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Biomedical subjects

Sally Blower

Publications and source records attributed to Sally Blower.

15 recordsLinked to original sources
PubMed2007

The emergence of HIV transmitted resistance in Botswana: "when will the WHO detection threshold be exceeded?".

BACKGROUND: The Botswana antiretroviral program began in 2002 and currently treats 42,000 patients, with a goal of treating 85,000 by 2009. The World Health Organization (WHO) has begun to implement a surveillance system for detecting transmitted resistance that exceeds a threshold of 5%. However, the WHO has not determined when this threshold will be reached. Here we model the Botswana government's treatment plan and predict, to 2009, the likely stochastic evolution of transmitted resistance. METHODS: We developed a model of the stochastic evolution of drug-resistant strains and formulated a birth-death Master equation. We analyzed this equation to obtain an analytical solution of the probabilistic evolutionary trajectory for transmitted resistance, and used treatment and demographic data from Botswana. We determined the temporal dynamics of transmitted resistance as a function of: (i) the transmissibility (i.e., fitness) of the drug-resistant strains that may evolve and (ii) the rate of acquired resistance. RESULTS: Transmitted resistance in Botswana will be unlikely to exceed the WHO's threshold by 2009 even if the rate of acquired resistance is high and the strains that evolve are half as fit as the wild-type strains. However, we also found that transmission of drug-resistant strains in Botswana could increase to approximately 15% by 2009 if the drug-resistant strains that evolve are as fit as the wild-type strains. CONCLUSIONS: Transmitted resistance will only be detected by the WHO (by 2009) if the strains that evolve are extremely fit and acquired resistance is high. Initially after a treatment program is begun a threshold lower than 5% should be used; and we advise that predictions should be made before setting a threshold. Our results indicate that it may be several years before the WHO's surveillance system is likely to detect transmitted resistance in other resource-poor countries that have significantly less ambitious treatment programs than Botswana.

Anti-HIV Agents↗
PubMed2006

Role of parametric resonance in virological failure during HIV treatment interruption therapy.

We present a novel hypothesis that could explain virological failure to structured treatment interruptions (STI). We analysed a classic mathematical model of HIV within-host viral dynamics and found that non-linear parametric resonance occurs when STI are added to the model; resonance is observed as virological failure. We simulated clinical trial data and calculated patient-specific resonant spectra. We gained two important insights. First, within an STI trial, patients who begin with similar viral loads can be expected to show very different virological responses as a result of resonance. Second, and more importantly, virological failure is not simply due to STI or patients' characteristics; instead it is the result of complex interaction between STI and the patient's viral dynamics. Hence, our analyses show that no universal regimen with periodic interruptions will be effective for all patients.

CD4 Lymphocyte Count↗
PubMed2005

Linking population-level models with growing networks: a class of epidemic models.

We introduce a class of growing network models that are directly applicable to epidemiology. We show how to construct a growing network model (individual-level model) that generates the same epidemic-level outcomes as a population-level ordinary differential equation (ODE) model. For concreteness, we analyze the susceptible-infected (SI) ODE model of disease invasion. First, we give an illustrative example of a growing network whose population-level variables are compatible with those of this ODE model. Second, we demonstrate that a growing network model can be found that is equivalent to the Crump-Mode-Jagers (CMJ) continuous-time branching process of the SI ODE model of disease invasion. We discuss the computational advantages that our growing network model has over the CMJ branching process.

Animals↗
PubMed2005

Predicting the potential individual- and population-level effects of imperfect herpes simplex virus type 2 vaccines.

BACKGROUND: The seroprevalence of herpes simplex virus (HSV) type 2 in the United States has increased dramatically since the 1970s. Vaccines are being developed to control the epidemic. We determined the potential public health impact that imperfect, preexposure HSV-2 vaccines could have on reducing the incidence of infection. METHODS: We modeled the future impact of preexposure vaccines with both prophylactic and therapeutic properties. We predicted the individual-level (cumulative number of new infections prevented per 1000 vaccinated individuals) and population-level (cumulative percentage reduction in new infections) impact. RESULTS: We show that the percentage reduction in incidence of infection would be relatively modest. However, HSV-2 incidence rates are extremely high; thus, we calculate that even imperfect vaccines would prevent >1 million infections in the United States within a decade after introduction. We found that vaccines would prevent 3 times as many infections per vaccinated person in a high-prevalence epidemic than in a moderate-prevalence epidemic. We also identified the vaccine characteristics that have the greatest impact on reducing the incidence of infection. We determined that vaccine take and degree of protection against infection are equally important, whereas therapeutic characteristics are unimportant. CONCLUSIONS: Designing preexposure HSV-2 vaccines with therapeutic characteristics will have little impact on reducing the incidence of infection. HSV-2 vaccines will have a substantially greater public health impact in developing than in developed countries.

