Abstract
AbstractFor decades, mathematical models of disease transmission have provided researchers and public health officials with critical insights into the progression, control, and prevention of disease spread. Of these models, one of most fundamental is the SIR differential equation model. However, this ubiquitous model has one significant and rarely acknowledged shortcoming: it is unable to account for a disease’s true infectious period distribution. As the misspecification of such a biological characteristic is known to significantly affect model behavior, there is a need to develop new modeling approaches that capture such information. Therefore, we illustrate an innovative take on compartmental models, derived from their general formulation as systems of nonlinear Volterra integral equations, to capture a broader range of infectious period distributions, yet maintain the desirable formulation as systems of differential equations. Our work illustrates a compartmental model that captures any Erlang distributed duration of infection with only 3 differential equations, instead of the typical inflated model sizes required by differential equation compartmental models, and a compartmental model that capture any mean, standard deviation, skewness, and kurtosis of an infectious period distribution with merely 4 differential equations. The significance of our work is that it opens up a new class of easy-to-use compartmental models to predict disease outbreaks that does not require a complete overhaul of existing theory, and thus provides a starting point for multiple research avenues of investigation under the contexts of mathematics, public health, and evolutionary biology.
Publisher
Cold Spring Harbor Laboratory
Reference38 articles.
1. Contributions to the mathematical theory of epidemics--III. Further studies of the problem of endemicity. 1933;Bull Math Biol,1991
2. Contributions to the mathematical theory of epidemics--II. The problem of endemicity.1932;Bull Math Biol,1991
3. Contributions to the mathematical theory of epidemics--I. 1927;Bull Math Biol,1991
4. Diekmann O , Metz H , Heesterbeek H. The legacy of Kermack and McKendrick. In: Mollison D , editor. Epidemic Models: Their Structure and Relation to Data. Cambridge, UK: Cambridge University Press; 1995. pp. 95–115.
5. General compartmental epidemic models
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献