Authors:
A Yvan Guifo Fodjo
1
;
2
;
3
;
Mikal Ziane
1
;
4
;
Serge Stinckwich
5
;
Bui Thi Mai Anh
6
and
Samuel Bowong
7
;
2
Affiliations:
1
CNRS, UMR 7606, LIP6, Sorbonne Université, Paris, France
;
2
IRD, UMI 209, UMMISCO, Bondy, France
;
3
URIFIA, Université de Dschang, Dschang, Cameroon
;
4
Université de Paris, Paris, France
;
5
United Nations University Institute in Macau, Macau SAR, China
;
6
School of Information and Communication Technology, Laboratory of Intelligent Software Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam
;
7
Département de Mathématiques, Université de Douala, Douala, Cameroon
Keyword(s):
Separation of Concerns, Compartmental Models, Contact Network, Epidemiology Modeling Tool.
Abstract:
Epidemiological models become more and more complex as new concerns are taken into account (age, sex, spatial heterogeneity, containment or vaccination policies, etc.). This is problematic because these aspects are typically intertwined which makes models difficult to extend, change or reuse. The Kendrick approach has shown promising results to separate epidemiological concerns but is restricted to homogeneous compartmental models. In this paper, we report on an attempt to generalize the Kendrick approach to support some aspects of contact networks, thereby improving the predictive quality of models with significant heterogeneity in the structure of contacts, while keeping the simplicity of compartmental models. This approach has been validated on two different techniques to generalize compartmental models.