Buonomo Bruno, Manfredi Piero, d'Onofrio Alberto
Department of Mathematics and Applications, University of Naples Federico II, via Cintia, 80126, Naples, Italy.
Department of Economics and Management, University of Pisa, Via Ridolfi 1, 56124, Pisa, Italy.
J Math Biol. 2019 Mar;78(4):1089-1113. doi: 10.1007/s00285-018-1303-1. Epub 2018 Nov 2.
In order to seek the optimal time-profiles of public health systems (PHS) Intervention to favor vaccine propensity, we apply optimal control (OC) to a SIR model with voluntary vaccination and PHS intervention. We focus on short-term horizons, and on both continuous control strategies resulting from the forward-backward sweep deterministic algorithm, and piecewise-constant strategies (which are closer to the PHS way of working) investigated by the simulated annealing (SA) stochastic algorithm. For childhood diseases, where disease costs are much larger than vaccination costs, the OC solution sets at its maximum for most of the policy horizon, meaning that the PHS cannot further improve perceptions about the net benefit of immunization. Thus, the subsequent dynamics of vaccine uptake stems entirely from the declining perceived risk of infection (due to declining prevalence) which is communicated by direct contacts among parents, and unavoidably yields a future decline in vaccine uptake. We find that for relatively low communication costs, the piecewise control is close to the continuous control. For large communication costs the SA algorithm converges towards a non-monotone OC that can have oscillations.
为了寻求公共卫生系统(PHS)干预的最优时间配置以促进疫苗接种倾向,我们将最优控制(OC)应用于一个带有自愿接种和PHS干预的SIR模型。我们关注短期情况,既研究由前向 - 后向扫描确定性算法得出的连续控制策略,也研究由模拟退火(SA)随机算法所研究的分段常数策略(这更接近PHS的工作方式)。对于儿童疾病,疾病成本远高于疫苗接种成本,最优控制解决方案在大部分政策期限内设定为最大值,这意味着PHS无法进一步改善对免疫净效益的认知。因此,随后的疫苗接种动态完全源于感知到的感染风险下降(由于患病率下降),这种下降通过父母之间的直接接触传播,并且不可避免地导致未来疫苗接种率下降。我们发现,对于相对较低的沟通成本,分段控制接近连续控制。对于高沟通成本,SA算法收敛到一个可能有振荡的非单调最优控制。