea, Cameroon

⁴  Department of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, P.O. Box 1364, Yaoundé, Cameroon

⁵  Tropical Medicine Research Station, P.O. Box 55, Kumba, Cameroon

⁶  UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), WHO, Geneva, Switzerland

Filaria Journal 2004, 3:7doi:10.1186/1475-2883-3-7

Published:	6 August 2004

Abstract

Background

Loa loa has recently emerged as a filarial worm of significant public health importance as a consequence of its impact on the African Programme for Onchocerciasis Control (APOC). Severe, sometimes fatal, encephalopathic reactions to ivermectin (the drug of choice for onchocerciasis control) have occurred in some individuals with high Loa loa microfilarial counts. Since high density of Loa loa microfilariae is known to be associated with high prevalence rates, a distribution map of the latter may determine areas where severe reactions might occur. The aim of the study was to identify variables which were significantly associated with the presence of a Loa microfilaraemia in the subjects examined, and to develop a spatial model predicting the prevalence of the Loa microfilaraemia.

Methods

Epidemiological data were collected from 14,225 individuals living in 94 villages in Cameroon, and analysed in conjunction with environmental data. A series of logistic regression models (multivariate analysis) was developed to describe variation in the prevalence of Loa loa microfilaraemia using individual level co-variates (age, sex, μl of blood taken for examination) and village level environmental co-variates (including altitude and satellite-derived vegetation indices).

Results

A spatial model of Loa loa prevalence was created within a geographical information system. The model was then validated using an independent data set on Loa loa distribution. When considering both data sets as a whole, and a prevalence threshold of 20%, the sensitivity and the specificity of the model were 81.7 and 69.4%, respectively.

Conclusions

The model developed has proven very useful in defining the areas at risk of post-ivermectin Loa-related severe adverse events. It is now routinely used by APOC when projects of community-directed treatment with ivermectin are examined.