使用流动数据的疟疾控制模型：塞内加尔Kedougou病例的早期解释
A Malaria Control Model Using Mobility Data: An Early Explanation of Kedougou's Case in Senegal
摘要：
疟疾防治研究涉及医学、社会学、生物学、数学、计算机科学等多个领域。数学领域的研究是为了预测疾病的发生并支持根除过程。基本上，建模方法主要是确定性和微分方程为基础的，同时选择临床和生物学特征，似乎是重要的。然而，如果在对疾病建模时个体特征很重要，那么疟疾的总体估计不是基于每个个体的健康状况，而是基于全球人口的非特定百分比。本文的目标是提出一个模型，依赖于个人的状态，这取决于他们的流动性和他们访问的地区的特点，每天的演变。因此，通过移动网络收集的一个人从一个地区移动到另一个地区的移动数据是预测疾病结果的重要组成部分。我们实施我们的解决方案，并通过实证实验证明其有效性。结果表明，该模型是多么有前途的疾病控制在Kedougou地区的失败提供了可能的见解。
英文摘要：
Studies in malaria control cover many areas such as medicine, sociology, biology, mathematic, physic, computer science and so forth. Researches in the realm of mathematic are conducted to predict the occurrence of the disease and to support the eradication process. Basically, the modeling methodology is predominantly deterministic and differential equation based while selecting clinical and biological features that seem to be important. Yet, if the individual characteristics matter when modeling the disease, the overall estimation of the malaria is not done based on the health status of each individual but in a non-specified percentage of the global population. The goal of this paper is to propose a model that relies on a daily evolution of the individual's state, which depends on their mobility and the characteristics of the area they visit. Thus, the mobility data of a single person moving from one area to another, gathered thanks to mobile networks, is the essential building block to predict the outcome of the disease. We implement our solution and demonstrate its effectiveness through empirical experiments. The results show how promising the model is in providing possible insights into the failure of the disease control in the Kedougou region.
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