Predicting an epidemic
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Predicting an Epidemic. A Quantitative Assessment of TSE Sampling Data to Predict Outbreak Magnitude Aspen Shackleford HONR299J. Variant Creutzfeldt-Jakob Disease (vCJD). Linked to BSE Unknown number of individuals who may be infected Iatrogenic contamination.

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Predicting an Epidemic

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Predicting an epidemic

Predicting an Epidemic

A Quantitative Assessment of TSE Sampling Data to Predict Outbreak Magnitude

Aspen Shackleford

HONR299J


Variant creutzfeldt jakob disease vcjd

Variant Creutzfeldt-Jakob Disease (vCJD)

  • 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


How are outbreak predictions made

How are outbreak predictions made?

  • Reporting

  • Statistical Models


Dealler kent 1995

Dealler & Kent, 1995

  • 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


Under reporting

Under-Reporting

  • 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


Paul brown s prediction

Paul Brown’s Prediction

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


Under reporting1

Under-Reporting

  • 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


Dealler and kent statistical model 1995

Dealler and Kent Statistical Model (1995)

  • 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


Poisson distribution

Poisson Distribution

  • 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


Dealler and kent statistical model 19951

Dealler and Kent Statistical Model (1995)

  • 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


Results

Results

  • 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


Hagenaars et al 2006

Hagenaars et al., 2006

  • Scrapie

    • Within-flock model

      • Sheep age

      • Genotypes: ARR (0.45), ARQ (0.5), VRQ (0.05)

    • Between-flock model

  • Model determines duration and magnitude of an outbreak


Predicting an epidemic

  • 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/


Within flock results

Within Flock Results

  • 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/


Predicting an epidemic

  • 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/


Between flock results

Between Flock Results

  • Low basic reproduction rate

  • High basic reproduction rate

  • Breeding for resistance

    • ARR/ARR genotype

  • Changes in management

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/


Conclusion

Conclusion

  • 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


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