Work

Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting

Year: 2020

Type: article

Abstract: We evaluated the performance of X-bar chart, exponentially weighted moving average, and C3 cumulative sums aberration detection algorithms for acute diarrheal disease syndromic surveillance at naval sites in Peru during 2007–2011. The 3 algorithms’ detection sensitivity was 100%, specificity was 97%–99%, and positive predictive value was 27%–46%.

Source: Emerging infectious diseases

DOI: 10.3201/eid09.191315

Authors: Emily Alsentzer, Sarah-Blythe Ballard, Joan Neyra, Delphis M. Vera, Victor B. Osorio, Jose Quispe, David L. Blazes, Luis Loayza

Institutions: Uniformed Services University of the Health Sciences, Massachusetts Institute of Technology

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4236610380

FWCI: 0.18

Cites: 9

Cited by: 2

Related to: 10