For most papers in epidemiological modeling, we seem to be doing the exact same thing over the years, that is, formulating a mathematical model for the
dynamics of the disease with some interventions and determining the equilibrium points, showing that the disease-free equilibrium points are locally and globally asymptotically stable, analyzing different
reproduction numbers at different tweaks of our interventions, and the cycle goes on and on. Models, however, are usually too simplified to reflect the reality, yet, some authors posit with too much certainty. Can we not develop better principles of communication so that our results are understood in a mathematical framework rather than the certainty we try to portray in our papers?
there is a statement called TRIPOD standard that can be used to standardize the reporting quality of studies involving prediction model. see reference:
Moons KG, Altman DG, Reitsma JB, et al: Transparent Reporting of
a multivariable prediction model for Individual Prognosis or Diagnosis
(TRIPOD): Explanation and elaboration. Ann Intern Med 2015;
162:W1–W73
Not likely, this is a fundamental limitation of modeling. If you want to try to bridge the gap, make a model of a potential intervention, actually implement it, then compare the results to your model to the observed effect on public health. You might find that it is more expensive and for many reasons, mostly things not included in the model, often does not work!
Models on the other hand, you can speculate wildly on things in the distant future, such as an increase in P vivax malaria in North Africa by 2080 (when you have become tenured and/or no longer around to see that your prediction was bogus). You can also reuse your dengue model for zika, publish in a high level journal with only modification of the name of the disease in your diagram, and pretend you are making a difference.
If anyone is to blame, it is peer reviewed journals that allow this rampant speculation to be published without proper limitations. Until that changes, we shall continue to feed the beast with the hope that we will at least contribute novel methods to the discourse.
You can the following paper. I find though the predictions are reasonable, but overall it helps us in sharing our interventions and strategies well.
As the saying goes:
“All models are wrong but some are useful.” George Box
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