Impact of cattle on the abundance of indoor and outdoor resting malaria vectors in southern Malawi.

BACKGROUND: Understanding the blood feeding preferences and resting habits of malaria vectors is important for assessing and designing effective malaria vector control tools. The presence of livestock, such as cattle, which are used as blood meal hosts by some malaria vectors, may impact malaria parasite transmission dynamics. The presence of livestock may provide sufficient blood meals for the vectors, thereby reducing the frequency of vectors biting humans. Alternatively, the presence of cattle may enhance the availability of blood meals such that infectious mosquitoes may survive longer, thereby increasing the risk of malaria transmission. This study assessed the effect of household-level cattle presence and distribution on the abundance of indoor and outdoor resting malaria vectors. METHODS: Houses with and without cattle were selected in Chikwawa district, southern Malawi for sampling resting malaria vectors. Prokopack aspirators and clay pots were used for indoor and outdoor sampling, respectively. Each house was sampled over two consecutive days. For houses with cattle nearby, the number of cattle and the distances from the house to where the cattle were corralled the previous night were recorded. All data were analysed using generalized linear models fitted with Poisson distribution. RESULTS: The malaria vectors caught resting indoors were Anopheles gambiae sensu stricto (s.s.), Anopheles arabiensis and Anopheles funestus s.s. Outdoor collections consisted primarily of An. arabiensis. The catch sizes of indoor resting An. gambiae sensu lato (s.l.) were not different in houses with and without cattle (P = 0.34). The presence of cattle near a house was associated with a reduction in the abundance of indoor resting An. funestus s.l. (P = 0.04). This effect was strongest when cattle were kept overnight ≤ 15 m away from the houses (P = 0.03). The blood meal hosts varied across the species. CONCLUSION: These results highlight differences between malaria vector species and their interactions with potential blood meal hosts, which may have implications for malaria risk. Whereas An. arabiensis remained unaffected, the reduction of An. funestus s.s. in houses near cattle suggests a potential protective effect of cattle. However, the low abundance of mosquitoes reduced the power of some analyses and limited the generalizability of the results to other settings. Therefore, further studies incorporating the vectors' host-seeking behaviour/human biting rates are recommended to fully support the primary finding.

Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi.

INTRODUCTION: In the context of malaria elimination, interventions will need to target high burden areas to further reduce transmission. Current tools to monitor and report disease burden lack the capacity to continuously detect fine-scale spatial and temporal variations of disease distribution exhibited by malaria. These tools use random sampling techniques that are inefficient for capturing underlying heterogeneity while health facility data in resource-limited settings are inaccurate. Continuous community surveys of malaria burden provide real-time results of local spatio-temporal variation. Adaptive geostatistical design (AGD) improves prediction of outcome of interest compared to current random sampling techniques. We present findings of continuous malaria prevalence surveys using an adaptive sampling design. METHODS: We conducted repeated cross sectional surveys guided by an adaptive sampling design to monitor the prevalence of malaria parasitaemia and anaemia in children below five years old in the communities living around Majete Wildlife Reserve in Chikwawa district, Southern Malawi. AGD sampling uses previously collected data to sample new locations of high prediction variance or, where prediction exceeds a set threshold. We fitted a geostatistical model to predict malaria prevalence in the area. FINDINGS: We conducted five rounds of sampling, and tested 876 children aged 6-59 months from 1377 households over a 12-month period. Malaria prevalence prediction maps showed spatial heterogeneity and presence of hotspots-where predicted malaria prevalence was above 30%; predictors of malaria included age, socio-economic status and ownership of insecticide-treated mosquito nets. CONCLUSIONS: Continuous malaria prevalence surveys using adaptive sampling increased malaria prevalence prediction accuracy. Results from the surveys were readily available after data collection. The tool can assist local managers to target malaria control interventions in areas with the greatest health impact and is ready for assessment in other diseases.