Chapter 18 Epizootic Risk Model

18.1 What is the Epizootic Risk Model?

The Epizootic Risk Model depicts the hypothetical consequences of prion introduction into a herd of otherwise healthy hosts. The higher the epizootic potential, the higher the consequences from an outbreak.

18.2 What Questions Does it Answer?

Question 1. Where should I sample for CWD? Consider sampling in places where the epizootic potential is greater than 1, because any introduction of prions will result in an outbreak among the live herd.

Can’t afford to sample in all the places where epizootic potential is greater than 1? Then prioritize the locations where the risk of an epizootic is highest. When epizootic potential is greater than 1, introduction of prions will produce rapid spread, expanding disease prevalence beyond 1.5%, contaminating the environment, causing disease mortality, and becoming unmanageable - all in short order. Therefore, it is important to sample in the places with the highest epizootic potential so you can mobilize a response while there is still time to alter the eventual outcome.

Alternatively, if the epizootic potential is less than 1, then consider spending your surveillance resources elsewhere. After all, introduction of prions may not produce any spread and the disease will eventually die out on its own – with no human help needed.

Question 2. What management strategies can I enact to reduce the epizootic potential? The model reveals which parameters have the highest influence on the outcome of an introduction.

To answer this question, find the parameter with the largest influence on epizootic potential, alter it and rerun the model to see how that alteration translated into changes in epizootic potential. Repeat the exploration by altering additional parameters. Is there a pattern?

A classic way to reduce epizootic potential of CWD is to reduce density (or equivalently, increase mortality). However, don’t increase mortality so far that you extirpate your herds! When making any hypothetical manipulation, be sure to check that the population growth rate remains at 1 or higher.

18.3 Output Details

Epizootic Potential: The Epizootic Potential is the growth rate of the disease given the underlying population dynamics in the herd. The higher the epizootic potential, the faster the disease will spread from host to host. If epizootic potential is greater than 1, an outbreak can occur among the live population. If the epizootic potential is below 1, transmission is not sustained and the disease will die out on its own.
Rank of Epizootic Potential: Epizootic potential hinges on herd dynamics, so some herds will have high epizootic potential while others may have low potential. A rank of 1 means that herd has the highest potential for an epizootic outbreak relative to the other herds in the jurisdiction.
Population Growth Rate: The population growth rate measures the change in host abundances through time. A population growth rate below 1 signals population decline whereas a growth rate above 1 signals population persistence.
Influences on Epizootic Potential: Epizootic potential hinges on herd dynamics, transmission dynamics, and environmental contamination. Some of these factors can be manipulated through targeted management in order to reduce overall epizootic potential. In general, the larger the influence by a parameter, the smaller the change needed to that parameter to produce the desired disease outcome.

18.4 Abbreviated Tutorial

Select Epizootic Risk and choose your model parameters (see below).
Run the model with those desired parameters to understand how herd dynamics influence CWD outbreak.
On the resulting maps, pay particular attention to areas where epizootic potential is high (1 or greater). These are the herds that may need immediate CWD surveillance.
Pay attention to areas where epizootic potential is low (below 1). These are herds where you may be able to forgo surveillance in lieu of monitoring herds with higher epizootic risk elsewhere.
Rerun the model with different parameter values to see if or to what extent the alterations in herd dynamics attenuate or increase epizootic potential. Brainstorm whether you can modify that parameter in real life using field-based techniques.

