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美国军事设施污水监测试点:成本模型分析。

Wastewater Surveillance Pilot at US Military Installations: Cost Model Analysis.

机构信息

Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499.

United State Air Force Research Laboratory, Wright Patterson Air Force Base, OH, United States.

出版信息

JMIR Public Health Surveill. 2024 Sep 6;10:e54750. doi: 10.2196/54750.

DOI:10.2196/54750
PMID:39240545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11396592/
Abstract

BACKGROUND

The COVID-19 pandemic highlighted the need for pathogen surveillance systems to augment both early warning and outbreak monitoring/control efforts. Community wastewater samples provide a rapid and accurate source of environmental surveillance data to complement direct patient sampling. Due to its global presence and critical missions, the US military is a leader in global pandemic preparedness efforts. Clinical testing for COVID-19 on US Air Force (USAF) bases (AFBs) was effective but costly with respect to direct monetary costs and indirect costs due to lost time. To remain operating at peak capacity, such bases sought a more passive surveillance option and piloted wastewater surveillance (WWS) at 17 AFBs to demonstrate feasibility, safety, utility, and cost-effectiveness from May 2021 to January 2022.

OBJECTIVE

We model the costs of a wastewater program for pathogens of public health concern within the specific context of US military installations using assumptions based on the results of the USAF and Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense pilot program. The objective was to determine the cost of deploying WWS to all AFBs relative to clinical swab testing surveillance regimes.

METHODS

A WWS cost projection model was built based on subject matter expert input and actual costs incurred during the WWS pilot program at USAF AFBs. Several SARS-CoV-2 circulation scenarios were considered, and the costs of both WWS and clinical swab testing were projected. Analysis was conducted to determine the break-even point and how a reduction in swab testing could unlock funds to enable WWS to occur in parallel.

RESULTS

Our model confirmed that WWS is complementary and highly cost-effective when compared to existing alternative forms of biosurveillance. We found that the cost of WWS was between US $10.5-$18.5 million less expensive annually in direct costs as compared to clinical swab testing surveillance. When the indirect cost of lost work was incorporated, including lost work associated with required clinical swab testing, we estimated that over two-thirds of clinical swab testing could be maintained with no additional costs upon implementation of WWS.

CONCLUSIONS

Our results support the adoption of WWS across US military installations as part of a more comprehensive and early warning system that will enable adaptive monitoring during disease outbreaks in a more cost-effective manner than swab testing alone.

摘要

背景

COVID-19 大流行凸显了病原体监测系统的必要性,以增强早期预警和疫情监测/控制工作。社区污水样本为补充直接患者采样提供了快速、准确的环境监测数据来源。由于其全球存在和关键任务,美国军队是全球大流行防范工作的领导者。美国空军 (USAF) 基地对 COVID-19 进行临床检测是有效的,但直接货币成本和因时间损失而产生的间接成本都很高。为了保持最高产能,这些基地寻求更被动的监测选择,并于 2021 年 5 月至 2022 年 1 月在 17 个空军基地试点污水监测 (WWS),以展示可行性、安全性、实用性和成本效益。

目的

我们根据美国空军和联合化学、生物、辐射和核防御计划执行办公室试点计划的结果假设,为美国军事设施内公共卫生关注病原体的污水计划建模,以确定在所有空军基地部署 WWS 的成本与临床拭子检测监测方案的相对成本。

方法

根据主题专家的投入和 WWS 试点计划在 USAF 空军基地实际发生的成本,建立了 WWS 成本预测模型。考虑了几种 SARS-CoV-2 循环情况,并预测了 WWS 和临床拭子检测的成本。进行了分析以确定盈亏平衡点,以及减少拭子检测如何释放资金以使 WWS 能够并行进行。

结果

我们的模型证实,与现有的替代生物监测形式相比,WWS 具有互补性和高度成本效益。我们发现,与临床拭子检测监测相比,WWS 的直接成本每年节省 1050 万至 1850 万美元。当包括与所需临床拭子检测相关的旷工成本在内的间接成本时,我们估计在实施 WWS 后,可以维持三分之二以上的临床拭子检测,而无需额外成本。

结论

我们的结果支持在美国军事设施中采用 WWS,作为更全面和早期预警系统的一部分,这将使在疾病爆发期间以比单独拭子检测更具成本效益的方式进行自适应监测成为可能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/624d/11396592/a4af810bec2a/publichealth-v10-e54750-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/624d/11396592/eb019a5f2701/publichealth-v10-e54750-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/624d/11396592/a4af810bec2a/publichealth-v10-e54750-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/624d/11396592/eb019a5f2701/publichealth-v10-e54750-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/624d/11396592/a4af810bec2a/publichealth-v10-e54750-g002.jpg

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