MOOvPOPsurveillance (1.5.0)

MOOvPOPsurveillance incorporates real-world disease distribution and harvest heterogeneities, and can be used to simulate disease surveillance strategies under alternate assumptions. The model can be used to determine population-specific sample sizes for prompt detection of wildlife diseases like chronic wasting disease (CWD). MOOvPOPsurveillance is initialized with model-generated ( MOOvPOP: https://www.comses.net/codebases/5585/releases/2.2.0/ ) pre-harvest deer population snapshot (abundance, sex-age composition and distribution in the landscape) for selected sampling regions in Missouri. CWD+ deer are then distributed in the landscape under one of the two assumptions: random or clustered distribution. User selects the sampling region, age-sex class wise distribution of CWD prevalence, age-sex class wise sample sizes (proportion of harvest tested) and sampling method (random or non-random). Three processes are implemented: 1) individual growth (age of every deer increases by one month), 2) non-hunting mortality (determined by age- and sex- specific monthly mortality rates), and 3) hunting mortality and CWD testing. MOOvPOPsurveillance runs for one time-step (one month), and provides following outputs: total number of adult deer (male and female) remaining in the population after harvest, number of CWD+ deer in the population, in the hunter harvest, and in the sample (deer tested for CWD).

Release Notes

Output file is created in the same folder where MOOvPOPsurveillance_v2 is located.
Parameters with constant values are now simulated using reporters.

Associated Publications

Belsare, A.V., Gompper, M.E., Keller, B.J., Sumners, J.A., Hansen, L.P., and Millspaugh, J.J. An agent-based framework for improving wildlife disease surveillance: A case study of chronic wasting disease in Missouri white-tailed deer. 2020. Ecological Modelling 417 (108919). (F1000Prime Recommended Article).

Belsare, A.V., Gompper, M.E., Keller, B.J., Sumners, J.A., Hansen, L.P., and Millspaugh, J.J. Size Matters: Sample size assessments for chronic wasting disease surveillance using an agent-based modeling framework. 2020. MethodsX 7(100953). https://doi.org/10.1016/j.mex.2020.100953.

Mysterud A, Viljugrein H, Rolandsen CM, Belsare AV. 2021 Harvest strategies for the elimination of low prevalence wildlife diseases. R. Soc. Open Sci. 8: 210124. https://doi.org/10.1098/rsos.210124