Genital herpes, caused by herpes simplex virus (HSV-2), is the most prevalent sexually transmitted disease worldwide. In many developing countries genital herpes is untreated, and in the United States only 10% (or less) of cases are treated. We have developed a mathematical model that can be used as a health policy tool to predict the levels of antiviral drug resistance that would emerge, if treatment rates were increased. This model includes the effects of episodic treatment (i.e. we are modeling the effects of treating individuals only during a viral shedding episode).

We have coded up the first program (Applet 1.) to predict the prevalence of infection using the model developed in the following paper:

S.M. Blower, T.C. Porco, and G. Darby. 1998. Predicting and preventing the emergence of antiviral drug resistance in HSV-2. Nature Medicine. 4(6): 673-678.

If you are interested in the technical aspects of this model, here is a link to the state variables and their meanings. For a list of the parameters and their ranges please check here.

Instructions

First, please note that these applets are viewed best at resolutions of 800 x 600 or higher. If you are having a hard time running these applets because they don't fit on the screen, try clicking the 'Open without Frames' button at the bottom of this page. Also some browsers, such as the internet explorer have full screen modes, which enable more of a page to be displayed (for IE 5.0 the F11 key switches to the full screen mode).

The first applet (Applet 1.) graphs out the prevalence of infection (i.e. the % of individuals who are infected with HSV-2 in either the latent or viral shedding stage) over time. The red line represents the prevalence of drug-resistant HSV-2 and the dark blue line represents the prevalence of drug-sensitive HSV-2; this second applet (Applet 2.) graphs out the prevalence of individuals who are shedding virus (i.e. the prevalence of infectiousness) over time. The dark blue line represents the prevalence of individuals who are actively shedding drug-resistant virus; this group is made up of both individuals that have permanent and transient drug-resistant HSV-2. The red line represents the prevalence of individuals who are shedding drug-sensitive virus.

To change a parameter in the model just select the parameter you want to change by using the drop box. Enter the new value for the parameter in the text box and click the 'Set' button.

We have setup the model so you can change the following parameters:

1. alpha, which represents the reduction in transmissibility / infectiousness of drug-resistant strains relative to drug-sensitive strains (alpha can range from 0.0 to 1.0). If alpha is set at 0.0 this means that drug-resistant strains cannot be transmitted. If alpha is set at 1.0 this means that drug-resistant strains are as transmissible as drug-sensitive strains.
2. Ft, which represents the fraction of cases on episodic treatment (Ft can range from 0.0 to 0.5)
3. p1, which represents the probability of developing permanent drug-resistant HSV-2 during one treated episode (p1 can range from 0.0 to 0.01); a treated episode is the treatment of one viral shedding episode.
4. gamma, which represents the increased likelihood that transient drug resistance will develop during treatment relative to the probability that permanent drug resistance will develop (gamma can range from 1.0 to 10.0). If gamma is set at 1.0 this means the likelihood of developing transient drug resistance is the same as developing permanent drug resistance. If gamma is set at 10.0 this means the chance of developing transient drug resistance is ten times more likely than developing permanent drug resistance.

To run the simulation click on the 'Graph' button. Each time you hit the 'Graph' button the simulation advances time by another 50 years. Note that the basic reproductive rates (R_S and R_R) have been calculated for you. Click here for a brief explanation of epidemic and the role of the basic reproductive rate.