Evidence map›Paper›PMID 38167176›Full record

ArticleEmerging infectious diseases2024

Inferring Incidence of Unreported SARS-CoV-2 Infections Using Seroprevalence of Open Reading Frame 8 Antigen, Hong Kong.

Shi Zhao, Chris Ka Pun Mok, Yun Sang Tang, Chunke Chen, Yuanxin Sun, Ka Chun Chong, David S C Hui

Abstract read
In one paragraph

Article in Emerging infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

7 authors.

Shi Zhao
Chris Ka Pun Mok
Yun Sang Tang
Chunke Chen
Yuanxin Sun
Ka Chun Chong
David S C Hui

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We tested seroprevalence of open reading frame 8 antigens to infer the number of unrecognized SARS-CoV-2 Omicron infections in Hong Kong during 2022. We estimate 33.6% of the population was infected, 72.1% asymptomatically. Surveillance and control activities during large-scale outbreaks should account for potentially substantial undercounts.

Indexed as

COVID-19Hong KongHumansIncidenceOpen Reading FramesSARS-CoV-2Seroepidemiologic StudiesChinaCOVID-19Hong Konginfection attack rateORF8 antigenrespiratory infectionsSARS-CoV-2 Omicron variantviruseszoonoses

Identifiers

PMID38167176
PMCPMC10826773

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.