Evidence map›Paper›PMID 38187298›Full record

ArticleHeliyon2024

Impact of different nucleic acid testing scenarios on COVID-19 transmission.

Xuedong Zhang, Bo Chen, Jiaxu Le, Yi Hu

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 38% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 1 country.

Xuedong ZhangSchool of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 102627, China.
Bo ChenSchool of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 102627, China.
Jiaxu LeDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China.
Yi HuDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China.
Beijing University of Civil Engineering and Architecture · CNFudan University · CNMinistry of Education of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past three years, waves of COVID-19 infections have emerged one after another, and may enter a small-scale wave-like recurrent epidemic pattern in the future. When COVID-19 infections occur in small-scale, how to efficiently detect and prevent the disease has become the main problem. In this study, based on the characteristics of the Omicron variant and China's pandemic prevention and control strategies, the following three nucleic acid testing scenarios were simulated: scenario 1 (baseline scenario) included conducting nucleic acid testing at administrative region; scenario 2 included conducting nucleic acid testing at the community; and scenario 3 included conducting nucleic acid testing at the health facility closest to households. The model calibration showed that the baseline scenario was consistent with the actual transmission scenario of the disease. The simulation results revealed that compared with scenario 1, the cumulative cases in scenarios 2 and 3 were reduced by 9.52 % and 46.83 %, respectively. Compared with scenario 2, the cumulative cases in scenario 3 were reduced by 41.23 %. Thus, adopting nucleic acid testing measures at the household level can effectively limit the spread of COVID-19 and should be given a priority when local emergency occurs in the future.

Indexed as

Agent-based modelCOVID-19Nucleic acid testingPandemic prevention and control

Identifiers

PMID38187298
PMCPMC10767492
OpenAlexW4389688177

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.