Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms

Razvan G. Romanescu; Rob Deardon

doi:10.1515/scid-2018-0004

Article

Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms

Razvan G. Romanescu and Rob Deardon

Published/Copyright: June 22, 2019

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From the journal Statistical Communications in Infectious Diseases Volume 12 Issue 1

Abstract

Properties of statistical alarms have been well studied for simple disease surveillance models, such as normally distributed incidence rates with a sudden or gradual shift in mean at the start of an outbreak. It is known, however, that outbreak dynamics in human populations depend significantly on the heterogeneity of the underlying contact network. The rate of change in incidence for a disease such as influenza peaks early on during the outbreak, when the most highly connected individuals get infected, and declines as the average number of connections in the remaining susceptible population drops. Alarm systems currently in use for detecting the start of influenza seasons generally ignore this mechanism of disease spread, and, as a result, will miss out on some early warning signals. We investigate the performance of various alarms on epidemics simulated from an undirected network model with a power law degree distribution for a pathogen with a relatively short infectious period. We propose simple custom alarms for the disease system considered, and show that they can detect a change in the process sooner than some traditional alarms. Finally, we test our methods on observed rates of influenza-like illness from two sentinel providers (one French, one Spanish) to illustrate their use in the early detection of the flu season.

Keywords: surveillance; influenza; statistical alarms; epidemic models; power law networks

Funding statement: This work was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Received: 2018-05-19

Revised: 2019-03-27

Accepted: 2019-05-28

Published Online: 2019-06-22

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Articles in the same Issue

https://doi.org/10.1515/scid-2018-0004

Keywords for this article

surveillance; influenza; statistical alarms; epidemic models; power law networks