| A micro simulation model for the development of drug resistance in Plasmodium falciparum has been developed which combines the effects of transmission dynamics and parasite genetics. This discrete time model provides a conceptual framework for examining the inter-relationship among important factors: transmission rates, parasite genetics, host immunity, drug dosage regimens, drug action, environmental factors and untreated fraction of the population. The model may be used as a planning tool for the development of malaria control programs and will provide a coherent and accessible method for assessing the impact of various control strategies.; The model was validated using data from Clyde's study of pyrimethamine resistance in Tanzania. Field results were reproduced when parameters for biting rate, dosage regimens, length of drug activity, variable host immunity by age and initial parasite rates, were set to the conditions described in the report.; Methods of quantitative genetics are used to determine the impact of drugs whose genetic effects may involve multiple loci. Genotype frequencies of parasites are accounted for in terms of normal distributions of log tolerance dose to anti-malarial drug.; Program output includes a daily count of hosts by infection status, mean and variance of genotypes and the percentage of resistant parasites.; Qualitative conclusions may be drawn from the simulation relating to maximizing the time of drug effectiveness. Incomplete drug coverage and lowering of transmission rates minimize the emergence of resistant genotypes.; The ethical question raised for the clinician is that what may be the best treatment for an individual, a high dose aimed at eradication of parasites completely, may have the worst impact on the community in terms of accelerating the rate of take-over by resistant strains. |
