Evidence map›Paper›PMID 35934330›Full record

ArticleSpatial and spatio-temporal epidemiology2022

Space-time analysis of COVID-19 cases and SARS-CoV-2 wastewater loading: A geodemographic perspective.

J R Nelson, A Lu, J P Maestre, E J Palmer, D Jarma, K A Kinney, T H Grubesic, M J Kirisits

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Spatial and spatio-temporal epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Tracking epidemic viruses in wastewaters.Microbial biotechnology · 2024
    Review
  2. Review
  3. Article
  4. Article
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

8 authors.

J R NelsonDepartment of Geosciences, Auburn University, 2050 Beard Eaves Coliseum, Auburn, AL 36849, USA.
A LuDepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA.
J P MaestreDepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA.
E J PalmerDepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA.
D JarmaDepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA.
K A KinneyDepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA.
T H GrubesicGeoinformatics & Policy Analytics Laboratory, School of Information, University of Texas at Austin, USA.
M J KirisitsDepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome - coronavirus 2 (SARS-CoV-2) continues to effect communities across the world. One way to combat these effects is to enhance our collective ability to remotely monitor community spread. Monitoring SARS-CoV-2 in wastewater is one approach that enables researchers to estimate the total number of infected people in a region; however, estimates are often made at the sewershed level which may mask the geographic nuance required for targeted interdiction efforts. In this work, we utilize an apportioning method to compare the spatial and temporal trends of daily case count with the temporal pattern of viral load in the wastewater at smaller units of analysis within Austin, TX. We find different lag-times between wastewater loading and case reports. Daily case reports for some locations follow the temporal trend of viral load more closely than others. These findings are then compared to socio-demographic characteristics across the study area.

Indexed as

COVID-19SARS-CoV-2HumansSpatio-Temporal AnalysisWastewaterWastewater

Identifiers

PMID35934330
PMCPMC9142176

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.