Effects of antiviral usage on transmission dynamics of herpes simplex virus type 1 and on antiviral resistance: predictions of mathematical models

The basic reproductive number and particle-to-plaque ratio: comparison of these two parameters of viral infectivity

The COVID-19 pandemic has brought more widespread attention to the basic reproductive number (R_o), an epidemiologic measurement. A lesser-known measure of virologic infectivity is the particle-to-plaque ratio (P:PFU). We suggest that comparison between the two parameters may assist in better understanding viral transmission dynamics.

A perspective on antiviral resistance

More than 25 years after the licensure of aciclovir and then penciclovir, followed by their respective prodrugs valaciclovir and famciclovir, cases of clinically relevant resistance to these drugs in immunocompetent individuals remain very rare. The aim of this review is to focus on the mechanism of action of these anti HSV drugs and then briefly compare this favourable outcome with that of CMV, HIV, HBV and influenza. A central theme is that resistance is an epiphenomenon of failure to suppress virus replication, so that improved potency and selectivity should be prioritised when developing new drugs rather than activity against resistant strains per se.

Dynamic modeling of herpes simplex virus type-2 (HSV-2) transmission: issues in structural uncertainty

The sexually transmitted infection (STI) Herpes simplex virus type-2 (HSV-2) is of public health concern because it is a very common frequently unrecognized lifelong infection, which may facilitate HIV transmission. Within HIV/STI modeling, structural uncertainty has received less attention than parametric uncertainty. By merging the compartments of a "complex" model, a "simple" HSV-2 model is developed. Sexual interactions between female sex workers (FSWs) and clients are modeled using data from India. Latin Hypercube Sampling selects from parameter distributions and both models are run for each of the 10,000 parameter sets generated. Outputs are compared (except for 2,450 unrealistic simulations). The simple model is a good approximation to the complex model once the HSV-2 epidemic has reached 60% of the equilibrium prevalence (95% of the 7,550 runs produced <10% relative error). The simple model is a reduced version of the complex model that retains details implicitly. For late-stage epidemics, the simple model gives similar prevalence trends to the complex model. As HSV-2 epidemics in many populations are advanced, the simple model is accurate in most instances, although the complex model may be preferable for early epidemics. The analysis highlights the issue of structural uncertainty and the value of reducing complexity.

The role of compensatory mutations in the emergence of drug resistance

Pathogens that evolve resistance to drugs usually have reduced fitness. However, mutations that largely compensate for this reduction in fitness often arise. We investigate how these compensatory mutations affect population-wide resistance emergence as a function of drug treatment. Using a model of gonorrhea transmission dynamics, we obtain generally applicable, qualitative results that show how compensatory mutations lead to more likely and faster resistance emergence. We further show that resistance emergence depends on the level of drug use in a strongly nonlinear fashion. We also discuss what data need to be obtained to allow future quantitative predictions of resistance emergence.

Competition of pathogen strains leading to infection with variable infectivity and the effect of treatment

A model for the spread of two strains of a pathogen leading to an infection with variable infectivity is considered. The course of infection is described by two stages with different infectivity levels. The model is extended to account for treatment by including a third stage with different infectivity and survival for those treated. The contribution of each stage to incidence and prevalence is investigated and the effect of infectivity and survival on the basic reproduction ratio is examined. Standard equilibrium analysis is performed for both models, revealing that the successful strain is the one with highest reproduction ratio. If therapy, however, is more effective against the strain that wins in the absence of treatment and its reproduction ratio is sufficiently reduced, it might be outcompeted by the other strain after treatment becomes widely available. In this case, early introduction of treatment can prevent a major outbreak.

Modelling time–kill studies to discern the pharmacodynamics of meropenem

OBJECTIVES

Time-kill studies are commonly used in investigations of new antimicrobial agents. However, they typically provide descriptive information on pharmacodynamics. We developed a mathematical model to capture the relationship between microbial burden and antimicrobial agent concentrations.

METHODS

Time-kill studies were performed with 10(8) cfu/mL of Pseudomonas aeruginosa at baseline. Meropenem at 0, 0.25, 1, 4, 16 and 64 x MIC was used (MIC = 1 mg/L). Serial samples were obtained to quantify bacterial burden over 24 h. The data were analysed by a population analysis using the non-parametric adaptive grid program. The rate of change of bacteria over time was expressed as the difference between linear bacterial growth rate and sigmoidal kill rate. Regrowth was attributed to adaptation, which was explicitly modelled as increase in C(50k) (concentration to achieve 50% maximal kill rate), using a saturable function of selective pressure (both meropenem concentration and time).

RESULTS

The best-fit model consisted of eight parameters and the fit to the data was satisfactory. The r2 of maximum a-posteriori probability Bayesian predictions based on the mean parameter estimates was 0.984. Maximal killing rate at baseline was found to be 4.7 h(-1); C(90k) was achieved with meropenem at 5.0 mg/L. The model was validated by time-kill studies using 2x and 32x MIC of meropenem.

