Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ 85287-8101, USA.
Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ 85287-8101, USA; OneWaterOneHealth, Arizona State University Foundation, 1001 S. McAllister Avenue, Tempe, AZ 85287-8101, USA; AquaVitas, LLC, 9260 E. Raintree Dr., Ste 140, Scottsdale, AZ 85260, USA.
Sci Total Environ. 2020 Aug 15;730:138875. doi: 10.1016/j.scitotenv.2020.138875. Epub 2020 Apr 22.
With the economic and practical limits of medical screening for SARS-CoV-2/COVID-19 coming sharply into focus worldwide, scientists are turning now to wastewater-based epidemiology (WBE) as a potential tool for assessing and managing the pandemic. We employed computational analysis and modeling to examine the feasibility, economy, opportunities and challenges of enumerating active coronavirus infections locally and globally using WBE. Depending on local conditions, detection in community wastewater of one symptomatic/asymptomatic infected case per 100 to 2,000,000 non-infected people is theoretically feasible, with some practical successes now being reported from around the world. Computer simulations for past, present and emerging epidemic hotspots (e.g., Wuhan, Milan, Madrid, New York City, Teheran, Seattle, Detroit and New Orleans) identified temperature, average in-sewer travel time and per-capita water use as key variables. WBE surveillance of populations is shown to be orders of magnitude cheaper and faster than clinical screening, yet cannot fully replace it. Cost savings worldwide for one-time national surveillance campaigns are estimated to be in the million to billion US dollar range (US$), depending on a nation's population size and number of testing rounds conducted. For resource poor regions and nations, WBE may represent the only viable means of effective surveillance. Important limitations of WBE rest with its inability to identify individuals and to pinpoint their specific locations. Not compensating for temperature effects renders WBE data vulnerable to severe under-/over-estimation of infected cases. Effective surveillance may be envisioned as a two-step process in which WBE serves to identify and enumerate infected cases, where after clinical testing then serves to identify infected individuals in WBE-revealed hotspots. Data provided here demonstrate this approach to save money, be broadly applicable worldwide, and potentially aid in precision management of the pandemic, thereby helping to accelerate the global economic recovery that billions of people rely upon for their livelihoods.
随着全球范围内对 SARS-CoV-2/COVID-19 医学筛查的经济和实际限制急剧凸显，科学家们现在将基于污水的流行病学（WBE）作为评估和管理大流行的潜在工具。我们运用计算分析和建模来研究利用 WBE 局部和全球范围内计数活跃冠状病毒感染的可行性、经济性、机会和挑战。根据当地条件，在社区污水中检测到每 100 到 200 万例非感染人群中就有一例有症状/无症状感染者，这在理论上是可行的，目前世界各地都有一些实际成功的报道。对过去、现在和新兴的流行病热点（例如武汉、米兰、马德里、纽约市、德黑兰、西雅图、底特律和新奥尔良）的计算机模拟确定了温度、平均污水停留时间和人均用水量是关键变量。与临床筛查相比，对人群进行 WBE 监测要便宜和快速几个数量级，但不能完全替代它。一次性全国监测活动的全球成本节约估计为数百万至数十亿美元（美元），具体取决于一个国家的人口规模和进行的测试轮次数量。对于资源匮乏的地区和国家，WBE 可能是唯一可行的有效监测手段。WBE 的重要局限性在于其无法识别个人及其具体位置。不补偿温度效应会使 WBE 数据容易受到感染病例严重低估/高估的影响。有效的监测可以设想为一个两步过程，其中 WBE 用于识别和计数感染病例，之后临床测试用于识别 WBE 揭示的热点中的感染个体。此处提供的数据表明，这种方法可以节省资金，在全球范围内广泛适用，并有可能有助于精确管理大流行，从而帮助加速全球经济复苏，数以亿计的人依赖全球经济复苏来维持生计。
