We consider the spread of infectious disease through contact networks of
Configuration Model type. We assume that the disease spreads through contacts
and infected individuals recover into an immune state. We discuss a number of
existing mathematical models used to investigate this system, and show
relations between the underlying assumptions of the models. In the process we
offer simplifications of some of the existing models. The distinctions between
the underlying assumptions are subtle, and in many if not most cases this
subtlety is irrelevant. Indeed, under appropriate conditions the models are
equivalent. We compare the benefits and disadvantages of the different models,
and discuss their application to other populations (\emph{e.g.,} clustered
networks). Finally we discuss ongoing challenges for network-based epidemic
modeling.

本文研究了基于网络结构模型下的传染病传播，讨论了现有的数学模型的优势和劣势，并探讨了它们在其他人口群体中的应用和现有挑战。

网络中的疫情传播：现有方法和当前挑战

Epidemic spread in networks: Existing methods and current challenges

We introduce novel mathematical models and algorithms to generate (shortest
or k different) explanations for biomedical queries, using answer set
programming. We implement these algorithms and integrate them in BIOQUERY-ASP.
We illustrate the usefulness of these methods with some complex biomedical
queries related to drug discovery, over the biomedical knowledge resources
PHARMGKB, DRUGBANK, BIOGRID, CTD, SIDER, DISEASE ONTOLOGY and ORPHADATA. To
appear in Theory and Practice of Logic Programming (TPLP).

本研究采用 ANSWER SET PROGRAMMING（ASP）来生成医学查询的解释，包括最短或 k 个不同的解释，我们实现了这些算法并将其集成到 BIOQUERY-ASP 中，使用多种医学知识资源展示了这些方法的实用性，包括 PHARMGKB、DRUGBANK、BIOGRID、CTD、SIDER、DISEASE ONTOLOGY 和 ORPHADATA 等。