Leveraging wastewater surveillance to actively monitor Covid-19 community dynamics in rural areas with reduced reliance on clinical testing

Michelle M. Jarvie, Thu N. T. Nguyen, Benjamin Southwell, Derek Wright
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Abstract

The prevalence of coronavirus disease 2019 (Covid-19) in the community has become more difficult to gauge utilizing clinical testing due to a decrease in reported test results stemming from the availability of at-home test kits and a reduction in the number of cases seeking medical treatment. The purpose of this study was to examine the trend of diminishing correlation between reported clinical cases of Covid-19 and wastewater-based surveillance epidemiological data as home testing became available in the Eastern Upper Peninsula of Michigan. Wastewater grab samples were collected weekly from 16 regional locations from June 2021 to December 2022. Samples were analyzed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) N1 and N2 viral particles using reverse transcriptase digital droplet polymerase chain reaction (RT ddPCR). N1 and N2 gene copies were correlated with clinical cases. The t test was used to determine the correlation deterioration point. Clinical cases postdeterioration were calculated for high-correlated predeterioration locations using linear regression. Correlation between the wastewater-based surveillance of SARS-CoV-2 and reported clinical cases deteriorated after February 1, 2022. This corresponds with the timeframe in which commercially available at-home test kits became available in the United States. The increase in at-home testing for SARS-CoV-2 likely contributed to the decrease in reported clinical positive tests in early 2022, providing an unrealistic picture of the presence of Covid-19 in the community. As measures to reduce exposure such as personal masking, clinical testing, social isolating, and quarantining continue to decline, wastewater surveillance for the presence of SARS-CoV-2 may be the best method for public health professionals to remain aware of virus dynamics in localized regions. Time-series modeling adds another layer of information when clinical data is unobtainable or underreported.

利用废水监测积极监测农村地区 Covid-19 群落动态,减少对临床检测的依赖
COVID-19 在社区中的流行程度越来越难以通过临床检测来衡量,原因是家庭检测试剂盒的出现导致报告的检测结果减少,以及寻求医疗治疗的病例数量减少。本研究的目的是考察密歇根州东部上半岛地区随着家庭检测的普及,COVID-19 临床病例报告与基于废水的监测流行病学数据之间相关性降低的趋势。2021 年 6 月至 2022 年 12 月期间,每周从 16 个地区采集废水样本。使用逆转录酶数字液滴聚合酶链反应(RT ddPCR)分析样本中的 SARS-CoV-2 N1 和 N2 病毒颗粒。N1 和 N2 基因拷贝与临床病例相关。采用 t 检验确定相关性恶化点。使用线性回归法计算恶化前高相关性地点恶化后的临床病例。2022 年 2 月 1 日之后,基于废水的 SARS-CoV-2 监测与报告的临床病例之间的相关性下降。这与美国商业化家庭检测试剂盒上市的时间相吻合。SARS-CoV-2 居家检测的增加很可能导致 2022 年初报告的临床检测阳性病例的减少,从而提供了社区中存在 Covid-19 的不真实情况。随着个人遮蔽、临床检测、社会隔离和检疫等减少接触的措施不断减少,对 SARS-CoV-2 的存在进行废水监测可能是公共卫生专业人员了解局部地区病毒动态的最佳方法。当临床数据无法获得或报告不足时,时间序列模型可提供另一层信息。本文受版权保护。
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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