The effect of contact network accuracy and risk categorization on dynamic disease transmission models on the example of the Swiss pig population
Staff involved: Francesco Galli, Salome Dürr, Antoine Champetier de Ribes, Dima Farra
Duration: 2019 - 2023
Computer models are important tools in epidemiology to evaluate infectious disease interventions. In this project, we will collect contact data between the pig farmers from different sources to construct a contact network graph. By analysing it and integrating it in an infectious disease model, we will evaluate which data sources are most valuable to render accurate animal diseases simulations.
Infectious diseases in domestic animals often spread via animal transports. For this reason, the transports between pig farms must be reported in Switzerland and are documented in the animal transport database or Tierverkehrsdatenbank (TVD). A contact network analysis of the animal transports between pig farms informs which farms have the most contacts to other farms and are therefore more central for the spread of diseases. However, it is questionable, how good the quality of the transport data for pigs is. In this project, we would like to provide a first estimate of the amount of non-reported and indirect transports by using additional data sources from the private industry sector, and by interviewing farmers. A contact network analysis will be carried out with and without the additional data sources. By means of a transmission disease model, we will quantify whether model simulations are closer to reality if we include the additional information sources.
We will generate an algorithm which will estimate the amount of non-reported and indirect transports based on the TVD data. By means of socio-economical analysis we will elucidate which factors influence the swine network the most. This will help in turn to improve both the simulation models and the evaluation of intervention measures.
