PDF(Pubmed)
Abstract：
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.
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.
摘要：
背景：COVID-19大流行需要对流行病学数据进行快速实时监测，为政府和公众提供建议，但是这些数据的准确性取决于无数的辅助假设，尤其是公众对案件的准确报告。废水监测在国际上已成为评估疾病流行率的准确和客观手段，其潜伏期减少，对公众警觉的依赖减少，可靠性,和订婚。公共利益如何与COVID-19个人测试数据和废水监测保持一致，然而,非常糟糕的特点。
目的：本研究旨在评估与COVID-19相关的互联网搜索量数据之间的关联，以及南威尔士全国范围内SARS-CoV-2的废水监测，英国,随着时间的推移，调查对这一流行病的兴趣如何反映国家检测和废水监测所检测到的SARS-CoV-2的流行，以及如何使用这些数据来预测病例数。
方法：从Google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）从南威尔士的废水中产生的SARS-CoV-2数据进行比较，英国,使用多元线性模型，相关分析，和线性模型的预测。
结果：废水监测，大多数信息监控术语，和国家报告的病例显著相关，但是这些关系随着时间的推移而改变。废水监测数据和一些信息监测搜索词产生了与报告病例数相关的病例数预测，但是这些预测的准确性不一致，许多关系随着时间的推移而改变。
结论：废水监测为评估SARS-CoV-2的人群水平流行提供了一种有价值的手段，并且可以与其他数据类型（例如信息监测）相结合，以越来越准确地推断病毒流行。作为客观评估SARS-CoV-2流行的一种手段，这种监测的重要性越来越明显，以规避公众的动态兴趣和参与。提高了公众对废水监测数据的可得性,与其他国家数据一样，可能会加强公众对这些形式监测的参与。
目的：本研究旨在评估与COVID-19相关的互联网搜索量数据之间的关联，以及南威尔士全国范围内SARS-CoV-2的废水监测，英国,随着时间的推移，调查对这一流行病的兴趣如何反映国家检测和废水监测所检测到的SARS-CoV-2的流行，以及如何使用这些数据来预测病例数。
方法：从Google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）从南威尔士的废水中产生的SARS-CoV-2数据进行比较，英国,使用多元线性模型，相关分析，和线性模型的预测。
结果：废水监测，大多数信息监控术语，和国家报告的病例显著相关，但是这些关系随着时间的推移而改变。废水监测数据和一些信息监测搜索词产生了与报告病例数相关的病例数预测，但是这些预测的准确性不一致，许多关系随着时间的推移而改变。
结论：废水监测为评估SARS-CoV-2的人群水平流行提供了一种有价值的手段，并且可以与其他数据类型（例如信息监测）相结合，以越来越准确地推断病毒流行。作为客观评估SARS-CoV-2流行的一种手段，这种监测的重要性越来越明显，以规避公众的动态兴趣和参与。提高了公众对废水监测数据的可得性,与其他国家数据一样，可能会加强公众对这些形式监测的参与。
