title: Epidemiological models for the spread of anti-malarial resistance.
abstract: BACKGROUND
  The spread of drug resistance is making malaria control increasingly difficult. Mathematical models for the transmission dynamics of drug sensitive and resistant strains can be a useful tool to help to understand the factors that influence the spread of drug resistance, and they can therefore help in the design of rational strategies for the control of drug resistance.
  
  
  METHODS
  We present an epidemiological framework to investigate the spread of anti-malarial resistance. Several mathematical models, based on the familiar Macdonald-Ross model of malaria transmission, enable us to examine the processes and parameters that are critical in determining the spread of resistance.
  
  
  RESULTS
  In our simplest model, resistance does not spread if the fraction of infected individuals treated is less than a threshold value; if drug treatment exceeds this threshold, resistance will eventually become fixed in the population. The threshold value is determined only by the rates of infection and the infectious periods of resistant and sensitive parasites in untreated and treated hosts, whereas the intensity of transmission has no influence on the threshold value. In more complex models, where hosts can be infected by multiple parasite strains or where treatment varies spatially, resistance is generally not fixed, but rather some level of sensitivity is often maintained in the population.
  
  
  CONCLUSIONS
  The models developed in this paper are a first step in understanding the epidemiology of anti-malarial resistance and evaluating strategies to reduce the spread of resistance. However, specific recommendations for the management of resistance need to wait until we have more data on the critical parameters underlying the spread of resistance: drug use, spatial variability of treatment and parasite migration among areas, and perhaps most importantly, cost of resistance.
authors.affiliation: Laboratoire de Parasitologie Evolutive, Université P, & M, Curie, CNRS UMR 7103, 7 quai St, Bernard CC237, 75252 Paris, France. jkoella@snv.jussieu.fr
authors.forename: J C
authors.initials: JC
authors.lastname: Koella
authors.forename: R
authors.initials: R
authors.lastname: Antia
mesh_terms: D000483:Alleles; D000818:Animals; D000852:Anopheles / Q000469:parasitology; D000962:Antimalarials / Q000378:metabolism* / Q000627:therapeutic use; D018432:Drug Resistance, Multiple / Q000235:genetics; D017125:Genes, Protozoan / Q000235:genetics; D005828:Genetics, Population; D006801:Humans; D008288:Malaria / Q000188:drug therapy / Q000453:epidemiology* / Q000276:immunology / Q000635:transmission; D008954:Models, Biological; D008957:Models, Genetic; D010961:Plasmodium / Q000187:drug effects / Q000235:genetics / Q000276:immunology / Q000472:pathogenicity
chemical_list: D000962:Antimalarials