*BACKGROUND*

This application provides an easy-to-use interface for conducting weighted surveillance
for chronic wasting disease (CWD) in white-tailed deer (
*Odocoileus virginianus*
) populations. Weighted surveillance is based on the simple principle that within a population
there exists heterogeneity among individuals with regard to disease risk. To maximize efficiency
and potentially increase the likelihood of detecting new disease foci, weighted surveillance programs
exploit this heterogeneity by focusing disease detection efforts
in groups most at risk. The underlying methods were orginially developed by
Walsh et al. (2010)
using a Frequentist statistical approach. These results were then refined and recast into
a Bayesian statistical framework by
Heisey et al. (2014).
It is imporant to note that the use of weighted surveillance techniques requires that
prior information is available to estimate heterogeneity in individual risk. A general discussion of
CWD surveillance is given in
Walsh et al. (2012).

*DESCRIPTION*

This application provides two tools for use. They can be accessed by clicking on the tabs
above. The first tool called
**'Design'**
is used for planning weighted surveillance
activities. The user specifies how much confidence they need, and what minimum prevalence
they would like to detect in yearling males (e.g., I would like a 95% confidence of detecting at
least one case if the prevalence is at least 1%). This information then provides the total
number of points required to meet the specified confidence for the chosen minimum prevalence. The
user can then select from the potential sources of surveillance samples, and vary the number of
samples arising from each source. This provides a means of setting sampling objectives for each source
to ensure the requiste number of points is reached. This tool can also be used
to evaluate in real-time how close a program is to achieving its goal given the number of samples
collected from each source to date.

The second tool called
**'Estimation'**
is for use after sampling for CWD detection has
occurred and no positive cases were found. It provides the means to estimate the potential
underlying prevalence rate of CWD given the amount of samples collected during surveillance. Of
particular interest is the upper bound of the credible interval. If the disease is present in the
system, it provides the prevalence rate for which there is,
for example, a 95% probability the true prevalence is below. The
techniques and theory underpinning them used in this application are described in
Heisey et al. (2014).
This application takes advantage of the
R
statistical software for estimation. Heterogeneity of risk classes are based on the chronic wasting disease
information collected by the
Wisconsin Department of Natural Resources.
Jennelle et al. 2018
provide a description of the Wisconsin estimates and provide a case study of the application
of weighted surveillance to CWD detection.

White-tailed Deer (
*Odocoileus virginianus*
)

White-tailed Deer (
*Odocoileus virginianus*
)