Evidence map›Paper›PMID 36901318›Full record

ReviewInternational journal of environmental research and public health2023

The Impact of COVID-19 on Waste Infrastructure: Lessons Learned and Opportunities for a Sustainable Future.

Poornima A Jayasinghe, Hamoun Jalilzadeh, Patrick Hettiaratchi

Full text readReview
In one paragraph

Review in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Poornima A JayasingheDepartment of Civil Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.
Hamoun JalilzadehDepartment of Civil Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.
Patrick HettiaratchiDepartment of Civil Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.

Funding

Natural Sciences and Engineering Research Council 511060-2018
6 · The paper itself

Abstract

The onset of the COVID-19 pandemic posed many global challenges, mainly in the healthcare sector; however, the impacts on other vital sectors cannot be overlooked. The waste sector was one of the significantly impacted sectors during the pandemic, as it dramatically changed the dynamics of waste generation. Inadequate waste management practices during COVID-19 shed light on the opportunities for developing systematic, sustainable, and resilient waste infrastructure in the future. This study aimed to exploit the learnings of COVID-19 to identify any potential opportunities in post-pandemic waste infrastructure. A comprehensive review on existing case studies was conducted to understand the waste generation dynamics and the waste management strategies during COVID-19. Infectious medical waste from healthcare facilities had the largest influx of waste compared with non-medical waste from residential and other sectors. This study then identified five key opportunities from a long-term operational perspective: considering healthcare waste sector as a critical area of focus; encouraging the integration and decentralization of waste management facilities; developing systematic and novel approaches and tools for quantifying waste; shifting towards a circular economy approach; and modernizing policies to improve the effectiveness of the post-pandemic waste management infrastructure.

Indexed as

COVID-19Waste ManagementHealth FacilitiesHumansPandemicsCOVID-19pandemicsystematic solutionswaste infrastructurewaste management

Identifiers

PMID36901318
PMCPMC10001637

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read32
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.