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 o n human bait at seven fixed sites in the Lowveld Region of Mpumalanga Provi nce, South Africa, between August 1997 and May 1998 to contribute to the ev aluation and planning of the malaria vector control programme. Members of t he An. gambiae complex were distinguished from other anopheline species usi ng morphological keys and were subsequently specifically identified by poly merase chain reaction (PCR). A total of 5084 anophelines were collected dur ing the survey, of which 2837 (55.8 %) were Anopheles coustani Laveran, 141 8 (27.9 %) were members of the Anopheles funestus group, 435 (8.6 %) were m embers of the An. gambiae complex, 264 (5.2 %) were Anopheles pretoriensis Theobald, and 130 (2.6 %) comprised nine other anopheline species. From a t otal of 425 PCR identifications of adult females of the An. gambiae complex , 238 (56.0 %) were Anopheles merus Donitz, 129 (30.4 %) Anopheles quadrian nulatus Theobald and 58 (13.6 %) were Anopheles arabiensis Patton. No circu msporozoite antigen for Plasmodium falciparum was detected in any of the fe male An. gambiae complex mosquitoes. Monthly An. gambiae s.l. captures were significantly correlated with rainfall but there was no correlation betwee n mosquito captures and monthly malaria notifications. Malaria notification s 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 th e 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 n umbers of An. merus feeding on humans in Mpumalanga. Further analysis of ra infall and temperature patterns may facilitate the prediction of malaria ep idemics with sufficient lead-time to enable the Provincial Malaria Control Programme to launch pre-emptive control measures.