Title: Generalized contact matrices for epidemic modeling Show Chinese title

Title: 用于流行病建模的广义接触矩阵

Abstract: Contact matrices have become a key ingredient of modern epidemic models. They account for the stratification of contacts for the age of individuals and, in some cases, the context of their interactions. However, age and context are not the only factors shaping contact structures and affecting the spreading of infectious diseases. Socio-economic status (SES) variables such as wealth, ethnicity, and education play a major role as well. Here, we introduce generalized contact matrices capable of stratifying contacts across any number of dimensions including any SES variable. We derive an analytical expression for the basic reproductive number of an infectious disease unfolding on a population characterized by such generalized contact matrices. Our results, on both synthetic and real data, show that disregarding higher levels of stratification might lead to the under-estimation of the reproductive number and to a mis-estimation of the global epidemic dynamics. Furthermore, including generalized contact matrices allows for more expressive epidemic models able to capture heterogeneities in behaviours such as different levels of adoption of non-pharmaceutical interventions across different groups. Overall, our work contributes to the literature attempting to bring socio-economic, as well as other dimensions, to the forefront of epidemic modeling. Tackling this issue is crucial for developing more precise descriptions of epidemics, and thus to design better strategies to contain them. Show Chinese abstract

Abstract: 接触矩阵已成为现代流行病模型的关键组成部分。它们考虑了个体年龄的接触分层，以及在某些情况下互动的背景。然而，年龄和背景并不是唯一影响接触结构并影响传染病传播的因素。社会经济地位（SES）变量，如财富、种族和教育程度也起着重要作用。在这里，我们引入了广义接触矩阵，能够根据任何数量的维度进行接触分层，包括任何SES变量。我们推导了在具有此类广义接触矩阵的人口上展开的传染病的基本再生数的解析表达式。我们的结果在合成数据和真实数据上都表明，忽视更高层次的分层可能导致再生数的低估，并导致对全球流行病动态的错误估计。此外，包括广义接触矩阵可以使流行病模型更具表现力，能够捕捉行为上的异质性，例如不同群体对非药物干预措施的不同采用水平。总体而言，我们的工作为试图将社会经济以及其他维度推向流行病建模前沿的文献做出了贡献。解决这个问题对于开发更精确的流行病描述至关重要，从而设计出更好的控制策略。