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Causes of delayed outbreak responses and their impacts on epidemic spread

Citation

Tao, Yun et al. (2021), Causes of delayed outbreak responses and their impacts on epidemic spread, Dryad, Dataset, https://doi.org/10.25349/D9P315

Abstract

Livestock diseases have devastating consequences economically, socially, and politically across the globe. In certain systems, pathogens remain viable after host death, which enables residual transmissions from infected carcasses. Rapid culling and carcass disposal are well-established strategies for stamping out an outbreak and limiting its impact, however, wait-times for these procedures, i.e., response delays, are typically farm-specific and time-varying due to logistical constraints. Failing to incorporate variable response delays in epidemiological models may understate outbreak projections and mislead management decisions. We revisited the 2001 foot-and-mouth epidemic in the United Kingdom and sought to understand how misrepresented response delays can influence model predictions. Survival analysis identified farm size and control demand as key factors that impeded timely culling and disposal activities on individual farms. Using these factors in the context of existing policy to predict local variation in response times significantly affected predictions at the national scale. Models that assumed fixed, timely responses grossly underestimated epidemic severity and its long-term consequences. As a result, this study demonstrates how general inclusion of response dynamics and recognition of partial controllability of interventions can help inform management priorities during epidemics of livestock diseases.

Methods

We integrated different types of response delays into the well-established Warwick model. The model includes spatially explicit representation of registered farms and their livestock compositions. It treats the farm as the basic unit for infection and susceptibility, such that all the animals in each holding become infected en masse. The parameters are fitted to the incidence data from 2001 and account for nonlinear increases of farm-level transmission and susceptibility as a function of farm size. The original model description of control actions is extended to include the disposal process, carcass transmission rate, and variable culling and disposal delays that equate to an individual farm’s wait-times in the control queues. The model simulates a general scenario where only infected premises and premises with known dangerous contacts are targeted for removal. Additional details of the Warwick model can be found in:

Keeling et al. (2001) Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape. Science, 294, 813–817.
Keeling et al. (2003) Modelling vaccination strategies against foot-and-mouth disease. Nature, 421, 136–142.
Tildesley et al. (2008) Accuracy of models for the 2001 foot-and-mouth epidemic. Proc. Biol. Sci., 275, 1459–1468.
Tildesley et al. (2017) Mathematical Models of the Epidemiology and Control of Foot-and-mouth Disease. Foot and Mouth Disease Virus: Current Research and Emerging Trends.
Probert et al. (2018) Real-time decision-making during emergency disease outbreaks. PLoS Comput. Biol., 14, e1006202.

Funding

Intelligence Community Postdoctoral Research Fellowship Program

National Institutes of Health, Award: R01 GM105247-01

Ecosystem Mission Area of the U.S. Geological Survey

Biotechnology and Biological Sciences Research Council, Award: BB/T004312/1

Biotechnology and Biological Sciences Research Council, Award: BB/S01750X/1

Li Ka Shing Foundation