The Numerus WebKit SIRS App is a complete lesson in classic epidemiology using a new web-based modeling app that encourages experimentation. The app is fully documented and supported by instructional videos.
Follow the links below to access the app, documentation and videos. Additional links are included for viewing other WebKit applications and to learn about Numerus WebKit.
Click HERE to view the SIRS WebApp.
Documentation and tutorial are available HERE
Instructional videos can viewed HERE
Please register HERE if you are interested in using our application.
See examples of Numerus WebKit models HERE.
Visit the Numerus Wiki to learn more about the Numerus WebKit.
Submit comments and questions HERE
Numerus is seeking to partner with projects in teaching and research that can benefit from our technology. Interested parties should submit a project description using the comments form and we will get back to you.
This application was introduced in a workshop held at the MIDAS ’25 annual meeting in Bethesda, MD. Below is the abstract describing the workshop.
MIDAS Workshop to Support Teaching and Research in Epidemiological Dynamics
Wayne Getz, University of California, Berkeley
Richard Salter, Oberlin College
This workshop took place on November 3, 2025 in advance of the MIDAS annual meeting. The materials presented in the workshop are available for use by instructors to support the introduction of the SIRS Model.
We describe a set of Numerus WebKit Apps that are accessed in any browser at no cost to the user. They can be used to teach epidemiological concepts to students and professionals at all levels.
These WebApps are a translation of the Numerus RAMP Apps that the authors published in BMC Medical Education, 2022, 22:632 (Simulation applications to support teaching and research in epidemiological dynamics) and made available through the free distribution of a new online Web-based applications platform (Numerus WebKit). We will demonstrate how these WebApps can be used inter alia to teach the following concepts:
1. Disease prevalence curves of unmitigated outbreaks have a single peak and result in epidemics that ‘burn’ through the population to become extinguished when the proportion of the susceptible population drops below a critical level.
2. If immunity in recovered individuals wanes sufficiently fast then the disease persists indefinitely as an endemic state, with possible dampening oscillations following the initial outbreak phase.
3. The steepness and initial peak of the prevalence curve are influenced by the basic reproductive value R0, which must exceed 1 for an epidemic to occur.
4. The probability that a single infectious individual in a closed population (i.e. no migration) gives rise to an epidemic increases with the value of R0 > 1.
5. Behavior that adaptively decreases the contact rate among individuals with increasing prevalence has major effects on the prevalence curve including dramatic flattening of the prevalence curve along with the generation of multiple prevalence peaks.
6. The impacts of treatment are complicated to model because they effect multiple processes including transmission, recovery and mortality.
7. The impacts of vaccination policies, constrained by a fixed number of vaccination regimens and by the rate and timing of delivery, are crucially important to maximizing the ability of vaccination programs to reduce mortality.