Gastrointestinal Disease Outbreak Detection Using Multiple Data Streams from Electronic Medical Records

Greene, Sharon K.; Huang, Jie; Abrams, Alan; Gilliss, Debra; Reed, Mary; Platt, Richard; Huang, Susan S.; Kulldorff, Martin

doi:10.1089/fpd.2011.1036

Cited by 19 publications

(13 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this work, we have demonstrated how these sales indictors can be used to develop a public health surveillance indicator, which provides interpretable information over time and at a high geographical resolution. We do not know of any previous efforts to develop a similar sort of indicator using food sales data, but in public health settings, surveillance systems increasingly rely on automated feeds of data captured for other purposes, such as electronic medical records, telehealth calls, and pharmaceutical sales . With respect to our substantive finding, the small amount of evidence regarding the negative association between CSD sales and median personal income is based on survey data and is difficult to compare to our results, as the measures of added sugar intake and income were different in those studies .…”

Section: Discussioncontrasting

confidence: 56%

A method for neighborhood‐level surveillance of food purchasing

Buckeridge¹,

Charland²,

Labban

et al. 2014

Annals of the New York Academy of Sciences

View full text Add to dashboard Cite

Added sugar, particularly in carbonated soft drinks (CSDs), represents a considerable proportion of caloric intake in North America. Interventions to decrease the intake of added sugar have been proposed, but monitoring their effectiveness can be difficult due to the costs and limitations of dietary surveys. We developed, assessed the accuracy of, and took an initial step toward validating an indicator of neighborhood-level purchases of CSDs using automatically captured store scanner data in Montreal, Canada, between 2008 and 2010 and census data describing neighborhood socioeconomic characteristics. Our indicator predicted total monthly neighborhood sales based on historical sales and promotions and characteristics of the stores and neighborhoods. The prediction error for monthly sales in sampled stores was low (2.2%), and we demonstrated a negative association between predicted total sales and median personal income. For each $10,000 decrease in median personal income, we observed a fivefold increase in predicted monthly sales of CSDs. This indicator can be used by public health agencies to implement automated systems for neighborhood-level monitoring of an important upstream determinant of health. Future refinement of this indicator is possible to account for factors such as store catchment areas and to incorporate nutritional information about products.

show abstract

Section: Discussioncontrasting

confidence: 56%

A method for neighborhood‐level surveillance of food purchasing

Buckeridge¹,

Charland²,

Labban

et al. 2014

Annals of the New York Academy of Sciences

View full text Add to dashboard Cite

show abstract

“…Moreover, we demonstrate the value of testing model predictions by comparing them to out-of-sample data from different electronic surveillance systems. As electronic public health systems continue to be further developed and become increasingly adopted for disease surveillance (26,27), these types of analyses will enable a more refined and timely examination of the long-term impact of vaccination and other public health interventions so that strategies to further mitigate the burden of disease can be devised. At a minimum, infectious disease models and novel surveillance systems should be judged by their ability capture major shifts in the epidemiology of the disease-such as changes to the timing, age distribution, and severity of epidemics-in response to vaccination and other interventions or shocks to the system.…”

Section: Discussionmentioning

confidence: 99%

Surveillance data confirm multiyear predictions of rotavirus dynamics in New York City

et al. 2020

View full text Add to dashboard Cite

Prediction skill is a key test of models for epidemic dynamics. However, future validation of models against out-of-sample data is rare, partly because of a lack of timely surveillance data. We address this gap by analyzing the response of rotavirus dynamics to infant vaccination. Syndromic surveillance of emergency department visits for diarrhea in New York City reveals a marked decline in diarrheal incidence among infants and young children, in line with data on rotavirus-coded hospitalizations and laboratory-confirmed cases, and a shift from annual to biennial epidemics increasingly affecting older children and adults. A published mechanistic model qualitatively predicted these patterns more than 2 years in advance. Future efforts to increase vaccination coverage may disrupt these patterns and lead to further declines in the incidence of rotavirus-attributable gastroenteritis.

show abstract

“…In this outbreak, viruses could have already disappeared from the water or been present at much diluted concentrations in the supposed case of a transient contamination at the day of water sampling. Moreover, despite improvements in the methodology used, detection of viruses in water remains challenging and NoVs are not identified in water in most suspected Norovirus related waterborne outbreaks [27]. …”

Section: Discussionmentioning

confidence: 99%

Epidemiological investigation of two parallel gastroenteritis outbreaks in school settings

et al. 2013

View full text Add to dashboard Cite

BackgroundTwo parallel gastroenteritis outbreaks occurred in an elementary school and a neighboring kindergarten in Kilkis, Northern Greece in 2012. The aim of the study was the investigation of these two parallel outbreaks as well as their possible source.MethodsTwo retrospective cohort studies were performed to identify the mode and the vehicle of transmission as well as the possible connection between them.ResultsElementary school and kindergarten populations of 79.9% (119/149) and 51.1% (23/45) respectively, participated in the study. Case definition was satisfied by 65 pupils from the elementary school and 14 from the kindergarten. For elementary school, 53 cases were considered primary cases of the outbreak and were included in the analysis. Based on the results of the multivariate analysis, consumption of tap water was the only statistically significant independent risk factor of gastroenteritis (RR = 2.34, 95% C.I.: 1.55-3.53).; a finding supported by the shape of the epidemic curve which referred to a common point source outbreak with secondary cases. For kindergarten, no statistically significant risk factor was identified, and the epidemic curve supported a person-to-person transmission according univariate analysis. Norovirus GI and GII and human Adenovirus were detected by Real Time PCR in stool samples from seven children of elementary school, but stool samples were not collected by children of the kindergarten.ConclusionsEven though the etiological agent of the outbreak was not verified, combined epidemiological and laboratory results were in favor of a waterborne viral gastroenteritis outbreak at the elementary school, followed by a person to person spread at the kindergarten.

show abstract

Gastrointestinal Disease Outbreak Detection Using Multiple Data Streams from Electronic Medical Records

Cited by 19 publications

References 24 publications

A method for neighborhood‐level surveillance of food purchasing

A method for neighborhood‐level surveillance of food purchasing

Surveillance data confirm multiyear predictions of rotavirus dynamics in New York City

Epidemiological investigation of two parallel gastroenteritis outbreaks in school settings

Contact Info

Product

Resources

About