Session V For foot-and-mouth disease (FMD) and similar transboundary animal diseases (FAST), the need to prevent, detect and respond to shifting disease threats highlights the need for data-driven tools that can be used to collect critical health information, explore policy alternatives, anticipate consequences, and evaluate impacts. A variety of modelling tools are often used to evaluate alternative approaches to the control of FAST diseases; however, the use of these tools is not without pitfalls, and the dangers of “garbage in, garbage out” are increasingly present.

1. EuFMD
OS22 SUCCESSES AND PITFALLS
IN APPLYING MODEL
RESULTS TO POLICY
Amy Delgado, DVM PhD
Center for Epidemiology and Animal Health
USDA APHIS Veterinary Services

2. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 2
Amy Delgado
Successes and Pitfalls

3. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 3
Sweileh, W. M. (2022). "Global
research activity on mathematical
modeling of transmission and
control of 23 selected infectious
disease outbreaks." Global Health
18(1): 4.
23 selected human infectious
disease agents
NOTE agriculture/animal
disease was excluded
Amy Delgado
Successes and Pitfalls

4. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 4
What are we learning?
Assefa, A., et al. (2022). "Ecological niche modeling predicting the potential distribution of African horse sickness virus
from 2020 to 2060." Sci Rep 12(1): 1748.
Jiang, D., et al. (2022). "Quantifying risk factors and potential geographic extent of African swine fever across the
world." PLoS One 17(4): e0267128.
Cardenas, N. C., et al. (2022). "Multiple species animal movements: network properties, disease dynamics and the impact
of targeted control actions." Vet Res 53(1): 14.
Claypool, A. L., et al. (2022). "Assessing Interventions That Prevent Multiple Infectious Diseases: Simple Methods for
Multidisease Modeling." Med Decis Making 42(4): 436-449.
Knific, T., et al. (2022). "Modeling Paratuberculosis Transmission in a Small Dairy Herd Typical of Slovenia Suggests That
Different Models Should Be Used to Study Disease Spread in Herds of Different Sizes." Animals (Basel) 12(9).
Brown, E., et al. (2022). "Airborne Transmission of Foot-and-Mouth Disease Virus: A Review of Past and Present
Perspectives." Viruses 14(5).
Chen, L., et al. (2022). "Numerical Simulation of Airborne Disease Spread in Cage-Free Hen Housing with Multiple
Ventilation Options." Animals (Basel) 12(12).
Coldrick, S., et al. (2022). "Modeling and experimental study of dispersion and deposition of respiratory emissions with
implications for disease transmission." Indoor Air 32(2): e13000.
Amy Delgado
Successes and Pitfalls
Global
Local
Complexities

5. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
Schoch-Spana, M., et al. (2022). "Modeling epidemic recovery: An expert elicitation on issues and approaches." Soc Sci
Med 292: 114554.
Mingtao et al. (2022) “Controlling epidemics through optimal allocation of test kits and vaccine doses across networks.”
IEEE Transactions on Network Science and Engineering 9.3 (2022): 1422-1436.
Seitzinger, A. H., et al. (2022). "The economic benefits of targeted response strategies against foot-and-mouth disease in
Australia." Prev Vet Med 204: 105636.
Daghriri, T., et al. (2022). "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis:
A Literature Review and COVID-19 Sentiment Illustration." Int J Environ Res Public Health 19(6).
d'Andrea, V., et al. (2022). "Individual risk perception and empirical social structures shape the dynamics of infectious
disease outbreaks." PLoS Comput Biol 18(2): e1009760.
Mumtaz, Nabeela, Caroline Green, and Jim Duggan. "Exploring the Effect of Misinformation on Infectious Disease
Transmission." Systems 10.2 (2022): 50.
Zelner, Jon, et al. "There are no equal opportunity infectors: epidemiological modelers must rethink our approach to
inequality in infection risk." PLoS computational biology 18.2 (2022): e1009795.
5
Society,
Economics,
and
Equity
Amy Delgado
Successes and Pitfalls
What are we learning?

6. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 6
Tizzoni, M., et al. (2022). "Addressing the socioeconomic divide in computational modeling for infectious diseases." Nat Commun 13(1): 2897.
Amy Delgado
Successes and Pitfalls

7. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
Policy and behavioral response to shock events: An
agent-based model of the effectiveness and equity of
policy design features.
Shastry, V., et al. (2022). PLoS One 17(1): e0262172.
● “The extent to which individuals comply with different policy designs can further influence how effective the
policy responses are and how equitably their impacts are distributed in the population.”
● “We show that while an early policy response can be highly effective, the impact of the timing is moderated by
other aspects of policy design such as duration and targeting of the policy, as well as societal aspects such as
trust and compliance among the population. More importantly, we show that even policies that are more
effective overall can have disproportionate impacts on vulnerable populations.”
7
Amy Delgado
Successes and Pitfalls

8. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
How can we set ourselves up for success?
Build relationships
8
Amy Delgado
Successes and Pitfalls

9. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
How can we set ourselves up for success?
Build relationships
9
The questions drive the analysis, be flexible!
Amy Delgado
Successes and Pitfalls
Bison bison

10. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
How can we set ourselves up for success?
Build relationships
10
The questions drive the analysis, be flexible!
Amy Delgado
Successes and Pitfalls
Yadav, Shankar, et al. (2022) "Epidemiologic and
economic considerations regarding persistently
infected cattle during vaccinate-to-live strategies for
control of foot-and-mouth disease in FMD-free
regions." Frontiers in Veterinary Science: 1629.

11. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
How can we set ourselves up for success?
Build relationships
11
The questions drive the analysis, be flexible!
Focus on sustainable systems
Amy Delgado
Successes and Pitfalls

12. Thank you !..
https://www.aphis.usda.gov/aphis/ourfocus/animalhealth
Amy.H.Delgado@usda.gov