Evidence map›Paper›PMID 33765977›Full record

ArticleBMC public health2021

Human mobility and poverty as key drivers of COVID-19 transmission and control.

Matan Yechezkel, Amit Weiss, Idan Rejwan, Edan Shahmoon, Shachaf Ben-Gal, Dan Yamin

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 71 citations in OpenAlex.

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  8. Human mobility and the infectious disease transmission: A systematic review.Geo-spatial information science = Diqui kongjian xinxi kexue xuebao · 2024
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  19. Estimating the effect of mobility on SARS-CoV-2 transmission during the first and second wave of the COVID-19 epidemic, Switzerland, March to December 2020.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2022
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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

6 authors at 1 institution in 1 country.

Matan Yechezkel *Laboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel.
Amit Weiss *Laboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel.
Idan Rejwan *Laboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel.
Edan ShahmoonLaboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel.
Shachaf Ben-GalLaboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel.
Dan YaminLaboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel. dan.yamin@gmail.com.ORCID 0000-0002-1131-5572
Tel Aviv University · IL

Funding

Israel Science Foundation 3409/19
6 · The paper itself

Abstract

backgroundApplying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, and develop more focused and effective strategies. As human mobility drives transmission, data from cellphone devices can be utilized to achieve these goals.

methodsWe analyzed aggregated and anonymized mobility data from the cell phone devices of> 3 million users between February 1, 2020, to May 16, 2020 - in which several movement restrictions were applied and lifted in Israel. We integrated these mobility patterns into age-, risk- and region-structured transmission model. Calibrated to coronavirus incidence in 250 regions covering Israel, we evaluated the efficacy and effectiveness in decreasing morbidity and mortality of applying localized and temporal lockdowns (stay-at-home order).

resultsPoorer regions exhibited lower and slower compliance with the restrictions. Our transmission model further indicated that individuals from impoverished areas were associated with high transmission rates. Considering a horizon of 1-3 years, we found that to reduce COVID-19 mortality, school closure has an adverse effect, while interventions focusing on the elderly are the most efficient. We also found that applying localized and temporal lockdowns during regional outbreaks reduces the overall mortality and morbidity compared to nationwide lockdowns. These trends were consistent across vast ranges of epidemiological parameters, and potential seasonal forcing.

conclusionsMore resources should be devoted to helping impoverished regions. Utilizing cellphone data despite being anonymized and aggregated can help policymakers worldwide identify hotspots and apply designated strategies against future COVID-19 outbreaks.

Indexed as

Communicable Disease ControlCOVID-19Population DynamicsPovertyAgedChildHumansIsraelSARS-CoV-2Contact mixing patternsCOVID-19Human mobilitySIR modelTransmission model

Identifiers

PMID33765977
PMCPMC7993906
OpenAlexW3136224474

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.