Unmasking the truth: Experimental evidence of facemask compliance in Bangladesh, Kenya, and Nigeria during the COVID-19 pandemic

bracu.type.groupResearch Publications
datacite.rightsOpen Access
dc.contributor.authorGrépin, Karen A.
dc.contributor.authorMueller, Valerie
dc.contributor.authorWu, Nicole
dc.contributor.authorRabbani, Atonu
dc.contributor.departmentBRAC James P Grant School of Public Health
dc.date.accessioned2026-08-04T04:57:19Z
dc.date.available2026-08-04T04:57:19Z
dc.date.issued2023-03-01
dc.description.abstractHigh levels of compliance with public health measures are critical to ensure a successful response to the COVID-19 pandemic and other public health emergencies. However, most data on compliance are self-reported and the tendency to overreport due to social desirability could yield biased estimates of actual compliance. A list experiment is a widely used method to estimate social desirability bias in self-reported estimates of sensitive behaviours. We estimate rates of compliance with facemask mandates in Kenya, Nigeria, and Bangladesh using data from phone surveys conducted in March-April 2021. Data on compliance were collected from two different survey modules: a self-reported compliance module (stated) and a list experiment (elicited). We find large gaps between stated and elicited rates of facemask wearing for different groups depending on specific country contexts and high levels of overreporting of facemask compliance in self-reported surveys: there was an almost 40 percentage point gap in Kenya, 30 percentage points in Nigeria, and 20 percentage points in Bangladesh. We also observe differences in rates of self-reported facemask wearing among key groups but not using the elicited responses from the list experiment, which suggest that social desirability bias may vary by demographics. Data collected from self-reported surveys may not be reliable to monitor ongoing compliance with public health measures. Moreover, elicited compliance rates indicate levels of mask wearing are likely much lower than those estimated using self-reported data. © 2023 Grépin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.description.versionPublished
dc.format.extent16 pages
dc.identifier.citationGrépin KA, Mueller V, Wu N, Rabbani A (2023) Unmasking the truth: Experimental evidence of facemask compliance in Bangladesh, Kenya, and Nigeria during the COVID-19 pandemic. PLOS Glob Public Health 3(3): e0001086. https://doi.org/10.1371/journal.pgph.0001086
dc.identifier.doi10.1371/journal.pgph.0001086
dc.identifier.issn27673375
dc.identifier.other2-s2.0-85195388311
dc.identifier.urihttps://hdl.handle.net/10361/28771
dc.language.isoen_US
dc.publisherPublic Library of Science
dc.relation.hasversion10.1371/journal.pgph.0001086
dc.relation.ispartofPlos Global Public Health
dc.relation.ispartofseriesPlos Global Public Health
dc.relation.journalPLOS Global Public Health
dc.relation.urihttps://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0001086
dc.rightstrue
dc.subjectCOVID 19
dc.subjectBangladesh
dc.subjectNigeria
dc.subjectKenya
dc.subjectPublic and occupational heal
dc.subjectPandemics
dc.subjectLow and middle income count
dc.subject.lcshCOVID-19 (Disease)--Bangladesh.
dc.subject.lcshPublic health--Bangladesh.
dc.subject.lcshCOVID-19 (Disease)--Kenya.
dc.subject.lcshCOVID-19 (Disease)--Nigeria.
dc.subject.lcshCOVID-19 Pandemic, 2020-2023--Influence--Nigeria.
dc.titleUnmasking the truth: Experimental evidence of facemask compliance in Bangladesh, Kenya, and Nigeria during the COVID-19 pandemic
dc.typeArticle
oaire.citation.issue3
oaire.citation.volume3
person.affiliation.nameThe University of Hong Kong Li Ka Shing Faculty of Medicine
person.affiliation.nameArizona State University
person.affiliation.nameThe University of Hong Kong Li Ka Shing Faculty of Medicine
person.affiliation.nameUniversity of Dhaka
person.identifier.scopus-author-id24470948500
person.identifier.scopus-author-id34168039000
person.identifier.scopus-author-id57290494200
person.identifier.scopus-author-id24081227900

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