Evidence map›Paper›PMID 33542294›Full record

ArticleScientific reports2021

The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study.

Po Yang, Geng Yang, Jun Qi, Bin Sheng, Yun Yang, Shuhao Zhang, Gaoshan Bi, Xuxin Mao

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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  7. ANN Assisted-IoT Enabled COVID-19 Patient Monitoring.IEEE access : practical innovations, open solutions · 2021
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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.

Po YangDepartment of Computer Science, The University of Sheffield, Sheffield, UK. po.yang@sheffield.ac.uk.
Geng YangThe State Key Laboratory of Fluid Power and Electronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, China.
Jun QiDepartment of Computer Science and Software Engineering, Xi'an JiaoTong-Liverpool University, Suzhou, China.
Bin ShengDepartment of Computer Science and Engineering, Shanghai JiaoTong University, Shanghai, China.
Yun YangSchool of Software, Yunnan University, Kunming, China. yangyun@ynu.edu.cn.
Shuhao ZhangSchool of Software, Yunnan University, Kunming, China.
Gaoshan BiSchool of Software, Yunnan University, Kunming, China.
Xuxin MaoNational Institute of Economic and Social Research, London, UK.

Funding

National Natural Science Foundation of China 61876166Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems GZKF-201802WUN (world universities network) COVID-19 Special Grant Scheme 168057
6 · The paper itself

Abstract

For controlling recent COVID-19 outbreaks around the world, many countries have implemented suppression and mitigation interventions. This work aims to conduct a feasibility study for accessing the effect of multiple interventions to control the COVID-19 breakouts in the UK and other European countries, accounting for balance of healthcare demand. The model is to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in the UK, with two features considered: direct link between exposed and recovered population, and practical healthcare demand by separation of infections. We combined the calibrated model with COVID-19 data in London and non-London regions in the UK during February and April 2020. Our finding suggests that rolling intervention is an optimal strategy to effectively control COVID-19 outbreaks in the UK for balancing healthcare demand and morality ratio. It is better to implement regional based interventions with varied intensities and maintenance periods. We suggest an intervention strategy named as "Besieged and rolling interventions" to the UK that take a consistent suppression in London for 100 days and 3 weeks rolling intervention in other regions. This strategy would reduce the overall infections and deaths of COVID-19 outbreaks, and balance healthcare demand in the UK.

Indexed as

Disease OutbreaksHealth Services Needs and DemandCOVID-19HumansModels, TheoreticalUnited Kingdom

Identifiers

PMID33542294
PMCPMC7862317

What OpenQuestion holds

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Registered trials

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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.