Resolving sex and gender bias in COVID-19 vaccines R&amp;D and beyond

Vijayasingham, Lavanya; Heidari, Shirin; Munro, J. A.; Omer, Saad B.; MacDonald, Noni E.

doi:10.1080/21645515.2022.2035142

Cited by 6 publications

(11 citation statements)

References 15 publications

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“…Sex and gender are important factors in understanding the real-world effectiveness of vaccines and postmarketing safety monitoring [ 45 , 46 ]. Sex and gender differences in vaccine hesitancy and immunization outcomes have been observed for COVID-19 and other vaccine-preventable diseases, with women typically reporting more vaccine hesitancy and higher adverse reactions than men [ 47 - 49 ]. Our results support the accuracy of self-reported vaccination data from both men and women.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Self-Reported COVID-19 Vaccination Status Compared With a Public Health Vaccination Registry in Québec: Observational Diagnostic Study

Archambault,

Rosychuk,

Audet

et al. 2023

JMIR Public Health Surveill

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Background The accuracy of self-reported vaccination status is important to guide real-world vaccine effectiveness studies and policy making in jurisdictions where access to electronic vaccine registries is restricted. Objective This study aimed to determine the accuracy of self-reported vaccination status and reliability of the self-reported number of doses, brand, and time of vaccine administration. Methods This diagnostic accuracy study was completed by the Canadian COVID-19 Emergency Department Rapid Response Network. We enrolled consecutive patients presenting to 4 emergency departments (EDs) in Québec between March 24, 2020, and December 25, 2021. We included adult patients who were able to consent, could speak English or French, and had a proven COVID-19 infection. We compared the self-reported vaccination status of the patients with their vaccination status in the electronic Québec Vaccination Registry. Our primary outcome was the accuracy of the self-reported vaccination status (index test) ascertained during telephone follow-up compared with the Québec Vaccination Registry (reference standard). The accuracy was calculated by dividing all correctly self-reported vaccinated and unvaccinated participants by the sum of all correctly and incorrectly self-reported vaccinated and unvaccinated participants. We also reported interrater agreement with the reference standard as measured by unweighted Cohen κ for self-reported vaccination status at telephone follow-up and at the time of their index ED visit, number of vaccine doses, and brand. Results During the study period, we included 1361 participants. At the time of the follow-up interview, 932 participants reported at least 1 dose of a COVID-19 vaccine. The accuracy of the self-reported vaccination status was 96% (95% CI 95%-97%). Cohen κ for self-reported vaccination status at phone follow-up was 0.91 (95% CI 0.89-0.93) and 0.85 (95% CI 0.77-0.92) at the time of their index ED visit. Cohen κ was 0.89 (95% CI 0.87-0.91) for the number of doses, 0.80 (95% CI 0.75-0.84) for the brand of the first dose, 0.76 (95% CI 0.70-0.83) for the brand of the second dose, and 0.59 (95% CI 0.34-0.83) for the brand of the third dose. Conclusions We reported a high accuracy of self-reported vaccination status for adult patients without cognitive disorders who can express themselves in English or French. Researchers can use self-reported COVID-19 vaccination data on the number of doses received, vaccine brand name, and timing of vaccination to guide future research with patients who are capable of self-reporting their vaccination data. However, access to official electronic vaccine registries is still needed to determine the vaccination status in certain susceptible populations where self-reported vaccination data remain missing or impossible to obtain. Trial Registration Clinicaltrials.gov NCT04702945; https://clinicaltrials.gov/ct2/show/NCT04702945

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Section: Discussionmentioning

confidence: 99%

Accuracy of Self-Reported COVID-19 Vaccination Status Compared With a Public Health Vaccination Registry in Québec: Observational Diagnostic Study

Archambault,

Rosychuk,

Audet

et al. 2023

JMIR Public Health Surveill

View full text Add to dashboard Cite

show abstract

“…Some evidence of sex and gender related differences emerged once the vaccines were used outside trials. When vaccines began to be available to priority populations (healthcare workers) in early 2021, there were early reports of rare allergic reactions to mRNA vaccines and of thrombosis associated with viral vector vaccines, especially in women 722. Early post-vaccination survey reports from the UK and US also suggested that females reported more non-serious side effects than males 2324.…”

Section: Sex and Gender Gaps In Covid-19 Vaccine Researchmentioning

confidence: 99%

“…Countering gaps in sex related data and other dynamics of gender inequality can be good for business. Companies that work to address these issues can be perceived as socially conscious and responsive to user needs and preferences by target consumers, investors, and health payers 7. For example, the market for “femtech”—health technologies such as wearable devices and phone apps to monitor menstruation and fertility, discreet and comfortable breast pumps, and menstrual health products—is expected to grow to about $1tn by 2026 40.…”

Section: Realising the Market Oriented Potential Of Sex And Gendermentioning

confidence: 99%

“…To foster and accelerate change, regulators must continue to implement and enforce sex and gender related policies to normalise practice, including through dialogue with industry, innovators, and investors, and providing conditions that will support consistent action on sex and gender factors 17. Regulatory or policy levers are unlikely to be effective without support from industry and funders.…”

Section: Inclusive Innovation Requires Inclusive Collaborationmentioning

confidence: 99%

“…Innovators, investors, and industry tend to use cost as an excuse for excluding sex and gender related factors—that the extra work and resources would increase research costs and raise the product price. 1 6 7 Some examples of activities that add time, complexity, and cost to research include recruiting more people in clinical trials to show sex differentiated outcomes, analytical methods to account for hormonal changes in menstrual cycles, and navigating the risks, legal liabilities, and protectionary ethics of conducting research during pregnancy and lactation. 1 6 7 8 …”

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confidence: 99%

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