| Literature DB >> 12659657 |
Hayley B Gershengorn1, Graham Darby, Sally M Blower.
Abstract
BACKGROUND: Mathematical models can be used to predict the emergence and transmission of antiviral resistance. Previously it has been predicted that high usage of antivirals (in immunocompetent populations) to treat Herpes Simplex Virus type 2 (HSV-2) would only lead to fairly low levels of antiviral resistance. The HSV-2 predictions were based upon the assumption that drug-resistant strains of HSV-2 would be less infectious than drug-sensitive strains but that the drug-resistant strains would not be impaired in their ability to reactivate. Recent data suggest that some drug-resistant strains of HSV-2 are likely to be impaired in their ability to reactivate.Entities:
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Year: 2003 PMID: 12659657 PMCID: PMC154092 DOI: 10.1186/1471-2334-3-1
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Figure 1Biological attributes of the 1,000 strains of drug-resistant HSV-2 that were constructed using sampling constraints and LHS. Strains were generated to produce a strong positive correlation between the number of infectious episodes (NER) and the transmissibility (βR) of the drug-resistant strain. The correlation coefficient (r) of this data set is 0.83.
Figure 2Results of the uncertainty analyses using a previously published transmission model [1,2]. Blue data are predictions published previously (and described in detail in reference 1) assuming that viral attenuation in drug-resistant strains reduces only infectivity (in comparison with drug-sensitive strains). Red data are the new predictions assuming that viral attenuation in the drug-resistant strains reduces both infectivity and reactivation ability. (A) The median value of the 1,000 simulations in the uncertainty analysis is plotted. The prevalence of drug-resistant infectiousness (i.e., the prevalence of the individuals who are shedding drug-resistant HSV-2) is shown. (B) Predictions for the Treatment Evaluation Criterion (TEC(t)) is shown; the median value of the 1,000 simulations in the uncertainty analysis is plotted.