Anderson Benjamin, Ouyang Derek, D'Agostino Alexis, Bonin Brandon, Smith Emily, Kraushaar Vit, Rudman Sarah L, Ho Daniel E
Stanford University, Stanford, CA 94305, USA.
County of Santa Clara Public Health Department, San Jose, CA 95126, USA.
iScience. 2023 Nov 19;26(12):108488. doi: 10.1016/j.isci.2023.108488. eCollection 2023 Dec 15.
In the face of scarce public health resources, it is critical to understand which disease surveillance strategies are effective, yet such validation has historically been difficult. From May 1 to December 31, 2021, a cohort study was carried out in Santa Clara County, California, in which 10,131 high-quality genomic sequences from COVID-19 polymerase chain reaction tests were merged with disease surveillance data. We measured the informational value, the fraction of sequenced links surfaced that are biologically plausible according to genomic sequence data, of different disease surveillance strategies. Contact tracing appeared more effective than spatiotemporal methods at uncovering nonresidential spread settings, school reporting appeared more fruitful than workplace reporting, and passively retrieved links through survey information presented some promise. Given the rapidly dwindling cost of sequencing, the informational value metric may enable near real-time, readily available evaluation of strategies by public health authorities to fight viral diseases beyond COVID-19.
面对稀缺的公共卫生资源，了解哪些疾病监测策略有效至关重要，但历史上这种验证一直很困难。2021年5月1日至12月31日，在加利福尼亚州圣克拉拉县进行了一项队列研究，其中将来自新冠病毒聚合酶链反应检测的10131个高质量基因组序列与疾病监测数据合并。我们测量了不同疾病监测策略的信息价值，即根据基因组序列数据在生物学上合理的测序关联比例。在发现非家庭传播场所方面，接触者追踪似乎比时空方法更有效，学校报告似乎比工作场所报告更有成效，并且通过调查信息被动获取的关联显示出一定前景。鉴于测序成本迅速下降，信息价值指标可能使公共卫生当局能够近乎实时、随时对除新冠病毒之外的抗击病毒性疾病的策略进行评估。
