Evidence map›Paper›PMID 32998066›Full record

ArticleBiosensors & bioelectronics2020

An integrated biosensor system with mobile health and wastewater-based epidemiology (iBMW) for COVID-19 pandemic.

Kang Mao, Hua Zhang, Zhugen Yang

Open access · greenAbstract read
In one paragraph

Article in Biosensors & bioelectronics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 pooled it
1.3field-weighted citation impact, top 11% of its field
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

27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

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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

3 authors at 3 institutions in 2 countries.

Kang MaoState Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China.
Hua ZhangState Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China. Electronic address: zhanghua@mail.gyig.ac.cn.
Zhugen YangCranfield Water Science Institute, Cranfield University, Cranfield, MK43 0AL, United Kingdom. Electronic address: zhugen.yang@cranfield.ac.uk.
Chinese Academy of Sciences · CNCranfield University · GBInstitute of Geochemistry · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of coronavirus disease (COVID-19) has caused a significant public health challenge worldwide. A lack of effective methods for screening potential patients, rapidly diagnosing suspected cases, and accurately monitoring of the epidemic in real time to prevent the rapid spread of COVID-19 raises significant difficulties in mitigating the epidemic in many countries. As effective point-of-care diagnosis tools, simple, low-cost and rapid sensors have the potential to greatly accelerate the screening and diagnosis of suspected patients to improve their treatment and care. In particular, there is evidence that multiple pathogens have been detected in sewage, including SARS-CoV-2, providing significant opportunities for the development of advanced sensors for wastewater-based epidemiology that provide an early warning of the pandemic within the population. Sensors could be used to screen potential carriers, provide real-time monitoring and control of the epidemic, and even support targeted drug screening and delivery within the integration of emerging mobile health (mHealth) technology. In this communication, we discuss the feasibility of an integrated point-of-care biosensor system with mobile health for wastewater-based epidemiology (iBMW) for early warning of COVID-19, screening and diagnosis of potential infectors, and improving health care and public health. The iBMW will provide an effective approach to prevent, evaluate and intervene in a fast, affordable and reliable way, thus enabling real-time guidance for the government in providing effective intervention and evaluating the effectiveness of intervention.

Indexed as

Wastewater-Based Epidemiological MonitoringBetacoronavirusBiosensing TechniquesCoronavirus InfectionsCOVID-19Equipment DesignFeasibility StudiesHumansPandemicsPneumonia, ViralPoint-of-Care SystemsSARS-CoV-2SewageTelemedicineSewageEarly warningMobile healthPandemicPoint-of-use sensorsWastewater-based epidemiology

Identifiers

PMID32998066
PMCPMC7492834
OpenAlexW3084739029

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.