Anopheles – Open Malaria Warning

Yesterday an article by Lyons et al., “Stable and fluctuating temperature effects on the development rate and survival of two malaria vectors, Anopheles arabiensis and Anopheles funestus“, was published in Parasites & Vectors. This study is important to understand how climate change, changes in temperature between seasons, and from year-to-year influence the transmission of malaria. In this context it is interesting to see if the new data on Anopheles arabiensis alters the conclusion at which malaria is most efficiently transmitted. We refitted the egg-to-adult survival probability and mosquito development rate models described by Mordecai et al. with the data from the paper by Lyons et al., and calculated R0 according to temperature. While the old estimates for Anopheles gambiae s.s. suggested malaria is most efficiently transmitted at 25.6 C, the new data suggest malaria is most efficiently transmitted (by Anopheles arabiensis) at 25.7 C. The plot is showing transmission potential at the y-axis, and temperature in C at the x-axis. The red line is the estimate by Mordecai et al., while the black line is the estimate with the new data on Anopheles arabiensis.

A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. II. Validation of species distribution and seasonal variations

Background
The first part of this study aimed to develop a model for Anopheles gambiae s.l. with separate parametrization schemes for Anopheles gambiae s.s. and Anopheles arabiensis. The characterizations were constructed based on literature from the past decades. This part of the study is focusing on the model’s ability to separate the mean state of the two species of the An. gambiae complex in Africa. The model is also evaluated with respect to capturing the temporal variability of An. arabiensis in Ethiopia. Before conclusions and guidance based on models can be made, models need to be validated.

Methods
The model used in this paper is described in part one (Malaria Journal 2013, 12:28). For the validation of the model, a data base of 5,935 points on the presence of An. gambiae s.s. and An. arabiensis was constructed. An additional 992 points were collected on the presence An. gambiae s.l.. These data were used to assess if the model could recreate the spatial distribution of the two species. The dataset is made available in the public domain. This is followed by a case study from Madagascar where the model’s ability to recreate the relative fraction of each species is investigated. In the last section the model’s ability to reproduce the temporal variability of An. arabiensis in Ethiopia is tested. The model was compared with data from four papers, and one field survey covering two years.

Results
Overall, the model has a realistic representation of seasonal and year to year variability in mosquito densities in Ethiopia. The model is also able to describe the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. This implies this model can be used for seasonal and long term predictions of changes in the burden of malaria. Before models can be used to improving human health, or guide which interventions are to be applied where, there is a need to understand the system of interest. Validation is an important part of this process. It is also found that one of the main mechanisms separating An. gambiae s.s. and An. arabiensis is the availability of hosts; humans and cattle. Climate play a secondary, but still important, role.

Malaria Journal 2013, 12:78