Doctor of Medicine Program, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.
Public Health Ontario, Toronto, Canada.
PLoS One. 2022 Jan 11;17(1):e0262447. doi: 10.1371/journal.pone.0262447. eCollection 2022.
Limitations in laboratory diagnostic capacity impact population surveillance of COVID-19. It is currently unknown whether participatory surveillance tools for COVID-19 correspond to government-reported case trends longitudinally and if it can be used as an adjunct to laboratory testing. The primary objective of this study was to determine whether self-reported COVID-19-like illness reflected laboratory-confirmed COVID-19 case trends in Ontario Canada.
We retrospectively analyzed longitudinal self-reported symptoms data collected using an online tool-Outbreaks Near Me (ONM)-from April 20th, 2020, to March 7th, 2021 in Ontario, Canada. We measured the correlation between COVID-like illness among respondents and the weekly number of PCR-confirmed COVID-19 cases and provincial test positivity. We explored contemporaneous changes in other respiratory viruses, as well as the demographic characteristics of respondents to provide context for our findings.
Between 3,849-11,185 individuals responded to the symptom survey each week. No correlations were seen been self-reported CLI and either cases or test positivity. Strong positive correlations were seen between CLI and both cases and test positivity before a previously documented rise in rhinovirus/enterovirus in fall 2020. Compared to participatory surveillance respondents, a higher proportion of COVID-19 cases in Ontario consistently came from low-income, racialized and immigrant areas of the province- these groups were less well represented among survey respondents.
Although digital surveillance systems are low-cost tools that have been useful to signal the onset of viral outbreaks, in this longitudinal comparison of self-reported COVID-like illness to Ontario COVID-19 case data we did not find this to be the case. Seasonal respiratory virus transmission and population coverage may explain this discrepancy.
实验室诊断能力的限制影响了 COVID-19 的人群监测。目前尚不清楚 COVID-19 的参与式监测工具是否能与政府报告的病例趋势纵向对应，以及是否可以将其作为实验室检测的辅助手段。本研究的主要目的是确定自我报告的 COVID-19 样疾病是否反映了加拿大安大略省实验室确诊的 COVID-19 病例趋势。
我们回顾性分析了 2020 年 4 月 20 日至 2021 年 3 月 7 日期间，在加拿大安大略省使用在线工具“Outbreaks Near Me（ONM）”收集的纵向自我报告症状数据。我们测量了受访者 COVID-19 样疾病与每周 PCR 确诊 COVID-19 病例数和省级检测阳性率之间的相关性。我们还探讨了其他呼吸道病毒的同期变化，以及受访者的人口统计学特征，为我们的发现提供背景。
每周有 3849-11185 人对症状调查做出回应。自我报告的 CLI 与病例或检测阳性率之间没有相关性。在 2020 年秋季鼻病毒/肠道病毒先前记录的上升之前，CLI 与病例和检测阳性率之间存在强烈的正相关。与参与式监测受访者相比，安大略省的 COVID-19 病例中有更高比例来自该省收入较低、种族化和移民地区-这些群体在调查受访者中代表性不足。
尽管数字监测系统是低成本工具，对病毒爆发的发生有一定的提示作用，但在本研究中，我们将自我报告的 COVID-19 样疾病与安大略省 COVID-19 病例数据进行纵向比较，并未发现这种情况。季节性呼吸道病毒传播和人群覆盖率可能解释了这种差异。
