Evidence map›Paper›PMID 36310674›Full record

ArticleJournal of material cycles and waste management2023

Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies.

Fang Wang, Lean Yu, Junhong Long, Haoyue Bu, Changhua He, Aiping Wu

Open access · bronzeAbstract read
In one paragraph

Article in Journal of material cycles and waste management, 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
1.0field-weighted citation impact, top 24% of its field
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, 5 citations in OpenAlex.

  1. 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

6 authors at 3 institutions in 1 country.

Fang WangSchool of Economics and Management, Xidian University, Xi'an, 710126 China.
Lean YuPresent Address: Business School, Sichuan University, Chengdu, 610065 China.ORCID 0000-0002-8035-4938
Junhong LongThe Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710004 China.
Haoyue BuSchool of Economics and Management, Xidian University, Xi'an, 710126 China.
Changhua HeSchool of Economics and Management, Harbin Engineering University, Harbin, 150001 China.
Aiping WuSchool of Economics and Management, Xidian University, Xi'an, 710126 China.
Xidian University · CNHarbin Engineering University · CNSecond Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on the medical waste quantity and patient data during the corona virus disease 2019 (COVID-19) outbreak in China, this study used scenario analysis to quantitatively analyze the temporal and spatial evolution of medical waste generation during the pandemics. First, the results show that the estimated medical waste per capita reached 15.4 kg/day if only patients were considered in Scenario 1, while the figures were reduced to 3.2 kg/day in Scenario 2 and 2.5 kg/day in Scenario 3 when the effects of both the patient type and the number of medical staffs were considered. The estimated results also demonstrated that the per capita medical waste related to the epidemic showed the characteristics of a U-shaped and trailing phenomenon over time. Then, the amount of medical waste related to the COVID-19 generated that generated due to COVID-19 was estimated in Hubei, Heilongjiang, Zhejiang, Henan and Hunan provinces under Scenario 2 and Scenario 3. The results indicated that the spatiotemporal evolution characteristics of five provinces show the significant differences, and the patient type has a remarkable influence on the generation of medical waste. Finally, a novel decomposition-ensemble approach was designed to make a better short-term forecasting effect for future medical waste generation in different provinces. Supplementary Information: The online version contains supplementary material available at 10.1007/s10163-022-01523-5.

Indexed as

COVID-19Decomposition-ensemble approachMedical wastePer capita medical wastePublic health emergenciesScenario analysis

Identifiers

PMID36310674
PMCPMC9589721
OpenAlexW4307298795

What OpenQuestion holds

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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.