Meta AnalysisID 3091
配对废水和流行病学SARS-CoV-2时间序列的系统评价：探索源自废水的SARS-CoV-2流行病学信号相对于经典指标前置时间的变化
CRD42023393357
The aim of this systematic review is to systematically identify studies that contain both epidemiological (e.g. cases) and wastewater (e.g. concentration) data for SARS-CoV-2. Having identified these studies and extracte
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Record Fields
Scalar fields from the final meta_analysis record.
- Meta Analysis Id
- 3091
- Evidence Id
- 11649
- Core Evidence Id
- 11649
- Source Meta Analysis Id
- 3042
- Herb2 Meta Analysis Id
- HBMA003042
- Crd Id
- CRD42023393357
- Title
- A systematic review of paired wastewater and epidemiological SARS-CoV-2 time-series to explore variation in the lead-time of epidemiological signals derived from SARS-CoV-2 wastewater relative to classical indicators.
- Review Question
- The aim of this systematic review is to systematically identify studies that contain both epidemiological (e.g. cases) and wastewater (e.g. concentration) data for SARS-CoV-2. Having identified these studies and extracted the associated data, we will integrate them with grey literature sources and use this assembled collection of paired epidemiological and wastewater time-series to evaluate how much of a leading signal of SARS-CoV-2 transmission wastewater provides relative to classical epidemiological indicators, such as case counts. We will also use this collated data to evaluate how variable the lead time of this signal is across locations and characterise the factors underpinning this variation. Specifically, this review will aim to do the following: 1. Summarise available literature presenting both wastewater and epidemiological SARS-CoV-2 data from the same geographical location by identifying previously conducted studies containing such data. 2. Use this collated data to explore how lagged classical epidemiological indicators such as cases are relative to the signal of community transmission observed in wastewater. 3. Explore how estimates of epidemiologically-relevant quantities such as the time-varying reproduction number (Rt) vary depending on the data source used (i.e. compare estimates of Rt derived from classical epidemiological indicators or estimated using wastewater data). 4. Analyse and evaluate the factors (such as methodological differences between studies or climactic differences between locations) driving variation in the degree of lag or differences in R estimates.
- Study Type Included
- For the purposes the systematic review we carry out, we will include all primary studies containing wastewater and epidemiological time-series data relating to SARS-CoV-2.
- Condition Being Studied
- SARS-CoV-2 and COVID-19 (through surveying and analysing different opportunities for effective surveillance of the virus).
- Participant
- Inclusion: This review will include all studies containing time series epidemiological and wastewater SARS-CoV-2 data collected from the same geographical location in the same timeframe. Exclusion: Studies not containing both epidemiological and wastewater SARS-CoV-2 data.
- Animal
- Human Disease Modelled
- Intervention
- Location, methodological details (such as whether the wastewater data is normalised to PMMoV), and climactic variables (such as temperature) are the key exposures of interest. The outcome (lead-time and Rt) will be compared across these exposures
- Comparator Control
- Not relevant to the systematic review being described here.
- Main Outcome
- A series of summary statistics (including the pearson product moment correlation coefficient, evaluated across a range of lag times, and the time-varying reproduction number Rt) derived from longitudinally recorded data on i) the measured concentration of SARS-CoV-2 RNA in wastewater; and ii) epidemiological measures of SARS-CoV-2 transmission (e.g. clinically confirmed cases, hospitalisations), collected from the same geographical location. Measures of effect For each collated pair of wastewater and epidemiological time-series (derived from the studies we identify), the mean difference in lag-time (measured in calendar days) required to maximise the product moment correlation coefficient between the time-series; and the correlation coefficient of Rt estimates generated from each of the wastewater and epidemiological data sources.
- Outcome Measure
- Additional Outcome
- Not applicable
- Study Method
- Meta-analysis, Systematic review
- Keyword
- COVID-19; Gray Literature; Humans; Reproduction; SARS-CoV-2; Wastewater
- Contact
- Charles Whittaker [email protected]
- Organisational Affiliation
- Imperial College, London
- Funding Source
- CW is supported by a Sir Henry Wellcome Postdoctoral Fellowship, Ref 224190/Z/21/Z. JA's doctoral work is supported by Open Philanthropy Open Global Catastrophic Biological Risk Fellowship Program. Grant number(s) <span style=font-size: 14px>State the funder, grant or award number and the date of award</span> Sir Henry Wellcome Postdoctoral Fellowship; Ref 224190/Z/21/Z; Start Date 1st August 2022. JA's doctoral work is supported by the Open Philanthropy Open Global Catastrophic Biological Risk Fellowship Program; Start date 1st October 2020.
- Other Selection Criteria
- Final Publication
- Same Topic Review
- Published Protocol
- Review Type
- Language
- English
- Country
- England
- Review Stage
- Review Ongoing
- First Submission Date
- 2023-01-27
- Registration Date
- 2023-01-30
- Anticipated Start Date
- 2023-01-23
- Anticipated Completion Date
- 2023-03-31
- Title Cn
- 配对废水和流行病学SARS-CoV-2时间序列的系统评价：探索源自废水的SARS-CoV-2流行病学信号相对于经典指标前置时间的变化
- Title En
- A systematic review of paired wastewater and epidemiological SARS-CoV-2 time-series to explore variation in the lead-time of epidemiological signals derived from SARS-CoV-2 wastewater relative to classical indicators.
- Bilingual Status
- complete