Comparison of Virus Watch COVID-19 Positivity, Incidence, and Hospitalization Rates With Other Surveillance Systems: Surveillance Study.

IF 3.9 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Wing Lam Erica Fong, Vincent Grigori Nguyen, Sarah Beale, Thomas E Byrne, Cyril Geismar, Ellen Fragaszy, Jana Kovar, Alexei Yavlinsky, Ibrahim Abubakar, Andrew C Hayward, Robert W Aldridge
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引用次数: 0

Abstract

Background: Effective disease surveillance is essential for understanding pathogens' epidemiology, detecting outbreaks, and enabling timely public health responses. In the United Kingdom, large-scale studies, such as the Office for National Statistics COVID-19 Infection Survey (CIS), have monitored SARS-CoV-2 transmission but required significant resources, making them challenging to sustain when pandemic-specific funding ends and also in resource-limited settings. In contrast, the Virus Watch study, at lower cost, relied on self-reported and linked national testing data as well as symptomatic testing, while Severe Acute Respiratory Infections Watch (SARI) leveraged hospital data for cost-effective surveillance.

Objective: This study aimed to evaluate the effectiveness of Virus Watch as a surveillance system in monitoring COVID-19 positivity, incidence, and hospitalization rates in England and Wales, using data from the CIS and SARI as benchmarks for comparison, while considering the key differences in the study designs, including recruitment strategies, incentives, and testing criteria.

Methods: We used the Virus Watch prospective community cohort study to estimate COVID-19 positivity, incidence, and hospitalization rates in England and Wales from June 2020 to March 2023. Rate estimates were compared with CIS modeled positivity and incidence rates, and with SARI COVID-19 hospitalization rates. Global synchrony between datasets was measured using overall Spearman ⍴ and local synchrony using 9-week rolling Spearman ⍴. For England, comparisons with CIS estimates used Virus Watch rates calculated with and without linked national testing data. Positivity rates were also assessed overall and separately before and after the end of free national testing.

Results: A total of 58,628 participants were recruited into the Virus Watch study, of whom 52,526 (89.6%) were resident in England and 1532 (2.6%) in Wales; region was missing for the remainder. Virus Watch-estimated COVID-19 positivity and incidence rates in England, calculated with and without linked testing data, showed strong global synchrony with CIS estimates (positivity ⍴: 0.91 and 0.90; both P<.001 and incidence ⍴: 0.92 and 0.90; both P<.001) and strong local synchrony (positivity ⍴: median 0.75, IQR 0.53-0.85 and median 0.67, IQR 0.47-0.83, and incidence ⍴: median 0.76, IQR 0.49-0.88 and median 0.66, IQR 0.45-0.82), despite having lower absolute values. Global and local synchrony of positivity rates were similar for periods before and after the end of free national testing, although the difference between Virus Watch and CIS estimates was greater post-free testing. COVID-19 hospitalization rates were also lower and less synchronized with SARI estimates. In Wales, Virus Watch estimates exhibited greater variability (positivity ρ: 0.75, P<.001; incidence rate ρ: 0.85, P<.001) and lower local synchrony (positivity ρ: median 0.61, IQR 0.34-0.74, and incidence ρ: median 0.52, IQR 0.38-0.71) compared to England.

Conclusions: Our results highlight the effectiveness of the Virus Watch approach in providing accurate estimates of COVID-19 positivity and incidence rates, even in the absence of national surveillance systems. This low-cost method can be adapted to various settings, particularly low-resource ones, to strengthen public health surveillance and inform timely interventions.

COVID-19病毒监测阳性、发病率和住院率与其他监测系统的比较:监测研究
背景:有效的疾病监测对于了解病原体流行病学、发现疫情和及时作出公共卫生反应至关重要。在英国,国家统计局COVID-19感染调查(CIS)等大规模研究监测了SARS-CoV-2的传播,但需要大量资源,这使得在特定大流行的资金结束时以及在资源有限的情况下难以维持。相比之下,成本较低的病毒观察研究依赖于自我报告和相关的国家检测数据以及症状检测,而严重急性呼吸道感染观察(SARI)利用医院数据进行具有成本效益的监测。目的:本研究旨在评估病毒监测作为监测系统在英格兰和威尔士监测COVID-19阳性、发病率和住院率方面的有效性,使用CIS和SARI的数据作为比较基准,同时考虑研究设计中的关键差异,包括招募策略、激励措施和测试标准。方法:我们使用病毒观察前瞻性社区队列研究来估计2020年6月至2023年3月期间英格兰和威尔士的COVID-19阳性、发病率和住院率。将比率估计值与CIS模型的阳性和发病率以及SARI COVID-19住院率进行比较。数据集之间的全局同步使用总体Spearman方法进行测量,本地同步使用9周滚动Spearman方法进行测量。对于英格兰,与CIS估计的比较使用了有和没有相关国家检测数据计算的病毒监测率。在国家免费检测结束前后,还分别评估了总体和阳性率。结果:病毒观察研究共招募了58,628名参与者,其中52,526名(89.6%)居住在英格兰,1532名(2.6%)居住在威尔士;其余的区域都缺失了。在有和没有相关检测数据的情况下,病毒监测估计的英格兰COVID-19阳性和发病率显示出与CIS估计的强全球同步(阳性):0.91和0.90;两者都是p结论:我们的研究结果强调了病毒监测方法在提供准确估计COVID-19阳性和发病率方面的有效性,即使在没有国家监测系统的情况下。这种低成本方法可适用于各种环境,特别是资源匮乏的环境,以加强公共卫生监测并为及时干预提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
13.70
自引率
2.40%
发文量
136
审稿时长
12 weeks
期刊介绍: JMIR Public Health & Surveillance (JPHS) is a renowned scholarly journal indexed on PubMed. It follows a rigorous peer-review process and covers a wide range of disciplines. The journal distinguishes itself by its unique focus on the intersection of technology and innovation in the field of public health. JPHS delves into diverse topics such as public health informatics, surveillance systems, rapid reports, participatory epidemiology, infodemiology, infoveillance, digital disease detection, digital epidemiology, electronic public health interventions, mass media and social media campaigns, health communication, and emerging population health analysis systems and tools.
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