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).
MOOvPOPsurveillance v2.2.0: can read data directly from the ‘data’ folder and write result files in the ‘results’ folder.
|Version||Submitter||First published||Last modified||Status|
|2.2.0||Aniruddha Belsare||Tue May 12 16:37:24 2020||Tue May 12 16:37:24 2020||Published|
|2.1.2||Aniruddha Belsare||Thu Aug 8 21:31:35 2019||Thu Aug 8 21:31:35 2019||Published https://doi.org/10.25937/8hpz-9y96|
|1.8.0||Aniruddha Belsare||Thu Jan 18 22:35:11 2018||Thu Jan 18 22:35:11 2018||Published Peer Reviewed|
|1.7.0||Aniruddha Belsare||Mon Nov 27 02:22:12 2017||Mon Nov 27 02:22:12 2017||Published|
|1.6.0||Aniruddha Belsare||Sun Nov 26 23:19:23 2017||Sun Nov 26 23:19:23 2017||Published|
|1.5.0||Aniruddha Belsare||Sun Nov 26 23:12:05 2017||Sun Nov 26 23:12:05 2017||Published|
|1.4.0||Aniruddha Belsare||Sun Nov 26 22:30:19 2017||Sun Nov 26 22:30:19 2017||Published|
|1.3.0||Aniruddha Belsare||Mon Nov 6 18:55:51 2017||Mon Nov 6 18:55:51 2017||Published|
|1.2.0||Aniruddha Belsare||Mon Aug 14 04:52:53 2017||Mon Aug 14 04:52:53 2017||Published|
|1.1.0||Aniruddha Belsare||Tue Apr 4 21:03:28 2017||Tue Apr 4 21:03:28 2017||Published|
|1.0.0||Aniruddha Belsare||Tue Apr 4 17:03:40 2017||Tue Apr 4 17:03:40 2017||Published|