Causes of delayed outbreak responses and their impacts on epidemic spread

Author:

Tao Yun12ORCID,Probert William J. M.3,Shea Katriona45ORCID,Runge Michael C.6ORCID,Lafferty Kevin7,Tildesley Michael8,Ferrari Matthew45ORCID

Affiliation:

1. Intelligence Community Postdoctoral Research Fellowship Program, Oak Ridge, TN, USA

2. Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA, USA

3. Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK

4. Department of Biology, 208 Mueller Laboratory, Pennsylvania State University, University Park, PA, USA

5. The Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA

6. US Geological Survey, Patuxent Wildlife Research Center, Laurel, MD, USA

7. US Geological Survey, Western Ecological Research Center at Marine Science Institute, University of California, Santa Barbara, CA, USA

8. The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, West Midlands, UK

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 an 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.

Funder

U.S. Geological Survey

Intelligence Community Postdoctoral Research Fellowship Program

Li Ka Shing Foundation

National Institutes of Health

Biotechnology and Biological Sciences Research Council

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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