Stephenson Brittany, Lanzas Cristina, Lenhart Suzanne, Day Judy
Department of Mathematics, University of Tennessee, Knoxville, TN, USA.
Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC, USA.
J Math Biol. 2017 Dec;75(6-7):1693-1713. doi: 10.1007/s00285-017-1133-6. Epub 2017 May 8.
The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.
形成孢子的革兰氏阴性细菌艰难梭菌可导致严重的肠道疾病。医院中艰难梭菌感染(CDI)病例数的显著增加凸显了更好地了解如何预防CDI传播的必要性。在我们的论文中,我们修改并更新了一个医院内艰难梭菌传播的分区模型,以纳入疫苗接种。然后,我们应用最优控制理论来确定随时间变化的最优疫苗接种率,该接种率能将疾病在医院人群中的流行率和传播以及与疫苗接种相关的时间和金钱成本的组合降至最低。我们考虑了各种医院场景,例如抗生素处方率增加的时期和爆发时期,以了解这些场景如何改变最优疫苗接种率。通过将恒定疫苗接种率下的目标函数值与随时间变化的最优疫苗接种率下的目标函数值进行比较,我们说明了随时间变化控制的益处。