Evidence map›Paper›PMID 37239730›Full record

ArticleHealthcare (Basel, Switzerland)2023

Factors Associated with Reported COVID-like Symptoms and Seroprevalence Data Matched with COVID-like Symptoms in Slums and Non-Slums of Two Major Cities in Bangladesh.

Abdur Razzaque, Tarique Mohammad Nurul Huda, Razib Chowdhury, Md Ahsanul Haq, Protim Sarker, Evana Akhtar, Md Arif Billah, Mohammad Zahirul Islam, Dewan Md Emdadul Hoque, Shehlina Ahmed and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Abdur RazzaqueHealth System and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.
Tarique Mohammad Nurul HudaDepartment of Public Health, College of Public Health and Health Informatics, Qassim University, Al Bukairiyah 52741, Saudi Arabia.ORCID 0000-0002-9934-0739
Razib ChowdhuryHealth System and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.
Md Ahsanul HaqInfectious Disease Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.ORCID 0000-0002-4408-6104
Protim SarkerInfectious Disease Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.
Evana AkhtarInfectious Disease Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.
Md Arif BillahHealth System and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.ORCID 0000-0002-0235-5935
Mohammad Zahirul IslamEmbassy of Sweden in Bangladesh, Gulshan 2, Dhaka 1212, Bangladesh.
Dewan Md Emdadul HoquePopulation Fund (UNFPA), Dhaka 1207, Bangladesh.ORCID 0000-0001-8219-9196
Shehlina AhmedForeign, Commonwealth & Development Office (FCDO), Dhaka 1212, Bangladesh.
Yasmin H AhmedBangladesh Health Watch, James P Grant School of Public Health, BRAC University, Dhaka 1213, Bangladesh.
Fahmida TofailNutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.ORCID 0000-0003-2301-9196
Rubhana RaqibInfectious Disease Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1212, Bangladesh.ORCID 0000-0002-8116-4511

Funding

This research was funded by THE FOREIGN, COMMONWEALTH & DEVELOPMENT OFFICE (FCDO) through THE UNITED NATIONS POPULATION FUND (UNFPA), and GLOBAL AFFAIRS CANADA grant number-01967,01686
6 · The paper itself

Abstract

objectivesTo examine the levels and socio-demographic differentials of: (a) reported COVID-like symptoms; and (b) seroprevalence data matched with COVID-like symptoms.

methodsSurvey data of reported COVID-like symptoms and seroprevalence were assessed by Roche Elecsys

resultsThe odds of COVID-like symptoms were significantly higher for Chattogram city, for non-slum, people having longer years of schooling, working class, income-affected households, while for households with higher income had lower odd. The odds of matched seroprevalence and COVID-like symptoms were higher for non-slum, people having longer years of schooling, and for working class. Out of the seropositive cases, 37.77% were symptomatic-seropositive, and 62.23% were asymptomatic, while out of seronegative cases, 68.96% had no COVID-like symptoms.

conclusionsCollecting community-based seroprevalence data is important to assess the extent of exposure and to initiate mitigation and awareness programs to reduce COVID-19 burden.

Indexed as

Bangladeshnon-slumreported COVID-19seroprevalenceslum

Identifiers

PMID37239730
PMCPMC10218417

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.