John I. Githure

The ecology of malaria vectors particularly in semi-arid areas of Africa is poorly understood. Accurate knowledge on this subject will boost current efforts to reduce the burden of malaria in sub-Saharan Africa. The objective of this study was to describe the dynamics of malaria transmission in two model semi-arid sites (Kamarimar and Tirion) in Baringo in Kenya.

Pre-adult stages of malaria vectors in semi-arid areas are confronted with highly variable and challenging climatic conditions. The objective of this study was to determine which larval habitat types are most productive in terms of larval densities in the dry and wet seasons within semi-arid environments, and how vector species productivity is partitioned over time.

Reliable models of the transmission intensity of malaria, based on vector mosquito aquatic habitat larval productivity, are urgently needed, especially in endemic areas of Sub-Saharan Africa (SSA). Such models are fundamental for estimating the scale of the problem, and, hence, the resources needed to combat malaria in urban environments. These models also provide benchmarks for assessing the progress of control and indicate the geographical regions that should be prioritized. In this research, individual urban aquatic habitats of Anopheles gambiae s.l., a major malaria vector in SSA, were examined in terms of their spatial covariations by modelling ecologically sampled predictor variables within a Bayesian framework. Field sampling was conducted in two urban environments in Kenya, from July 2005 to December 2006. QuickBird satellite data, encompassing visible and near-infrared (NIR) bands, were selected to synthesize images of An. gambiae s.l. aquatic habitats. Statistical Analysis Software (SAS) was used to explore univariate statistics, correlations and distributions, and to perform Poisson regression analyses. These preliminary tests showed good type I error control mechanisms and precise parameter estimates. The model coefficients were then used to define expectations for prior distributions in a Markov chain Monte Carlo (MCMC) analysis. By specifying coefficient estimates in a Bayesian framework, depth of habitat was found to be a significant predictor, positively associated with urban An. gambiae s.l. aquatic habitats. There was no significant autocorrelation present in either the residual error or the predictor variable depth of habitat.

The diversity and abundance of Anopheles larvae has significant influence on the resulting adult mosquito population and hence the dynamics of malaria transmission. Studies were conducted to examine larval habitat dynamics and ecological factors affecting survivorship of aquatic stages of malaria vectors in three agro-ecological settings in Mwea, Kenya.

Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature.

Use of insecticide-treated nets (ITNs) continues to offer potential strategy for malaria prevention in endemic areas. However their effectiveness, sustainability and massive scale up remain a factor of socio-economic and cultural variables of the local community which are indispensable during design and implementation stages.

Integrated vector management (IVM) is defined as "a rational decision-making process for the optimal use of resources for vector control" and includes five key elements: 1) evidence-based decision-making, 2) integrated approaches 3), collaboration within the health sector and with other sectors, 4) advocacy, social mobilization, and legislation, and 5) capacity-building. In 2004, the WHO adopted IVM globally for the control of all vector-borne diseases. Important recent progress has been made in developing and promoting IVM for national malaria control programmes in Africa at a time when successful malaria control programmes are scaling-up with insecticide-treated nets (ITN) and/or indoor residual spraying (IRS) coverage. While interventions using only ITNs and/or IRS successfully reduce transmission intensity and the burden of malaria in many situations, it is not clear if these interventions alone will achieve those critical low levels that result in malaria elimination. Despite the successful employment of comprehensive integrated malaria control programmes, further strengthening of vector control components through IVM is relevant, especially during the "end-game" where control is successful and further efforts are required to go from low transmission situations to sustained local and country-wide malaria elimination. To meet this need and to ensure sustainability of control efforts, malaria control programmes should strengthen their capacity to use data for decision-making with respect to evaluation of current vector control programmes, employment of additional vector control tools in conjunction with ITN/IRS tactics, case-detection and treatment strategies, and determine how much and what types of vector control and interdisciplinary input are required to achieve malaria elimination. Similarly, on a global scale, there is a need for continued research to identify and evaluate new tools for vector control that can be integrated with existing biomedical strategies within national malaria control programmes. This review provides an overview of how IVM programmes are being implemented, and provides recommendations for further development of IVM to meet the goals of national malaria control programmes in Africa.

Malaria transmission in most agricultural ecosystems is complex and hence the need for developing a holistic malaria control strategy with adequate consideration of socio-economic factors driving transmission at community level. A cross-sectional household survey was conducted in an irrigated ecosystem with the aim of investigating vector control practices applied and factors affecting their application both at household and community level.

Studies were conducted between April 2004 and February 2006 to determine the blood-feeding pattern of Anopheles mosquitoes in Mwea Kenya.