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The social cost of contacts: Theory and evidence for the first wave of the COVID-19 pandemic in Germany
Read how the nonlinear optimization solver Artelys Knitro helps researchers in epidemiology analyze the evolution of Covid-19 pandemic in Germany, in this article from “PLOS ONE”.


  • Quantifying the gap between private and social cost of contacts
  • Determining the reduction of contacts from the perspective of a social planner


  • Development of an economic-epidemiological model
  • Analysis and assessment of the evolution of the Covid-19 pandemic

Human societies have always lived with periodic epidemics and pandemics. Predicting how an outbreak may progress and spread is becoming essential to mitigate its effects, not only on population health and life expectancy, but also the societal upheaval and economic disruptions that come with it.

The field of epidemiology is therefore central, and since the beginning of the 20th century mathematical modeling techniques have increasingly played an important role in understanding the dynamics of the spread of diseases.

By extending the epidemiological SIR (Susceptible, Infectious, Recovered) model, the authors have developed an economic-epidemiological model with additional equations to represent quarantine measures where heterogeneous individuals are susceptible to being infected by a virus.

The resulting dynamic nonlinear optimization model is solved with Artelys Knitro. Thanks to its efficient interior-point method and its multi-start option, Artelys Knitro allows the authors to conduct an extensive analysis on the evolution of Covid-19 first wave in Germany.



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