CONCLUSIONS

Our model reasonably described and predicted the time course of P. aeruginosa in time-kill studies, and provided quantitative information on the pharmacodynamics of meropenem. The structural model appeared robust and could be used to provide a realistic expectation of the killing performance of antimicrobial agents.

Inhibition of Cyclooxygenase 2 Synthesis SuppressesHerpes simplexVirus Type 1 Reactivation

Recurrent herpes virus infection, in which the virus reactivates from the nervous system and causes painful lesions in peripheral tissues, is a significant clinical problem. Our recent studies showing that the amount of cyclooxygenase 2 (COX-2) in the trigeminal ganglia of heat-stressed untreated mice is higher than the amount in heat-stressed mice treated with the COX-2 inhibitor, celecoxib, have indicated that the prostaglandin synthesis pathway--and in particular COX-2--may be an intermediate in the pathway to herpes viral reactivation. To further study this process, we infected the corneas of mice using topical application to a lightly scratched epithelium and waited 30 days for Herpes simplex virus type 1 (HSV-1) latency to be established in the trigeminal ganglia. Prior to the induction of viral reactivation, the mice were treated orally with celecoxib. Treated and untreated mice were induced to undergo reactivation by immersion in 43 degrees C water for 10 min. The shedding of virus at the ocular surface was determined by culturing ocular swabs with indicator cells. The presence of infectious virus in the trigeminal ganglion was evaluated by incubating ganglion homogenates with indicator cells and observing for cytopathic effect. Celecoxib treatment significantly suppressed viral reactivation when given prophylactically by the gastrointestinal route. The numbers of corneas and ganglia containing infectious virus were significantly lower in the celecoxib-treated animals, compared to the placebo-treated mice. These experiments demonstrate that a selective COX-2 inhibitor can suppress hyperthermic stress-induced herpes viral reactivation in the nervous system. It may be possible to use COX-2 inhibitors to prevent viral reactivation in high-risk patients by drug prophylaxis.

Modeling infection transmission

Understanding what determines patterns of infection spread in populations is important for controlling infection transmission. The science that advances this understanding uses mathematical and computer models that vary from deterministic models of continuous populations to models of dynamically evolving contact networks between individuals. These provide insight, serve as scientific theories, help design studies, and help analyze data. The key to their use lies in assessing the robustness of inferences made using them to violation of their simplifying assumptions. This involves changing model forms from deterministic to stochastic and from compartmental to network, as well as adding realistic detail and changing parameter values. Currently inferences about infection transmission are often made using stratified rate or risk comparisons, logistic regression models, or proportionate hazards models that assume an absence of transmission. Robustness assessment will show many of these inferences to be wrong. A community of epidemiologist modelers is needed for effective robustness assessment.

Herpes simplex virus resistance to acyclovir and penciclovir after two decades of antiviral therapy

Acyclovir, penciclovir, and their prodrugs have been widely used during the past two decades for the treatment of herpesvirus infections. In spite of the distribution of over 2.3 x 10(6) kg of these nucleoside analogues, the prevalence of acyclovir resistance in herpes simplex virus isolates from immunocompetent hosts has remained stable at approximately 0.3%. In immuncompromised patients, in whom the risk for developing resistance is much greater, the prevalence of resistant virus has also remained stable but at a higher level, typically 4 to 7%. These observations are examined in the light of characteristics of the virus, the drugs, and host factors.

Antimicrobial use and antimicrobial resistance: a population perspective

The need to stem the growing problem of antimicrobial resistance has prompted multiple, sometimes conflicting, calls for changes in the use of antimicrobial agents. One source of disagreement concerns the major mechanisms by which antibiotics select resistant strains. For infections like tuberculosis, in which resistance can emerge in treated hosts through mutation, prevention of antimicrobial resistance in individual hosts is a primary method of preventing the spread of resistant organisms in the community. By contrast, for many other important resistant pathogens, such as penicillin-resistant Streptococcus pneumoniae, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant Enterococcus faecium resistance is mediated by the acquisition of genes or gene fragments by horizontal transfer; resistance in the treated host is a relatively rare event. For these organisms, indirect, population-level mechanisms of selection account for the increase in the prevalence of resistance. These mechanisms can operate even when treatment has a modest, or even negative, effect on an individual host's colonization with resistant organisms.

The rise and fall of antimicrobial resistance

Antimicrobial resistance is a growing problem in nearly every infectious disease, but the extent and rate of increase of the problem varies widely with different pathogen-drug combinations. The rate of increase of resistance depends primarily on the availability of resistant variants and the intensity of selection imposed by antimicrobial treatment (appropriately measured). Declines in resistance following antimicrobial control measures are typically faster in hospital-acquired infections than in community-acquired ones, probably owing to the dependence in the latter case on the fitness cost of resistance. Open questions and approaches for testing the hypotheses proposed here are outlined.