Evidence map›Paper›PMID 42344581›Full record

ArticleEnvironment & health (Washington, D.C.)2026

Antiviral Drugs in Wastewater-Based Epidemiology for Epidemic Surveillance and Alerting.

Bin Wang, Xiaogang Wang, Jiaqi Wen, Lei Duan, Liping Heng, Gang Yu

Abstract read
In one paragraph

Article in Environment & health (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Bin WangState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.ORCID https://orcid.org/0000-0002-6242-7726
Xiaogang WangState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Jiaqi WenDepartment of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey 08544, United States.
Lei DuanState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Liping HengSchool of Chemistry, Beihang University, Beijing 100191, China.
Gang YuGuangdong Provincial Key Laboratory of Wastewater Information Analysis and Early Warning, Advanced Interdisciplinary Institute of Environment and Ecology, School of Technology for Sustainability, Beijing Normal University, Zhuhai 519087, China.ORCID https://orcid.org/0000-0002-8136-2307

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater-Based Epidemiology (WBE) has provided critical surveillance and alerting during epidemic outbreaks such as COVID-19 through viral nucleic acid detection, yet it faces limitations including a narrow short detection time window and the potential for viral variants to escape. The high global incidence of viral diseases has driven increased consumption of antiviral drugs (AVDs). Serving as direct chemical signatures of diagnosis and treatment behaviors, AVDs offer new indicators for epidemic Surveillance and Alerting. This paper systematically outlines the scientific basis for applying AVDs in WBE-based alerting, analyzes core challenges such as data availability, target biomarker selection, and methodological standardization, and proposes a pathway of "Biomarker Validation-Technical Standard Harmonization -Methodologies Optimizing -Global Network Building". This AVD-based WBE supports improving epidemic surveillance and alerting system.

Identifiers

PMID42344581
PMCPMC13288225

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.