Abstract
The rapid detection of outbreaks is a key step in the effective control and containment of infectious diseases. In particular, the identification of cases which might be epidemiologically linked is crucial in directing outbreak-containment efforts and shaping the intervention of public health authorities. Often this requires the detection of clusters of cases whose numbers exceed those expected by a background of sporadic cases. Quantifying exceedances rapidly is particularly challenging when only few cases are typically reported in a precise location and time. To address such important public health concerns, we present a general method which can detect spatio-temporal deviations from a Poisson point process and estimate the odds of an isolate being part of a cluster. This method can be applied to diseases where detailed geographical information is available. In addition, we propose an approach to explicitly take account of delays in microbial typing. As a case study, we considered invasive group A Streptococcus infection events as recorded and typed by Public Health England from 2015 to 2020.
Funder
Health Data Research UK
National Institute for Health Research Health Protection Research Units
UK Research and Innovation
Publisher
Public Library of Science (PLoS)
Subject
Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics
Reference56 articles.
1. Updated guidelines for evaluating public health surveillance systems: recommendations from the Guidelines Working Group;R.R. German;MMWR,2001
2. The COVID-19 pandemic: a new challenge for syndromic surveillance;A.J. Elliot;Epidemiology and Infection,2020
3. Antimicrobial Resistance;H.D. Marston;Jama-Journal of the American Medical Association,2016
4. Trends in premature avertable mortality from non-communicable diseases for 195 countries and territories, 1990–2017: a population-based study;R. Martinez;Lancet Glob Health,2020
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献