School of Biosciences, Cardiff University, Cardiff, United Kingdom.
School of Natural and Environmental Sciences, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
JMIR Infodemiology. 2023 Nov 23;3:e43891. doi: 10.2196/43891.
The COVID-19 pandemic necessitated rapid real-time surveillance of epidemiological data to advise governments and the public, but the accuracy of these data depends on myriad auxiliary assumptions, not least accurate reporting of cases by the public. Wastewater monitoring has emerged internationally as an accurate and objective means for assessing disease prevalence with reduced latency and less dependence on public vigilance, reliability, and engagement. How public interest aligns with COVID-19 personal testing data and wastewater monitoring is, however, very poorly characterized.
This study aims to assess the associations between internet search volume data relevant to COVID-19, public health care statistics, and national-scale wastewater monitoring of SARS-CoV-2 across South Wales, United Kingdom, over time to investigate how interest in the pandemic may reflect the prevalence of SARS-CoV-2, as detected by national testing and wastewater monitoring, and how these data could be used to predict case numbers.
Relative search volume data from Google Trends for search terms linked to the COVID-19 pandemic were extracted and compared against government-reported COVID-19 statistics and quantitative reverse transcription polymerase chain reaction (RT-qPCR) SARS-CoV-2 data generated from wastewater in South Wales, United Kingdom, using multivariate linear models, correlation analysis, and predictions from linear models.
Wastewater monitoring, most infoveillance terms, and nationally reported cases significantly correlated, but these relationships changed over time. Wastewater surveillance data and some infoveillance search terms generated predictions of case numbers that correlated with reported case numbers, but the accuracy of these predictions was inconsistent and many of the relationships changed over time.
Wastewater monitoring presents a valuable means for assessing population-level prevalence of SARS-CoV-2 and could be integrated with other data types such as infoveillance for increasingly accurate inference of virus prevalence. The importance of such monitoring is increasingly clear as a means of objectively assessing the prevalence of SARS-CoV-2 to circumvent the dynamic interest and participation of the public. Increased accessibility of wastewater monitoring data to the public, as is the case for other national data, may enhance public engagement with these forms of monitoring.
COVID-19 大流行需要快速实时监测流行病学数据，为政府和公众提供建议，但这些数据的准确性取决于无数辅助假设，尤其是公众对病例的准确报告。国际上已经出现了废水监测，作为一种评估疾病流行率的准确和客观手段，可以减少潜伏期，减少对公众警惕性、可靠性和参与度的依赖。然而，公众利益与 COVID-19 个人检测数据和废水监测之间的关系还没有得到很好的描述。
本研究旨在评估与 COVID-19 相关的互联网搜索量数据、公共卫生统计数据和英国南威尔士国家规模的 SARS-CoV-2 废水监测之间的关联，随着时间的推移，以调查对大流行的兴趣如何反映 SARS-CoV-2 的流行率，如全国性检测和废水监测检测到的那样，以及这些数据如何用于预测病例数量。
从谷歌趋势中提取与 COVID-19 大流行相关的搜索词的相对搜索量数据，并与英国南威尔士的政府报告的 COVID-19 统计数据和定量逆转录聚合酶链反应（RT-qPCR）SARS-CoV-2 数据进行比较，使用多元线性模型、相关分析和线性模型的预测。
废水监测、大多数信息监测术语和全国报告的病例显著相关，但这些关系随时间而变化。废水监测数据和一些信息监测搜索词生成的病例数预测与报告的病例数相关，但这些预测的准确性不一致，而且许多关系随时间而变化。
废水监测为评估 SARS-CoV-2 的人群流行率提供了有价值的手段，并且可以与其他数据类型（如信息监测）集成，以更准确地推断病毒流行率。随着公众对 SARS-CoV-2 的动态兴趣和参与程度的规避，这种监测的重要性越来越明显。增加公众对废水监测数据的访问，就像其他国家数据一样，可以增强公众对这些监测形式的参与度。
