In the context of VMI, efforts are ongoing to use simulations of malaria transmission to address and evaluate control options in Africa. An individual-based Monte-Carlo simulation model for malaria transmission has been developed to incorporate a suite of current tools and to explore a range of intervention packages. Information on the three principal vector species, the human transmission cycle and parasite prevalence data has been incorporated.
Using these models, the effect of the switch to artemisinin-combination therapy (ACT) and increasing coverage of long-lasting insecticide treated nets (LLIN) from 2000 onwards was studied. In addition, the impact on transmission of continued roll-out of LLINs, additional rounds of indoor residual spraying (IRS), mass screening and treatment (MSAT) and a future RTS’S/AS01 vaccine in six representative settings with varying transmission intensity was assessed.
The model has also been implemented spatially at a continental scale for Africa. At present the model uses Malaria Atlas Project (MAP) parasite prevalence estimates to determine transmission intensity at each location. We are currently analyzing and fitting a range of extended models incorporating climate impact on larval and vector developmental stages to parasite prevalence data from the MARA database which is openly accessible.
Mass treatment as a means to reducing malaria transmission was largely discontinued after the first Global Malaria Eradication Programme but is currently being reconsidered by several regional control programmes. In the past it has shown great variation in impact in different settings. Over the past year, we have developed both simple analytic tools and a range of transmission models to explore both the short and long term impact of possible mass treatment strategies and to relate these to past mass treatment outcomes.
Immunity to severe disease is known to develop with repeat infections of Plasmodium falciparum. We have extended a previous model to stratify by the symptoms of severe disease, namely cerebral malaria, malarial anemia and respiratory distress syndrome, and to incorporate outcomes (death or recovery). The development of immunity to these different disease outcomes is explored using data from severe malarial cases in children under 15 from a range of transmission settings in Northern Tanzania.
Further models are being developed that estimate the dynamics of malaria transmission that could be expected in various vaccination strategy, including CSP based vaccines that include a TRAP component (such as RTS,S). We have also considered the impact of heterogeneity in exposure and in vaccine response on measures of vaccine efficacy that would be derived from a Phase II trial. Heterogeneity in exposure and vaccine response leads to a smaller proportion of trial participants becoming infected than one would expect in a homogeneous setting. This causes estimates of vaccine efficacy from clinical trials to be underestimated if transmission heterogeneity is ignored, and overestimated if heterogeneity in vaccine response is ignored. Waning of vaccine efficacy can bias estimates of vaccine efficacy in both directions. Appropriate methods to reduce these biases, therefore, need to be used to ensure accurate interpretation and comparability between trial sites of results from the upcoming Phase III clinical trials of RTS,S.