A theoretical framework to identify invariant thresholds in infectious disease epidemiology

• Published in: Journal of theoretical biology Vol. 395; no. C; pp. 97 - 102
• Main Authors: Gomes, M. Gabriela M., Gjini, Erida, Lopes, Joao S., Souto-Maior, Caetano, Rebelo, Carlota
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 21.04.2016; Elsevier
• Subjects: Communicable Diseases - epidemiology; Communicable Diseases - transmission; Endemic infection; Epidemic threshold; Global health; Heterogeneity; Humans; Models, Biological; Reinfection threshold; Heterogeneity; Global health; Endemic infection; Reinfection threshold; Epidemic threshold
• ISSN: 0022-5193; 1095-8541
• DOI: 10.1016/j.jtbi.2016.01.029

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. •Host heterogeneity modifies the relationship between R0 and disease prevalence.•Neglecting heterogeneity results in underestimated efforts to meet control targets.•Invariant transmission thresholds are robust indicators for control planning.