18.5 Parameters Needed to Execute the Model

Model type: Select ‘Epizootic Risk Model’ from the drop-down list.
Reference name: Label the run.
(Optional) Applicable season year: Label the season-year. This label is not used in the model execution and is intended to assist the provider in documenting the model execution.
(Optional) Notes: Enter any additional remarks about the run.
Species: Select the species to be used in the model.
Season-year(s): Select one (or more) season-years to compute reservoir contamination.
Host density: The number of hosts that reside in one square kilometer of land area. Complete one of two actions:
1. Use the drop-down menu at left to select the season-year to auto populate the model with density data from the Warehouse (option exists when data are present), -or-
2. Leave the drop-down menu at left blank and hand-enter on the right a value (1-25) for host density that best represents average density in your herds. Note: The model will use density data when it exists, but will use hand-entered values when these data do not exist.
Host fecundity: The number of hosts born per reproductive female host per year (assuming an equal sex ratio of offspring). Complete one of two actions:
1. Use the drop-down menu at left to select the season-year to auto populate the model with fecundity data from the Warehouse (option exists when data are present), -or-
2. Leave the drop-down menu at left blank and hand-enter on the right a value (0.5-2.5) for host fecundity that best represents average reproduction in your herds. Note: The model will use fecundity data when it exists, but will use hand-entered values when these data do not exist.
Harvest mortality: The proportion of hosts taken each year through hunter harvest. Complete one of two actions:
1. Use the drop-down menu at left to select the season-year to auto populate the model with harvest data from the Warehouse (option exists when data are present), -or-
2. Leave the drop-down menu at left blank and hand-enter on the right a value (0-0.5) of harvest that best represents average harvest in your herds. Note: The model will use harvest data when it exists, but will use hand-entered values when these data do not exist.
Natural mortality: The proportion of hosts removed each year from all other causes (not including death by harvest or death from CWD). Complete one of two actions:
1. Use the drop-down menu at left to select the season-year to auto populate the model with natural mortality data from the Warehouse (option exists when data are present), -or-
2. Leave the drop-down menu at left blank and hand-enter on the right a value (0-0.5) for natural mortality that best represents average mortality (not including death by harvest or CWD) in your herds. Note: The model will use natural mortality data when it exists, but will use hand-entered values when these data do not exist.
Transmission via subclinical hosts: The rate that new hosts acquire the disease from subclinical hosts. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-0.3), where 0 indicates no transmission and larger positive numbers represent higher transmission rates. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Transmission via clinical hosts: The rate that new hosts incur the disease from clinical hosts. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-0.3), where 0 indicates no transmission and larger positive numbers represent higher transmission rates. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
System type: The relationship between population size and transmission intensity. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (a value between 0 and 1), where 0 represents density-dependent contact rates leading to disease transfer among hosts and 1 represents frequency-dependent contact rates leading to disease transfer among hosts. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Shedding by sublinical hosts: The rate that subclinical hosts shed prions into the environment through urine, saliva, blood, and feces. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-1.0), where 0 indicates no shedding and larger positive numbers represent higher rates of shedding. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Shedding by clinical hosts: The rate that clinical hosts shed prions into the environment through urine, saliva, blood, and feces. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-1.0), where 0 indicates no shedding and larger positive numbers represent higher rates of shedding. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Deposition of prions from subclinical carcasses: The proportion of prions that contribute to the environment when a subclinical host dies a natural death. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-1.0), where 0 indicates no deposition and larger positive numbers represent higher rates of deposition. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Deposition of prions from clinical carcasses: The proportion of prions that contribute to the environment when a clinical host dies a natural death. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-1.0), where 0 indicates no deposition and larger positive numbers represent higher rates of deposition. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Deposition of prions from CWD mortality: The proportion of prions that contribute to the environment when a host dies of CWD. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-1.0), where 0 indicates no deposition and larger positive numbers represent higher rates of deposition. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.
Disease progression to subclinical status: The rate in which new hosts progress in their disease to subclinical status. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-8.0). The lower the estimate, the longer a host will remain in this disease stage. Note: The default value of 4 corresponds to ¼ = 0.25 years, which is an example from white-tailed deer where 0.25 years is the minimum amount of time that a new deer fawn can develop into subclinical status. If you desire to initialize the model with a longer timeline for this disease stage, then reduce the input value. For example, an input value of 2 corresponds to ½, which implies this stage lasts 0.5 year. Similarly, if you desire to initialize the model with a shorter timeline for this disease stage, then increase the input value.
Disease progression from subclinical to clinical status: The rate in which hosts with subclinical infections progress in their disease to clinical status. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-8.0). The lower the estimate, the longer a host will remain in this disease stage. Note: The default value of 0.8 corresponds to 1/0.8 = 1.25 years, which is an example from white-tailed deer, where 1.25 years is the minimum amount of time a subclinical deer stays subclinical before advancing to clinical status. If you desire to initialize the model with a longer timeline for this disease stage, then reduce the input value. For example, an input value of 2 corresponds to ½, which implies this stage lasts 0.5 year. Similarly, if you desire to initialize the model with a shorter timeline for this disease stage, then increase the input value.
Disease progression from clinical status to CWD mortality: The rate in which hosts with clinical infections die of CWD. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate (0-8.0). The lower the estimate, the longer a host will remain in this disease stage. Note: The default value of 1 corresponds to 1/1 = 1 year, which is an example from white-tailed deer, where 1 year is the minimum amount of time a clinical deer stays clinical before dying from CWD. If you desire to initialize the model with a longer timeline for this disease stage, then reduce the input value. For example, an input value of 2 corresponds to ½, which implies this stage lasts 0.5 year. Similarly, if you desire to initialize the model with a shorter timeline for this disease stage, then increase the input value.
Rate that prions become unavailable: The proportion of prions in the reservoir that lose the ability to infect new hosts each year. Complete one of two actions:
1. Leave the default rate, -or-
2. Enter a new estimate for this rate, where 0 indicates infinite infectiousness and an increasingly large positive number indicates faster removal. Note: The default value corresponds to the example used in Hanley et al. (2022) to model white-tailed deer.

18.6 Details on the Theory

Hanley B, M Carstensen, D Walsh, S Christensen, D Storm, J Booth, J Guinness, C Them, M Ahmed, & K Schuler. 2022. Informing Surveillance through the Characterization of Outbreak Potential of Chronic Wasting Disease in White-Tailed Deer. Ecological Modelling 471C, 110054. https://doi.org/10.1016/j.ecolmodel.2022.110054

18.7 Code

The GitHub Repository is at https://github.com/Cornell-Wildlife-Health-Lab/epizootic-risk-model-v2.

CWD Data Warehouse User Manual