Robust outbreak surveillance of epidemics in Sweden

Outbreak detection is of interest in connection with several diseases and syndromes. The aim is to detect the progressive increase in the incidence as soon as possible after the onset of the outbreak. A semiparametric method is applied to Swedish data on tularaemia and influenza. The method is constructed to detect a change from a constant level to a monotonically increasing incidence. If seasonal effects are present, the residuals from a model incorporating these can be used. The properties of the method are evaluated by application to Swedish data on tularaemia and influenza and by simulations. The suggested method is compared with subjective judgments as well as with other algorithms. The conclusion is that the method works well. A user-friendly computer program is described.

[1]  R. Serfling.  Methods for current statistical analysis of excess pneumonia-influenza deaths. , 1963, Public health reports.

[2]  F. T. Wright,et al.  Order restricted statistical inference , 1988 .

[3]  L. Stern,et al.  Automated outbreak detection: a quantitative retrospective analysis , 1999, Epidemiology and Infection.

[4]  P. Sebastiani,et al.  A Bayesian dynamic model for influenza surveillance , 2006, Statistics in medicine.

[5]  R. Rosychuk,et al.  Spatial Event Cluster Detection Using a Compound Poisson Distribution , 2006, Biometrics.

[6]  Explorative analysis of spatial aspects on the Swedish influenza data , 2007 .

[7]  A. Linde,et al.  Predictions by early indicators of the time and height of yearly influenza outbreaks in Sweden , 2007 .

[8]  S. Leach,et al.  Real-time epidemic forecasting for pandemic influenza , 2006, Epidemiology and Infection.

[9]  Nick Andrews,et al.  Outbreak detection: application to infectious disease surveillance , 2003 .

[10]  Eva Andersson,et al.  Semiparametric surveillance of outbreaks , 2008 .

[11]  Marianne Frisén,et al.  Principles for Multivariate Surveillance , 2007 .

[12]  E. Andersson,et al.  Effect of Dependency in Systems for Multivariate Surveillance , 2009, Commun. Stat. Simul. Comput..

[13]  P. Quénel,et al.  Sensitivity, specificity and predictive values of health service based indicators for the surveillance of influenza A epidemics. , 1994, International journal of epidemiology.

[14]  Nick Andrews,et al.  A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease , 1996 .

[15]  Paola Sebastiani,et al.  Automated Detection of Influenza Epidemics with Hidden Markov Models , 2003, IDA.

[16]  S B Thacker,et al.  Application of multiple time series analysis to the estimation of pneumonia and influenza mortality by age 1962-1983. , 1988, Statistics in medicine.

[17]  David Bock,et al.  Statistical surveillance of cyclical processes with application to turns in business cycles , 2005 .

[18]  Eva Andersson,et al.  Statistical Surveillance of Epidemics: Peak Detection of Influenza in Sweden , 2008, Biometrical journal. Biometrische Zeitschrift.

[19]  M. Frisén,et al.  Semiparametric estimation of outbreak regression , 2010 .

[20]  Andrew B. Lawson,et al.  Spatial and syndromic surveillance for public health , 2005 .

[21]  Christian Sonesson,et al.  A CUSUM framework for detection of space–time disease clusters using scan statistics , 2007, Statistics in medicine.

[22]  M. Frisén.  Statistical surveillance of business cycles , 1994 .

[23]  F. Carrat,et al.  Monitoring epidemiologic surveillance data using hidden Markov models. , 1999, Statistics in medicine.

[24]  E. S. Page.  CONTINUOUS INSPECTION SCHEMES , 1954 .

[25]  M. Kulldor,et al.  Prospective time-periodic geographical disease surveillance using a scan statistic , 2001 .

[26]  Eva Andersson,et al.  Predictions by early indicators of the time and height of the peaks of yearly influenza outbreaks in Sweden , 2008, Scandinavian journal of public health.

[27]  A. Shiryaev.  On Optimum Methods in Quickest Detection Problems , 1963 .

[28]  C. P. Farrington,et al.  The Detection of Outbreaks of Infectious Disease , 1997, Geomed.

[29]  A. R. Crathorne,et al.  Economic Control of Quality of Manufactured Product. , 1933 .

[30]  M. Kathleen Glynn,et al.  Endemic, Notifiable Bioterrorism-Related Diseases, United States, 1992–1999 , 2003, Emerging infectious diseases.

[31]  Yann Le Strat,et al.  Influenza pandemic preparedness in France: modelling the impact of interventions , 2006, Journal of Epidemiology and Community Health.

[32]  David Bock,et al.  Aspects on the control of false alarms in statistical surveillance and the impact on the return of financial decision systems , 2008 .

[33]  S. W. Roberts.  A Comparison of Some Control Chart Procedures , 1966 .

[34]  Computer-aided detection of temporal clusters of organisms reported to the Communicable Disease Surveillance Centre. , 1993 .

[35]  Eva Andersson,et al.  Detection of Turning Points in Business Cycles , 2003 .

[36]  K. Ekdahl,et al.  An evaluation and comparison of three commonly used statistical models for automatic detection of outbreaks in epidemiological data of communicable diseases , 2005, Epidemiology and Infection.

[37]  Eva Andersson,et al.  Modeling influenza incidence for the purpose of on-line monitoring , 2007, Statistical methods in medical research.