Chapter 15 Annual Surveillance Collection
The Annual Surveillance Collection describes the annual surveillance goals of the Provider for each Season-year. Annual surveillance goals are set per sub-administrative area and can be based on any previously executed model that generates suggested sampling quotas. The Annual Surveillance Collection is unique compared to the other data Collections, in that it is normally created only after a model has been executed.
The Annual Surveillance Collection can be used by Agencies for a variety of purposes. The Collection allows the Provider and its staff to monitor surveillance activity and provide real-time feedback on sampling progress. To track surveillance activity, create a Surveillance Activity Visualization. A Provider may also use the Annual Surveillance Collection to document past surveillance activity to understand how surveillance goals have changed over time and space.
15.1 Understanding and using the Annual Surveillance Collection
There are several key features and properties of the Agency Expense Collection that users should understand to effectively use the Collection:
- one annual surveillance entry per Season-year
- sample weights
- sample weights and surveillance quotas
- additional map layers
15.1.1 One annual surveillance entry per Season-year
Only one Annual Surveillance entry can be created for each Season-year.
15.1.2 Sample weights
Many wildlife agencies use a “weighted sampling” approach for CWD surveillance. Samples from different population segments are given different numeric weights that reflect the heterogeneity in disease risk across population segments. The use of weights can reduce the amount of sampling needed (relative to the reference population segment) to determine freedom from disease in an area (disease prevalence is below a given threshold at a specific level of confidence). For more information about sampling weights for CWD surveillance see:
- Walsh, D, Miller M. 2010. A Weighted Surveillance Approach for Detecting Chronic Wasting Disease Foci. Journal of Wildlife Diseases. 46. 118-35. 10.7589/0090-3558-46.1.118.
- Heisey DM, Jennelle CS, Russell RE, Walsh DP. 2014. Using Auxiliary Information to Improve Wildlife Disease Surveillance When Infected Animals Are Not Detected: A Bayesian Approach. PLOS ONE 9(3): e89843. https://doi.org/10.1371/journal.pone.0089843
- Jennelle CS, Walsh DP, Samuel MD, Osnas EE, Rolley R, Langenberg J, Powers JG, Monello RJ, Demarest ED, Gubler R, Heisey DM. 2018. Applying a Bayesian Weighted Surveillance Approach to Detect Chronic Wasting Disease in White-tailed Deer. Journal of Applied Ecology 55: 2944-2953. https://doi.org/10.1111/1365-2664.13178
15.1.3 Sample weights and surveillance quotas
In the CWD Data Warehouse, sample weights determine if and how much samples count towards surveillance quotas. For example, if a hunter-harvested adult male white-tailed deer is given a sample weight of 3 points, a sample from an individual with these characteristics will be worth 3 points towards the sampling quota, and in the Surveillance Activity Visualization will count towards the surveillance quota for the sub-administrative area in which the sample was collected.
Any sample that does not have a weight based on a corresponding species/sample source/age/sex segment will be given a sample weight of zero by default. Therefore, it is critical that sample weights be provided for all samples which a Provider wants to count toward surveillance quotas. Any segments not given sample weights will not be counted towards surveillance quotas.
If all segments of interest are given a sample weight of one, surveillance effort will, in effect, be a measure of the number of samples collected. This scheme may be useful, for interest, if a surveillance program counts samples, rather than points, for fulfilling surveillance quotas.
15.1.4 Additional map layers
The Annual Surveillance Collection allows Providers to include additional geospatial datasets that describe additional Surveillance-related features which they may wish to display in Visualizations. For instance, a geospatial dataset depicting disease management areas for the associated annual surveillance period can be included.
Multiple map layers may be uploaded. Disease management areas may be represented in a single uploaded map layer or in multiple separate map layers. For data management purposes, it is recommended that, in general, all features that are equivalent or have one shared theme be uploaded as a single map layer.
The additional map layers must be uploaded in GeoJSON format, a common open-source format which can be created using most geographic information system (GIS) software.
If a map layer depicting disease management areas at the beginning of a surveillance season are provided, it may be necessary to update the layer if the disease management areas change during the surveillance period. It is assumed that, for past years, the additional map layers represent the ‘final’ version of the given dataset.
In Visualizations, any feature attributes will be displayed in pop-ups.
15.2 Visualizations that can use the Annual Surveillance Collection
- Surveillance activity
- Regional ad hoc
- Provider ad hoc
15.2.0.1 Properties
An asterisk (*) denotes a required field.
| Field name | Definition | Allowed values |
|---|---|---|
| Season-year* | The one-year period spanning July 1 to June 30 of the following year (e.g., 2020-21 is the Season-year for the time period from July 1, 2020 through June 30, 2021) | YYYY-yy where YYYY is a 4-digit year and yy is the 2-digit year immediately following YYYY (e.g., 2020-21) |
| Description | Provider notes that may be useful for understanding how the annual surveillance quotas were determined | plain text |
| Risk-weighted Surveillance Quotas Model output/Optimization Model output | The model upon which surveillance quotas for the surveillance period are based; provides default values if values are not manually overridden in the surveillance quotas section | drop-down list of previously run models |
| Surveillance quotas | ||
| Sub-administrative areas | ||
| Model suggested quota | Default model recommended surveillance quotas are given next to each sub-administrative area name | integer |
| Override value | A suggested quota may be overridden by entering a value in the Override value space to the right of the suggested value | integer |
| Weights | Sample weights for all combinations of species, sex, age group, and sample source | |
| Species | The species from which the samples came | white-tailed deer, black-tailed deer, elk, moose, mule deer, red deer, reindeer, axis deer, Eid’s deer, fallow deer, muntjac, Pere David’s deer, samba deer, sika, tufted deer, caribou, hybrid, unknown |
| Sample source | The collection category, purpose, or origin of the sample | Captive cervid facility, Clinical suspect, Hunter harvest, Illegal import, Removal for crop damage, Research, Road kill, Targeted removal, Unknown |
| Weight values | Sample weights by sex and age group; if a weight is not enered for a segment, its weight will be zero | integer or decimal number |
| Display layers | Geospatial dataset(s) representing surveillance-related features, such as disease management areas | geoJSON files only |