Evidence map›Paper›PMID 34971822›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2022

Community seroprevalence and risk factors for SARS-CoV-2 infection in different subpopulations in Vellore, India, and their implications for future prevention.

Divya Dayanand, Indhuja Irudhayanathan, Debasree Kundu, Abi Manesh, Vinod Abraham, Kundavaram Pp Abhilash, Binila Chacko, Mahesh Moorthy, Prasanna Samuel, Pimnara Peerawaranun and 4 more

Abstract read
In one paragraph

Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

14 authors.

Divya DayanandDepartment of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India.
Indhuja IrudhayanathanDepartment of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India.
Debasree KunduDepartment of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India.
Abi ManeshDepartment of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India.
Vinod AbrahamDepartment of Community Health, Christian Medical College, Vellore, Tamil Nadu, India.
Kundavaram Pp AbhilashDepartment of Emergency Medicine, Christian Medical College, Vellore, Tamil Nadu, India.
Binila ChackoDepartment of Critical Care Medicine, Christian Medical College, Vellore, Tamil Nadu, India.
Mahesh MoorthyDepartment of Clinical Virology, Christian Medical College, Vellore, Tamil Nadu, India.
Prasanna SamuelDepartment of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India.
Pimnara PeerawaranunMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Mavuto MukakaMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, University of Oxford, UK.
Jayaraj JosephDepartment of Electrical Engineering, Indian Institute of Technology Madras, Tamil Nadu, India; Healthcare Technology Innovation Centre (HTIC), Indian Institute of Technology Madras, Tamil Nadu, India.
Mohanasankar SivaprakasamDepartment of Electrical Engineering, Indian Institute of Technology Madras, Tamil Nadu, India; Healthcare Technology Innovation Centre (HTIC), Indian Institute of Technology Madras, Tamil Nadu, India.
George M VargheseDepartment of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India. Electronic address: georgemvarghese@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of this study was to inform public health policy decisions through the assessment of IgG antibody seroprevalence in the population and the risk factors for SARS-CoV-2 infection.

methodsThe seroprevalence of IgG antibodies among different subpopulations at the end of the first and second waves of the pandemic was estimated. Various risk factors associated with seropositivity, including sociodemography, IgG antibodies against endemic human coronavirus, and vaccination status, were also assessed.

resultsFor all 2433 consenting participants, the overall estimated seroprevalences at the end of first and second waves were 28.5% (95% CI 22.3-33.7%) and 71.5% (95% CI 62.8-80.5%), respectively. The accrual of IgG positivity was heterogeneous, with the highest seroprevalences found in urban slum populations (75.1%). Vaccine uptake varied among the subpopulations, with low rates (< 10%) among rural and urban slum residents. The majority of seropositive individuals (75%) were asymptomatic. Residence in urban slums (OR 2.02, 95% CI 1.57-2.6; p < 0.001), middle socioeconomic status (OR 1.77, 95% CI 1.17-2.67; p = 0.007), presence of diabetes (OR 1.721, 95% CI 1.148-2.581; p = 0.009), and hypertension (OR 1.75, 95% CI 1.16-2.64; p = 0.008) were associated with seropositivity in multivariable analyses.

conclusionAlthough considerable population immunity has been reached, with more than two-thirds seropositive, improved vaccination strategies among unreached subpopulations and high-risk individuals are suggested for better preparedness in future.

Indexed as

COVID-19Antibodies, ViralHumansIndiaRisk FactorsSARS-CoV-2Seroepidemiologic StudiesAntibodies, ViralCOVIDIndiaSARS-CoV-2Seroprevalence

Identifiers

PMID34971822
PMCPMC8712712

What OpenQuestion holds

Textmetadata
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.