Ghosh Indrajit, Sardar Tridip, Chattopadhyay Joydev
Agricultural and Ecological Research Unit, Indian Statistical Institute, 203, B. T. Road, Kolkata, West Bengal, 700108, India.
Department of Mathematics, Dinabandhu Andrews College, Baishnabghata, P.O. Garia, Dist. 24 Paraganas (S), Kolkata, West Bengal, 700084, India.
Bull Math Biol. 2017 May;79(5):1100-1134. doi: 10.1007/s11538-017-0274-5. Epub 2017 Mar 29.
In this manuscript, we propose and analyze a compartmental model of visceral leishmaniasis (VL). We model the human population with six compartments including asymptomatic, symptomatic and PKDL-infected, animal population as second host and sandfly population as the vector. Furthermore, the non-adult stage of the sandfly population is introduced in the system, which was not considered before in the literature. We show that the increase in the number of host of sandfly population generates a backward bifurcation. Thus, multiple hosts will cause disease persistence even if the basic reproduction number ([Formula: see text]) is below unity. We perform a sensitivity analysis of important model parameters with respect to some epidemiologically significant responses. We validate our model by calibrating it to weekly VL incidence data from South Sudan for the year 2013. We perform cost-effectiveness analysis on different interventions: treatment, non-adult control, adult control and their different layered combinations based on their implementation cost (in USD) and case reduction. We also use a global sensitivity analysis technique to understand the effect of important parameters of our model on the implementation cost of different controls. This cost-effectiveness study and cost-sensitivity analysis are relatively new in existing literature of this disease.
在本手稿中,我们提出并分析了一种内脏利什曼病(VL)的 compartmental 模型。我们将人类群体建模为六个隔室,包括无症状、有症状和感染 PKDL 的个体,将动物群体作为第二宿主,将白蛉群体作为传播媒介。此外,系统中引入了白蛉群体的非成虫阶段,这在以前的文献中未曾考虑过。我们表明,白蛉群体宿主数量的增加会产生反向分岔。因此,即使基本再生数([公式:见原文])低于 1,多个宿主也会导致疾病持续存在。我们针对一些具有流行病学意义的反应对重要模型参数进行了敏感性分析。我们通过将模型校准到 2013 年南苏丹的每周 VL 发病率数据来验证我们的模型。我们基于不同干预措施(治疗、非成虫控制、成虫控制及其不同分层组合)的实施成本(以美元计)和病例减少情况进行成本效益分析。我们还使用全局敏感性分析技术来了解模型的重要参数对不同控制措施实施成本的影响。这种成本效益研究和成本敏感性分析在该疾病的现有文献中相对较新。