33 research outputs found
Evolutionary Epidemiology of Drug-Resistance in Space
The spread of drug-resistant parasites erodes the efficacy of therapeutic
treatments against many infectious diseases and is a major threat of the 21st
century. The evolution of drug-resistance depends, among other things, on how
the treatments are administered at the population level. “Resistance
management” consists of finding optimal treatment strategies that both
reduce the consequence of an infection at the individual host level, and limit
the spread of drug-resistance in the pathogen population. Several studies have
focused on the effect of mixing different treatments, or of alternating them in
time. Here, we analyze another strategy, where the use of the drug varies
spatially: there are places where no one receives any treatment. We find that
such a spatial heterogeneity can totally prevent the rise of drug-resistance,
provided that the size of treated patches is below a critical threshold. The
range of parasite dispersal, the relative costs and benefits of being
drug-resistant compared to being drug-sensitive, and the duration of an
infection with drug-resistant parasites are the main factors determining the
value of this threshold. Our analysis thus provides some general guidance
regarding the optimal spatial use of drugs to prevent or limit the evolution of
drug-resistance
A Two-Locus Model of the Evolution of Insecticide Resistance to Inform and Optimise Public Health Insecticide Deployment Strategies
We develop a flexible, two-locus model for the spread of insecticide resistance applicable to mosquito species that transmit human diseases such as malaria. The model allows differential exposure of males and females, allows them to encounter high or low concentrations of insecticide, and allows selection pressures and dominance values to differ depending on the concentration of insecticide encountered. We demonstrate its application by investigating the relative merits of sequential use of insecticides versus their deployment as a mixture to minimise the spread of resistance. We recover previously published results as subsets of this model and conduct a sensitivity analysis over an extensive parameter space to identify what circumstances favour mixtures over sequences. Both strategies lasted more than 500 mosquito generations (or about 40 years) in 24% of runs, while in those runs where resistance had spread to high levels by 500 generations, 56% favoured sequential use and 44% favoured mixtures. Mixtures are favoured when insecticide effectiveness (their ability to kill homozygous susceptible mosquitoes) is high and exposure (the proportion of mosquitoes that encounter the insecticide) is low. If insecticides do not reliably kill homozygous sensitive genotypes, it is likely that sequential deployment will be a more robust strategy. Resistance to an insecticide always spreads slower if that insecticide is used in a mixture although this may be insufficient to outperform sequential use: for example, a mixture may last 5 years while the two insecticides deployed individually may last 3 and 4 years giving an overall ‘lifespan’ of 7 years for sequential use. We emphasise that this paper is primarily about designing and implementing a flexible modelling strategy to investigate the spread of insecticide resistance in vector populations and demonstrate how our model can identify vector control strategies most likely to minimise the spread of insecticide resistance