N. Cespedes - A multi-species contact-network model: between-farm disease spreading

A MULTI-SPECIES CONTACT-NETWORK MODEL: BETWEEN-FARM DISEASE SPREADING AMONG BOVINE, SMALL RUMINANTS AND SWINE POPULATIONS.

Introduction

Many infectious diseases infect multiple species and persist through a combination of within- and between-species transmission dynamics and processes. Here, we explore the epidemiological impacts of host-specific disease spread dynamics, among farms raising multiple livestock species: cattle, buffalo, pigs, sheep and goat.

Materials and methods

We reconstructed multiscale stochastic susceptible-infected network-based transmission model for within-farm dynamics and between-farm animal movements. A wide range of introduction scenarios was simulated on the empirical network. To mimic an initial stage of an introduced foreign animal disease we generated 100 runs over available 2-year network starting with 1.000 infected farms. Infection was then started randomly in farms with only swine, only cattle, only small ruminants and final scenario it started in farms with all species. The model was used to simulate control actions based on the identification of farms mode likely to be infected by its contact network.

Results

The largest epidemic had 45% infected swine farms whiten the first six months of simulation. We found that epidemic sizes were governed by which species the index was seeded to. As expected, the swine contact network was the most prone to spread disease, with a simulated prevalence of over 60% at the end of second year of simulation, followed by small ruminants’ and cattle with prevalence over 20% and 10% respectively.

Discussion

The size of epidemics initiated in cattle and small ruminants generated a higher amount of infection into other single species farm holdings. This work highlights the relevance of other than cattle farms in the between-farm transmission of possible foreign animal disease, i.e., foot and mouth disease. These results may serve as basic data in the planning of national or regional to designing risk-based targeted surveillance strategies considering a multi-species approach.

1N. Cárdenas,
2A. Omar, 3F.P. Nunes Lopes, 2G. Machado

1 Department of Preventive Veterinary Medicine and Animal Health, School of Veterinary Medicine and Animal Science, University of São Paulo, São Paulo, Brazil.
2 Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA.
3Secretary of Agriculture, Livestock and Agribusiness of State of Rio Grande do Sul (SEAPA-RS), Porto Alegre, Brazil.

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