Wastewater-based surveillance data to determine the COVID-19 trends in communities with low population

The data presented in this article show SARS-CoV-2 viral concentration and trends in wastewater among communities with different population size. Particularly, the data show that wastewater SARS-CoV-2 concentration can better predict COVID-19 transmission in communities than clinical data. The article also reports PMMoV data in wastewater and population data in each community, and their effects on the correlation between wastewater SARS-CoV-2 and clinical COVID-19 data. The wastewater and clinical data reported in this article are collected from 7 students' housing communities with population ranging between 300 and 4000 residents per community. The dataset presents SARS-CoV-2 N2 and E gene as well as PMMoV concentrations in the raw wastewater samples collected from 13 sewer manholes at these communities roughly three times per week for a period of 6-months between December 2021 and June 2022. This dataset will help to 1) improve future wastewater based epidemiological models, 2) improve understanding on PMMoV concentration ranges in wastewater at low population communities, 3) develop methods to support data interpretation, and 4) understand the effects of spatial scales on sampling frequency and infection outbreak detection.

Authors

Institutions

Publication Details

Journal
Data in Brief
Published
2025-06-07
DOI
https://doi.org/10.1016/j.dib.2025.111756
Citations
1
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
1.36

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Wastewater-based surveillance data to determine the COVID-19 trends in communities with low population

Sunny C. Jiang, Michael Oakes, Ashley Green, Aiswarya Rani Pappu
1 citations
Data in Brief
COVID-19 diagnosis using AI
1.36
article

Wastewater-based surveillance data to determine the COVID-19 trends in communities with low population

Sunny C. Jiang, Michael Oakes, Ashley Green, Aiswarya Rani Pappu
article en
1 citations

Abstract

The data presented in this article show SARS-CoV-2 viral concentration and trends in wastewater among communities with different population size. Particularly, the data show that wastewater SARS-CoV-2 concentration can better predict COVID-19 transmission in communities than clinical data. The article also reports PMMoV data in wastewater and population data in each community, and their effects on the correlation between wastewater SARS-CoV-2 and clinical COVID-19 data. The wastewater and clinical data reported in this article are collected from 7 students' housing communities with population ranging between 300 and 4000 residents per community. The dataset presents SARS-CoV-2 N2 and E gene as well as PMMoV concentrations in the raw wastewater samples collected from 13 sewer manholes at these communities roughly three times per week for a period of 6-months between December 2021 and June 2022. This dataset will help to 1) improve future wastewater based epidemiological models, 2) improve understanding on PMMoV concentration ranges in wastewater at low population communities, 3) develop methods to support data interpretation, and 4) understand the effects of spatial scales on sampling frequency and infection outbreak detection.

Data in BriefVol. 61
University of California, Irvine (US), Irvine University (US)
National Science Foundation, U.S. Environmental Protection Agency, Water Research Foundation
Clean water and sanitation
Openalex Percentile: Top 19%
COVID-19 diagnosis using AI
1.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Wastewater-based surveillance data to determine the COVID-19 trends in communities with low population — Sunny C. Jiang, Michael Oakes, et al. · Data in Brief (2025) | TGRS Research Map | TGRS