Every community is different. What looks safe for one place might not be for another.
With federal and provincial agencies balancing multiple regions, we wanted to help smaller communities, towns, villages, and rural areas plan and respond should the worst happen. To do this, we've built a COVID 19 response simulation. It forecasts what might happen in specific towns and surrounding areas if an outbreak occurs. We don't think any other tool like this exists specifically for small towns, which is why it's important to make this widely available.
Simulation software is expensive and we're a small two-person team. We're also currently working for free. To continue building the simulation and to get it to those who need it, we need your support. Funds will go towards paying for simulation licenses and related software, computing power and equipment, travel to key stakeholders, Kezia and Dylan's wages (we enjoy eating too), and other simulation-related costs. The more we raise the more time we can dedicate to the simulation and the more we can subsidize the projects that use it.
We hope you can contribute -- even $5 helps. Equally important is sharing this work with friends and family in public health and administration. This simulation is the most useful in front of people who can use it and make decisions. If you know them, please help us get it to them. You can even show them an interactive demo here (hosted by AnyLogic) , which lets you see what might happen if an outbreak struck the major employers in a small town.
We're extremely grateful for any help you can provide. Thank you enormously, stay safe, and keep those hands washed.
Dylan & Kezia
Our anticipated near-future development items if we raise our goal are as follows. The priority and depth to which we pursue each item will be dependent on the funds raised:
1. Produce experiments to formally quantify the effects of interventions, e.g. run the simulation 30 times, calculate median values, report on distribution of outcomes. Formally document any outcomes and their relation to existing studies.
2. Improve the ease with which simulation users can create input datasets, e.g. the GIS regions, populations, businesses, schools etc. for a town and surrounding rural municipalities. We do much of this manually, but have not formally documented the process and have only partial automation.
3. Reach out to contacts in nearby / known communities to find early adopters.
4. Analyze and incorporate data from our survey .
5. Code cleanup
- Steph Stammel
- Charles Fowler
- Robyn Peterie
- Rheanne Haines
Fundraising team: Luminesim Simulation and Analytics (2)
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