TY - JOUR
T1 - Biosurveillance of emerging biothreats using scalable genotype clustering
AU - Gallego, Blanca
AU - Sintchenko, Vitali
AU - Wang, Qinning
AU - Hiley, Lester
AU - Gilbert, Gwendolyn L.
AU - Coiera, Enrico
PY - 2009/2
Y1 - 2009/2
N2 - Developments in molecular fingerprinting of pathogens with epidemic potential have offered new opportunities for improving detection and monitoring of biothreats. However, the lack of scalable definitions for infectious disease clustering presents a barrier for effective use and evaluation of new data types for early warning systems. A novel working definition of an outbreak based on temporal and spatial clustering of molecular genotypes is introduced in this paper. It provides an unambiguous way of clustering of causative pathogens and is adjustable to local disease prevalence and availability of public health resources. The performance of this definition in prospective surveillance is assessed in the context of community outbreaks of food-borne salmonellosis. Molecular fingerprinting augmented with the scalable clustering allows the detection of more than 50% of the potential outbreaks before they reach the midpoint of the cluster duration. Clustering in time by imposing restrictions on intervals between collection dates results in a smaller number of outbreaks but does not significantly affect the timeliness of detection. Clustering in space and time by imposing restrictions on the spatial and temporal distance between cases results in a further reduction in the number of outbreaks and decreases the overall efficiency of prospective detection. Innovative bacterial genotyping technologies can enhance early warning systems for public health by aiding the detection of moderate and small epidemics.
AB - Developments in molecular fingerprinting of pathogens with epidemic potential have offered new opportunities for improving detection and monitoring of biothreats. However, the lack of scalable definitions for infectious disease clustering presents a barrier for effective use and evaluation of new data types for early warning systems. A novel working definition of an outbreak based on temporal and spatial clustering of molecular genotypes is introduced in this paper. It provides an unambiguous way of clustering of causative pathogens and is adjustable to local disease prevalence and availability of public health resources. The performance of this definition in prospective surveillance is assessed in the context of community outbreaks of food-borne salmonellosis. Molecular fingerprinting augmented with the scalable clustering allows the detection of more than 50% of the potential outbreaks before they reach the midpoint of the cluster duration. Clustering in time by imposing restrictions on intervals between collection dates results in a smaller number of outbreaks but does not significantly affect the timeliness of detection. Clustering in space and time by imposing restrictions on the spatial and temporal distance between cases results in a further reduction in the number of outbreaks and decreases the overall efficiency of prospective detection. Innovative bacterial genotyping technologies can enhance early warning systems for public health by aiding the detection of moderate and small epidemics.
UR - http://www.scopus.com/inward/record.url?scp=60049092514&partnerID=8YFLogxK
UR - http://purl.org/au-research/grants/arc/LP0667531
U2 - 10.1016/j.jbi.2008.07.002
DO - 10.1016/j.jbi.2008.07.002
M3 - Article
C2 - 18723122
AN - SCOPUS:60049092514
SN - 1532-0464
VL - 42
SP - 66
EP - 73
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
IS - 1
ER -