Improving national surveillance of Lyme neuroborreliosis in Denmark through electronic reporting of specific antibody index testing from 2010 to 2012

被引:43
作者
Dessau, R. B. [1 ]
Espenhain, L. [2 ]
Molbak, K. [2 ]
Krause, T. G. [2 ]
Voldstedlund, M. [2 ]
机构
[1] Slagelse Sygehus, Dept Clin Microbiol, Slagelse, Denmark
[2] Statens Serum Inst, Dept Infect Dis Epidemiol, DK-2300 Copenhagen, Denmark
来源
EUROSURVEILLANCE | 2015年 / 20卷 / 28期
关键词
MICROBIOLOGY DATABASE MIBA; BORRELIOSIS; DIAGNOSIS; MANAGEMENT; DISEASE; EUROPE;
D O I
10.2807/1560-7917.ES2015.20.28.21184
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Our aim was to evaluate the results of automated surveillance of Lyme neuroborreliosis (LNB) in Denmark using the national microbiology database (MiBa), and to describe the epidemiology of laboratory-confirmed LNB at a national level. MiBa-based surveillance includes electronic transfer of laboratory results, in contrast to the statutory surveillance based on manually processed notifications. Antibody index (AI) testing is the recommend laboratory test to support the diagnosis of LNB in Denmark. In the period from 2010 to 2012, 217 clinical cases of LNB were notified to the statutory surveillance system, while 533 cases were reported AI positive by the MiBa system. Thirty-five unconfirmed cases (29 AI-negative and 6 not tested) were notified, but not captured by MiBa. Using MiBa, the number of reported cases was increased almost 2.5 times. Furthermore, the reporting was timelier (median lag time: 6 vs 58 days). Average annual incidence of AI-confirmed LNB in Denmark was 3.2/100,000 population and incidences stratified by municipality ranged from none to above 10/100,000. This is the first study reporting nationwide incidence of LNB using objective laboratory criteria. Laboratory-based surveillance with electronic data-transfer was more accurate, complete and timely compared to the surveillance based on manually processed notifications. We propose using AI test results for LNB surveillance instead of clinical reporting.
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页数:11
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