Testing behaviour and positivity for SARS-CoV-2 infection: insights from web-based participatory surveillance in the Netherlands.

Testing behaviour and positivity for SARS-CoV-2 infection: insights from web-based participatory surveillance in the Netherlands.
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DOI:
10.1136/bmjopen-2021-056077
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发表时间:
2021-12-21
期刊:
影响因子:
2.9
通讯作者:
van Hoek AJ
van Hoek AJ
中科院分区:
医学3区
文献类型:
--
作者:
McDonald SA;Soetens LC;Schipper CMA;Friesema I;van den Wijngaard CC;Teirlinck A;Neppelenbroek N;van den Hof S;Wallinga J;van Hoek AJ

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我们的目标是通过确定哪些社会人口和家庭因素与较低的检测倾向相关,以及如果检测结果呈阳性的较高风险,来确定具有SARS-CoV-2感染高危但不太可能出现检测的人群。来自荷兰普通民众的基于互联网的参与性监测数据。分析了在5个月期间(2020年11月17日至2021年4月18日)从总共12名 026参与者那里收集的每周调查数据,这些参与者至少贡献了2次 每周调查。使用二项式结果的广义估计方程进行了多变量分析,以估计与参与者和家庭特征相关的测试和测试阳性的调整后的OR。男性(ORT:0.92;ORP:1.3)、20岁(ORT:0.89;ORP:1.27)、50岁(ORT:0.94;ORP:1.06)和65岁以上(ORT:0.78;ORP:1.24)、糖尿病患者(ORT:0.97;ORP:1.06)和销售/行政人员(ORT:0.93;ORP:1.90)为低检测倾向/高检测阳性因素。使用这种方法确定的因素可以帮助确定潜在目标群体,以改善沟通并鼓励有症状的人进行检测,从而提高检测的有效性,这对于应对新冠肺炎大流行和长期公共卫生战略至关重要。
We aimed to identify populations at a high risk for SARS-CoV-2 infection but who are less likely to present for testing, by determining which sociodemographic and household factors are associated with a lower propensity to be tested and, if tested, with a higher risk of a positive test result. Internet-based participatory surveillance data from the general population of the Netherlands. Weekly survey data collected over a 5-month period (17 November 2020 to 18 April 2021) from a total of 12 026 participants who had contributed at least 2 weekly surveys was analysed. Multivariable analyses using generalised estimating equations for binomial outcomes were conducted to estimate the adjusted ORs of testing and of test positivity associated with participant and household characteristics. Male sex (adjusted OR for testing (ORt): 0.92; adjusted OR for positivity (ORp): 1.30, age groups<20 (ORt: 0.89; ORp: 1.27), 50–64 years (ORt: 0.94; ORp: 1.06) and 65+ years (ORt: 0.78; ORp: 1.24), diabetics (ORt: 0.97; ORp: 1.06) and sales/administrative employees (ORt: 0.93; ORp: 1.90) were distinguished as lower test propensity/higher test positivity factors. The factors identified using this approach can help identify potential target groups for improving communication and encouraging testing among those with symptoms, and thus increase the effectiveness of testing, which is essential for the response to the COVID-19 pandemic and for public health strategies in the longer term.
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