Herpes Genitalis↗
PubMed2005

The antiretroviral rollout and drug-resistant HIV in Africa: insights from empirical data and theoretical models.

The U.S. Government has pledged to spend $15 billion in Africa and the Caribbean on AIDS. A central focus of this plan is to provide antiretroviral treatment (ART) to millions. Here, we evaluate whether the plan to rollout ART in Africa is likely to generate an epidemic of drug-resistant strains of HIV. We review what has occurred as a result of high usage of ART in developed countries in terms of changes in risky behavior, and the emergence and transmission of drug-resistant HIV. We also review how mathematical models have been used to predict the evolution of drug-resistant HIV epidemics. We then show how models can be used to predict the likely impact of the ART rollout on the evolution of drug-resistant HIV in Africa. At currently planned levels of treatment coverage, we predict that (over the next decade) in Africa: (i) the impact of ART on reducing HIV transmission (and prevalence) is likely to be undetectable (unless accompanied by substantial changes in behavior), (ii) the transmission rate of drug-resistant HIV will be below the WHO surveillance threshold of 5%, and (ii) the majority of cases of drug-resistant HIV that will occur will be due to acquired (and not transmitted) resistance. For the next decade, large-scale surveillance for detecting transmitted resistance in Africa is unnecessary. Instead, we recommend that patients should be closely monitored for acquired resistance, and sentinel surveillance (in a few urban centers) should be used to monitor transmitted resistance.

Africa↗
PubMed2005

A queueing model for chronic recurrent conditions under panel observation.

In many chronic conditions, subjects alternate between an active and an inactive state, and sojourns into the active state may involve multiple lesions, infections, or other recurrences with different times of onset and resolution. We present a biologically interpretable model of such chronic recurrent conditions based on a queueing process. The model has a birth-death process describing recurrences and a semi-Markov process describing the alternation between active and inactive states, and can be fit to panel data that provide only a binary assessment of the active or inactive state at a series of discrete time points using a hidden Markov approach. We accommodate individual heterogeneity and covariates using a random effects model, and simulate the posterior distribution of unknowns using a Markov chain Monte Carlo algorithm. Application to a clinical trial of genital herpes shows how the method can characterize the biology of the disease and estimate treatment efficacy.

Algorithms↗
PubMed2004

Calculating the contribution of herpes simplex virus type 2 epidemics to increasing HIV incidence: treatment implications.

Herpes simplex virus type 2 (HSV-2) is the most prevalent sexually transmitted pathogen worldwide. There is considerable biological and epidemiological evidence that HSV-2 infection increases the risk of acquiring HIV infection and may also increase the risk of transmitting HIV. Here, we use a mathematical model to predict the effect of a high-prevalence HSV-2 epidemic on HIV incidence. Our results show that HSV-2 epidemics can more than double the peak HIV incidence; that the biological heterogeneity in susceptibility and transmission induced by an HSV-2 epidemic causes HIV incidence to rise, fall, and then rise again; and that HSV-2 epidemics concentrate HIV epidemics, creating a "core group" of HIV transmitters. Our modeling results imply that findings from HSV-2 intervention trials aimed at reduction of HIV incidence will be variable and that positive findings will be obtained only from trials in communities in which HIV incidence is steeply rising.

Disease Susceptibility↗
PubMed2004

Targeting virological core groups: a new paradigm for controlling herpes simplex virus type 2 epidemics.

BACKGROUND: Classic modeling of sexually transmitted diseases has focused on modeling behavioral heterogeneity and designing epidemic control strategies targeted at behavioral core groups. METHODS: We analyzed a new mathematical model of herpes simplex virus type 2 (HSV-2) epidemics that includes virological core groups (i.e., groups of individuals with high rates of viral reactivation) and suggest a new paradigm for epidemic control. We used our model, in conjunction with virological data, to determine the potential role of virological core groups in contributing to transmission and the effect that daily antiviral therapy (DAT) could have on reducing transmission if virological core groups were targeted. RESULTS: We estimated that a virological core group (11% of infected individuals) can cause a disproportionately large percentage (44%) of new infections and that a median of only 6.4 person-years of DAT would be necessary to prevent 1 HSV-2 infection. We determined that relatively few individuals would need to receive DAT to substantially reduce the incidence of HSV-2 infection. CONCLUSION: Identifying and targeting individuals in the virological core group could be an effective and practical public health strategy for reducing transmission. Treating individuals who are high-frequency viral shedders should be evaluated as a strategy for reducing HSV-2 transmission.

Antiviral Agents↗
PubMed2004

Potential public health impact of new tuberculosis vaccines.

