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Managing infectious diseases is a world public health issue, plagued by uncertainties. In this paper, we analyze the problem of viable control of a dengue outbreak under uncertainty. For this purpose, we develop a controlled Ross–Macdonald model with mosquito vector control by fumigation, and with uncertainties affecting the dynamics; both controls and uncertainties are supposed to change only once a day, then remain stationary during the day. The robust viability kernel is the set of all initial states such that there exists at least a strategy of insecticide spraying which guarantees that the number of infected individuals remains below a threshold, for all times, and whatever the sequences of uncertainties. Having chosen three nested subsets of uncertainties – a deterministic one (without uncertainty), a medium one and a large one – we can measure the incidence of the uncertainties on the size of the kernel, in particular on its reduction with respect to the deterministic case. The numerical results show that the viability kernel without uncertainties is highly sensitive to the variability of parameters — here the biting rate, the probability of infection to mosquitoes and humans, and the proportion of female mosquitoes per person. So, a robust viability analysis is a possible tool to reveal the importance of uncertainties regarding epidemics control

Titel:	Robust viability analysis of a controlled epidemiological model
Autor/in / Beteiligte Person:	Sepulveda Salcedo, Lilian Sofia ; De Lara, Michel
Link:	https://doi.org/10.1016/j.tpb.2019.02.003 Volltext
Zeitschrift:	instname:Universidad Autónoma de Occidente ; reponame:Repositorio Institucional UAO, 2019, S. 14-23
Veröffentlichung:	Elsevier, 2019
Medientyp:	academicJournal
DOI:	10.1016/j.tpb.2019.02.003
Schlagwort:	Control vectorial Vector control Epidemics control Viability Uncertainty and robustness Ross–Macdonald model Dengue Time: Universidad Autónoma de Occidente. Calle 25 115-85. Km 2 vía Cali-Jamundí
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Robust viability analysis of a controlled epidemiological model