oa African Entomology - Captures of mosquitoes of the Anopheles gambiae complex (Diptera: Culicidae) in the Lowveld Region of Mpumalanga Province, South Africa
Monthly collections of the Anopheles gambiae complex mosquitoes were made on human bait at seven fixed sites in the Lowveld Region of Mpumalanga Province, South Africa, between August 1997 and May 1998 to contribute to the evaluation and planning of the malaria vector control programme. Members of the An. gambiae complex were distinguished from other anopheline species using morphological keys and were subsequently specifically identified by polymerase chain reaction (PCR). A total of 5084 anophelines were collected during the survey, of which 2837 (55.8 %) were Anopheles coustani Laveran, 1418 (27.9 %) were members of the Anopheles funestus group, 435 (8.6 %) were members of the An. gambiae complex, 264 (5.2 %) were Anopheles pretoriensis Theobald, and 130 (2.6 %) comprised nine other anopheline species. From a total of 425 PCR identifications of adult females of the An. Gambiae complex, 238 (56.0 %) were Anopheles merus Donitz, 129 (30.4 %) Anopheles quadriannulatus Theobald and 58 (13.6 %) were Anopheles arabiensis Patton. No circumsporozoite antigen for Plasmodium falciparum was detected in any of the female An. gambiae complex mosquitoes. Monthly An. gumbiae s.l. captures were significantly correlated with rainfall but there was no correlation between mosquitoes captures and monthly malaria notifications. Malaria notifications were, however, strongly associated with mean daily temperatures. The peak in malaria incidence paralleled the peak in rainfall with a time lag of 2-3 months. This study provides updated information on the distribution of the An. gambiae complex in Mpumalanga Province's Lowveld Region, notably the incidence of mosquitoes biting humans outside sprayed houses between 18:00 and 22:00. The study also provides the first documented evidence of large numbers of An. merus feeding on humans in Mpumalanga. Further analysis of rainfall and temperature patterns may facilitate the prediction of malaria epidemics with sufficient lead-time to enable the Provincial Malaria Control Programme to launch pre-emptive control measures.
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