Eclipse software samples

Pigs were fattened for days. According to Methner et al. Transport was assumed to take one day. The possibility of infection during transport and lairage was not calculated. There are several publications with models for the transmission of pathogens during lairage and slaughter. These are usually complex models with compartments different from the standard SIR compartment models.

Van der Gaag et al. This model is currently not yet implemented in STEM and this is why only the prevalence of Salmonella in pork was used. In , 2. The contamination rates can be calculated from these values:.

The transformation of pig to pork was set to , meaning that a fattened pig — weighing about kg on average — was processed to pieces of pork g each.

An increase of the Salmonella concentration due to inappropriate cooling and the possibility that not all units of pork might be sold were not taken into account.

In , 31, human salmonellosis cases were reported in Germany RKI, However, this model computes the spread of foodborne Salmonella for only a part of Germany with much smaller numbers of pigs for only a part of the year. This is why the number of infected humans is much smaller in the described model. A window opened showing the chosen country with nodes containing the area and the human population.

By right clicking we added a node, named it, and defined its size. Next we right clicked this new node and added population labels for each population we wanted to assign to this node. Because pigs are processed to pork, these nodes need labels for both pig and pork populations.

Pork migrates from slaughterhouses to retail and from there to the counties. This way all the retail facilities were connected to slaughterhouses on one side and to county nodes on the other side. Here we entered the data found in the literature, dragged the diseases into our model here: PopulationModelGER. When we entered the correct name of the source and target population, the diseases were chosen automatically if there is only one disease like in this description.

After we finished this population transformer, we defined another one for the second slaughterhouse here: SlaughterBR. In this case we did not pick a target location because we assumed the whole human population should be able to eat pork. As always, when we built the scenario, we included a sequencer and defined a disease initializer. The location was the pig farm. In our scenario, the pigs fattened for days with no migration of pigs from the pig farm to the slaughterhouses until day To reflect this, we used a migration trigger with a predicate days and migration modifiers definition of the proportion of pigs migrating to either slaughterhouse.

Identification and quantification of risk factors regarding Salmonella spp. Int J Food Microbiol. Impact on human health of Salmonella spp. Hartung, M. Salmonella status of pigs at slaughter--bacteriological and serological analysis. Epub Aug 3. Soumpasis I, Butler F. Development and application of a stochastic epidemic model for the transmission of Salmonella Typhimurium at the farm level of the pork production chain.

Risk Anal. Epub Jul Steinbach G, Kroell U. Dtsch Tierarztl Wochenschr. Van der Gaag, M. A state-transition simulation model for the spread of Salmonella in the pork supply chain. The Migratory Birds project demonstrates how the Seasonal Migration Edge Graph Generator can be used together with a Seasonal Migratory Population Model to create models where animals migrate seasonally between regions.

The evacuation demonstration project aims to demonstrate how interventions can be used in STEM to control an outbreak. In this simple example, we have two regions Square 0 and Square 1. Hence the total population count is preserved in each region.

Region 1 has a hospital. The hospital is represented by a intervention label inside the HospitalGraph. You'll see that the hospital has the capacity to vaccinate 50 people per time step daily. In the scenario "NoEvacuationsScenario", an outbreak occurs in region 0 and no intervention takes place. Via migration the disease also spreads to region 1. In "EvacuationScenario", after more than 5 cases per day occurs in region 0, an intervention policy is triggered.

The policy does the following:. Once the number of cases in region 0 drops below 5 per day again, migration and vaccination are set back to their original settings. In the figure below, you'll see that the policy triggers around time step 6 and the population numbers starts dropping in region 0 due to evacuation. Correspondingly, the population increases in region 1. When the outbreak is under control at around time step 25, the migration is balanced out and the population numbers converges back towards the original values.

If we look at the cumulative disease deaths occurring in both scenarios, the figure below indicates that by evacuating and increasing vaccination capacity, a total of about 65 lives are saved.

This downloadable scenario demonstrates how the earth science data can be used to generate seasonal mosquito density estimates in Asia. You can easily reconfigure this scenario for the entire globe or for other selected regions.

The screenshot below shows the Asia Mosquito Model running as downloaded. On the right hand side in the Project Explorer the scenario is expanded to show how it is constructed. The model contains the prebuild Global Geography Model Human for Asia along with its polygons, nodes, and edges, as well as the corresponding Asia earth science model this in turn contains rainfall, temperature, vegetation, and elevation data for the same regions of Asia.

These, together with an Anopheles Initializer, are contained in a parent model simply called Asia. The parent model along with the STEM population model for Anopheles are placed in the parent scenario. Users may easily modify this to study other regions.

In the future the Anopheles model will be used as part of a complete vector disease model for Malaria and other conditions. Notice: You probably need to change the reference population and reference population density in the STEM preferences to ensure the map colors are not saturated.

When STEM determines the intensity of the color used to fill regions on the map, it takes the actual count in case the number of Anopheles mosquitos and divides by the reference population. The number between 0 and 1 if it's larger than 1 it's set to 1 determines the intensity of the color. See screenshot below for numbers that are reasonable for this particular scenario:. In this example, we have been given historical incidence data for a disease with unknown epi parameters and we want to try and determine what those parameters are.

All we know is that the first cases showed up in Stockholm. We decide to try and fit an SIR model to the incidence data, and we would like to determine three unknown parameters:. Given these two parameters it's possible to determine the reproductive number of the disease, an important epi parameter.

Next, open the "Experiments" folder in the project explorer and double click "AutomatedExperiment. Select the top node in the editor and look at its properties in the properties view.

You will notice that the automatic experiment will run a scenario called "AutomatedExperiment. Generate complex region definitions easy and fast, take full control calculating reservoir regions using the reservoir properties through a series of logical mathematical operations directly from the data set. New insights can be gained through the utilization of the secure, cloud-based environment as increased accessibility and flexibility to more science in the ECLIPSE simulator is automatically and instantly at your fingertips.

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Top New Features. Easy and flexible grid operations capabilities to better define reservoir regions Generate complex region definitions easy and fast, take full control calculating reservoir regions using the reservoir properties through a series of logical mathematical operations directly from the data set.

Training Courses. View Training Courses. Petrel Reservoir Engineering View Product. NOTE: these instructions will only work for Eclipse 3.

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