论文标题
流行模型的体系结构：从经验和临床数据中限制的限制
Architectures of epidemic models: accommodating constraints from empirical and clinical data
论文作者
论文摘要
确定性隔室模型已广泛用于建模流行病传播。这些模型需要拟合可用的数据，并且通常将数值程序实施到此目的。但是，并非每个模型体系结构都能够符合数据，因为模型的结构对解决方案施加了硬约束。我们在这项工作中调查了两种情况：首先，从隔间到另一个隔间的过渡时间的分布可能会施加可变数量的中间状态；其次，隔室大小的时间依赖性度量之间的非线性关系可能表明需要进行结构（即考虑几组异质特征的个体）。
Deterministic compartmental models have been used extensively in modeling epidemic propagation. These models are required to fit available data and numerical procedures are often implemented to this end. But not every model architecture is able to fit the data because the structure of the model imposes hard constraints on the solutions. We investigate in this work two such situations: first the distribution of transition times from a compartment to another may impose a variable number of intermediary states; secondly, a non-linear relationship between time-dependent measures of compartments sizes may indicate the need for structurations (i.e., considering several groups of individuals of heterogeneous characteristics).
