Monthly Archives: September 2020

Tracking animal movements over time may fundamentally determine the success of disease control interventions. In commercial pig production growth stages determine animal transportation schedule, thus it generates time-varying contact networks showed to influence the dynamics of disease spread. In this study, we reconstructed pig networks of one Brazilian state from 2017 to 2018, comprising 351,519 movements and 48 million transported pigs. The static networks view did not capture time-respecting movement pathways. For this reason, we propose a time-dependent network approach. A susceptible-infected model was used to spread an epidemic over the pig network globally through the temporal between-farm networks, and locally by a stochastic model to account for within-farm dynamics. We propagated disease to calculate the cumulative contacts as a proxy of epidemic sizes and evaluate the impact of network-based disease control strategies in the absence of other intervention alternatives. The results show that targeting 1,000 farms ranked by degree would be sufficient and feasible to diminish disease spread considerably. Our modeling results indicated that independently from where initial infections were seeded (i.e., independent, commercial farms), the epidemic sizes and the number of farms needed to be targeted to effectively control disease spread were quite similar, indeed this finding can be explained by the presence of contact among all pig operation types The proposed strategy limited the transmission the total number of secondarily infected farms to 29, over two simulated years. The identified 1,000 farms would benefit from enhanced biosecurity plans and improved targeted surveillance. Overall, the modeling framework provides a parsimonious solution for targeted disease surveillance when temporal movement data is available. Machado G, Galvis J, Lopes F, Voges J, Medeiros A, Cárdenas N. Quantifying the dynamics of pig movements improves targeted disease surveillance and control plans. Transbound Emerg Dis. 2020 Sep. https://doi.org/10.1111/tbed.13841

Most H1 influenza A viruses (IAVs) of swine are derived from past human viruses. As human population immunity against these IAVs gradually decreases, the risk of reintroduction to humans increases. We examined 549 serum samples from persons 0-97 years of age collected in Belgium during 2017-2018 for hemagglutination inhibiting and virus neutralizing antibodies against 7 major H1 swine IAV (swIAV) clades and 3 human progenitor IAVs. Seroprevalence (titers >40) rates were >50% for classical swine and European human-like swIAVs, >24% for North American human-like δ1a and Asian avian-like swIAVs, and