Founding Customer ProgramFirst year of Vesta Online for $399 (list $595). Limited seats.See the offer →
Veterinary epidemiology & animal health

Track animal disease across farms, regions and borders.

Scan WAHIS poultry outbreak reports for space-time clusters, using GLW4 chicken numbers as the population, and map where the counts stand out.

Add Data · the Data Library's agriculture and geography categories
The Add Data dialog's Data Library list, two rows: Agriculture & Livestock (WOAH and FAO data on animal disease) and Geography & Climate (worldwide elevation, bioclimatic data and vegetation, and GRIP4 road density, the description cut off at the edge).
The challenge

Outbreak reports arrive irregularly in time and space, and you need to know which clusters stand out from what the chicken population would predict.

Step 1Import the outbreak reportsAdd WAHIS outbreaks from the Data Library, or import your own outbreak file as one dataset with coordinates or area codes for each report.How to: Importing data
Step 2Add the chicken populationPut a chicken population count on the same grid or areas as the outbreaks with Change of scale; the scan needs a count, not a density.How to: Preparing data
Step 3Scan for space-time clustersRun a space-time scan with the Poisson model: cases against population, with each cluster capped at a share of the population and of the study period.How to: Scan statistics
Step 4Deliver the clustersMap the clusters with the classes and ramp you choose, then export the results and a report for the surveillance plan.How to: Exporting data and pictures
Worked example · Avian influenza in Europe

Where and when did poultry avian influenza hit harder than the chicken population would predict?

  1. Start from the outbreaks3,443 WAHIS outbreak reports for poultry, October 2021 to September 2023; 3,375 of them fall on a 50 km grid of 1,664 cells.How to: Data Library
  2. Set the populationChicken counts from GLW4 for 2020 were aggregated onto the same grid, to serve as each cell's population.How to: Preparing data
  3. Run the scanSpace-time scan, Poisson, high rates: at most 10% of the population and 20% of the study period in one cluster, 999 replications, seed 42.How to: Scan statistics
What it found

The scan reports 11 clusters, all at p = 0.001. The most likely is 1,319 outbreaks in western France from February to June 2022, against 30.4 expected. A smaller one, 170 outbreaks in east-central Europe in April and May 2022, has a relative risk of 205.

A scan finds where and when outbreaks cluster, not why. Rerun at a smaller maximum before calling a cluster local or short-lived.

Avian influenza in Europe · space-time clusters, April 2022
The sample project's own thumbnail: a grid map of Europe with the largest space-time cluster of outbreaks highlighted in western France.
Open the sample projectRead-only · no sign-in
Methods
Space-time scanKrigingRegression and GWR
Data
WAHISGLW livestockFAOSTATYour farm data
Evidence
Published research by BioMedware scientistsEvaluation of the risk of neighbourhood infection of H7N1 highly pathogenic avian influenza in Italy using Q statisticMulatti, P., Kitron, U., Jacquez, G.M., et al. Preventive Veterinary Medicine 95, 2010.
See every sample project
Common use cases

Track your next outbreak across farms and borders.

Analyze your outbreak or herd data, or start from WAHIS, in a 14-day trial. Bring your data to an optional kickoff call if you want help.

14-day trial · Optional kickoff call · No credit card