1934 Bantus and 379 Pygmies were investigated for Loa loa and Mansonella perstans filariasis in 7 villages in the Chaillu forest of the Congo. Bantus were more frequently infected with L. loa than Pygmies (18.9% of microfilariae carriers compared with 10.6%). In individuals over 30 years of age, males were more frequently infected than females. Microfilarial densities increased until the age of 20 years and then remained stable. Parasite load was not significantly different in the two ethnic groups. For mansonelliasis, the microfilarial rate was higher in the Pygmies (67.5% compared with 22.0%) and males of the 2 groups were more frequently infected than females. Microfilarial load was also higher in Pygmies than in Bantus (mean microfilarial densities (MfD 50) 13 and 2 respectively). In the Pygmy group, MfD 50 for M. perstans increased with age whereas it remained stable in the Bantus. 53.8% of the 249 questioned persons had experienced worm migration under the conjunctiva. Both ethnic groups were equally exposed to the vectors of L. loa and reasons for the difference in prevalence of microfilaria carriers are discussed. For mansonelliasis increased contact with vectors may explain the higher degree of infestation observed in Pygmies. Other filariases were infrequent in (Mansonella streptocerca), or absent from (Onchocerca volvulus and Wuchereria bancrofti), the study area.
An agent-based model (AMB) used to simulate the spread of Human African Trypanosomiasis is presented together with the results of simulations of a focus of the disease. This model is a completely spatialized approach taking into account a series of often overlooked parameters such as human behaviour (activity-related movements), the density and mobility of the disease vectors -tsetse flies (Glossina spp.) -and the influence of other tsetse feeding hosts (livestock and wild animal populations). The agents that represent humans and tsetse flies move in a spatially structured environment managed by specialized location agents. Existing compartmental mathematical models governed by differential equations fail to incorporate the spatial dimension of the disease transmission. Furthermore, on a small scale, transmission is unrealistically represented by entities less than one. This ABM was tested with data from one village of the Bipindi sleeping sickness focus (southern Cameroon) and with obtained realistic simulations of stable transmission involving an animal reservoir. In varying different spatial configurations, we observe that the stability of spread is linked to the spatial complexity (number of heterogeneous locations). The prevalence is very sensitive to the human densities and to the number of tsetse flies initially infected in a given location. A relatively low and durable prevalence is obtained with shortening the phase I. In addition, we discuss some upgrading possibilities, in particular the linkage to a Geographical Information System (GIS). The agent-based approach offers new ways to understanding the spread of the disease and a tool to evaluate risk and test control strategies.
Vector control and the detection (followed by treatment) of infected individuals are the two methods currently available for the control of sleeping sickness. The basic reproduction rate of a compartmental model is used to analyse and compare the two strategies. The efficiency of each strategy will depend on two epidemiologic parameters; the intrinsic contamination rate Q (closely related to the index of new contaminations) that captures the potential spread of the disease, and the intrinsic removal rate from the first stage (intrinsic to the particular trypanosome strain and to the population's susceptibility). The model shows that when the intrinsic removal rate is low (that is, when there is a long first stage characteristic of an endemic situation) the detection of sick individuals is more efficient than vector control. The situation is reversed when the removal rate is high (in an epidemic situation). The conclusions of the analysis are shown to be in general agreement with results obtained in two different sleeping sickness foci of Central Africa.
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