Abstract
Setting global strategies and targets for disease prevention and control often involves mathematical models. Model structure is typically subject to intense scrutiny, such as confrontation with empirical data and alternative formulations, while a less frequently challenged aspect is the widely adopted reduction of parameters to their average values. Focusing on endemic diseases, we use a general transmission model to explain how mean field approximations decrease the estimated R0 from prevalence data, while threshold phenomena - such as the epidemic and reinfection thresholds - remain invariant. This results in an underestimation of the effort required to control disease, which may be particularly severe when the approximation inappropriately places transmission estimates below important thresholds. These concepts are widely applicable across endemic pathogen systems.
| Original language | English |
|---|---|
| Pages (from-to) | 97-102 |
| Number of pages | 6 |
| Journal | Journal of Theoretical Biology |
| Volume | 395 |
| Early online date | 8 Feb 2016 |
| DOIs | |
| Publication status | Published - 21 Apr 2016 |
Funding
We thank Professor Antonio Coutinho for constructively challenging the practical usage of earlier versions, urging us to aim for finer concepts. We also thank two anonymous reviewers for constructive comments. MGMG is grateful to Instituto Gulbenkian de Ciência for hosting and to FCT ( IF/01346/2014 ) and CAPES (Science without Borders) for funding. CR is supported by Fundação para a Ciência e Tecnologia , UID/MAT/04561/2013 .
Keywords
- endemic infection
- epidemic threshold
- global health
- heterogeneity
- reinfection threshold