inst/shiny/coverage1/about.md

A simple interactive graphical model to demonstrate how different interventions can be combined to target mosquito vectors exhibiting different behaviours, the distribution of which can change in response to those interventions.

This is a very simple model based on arithmetic and not directly derived from data (Kiware et al. 2012, Killeen et al. 2014). It is based on simple proportions and that interventions target vectors exhibiting different behaviour. In this implementation one intervention (bed nets) is assumed to only target vectors feeding indoors on humans, while another (insecticide vapour emanators) targets only vectors feeding outdoors upon humans, while another (veterinary insecticides) targets only vectors feeding outdoors upon livestock.

Of course, real field settings will be more complex with vectors being able to evolve altered behavioural preferences, interventions targeting more than one of these blood sources , and there being more than one vector present. Nevertheless, the model demonstrates the broad principles of how interventions can be rationally targeted to well-matched mosquito behaviours, and can create new opportunities for complementary interventions, allowing users to investigate and explore for themselves. This simple model can easily be modified to address alternative baseline assumptions, and expanded to consider more complex vector systems.

The research behind this model is described in an accompanying submitted paper.

The code is hosted here : https://github.com/AndySouth/coverage

Andy South, Gerry F. Killeen, John M. Marshall, Samson S. Kiware, Prosper P. Chaki, Nicodem J. Govella and Lucy S. Tusting

Human & Cow Icons from phylopic.org

References

Killeen GF. Characterizing, controlling and eliminating residual malaria transmission. Malar J 2014;13:330.

Kiware SS, Chitnis N, Devine GJ, et al. Biologically meaningful coverage indicators for eliminating malaria transmission. Biol Lett 2012;8:874-77.



AndySouth/coverage documentation built on May 5, 2019, 6:01 a.m.