Evidence map›Paper›PMID 39204285›Full record

ReviewPathogens (Basel, Switzerland)2024

Advancing Public Health Surveillance: Integrating Modeling and GIS in the Wastewater-Based Epidemiology of Viruses, a Narrative Review.

Diego F Cuadros, Xi Chen, Jingjing Li, Ryosuke Omori, Godfrey Musuka

Abstract readReview
In one paragraph

Review in Pathogens (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Public health consequences of global climate change. A narrative review.Frontiers in cellular and infection microbiology · 2026
    Review
  5. Article
  6. Review
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

5 authors.

Diego F CuadrosDigital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH 41221, USA.ORCID 0000-0001-7060-4203
Xi ChenDigital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH 41221, USA.ORCID 0000-0002-0293-7417
Jingjing LiDepartment of Land Resources Management, China University of Geosciences, Wuhan 430074, China.
Ryosuke OmoriDivision of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo 002-8501, Japan.
Godfrey MusukaInternational Initiative for Impact Evaluation, Harare 0002, Zimbabwe.ORCID 0000-0001-9077-4429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review article will present a comprehensive examination of the use of modeling, spatial analysis, and geographic information systems (GIS) in the surveillance of viruses in wastewater. With the advent of global health challenges like the COVID-19 pandemic, wastewater surveillance has emerged as a crucial tool for the early detection and management of viral outbreaks. This review will explore the application of various modeling techniques that enable the prediction and understanding of virus concentrations and spread patterns in wastewater systems. It highlights the role of spatial analysis in mapping the geographic distribution of viral loads, providing insights into the dynamics of virus transmission within communities. The integration of GIS in wastewater surveillance will be explored, emphasizing the utility of such systems in visualizing data, enhancing sampling site selection, and ensuring equitable monitoring across diverse populations. The review will also discuss the innovative combination of GIS with remote sensing data and predictive modeling, offering a multi-faceted approach to understand virus spread. Challenges such as data quality, privacy concerns, and the necessity for interdisciplinary collaboration will be addressed. This review concludes by underscoring the transformative potential of these analytical tools in public health, advocating for continued research and innovation to strengthen preparedness and response strategies for future viral threats. This article aims to provide a foundational understanding for researchers and public health officials, fostering advancements in the field of wastewater-based epidemiology.

Indexed as

COVID-19Geographic Information SystemsPublic Health SurveillanceWastewaterHumansPublic HealthSARS-CoV-2VirusesWastewater-Based Epidemiological MonitoringWastewaterCOVID-19geographic information systemsmathematical modelingpublic health surveillanceremote sensingwastewater-based epidemiology

Identifiers

PMID39204285
PMCPMC11357455

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.