Back to Search Start Over

Lyme Disease Surveillance Using Sampling Estimation: Evaluation of an Alternative Methodology in New York State.

Authors :
Lukacik G
White J
Noonan-Toly C
DiDonato C
Backenson PB
Source :
Zoonoses and public health [Zoonoses Public Health] 2018 Mar; Vol. 65 (2), pp. 260-265. Date of Electronic Publication: 2016 Feb 29.
Publication Year :
2018

Abstract

In the 14-year period from 1993 to 2006, New York State (NYS) accounted for over one-quarter (27.1%) of all confirmed Lyme disease (LD) cases in the United States. During that time period, a nine-county area in south-east NYS accounted for 90.6% of the reported LD cases in the state. Based on concerns related to diminishing resources at both the state and local level and the increasing burden of traditional LD surveillance, the NYS Department of Health (DOH) sought to develop an alternative to traditional surveillance that would reduce the investigative workload while maintaining the ability to track LD trends by developing a system to estimate county-level LD cases based on a 20% random sample of positive laboratory reports. Estimates from this system were compared to observed cases from traditional surveillance for select counties in 2007-2009 and 2011. There were no significant differences between the two methodologies in six of nine evaluations conducted. In addition, in 93 of 98 (94.9%) demographic, symptom and other variable proportion comparisons made between the two methodologies in 2009 and 2011, there were no significant differences found. Overall, using sampling estimates was accurate and efficient in estimating LD cases at the county level. Use of case estimates for LD should be considered as a useful surveillance alternative by health policy makers for states with endemic LD.<br /> (© 2016 Blackwell Verlag GmbH.)

Details

Language :
English
ISSN :
1863-2378
Volume :
65
Issue :
2
Database :
MEDLINE
Journal :
Zoonoses and public health
Publication Type :
Academic Journal
Accession number :
26924579
Full Text :
https://doi.org/10.1111/zph.12261