Editorial: Modeling Disease Spread and Control

Infectious diseases are a major burden for health (1) for both humans and animals and pose a constant economic challenge for the global economy (2, 3). Climate change, intensive global trade, emergence/reemergence of infectious agents and of antimicrobial resistance, combined with intensive livestock production systems make prevention and control of livestock infectious diseases a major global challenge. This intensifies the demand for tools to aid in better understanding of disease spread for cost-effective contingency planning and disease prevention and control. Mathematical and simulation models have contributed to improve our understanding of the population dynamics of infectious diseases. In addition, they have provided decision makers with tools to aid in disease prevention and control based on scientific evidence (4–6). This research topic includes 10 scientific studies presenting different aspects and implementations of mathematical modeling for disease spread and control. The studies can be divided into: (1) model construction (two studies); (2) network analysis (two studies); (3) tools for decision makers (four studies); and (4) cost-effective control of endemic diseases (two studies).