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Predicting an Epidemic

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Predicting an Epidemic

A Quantitative Assessment of TSE Sampling Data to Predict Outbreak Magnitude

Aspen Shackleford

HONR299J

- Linked to BSE
- Unknown number of individuals who may be infected
- Iatrogenic contamination

The National CJD Research & Surveillance Unit. (2014). Variant Creutzfeldt-Jakob Disease current data (March 2014) [Data file]. Retrieved from http://www.cjd.ed.ac.uk/documents/worldfigs.pdf

- Reporting
- Statistical Models

- Age of onset of clinical BSE symptoms was sampled
- Results
- Decrease in peak age of onset
- Led to further investigation of under-reporting

Dealler, S.F. & Kent, J.T. (1995). BSE: an update on the statistical evidence. British Food Journal, 97 (8), 3-18. http://docserver.ingentaconnect.com

- MAFF Requirements
- 2 visits by a veterinarian
- Slaughter and send in tissue sample

- Case denial
- Dealler and Kent Suspicion
- Paul Brown’s predictions

- Farmer Initiative

Brown, Paul. (2004). Mad Cow Disease in cattle and human beings: Bovine spongiform encephalopathy provides a case study in how to manage risks while still learning facts. American Scientist, 92 (4), 334-341. http://www.jstor.org/stable/27858422

- MAFF Requirements
- 2 visits by a veterinarian
- Slaughter and send in tissue sample

- Case denial
- Dealler and Kent Suspicion
- Paul Brown’s predictions

- Farmer Initiative

- Based upon data collection year (i) and bovine age (j)
- Follows a Poisson Distribution
- Predicts the expected number of deaths at age j in year i from 1984 to 2001
- Reporting effect and parameters compensated for under-reporting

- Requirements
- Used to determine the frequency of an abnormal event
- Graphical representation
- r-curve closer to zero signifies a rare event

The Warring States Project. (2007, August 24). Statistics: The Poisson distribution. Retrieved from http://www.umass.edu/wsp/resources/poisson/index.html

- Based upon data collection year and bovine age
- Follows a Poisson Distribution
- Predicts the expected number of deaths at age j in year i from 1984 to 2001
- Reporting effect and parameters compensated for under-reporting

- Model predictions from 1984 through 2001 (solid line)
- Actual reports from 1984 to 1993 (dotted line)
- Under-reporting
- Peak in 1994
- Overlap

Dealler, S.F. & Kent, J.T. (1995). BSE: an update on the statistical evidence. British Food Journal, 97 (8), 3-18. http://docserver.ingentaconnect.com

- Scrapie
- Within-flock model
- Sheep age
- Genotypes: ARR (0.45), ARQ (0.5), VRQ (0.05)

- Between-flock model

- Within-flock model
- Model determines duration and magnitude of an outbreak

- N - flock-size
- n - geometric mean of the size distribution
- c1 , c2 – constants

Hagenaars, T.J, Donnelly, C.A., & Ferguson, N.M. (2006). Epidemiological analysis of data for scrapie in Great Britain. Epidemiology and Infection, 134 (2), 359-367. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2870388/

- Large case rate
- Case rate less than 5 per year
- Average number of cases: 2.8 per year

Hagenaars, T.J, Donnelly, C.A., & Ferguson, N.M. (2006). Epidemiological analysis of data for scrapie in Great Britain. Epidemiology and Infection, 134 (2), 359-367. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2870388/

- γ – the rate of recovery of affected farms
- λ - the rate per capita that a farm becomes affected
- t - time (in years)
- at>0 - the number of sheep flocks that have experienced at least one BSE case since the starting year

Hagenaars, T.J, Donnelly, C.A., & Ferguson, N.M. (2006). Epidemiological analysis of data for scrapie in Great Britain. Epidemiology and Infection, 134 (2), 359-367. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2870388/

- Low basic reproduction rate
- High basic reproduction rate
- Breeding for resistance
- ARR/ARR genotype

- Changes in management

- Statistical models are widely used
- Statistical models offer information that uses parameters and constraints that model real life
- The predictions of statistical models can be used to make decisions about how to best prevent an outbreak that threatens human and animal populations