Alderton Simon, Macleod Ewan T, Anderson Neil E, Schaten Kathrin, Kuleszo Joanna, Simuunza Martin, Welburn Susan C, Atkinson Peter M
Institute of Complex System Simulation, School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom.
Geography and Environment, Faculty of Social and Human Sciences, University of Southampton, Southampton, United Kingdom.
PLoS Negl Trop Dis. 2016 Dec 27;10(12):e0005252. doi: 10.1371/journal.pntd.0005252. eCollection 2016 Dec.
This paper presents a new agent-based model (ABM) for investigating T. b. rhodesiense human African trypanosomiasis (rHAT) disease dynamics, produced to aid a greater understanding of disease transmission, and essential for development of appropriate mitigation strategies.
The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The method offers a complementary approach to traditional compartmentalised modelling techniques, permitting incorporation of fine scale demographic data such as ethnicity, age and gender into the simulation.
Through identification of possible spatial, demographic and behavioural characteristics which may have differing implications for rHAT risk in the region, the ABM produced output that could not be readily generated by other techniques. On average there were 1.99 (S.E. 0.245) human infections and 1.83 (S.E. 0.183) cattle infections per 6 month period. The model output identified that the approximate incidence rate (per 1000 person-years) was lower amongst cattle owning households (0.079, S.E. 0.017), than those without cattle (0.134, S.E. 0.017). Immigrant tribes (e.g. Bemba I.R. = 0.353, S.E.0.155) and school-age children (e.g. 5-10 year old I.R. = 0.239, S.E. 0.041) were the most at-risk for acquiring infection. These findings have the potential to aid the targeting of future mitigation strategies.
ABMs provide an alternative way of thinking about HAT and NTDs more generally, offering a solution to the investigation of local-scale questions, and which generate results that can be easily disseminated to those affected. The ABM can be used as a tool for scenario testing at an appropriate spatial scale to allow the design of logistically feasible mitigation strategies suggested by model output. This is of particular importance where resources are limited and management strategies are often pushed to the local scale.
本文提出了一种新的基于主体的模型(ABM),用于研究罗德西亚布氏锥虫引起的人类非洲锥虫病(rHAT)的疾病动态,旨在帮助更好地理解疾病传播,这对于制定适当的缓解策略至关重要。
开发该ABM以模拟赞比亚卢安瓜山谷一条75公里样带精细空间尺度上的rHAT发病率。该方法为传统的 compartmentalised 建模技术提供了一种补充方法,允许将诸如种族、年龄和性别等精细尺度的人口数据纳入模拟。
通过识别可能对该地区rHAT风险有不同影响的空间、人口和行为特征,ABM产生了其他技术难以轻易生成的输出。每6个月期间平均有1.99例(标准误0.245)人类感染和1.83例(标准误0.183)牛感染。模型输出表明,养牛家庭的近似发病率(每1000人年)(0.079,标准误0.017)低于无牛家庭(0.134,标准误0.017)。移民部落(如本巴族,发病率比值=0.353,标准误0.155)和学龄儿童(如5至10岁儿童,发病率比值=0.239,标准误0.041)感染风险最高。这些发现有可能有助于确定未来缓解策略的目标。
ABM更广泛地为思考HAT和被忽视热带病提供了一种替代方式,为调查地方尺度问题提供了解决方案,并产生易于传播给受影响人群的结果。ABM可作为一种工具,在适当空间尺度上进行情景测试,以便根据模型输出设计后勤上可行的缓解策略。在资源有限且管理策略往往侧重于地方尺度的情况下,这一点尤为重要。