As described by many authors previously (see the links in the previous blog), a major use of modeling is to help researchers think carefully about a problem. That's especially true in the current situation, where models can help analyze complex issues. A few examples include:
- What can be derived from data in hand, or data that can be collected, to improve our ability to clarify the situation?
- Can we infer how quickly the virus is being transmitted and whether it is decreasing, increasing, or staying the same (questions regarding the basic reproduction ratio, R0, and the effective reproduction ratio, Reff)?
- If vaccines become available, what coverage and efficacy might be necessary to control the outbreak (i.e., reduce Reff below 1)? What vaccination strategies are likely to make optimal use of resources?
- Are there combination interventions that might prove effective at reducing the incidence of infection?
- What is the likelihood of Ebola cases arriving in distant nations via air travel?
One should be skeptical about any epidemiologic method, including mathematical and computer modeling, when the stakes for public health are so high. Ultimately, however, policymakers need timely and defensible analytic guidance to support allocation of scarce resources. Modeling is one component of such guidance.
(image source: David Hartley)