Developing effective tuberculosis (TB) vaccines is a high priority. We use mathematical models to predict the potential public health impact of new TB vaccines in high-incidence countries. We show that preexposure vaccines would be almost twice as effective as postexposure vaccines in reducing the number of new infections. Postexposure vaccines would initially have a substantially greater impact, compared to preexposure vaccines, on reducing the number of new cases of disease. However, the effectiveness of postexposure vaccines would diminish over time, whereas the effectiveness of preexposure vaccines would increase. Thus, after 20 to 30 years, post- or preexposure vaccination campaigns would be almost equally effective in terms of cumulative TB cases prevented. Even widely deployed and highly effective (50%-90% efficacy) pre- or postexposure vaccines would only be able to reduce the number of TB cases by one third. We discuss the health policy implications of our analyses.

Disease Outbreaks↗
PubMed2004

Modelling the genital herpes epidemic.

Mathematical models are useful tools for summarizing and testing current knowledge about a system and predicting trends. Models have shown that medical and behavioural changes can substantially affect herpes simplex virus type 2 (HSV-2) transmission and can be used to develop rational epidemic control policies. The spread of the genital herpes epidemic and the potential impact of HSV antiviral treatment in the immunocompetent population have been addressed by four models. HSV drug resistance to antiviral drugs is predicted to be minimal. Assuming that drug-resistant mutants are attenuated both in infectivity and reactivity, one model predicted that even after 25 years, only 5 in 10,000 individuals will shed drug-resistant virus, even if rates of usage of antivirals are high. The models show that increased usage of episodic antiviral therapy will be beneficial in reducing the herpes epidemic. Results also show that the transmission rate can be reduced by preventing infection (safer sex), reduced time spent in non-monogamous relationships or the advent of effective therapeutic HSV vaccines. One model has indicated that suppressive therapy will have only a minimal impact on HSV prevalence; however, the results of this modelling study are limited as it assumed that suppressive therapy would only be given to incident infections. More recent research using a model based upon virological core groups (and treating both incident and prevalent infections) shows that suppressive therapy could cause a substantial reduction in HSV-2 incidence rates. Current modelling is also focused on modelling how HSV-2 antiviral treatment will impact the HIV epidemic.

Herpes Genitalis↗
PubMed2003

Predicting the impact of antiretrovirals in resource-poor settings: preventing HIV infections whilst controlling drug resistance.

There is currently an opportunity to carefully plan the implementation of antiretroviral (ARV) therapy in the developing world. Here, we use mathematical models to predict the potential impact that low to moderate usage rates of ARVs might have in developing countries. We use our models to predict the relationship between the specific usage rate of ARVs (in terms of the percentage of those infected with HIV who receive such treatment) and: (i) the prevalence of drug-resistant HIV that will arise, (ii) the future transmission rate of drug-resistant strains of HIV, and (iii) the cumulative number of HIV infections that will be prevented through more widespread use of ARVs. We also review the current state of HIV/AIDS treatment programs in resource-poor settings and identify the essential elements of a successful treatment project, noting that one key element is integration with a strong prevention program. We apply both program experience from Haiti and Brazil and the insights gleaned from our modeling to address the emerging debate regarding the increased availability of ARVs in developing countries. Finally, we show how mathematical models can be used as tools for designing robust health policies for implementing ARVs in developing countries. Our results demonstrate that designing optimal ARV-based strategies to control HIV epidemics is extremely complex, as increasing ARV usage has both beneficial and detrimental epidemic-level effects. Control strategies should be based upon the overall impact on the epidemic and not simply upon the impact ARVs will have on the transmission and/or prevalence of ARV-resistant strains.

Anti-Retroviral Agents↗
PubMed2002

What can modeling tell us about the threat of antiviral drug resistance?

PURPOSE OF REVIEW: Currently, antiviral resistance is a major public health concern. Here, we review how mathematical models have been used to provide insights into the emerging threat of antiviral resistance. We focus mainly on the problem of drug resistance to HIV. RECENT FINDINGS: We review how antiviral models of HIV have been used: (1) to understand the evolution of an epidemic of drug-resistant HIV, (2) to predict the incidence and prevalence of drug-resistant HIV, (3) to conduct biological 'cost-benefit' analyses, and(4) to make public health policy recommendations. We also briefly discuss antiviral resistance for HSV-2 and influenza. Recent studies indicate that for HSV-2 and influenza drug resistance is not likely to become a major public health problem. However, for HIV the situation is very different. Results from several studies predict that a high prevalence of drug-resistant HIV will be an inevitable consequence of more widespread usage of antiretroviral therapies (ART). However more widespread usage of ART will save a substantial number of lives, and could even result in epidemic eradication. SUMMARY: Models have been used in many ways to provide insight into the emerging threat of antiviral resistance, particularly for HIV. At this stage in the HIV epidemic the most important future use of models may be that they will force the goals of public health policies to be clearly defined. Once goals have been defined it can then be decided whether a high prevalence of drug-resistant HIV is a threat or simply a justified means to an end.

Anti-HIV Agents↗