title: Characterization of contact structures for the spread of infectious diseases in a pork supply chain in northern Germany by dynamic network analysis of yearly and monthly networks.
abstract: A major risk factor in the spread of diseases between holdings is the transport of live animals. This study analysed the animal movements of the pork supply chain of a producer group in Northern Germany. The parameters in-degree and out-degree, ingoing and outgoing infection chain, betweenness and ingoing and outgoing closeness were measured using dynamic network analysis to identify holdings with central positions in the network and to characterize the overall network topology. The potential maximum epidemic size was also estimated. All parameters were calculated for three time periods: the 3-yearly network, the yearly and the monthly networks. The yearly and the monthly networks were more fragmented than the 3-yearly network. On average, one-third of the holdings were isolated in the yearly networks and almost three quarters in the monthly networks. This represented an immense reduction in the number of holdings participating in the trade of the monthly networks. The overall network topology showed right-skewed distributions for all calculated centrality parameters indicating that network resilience was high concerning the random removal of holdings. However, for a targeted removal of holdings according to their centrality, a rapid fragmentation of the trade network could be expected. Furthermore, to capture the real importance of holdings for disease transmission, indirect trade contacts (infection chain) should be considered. In contrast to the parameters regarding direct trade contacts (degree), the infection chain parameter did not underestimate the potential risk of disease transmission. This became more obvious, the longer the observed time period was. For all three time periods, the results for the estimation of the potential maximum epidemic size illustrated that the outgoing infection chain should be chosen. It considers the chronological order and the directed nature of the contacts and has no restrictions such as the strongly connected components of a cyclic network.
authors.affiliation: Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, Kiel, Germany; Max Planck Institute for Evolutionary Biology, Plön, Germany.
authors.forename: K
authors.initials: K
authors.lastname: Büttner
authors.forename: J
authors.initials: J
authors.lastname: Krieter
authors.forename: I
authors.initials: I
authors.lastname: Traulsen
mesh_terms: D000818:Animals; D003141:Communicable Diseases / Q000453:epidemiology / Q000635:transmission / Q000662:veterinary*; D016358:Contact Tracing / Q000662:veterinary*; D005523:Food Supply / Q000379:methods*; D005858:Germany / Q000453:epidemiology; D008460:Meat; D012307:Risk Factors; D013552:Swine; D013553:Swine Diseases / Q000453:epidemiology* / Q000635:transmission*; D013997:Time Factors; D014186:Transportation / Q000379:methods*
keywords: Germany; animal movements; monthly networks; network analysis; pig trade network; yearly networks