Detection of Infectious Disease Outbreaks From Laboratory Data With Reporting Delays

Journal of the American Statistical Association

Volumn 111, Issue 514, 2016, Pages 488-499

  Noufaily, Angela ^a   Farrington, Paddy ^a   Garthwaite, Paul ^a   Enki, Doyo Gragn ^a   Andrews, Nick ^a   Charlett, Andre ^a  

^a UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

Aberrance; Epidemic; Exceedance; Infection; Quasi Poisson; Surveillance

Indexed keywords

EID: 84983260721     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.2015.1119047     Document Type: Article

References (25)

1. N.G.Becker, L.F.Watson, and J.B.Carlin, (1991), “A Method of Non-Parametric Back-Projection and its Application to AIDS Data,” Statistics in Medicine, 10, 1527–1542.
2. R.Brookmeyer, and A.Damiano, (1989), “Statistical Methods for Short-term Projections of AIDS Incidence,” Statistics in Medicine, 8, 23–34.
3. R.Brookmeyer, and M.H.Gail, (1988), “A Method for Obtaining Short-term Projections and Lower Bounds on the Size of the AIDS Epidemic,” Journal of the American Statistical Association, 83, 301–308.
4. R.Brookmeyer, and J.Liao, (1990), “The Analysis of Delays in Disease Reporting:Methods and Results for the Acquired Immunodeficiency Syndrome,” American Journal of Epidemiology, 132, 355–365.
5. D.L.Buckeridge, H.S.Burkom, M.Campbell, W.R.Hogan, and A.Moore, (2005), “Algorithms for Rapid Outbreak Detection:A Research Synthesis,” Journal of Biomedical Informatics, 38, 99–113.
6. D.R.Cox, and G.F.Medley, (1989), “A Process of Events With Notification Delay and the Forecasting of AIDS,” Philosophical Transactions of the Royal Society of London, 325, 135–145.
7. T.Donker, M.van Boven, W.M.van Ballegooijen, van’t T.M.Klooster, C.C.Wielders, and J.Wallinga, (2011), “Nowcasting Pandemic Influenza A/H1N1 2009 Hospitalizations in the Netherlands,” European Journal of Epidemiology, 26, 195–201.
8. D.G.Enki, A.Noufaily, P.H.Garthwaite, N.J.Andrews, A.Charlett, C.Lane, and C.P.Farrington, (2013), “Automated Biosurveillance Data From England and Wales, 1991–2011,” Emerging Infectious Diseases, 19, 35–42.
9. C.P.Farrington, N.J.Andrews, A.D.Beale, and M.A.Catchpole, (1996), “A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease,” Journal of the Royal Statistical Society, Series A, 159, 547–563.
10. T.A.Green, (1998), “Using Surveillance Data to Monitor Trends in the AIDS Epidemic,” Statistics in Medicine, 17, 143–154.
11. A.Guillou, M.Kratz, and Y.L.Strat, (2014), “An Extreme Value Theory Approach for the Early Detection of Time Clusters. A Simulation-Based Assessment and an Illustration to the Surveillance of Salmonella,” Statistics in Medicine, 33, 5015–5027.
12. M.Hohle, and an M.der Heiden, (2014), “Bayesian Nowcasting During the STEC O104:H4 Outbreak in Germany, 2011,” Biometrics, 70, 993–1002.
13. A.Hulth, N.Andrews, S.Ethelberg, J.Dreesman, D.Faensen, W.van Pelt, and J.Schnitzler, (2010), “Practical Usage of Computer-Supported Outbreak Detection in Five European Countries,” Eurosurveillance, 15, Article 3.
14. G.Jones, S.L.Hello, N.J.da Silva, V.Vaillant, H.de Valk, F.X.Weill, and Y.L.Strat, (2014), “The French Human Salmonella Surveillance System:Evaluation of Timeliness of Laboratory Reporting and Factors Associated With Delays, 2007 to 2011,” Eurosurveillance, Surveillance and Outbreak Reports, 19, 206–264.
15. J.F.Lawless, (1994), “Adjustments for Reporting Delays and the Prediction of Occurred but not Reported Events,” Canadian Journal of Statistics, 22, 15–31.
16. D.N.Midthune, M.P.Fay, L.X.Clegg, and E.J.Feuer, (2005), “Modeling Reporting Delays and Reporting Corrections in Cancer Registry Data,” Journal of the American Statistical Association, 100, 61–69.
17. A.Noufaily, D.G.Enki, C.P.Farrington, P.Garthwaite, N.Andrews, and A.Charlett, (2013), “An Improved Algorithm for Outbreak Detection in Multiple Surveillance Systems,” Statistics in Medicine, 32, 1206–1222.
18. A.Noufaily, Y.G.Weldeselassie, D.G.Enki, P.Garthwaite, N.Andrews, A.Charlett, and C.P.Farrington, (2015), “Modeling Reporting Delays for Outbreak Detection in Infectious Disease Data,” Journal of the Royal Statistical Society, Series A, 178, 205–222.
19. M.Pagano, X.M.Tu, V.D.Gruttola, and S.MaWhinney, (1994), “Regression Analysis of Censored and Truncated Data:Estimating Reporting-delay Distributions and AIDS Incidence From Surveillance Data,” Biometrics, 50, 1203–1214.
20. P.S.Rosenberg, and M.H.Gail, (1991), “Backcalculation of Flexible Linear Models of the Human Immunodeficiency Virus Infection Curve,” Applied Statistics, 40, 269–282.
21. M.Salmon, D.Schumacher, K.Stark, and M.Hohle, (2015), “Bayesian Outbreak Detection in the Presence of Reporting Delays,” Biometrical Journal, 57, 1–17.
22. W.A.Shewhart, (1931), Economic Control of Quality of Manufactured Product, Princeton:Van NostrandReinhold.
23. G.Shmueli, and H.Burkom, (2010), “Statistical Challenges Facing Early Outbreak Detection in Biosurveillance,” Technometrics, 52, 39–51.
24. C.Sonesson, and D.Bock, (2003), “A Review and Discussion of Prospective Statistical Surveillance in Public Health,” Journal of the Royal Statistical Society, Series A, 166, 5–21.
25. S.Unkel, C.P.Farrington, P.H.Garthwaite, C.Robertson, and N.Andrews, (2012), “Statistical Methods for the Prospective Detection of Infectious Disease Outbreaks:A Review,” Journal of the Royal Statistical Society, Series A, 175, 49–82.