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      HIV Drug-resistant Strains as Epidemiologic Sentinels

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          Abstract

          The decrease in the proportion of drug resistance among newly infected HIV-1 patients may signal a worsening of the epidemic.

          Abstract

          Observed declines in drug resistance to nucleoside reverse transcriptase inhibitors among persons recently infected with HIV-1 in monitored subpopulations can be interpreted as a positive sign and lead public health officials to decrease efforts towards HIV prevention. By means of a mathematical model, we identified 3 processes that can account for the observed decline: increase in high-risk behavior, decrease in proportion of acutely infected persons whose conditions are treated, and change in treatment efficacy. These processes, singly or in combination, can lead to increases or decreases in disease and drug-resistance prevalence in the general population. We discuss the most appropriate public health response under each scenario and emphasize how further data collection and analyses are required to more reliably evaluate the observed time trends and the relative importance of forces shaping the epidemic. Our study highlights how drug resistance markers can be used as epidemiologic sentinels to devise public health solutions.

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          Most cited references36

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          Time trends in primary HIV-1 drug resistance among recently infected persons.

          Transmission of multiclass drug-resistant human immunodeficiency virus type 1 (HIV-1) may increase with wider use of antiretroviral therapy. To determine trends in prevalence of HIV-1 drug resistance among recently infected individuals in a geographic area with a high penetration of antiviral treatment. Consecutive case series of 225 patients referred to a San Francisco, Calif, hospital with recent HIV-1 infection from June 1996 through June 2001. Time trends in the prevalence of genotypic and phenotypic primary drug resistance. Mutations associated with resistance to nonnucleoside reverse transcriptase inhibitors (NNRTIs) steadily increased from 0% in 1996-1997 to 12 (13.2%) in 2000-2001 (P =.01). There was 1 mutation associated with protease inhibitor resistance in 1996-1997 (2.5%) and there were 7 (7.7%) in 2000-2001 (P =.25). Genotypic resistance to nucleoside reverse transcriptase inhibitors (NRTIs) initially decreased and then returned to prior levels (P =.007 for test of homogeneity). Genotypic resistance to 2 or more classes of drugs increased from 1 (2.5%) to 12 (13.2%) (P =.004), but only 1 infection (1.2%) in the latter period was resistant to all 3 classes of agents (P =.58). Primary phenotypic resistance decreased for NRTIs from 21% to 6.2% (P =.03) and increased for NNRTIs from 0 to 8 (9.9%) (P =.02). Phenotypic resistance increased for protease inhibitors from 2.6% to 6.2% (P =.32). Median time to virologic suppression (<500 copies/mL) during therapy was 12 weeks for patients with genotypic evidence of resistance compared with 5 weeks for patients with drug-sensitive infections (P =.02). The frequency of primary resistance to NNRTIs is increasing, although resistance to all available classes of antiretroviral therapy remains rare. Genotypic resistance testing in recently infected persons predicts time to viral suppression during therapy.
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            Could widespread use of combination antiretroviral therapy eradicate HIV epidemics?

            Current combination antiretroviral therapies (ARV) are widely used to treat HIV. However drug-resistant strains of HIV have quickly evolved, and the level of risky behaviour has increased in certain communities. Hence, currently the overall impact that ARV will have on HIV epidemics remains unclear. We have used a mathematical model to predict whether the current therapies: are reducing the severity of HIV epidemics, and could even lead to eradication of a high-prevalence (30%) epidemic. We quantified the epidemic-level impact of ARV on reducing epidemic severity by deriving the basic reproduction number (R(0)(ARV)). R(0)(ARV) specifies the average number of new infections that one HIV case generates during his lifetime when ARV is available and ARV-resistant strains can evolve and be transmitted; if R(0)(ARV) is less than one epidemic eradication is possible. We estimated for the HIV epidemic in the San Francisco gay community (using uncertainty analysis), the present day value of R(0)(ARV), and the probability of epidemic eradication. We assumed a high usage of ARV and three behavioural assumptions: that risky sex would (1) decrease, (2) remain stable, or (3) increase. Our estimated values of R(0)(ARV) (median and interquartile range [IQR]) were: 0.90 (0.85-0.96) if risky sex decreases, 1.0 (0.94-1.05) if risky sex remains stable, and 1.16 (1.05-1.28) if risky sex increases. R(0)(ARV) decreased as the fraction of cases receiving treatment increased. The probability of epidemic eradication is high (p=0.85) if risky sex decreases, moderate (p=0.5) if levels of risky sex remain stable, and low (p=0.13) if risky sex increases. We conclude that ARV can function as an effective HIV-prevention tool, even with high levels of drug resistance and risky sex. Furthermore, even a high-prevalence HIV epidemic could be eradicated using current ARV.
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              Modelling the effect of combination antiretroviral treatments on HIV incidence.

              To assess the competing effects on HIV incidence in homosexual men of the decreased infectiousness of men with HIV receiving effective combination antiretroviral treatments and homosexual men engaging in unprotected anal intercourse with increased numbers of partners (levels of unsafe sex). A mathematical model of HIV transmission in homosexual men was developed, based on the HIV epidemic in Australia in 1996, when effective antiretroviral treatments first became widely available. Uncertainties in parameters were modelled using 1000 simulations. The effect of treatments on decreasing infectiousness was randomly sampled with a median 10-fold decrease in infectiousness (range 100-fold to no decrease). Levels of unsafe sex were randomly sampled with a median 50% increase in unsafe sex (range 100% to no increase). The percentage change in HIV incidence after one year was obtained by comparison with a null model in which there was no decrease in infectiousness as a result of treatment and no change in unsafe sex. Results of the models suggested that whereas increased levels of unsafe sex were linearly associated with increases in HIV incidence, decreases in infectiousness because of treatments were non-linearly associated with decreases in HIV incidence. An assessment of the competing effects suggested that decreases in infectiousness of two-, five-, and 10-fold would be counterbalanced by increases in unsafe sex of approximately 40, 60 and 70%, respectively. These models suggest that apparently large decreases in infectiousness as a result of treatment could be counterbalanced in terms of new HIV infections by much more modest increases in unsafe sex.
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                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                February 2006
                : 12
                : 2
                : 191-197
                Affiliations
                [* ]University of California, Berkeley, California, USA;
                []Gladstone Institute of Virology and Immunology, San Francisco, California, USA;
                []California Department of Health Services, Berkeley, California, USA
                Author notes
                Address for correspondence: María S. Sánchez, Department. of Environmental Sciences, Policy and Management, University of California, Berkeley, CA 94720, USA; fax: 510-642-7428; email: msanchez@ 123456nature.berkeley.edu
                Article
                05-0321
                10.3201/eid1202.050321
                3373094
                16494741
                b48b1baf-31a1-4273-b462-bddd39f93770
                History
                Categories
                Perspective
                Perspective

                Infectious disease & Microbiology
                acute infection,drug resistance,epidemiology,hiv,infectious disease,mathematical model,population dynamics,prevalence,primary infection,transmission

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