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BackgroundMultimorbidity and pregnancy are two risk factors for more severe outcomes after a SARS-CoV-2 infection, thus vaccination uptake is important for pregnant women living with multimorbidity. This study aimed to examine the impact of multimorbidity, smoking status, and demographics (age, ethnic group, area of deprivation) on vaccine hesitancy among pregnant women in Wales using electronic health records (EHR) linkage. MethodsThis cohort study utilised routinely collected, individual-level, anonymised population-scale linked data within the Secure Anonymised Information Linkage (SAIL) Databank. Pregnant women were identified from 13th April 2021 to 31st December 2021. Survival analysis was utilised to examine and compare the length of time to vaccination uptake in pregnancy by multimorbidity and smoking status, as well as depression, diabetes, asthma, and cardiovascular conditions independently. Variation in uptake by; multimorbidity, smoking status, and demographics was examined jointly and separately for the independent conditions using hazard ratios (HR) from the Cox regression model. A bootstrapping internal validation was conducted to assess the performance of the models. ResultsWithin the population cohort, 8,203 (32.7%) received at least one dose of the COVID-19 vaccine during pregnancy, with 8,572 (34.1%) remaining unvaccinated throughout the follow-up period, and 8,336 (33.2%) receiving the vaccine postpartum. Women aged 30 years or older were more likely to have the vaccine in pregnancy. Those who had depression were slightly but significantly more likely to have the vaccine compared to those without depression (HR = 1.08, 95% CI 1.03 to 1.14, p = 0.02). Women living with multimorbidity (> 1 health condition) were 1.12 times more likely to have the vaccine compared to those living without multimorbidity (HR = 1.12, 95% CI 1.04 to 1.19, p = 0.001). Vaccine uptakes were significantly lower among both current smokers and former smokers compared to never smokers (HR = 0.87, 95% CI 0.81 to 0.94, p < 0.001 and HR = 0.92, 95% CI 0.85 to 0.98, p = 0.015 respectively). Uptake was also lower among those living in the most deprived areas compared to those living in the most affluent areas (HR = 0.89, 95% CI 0.83 to 0.96, p = 0.002). The validated model had similar performance and revealed that multimorbidity, smoking status, age, and deprivation level together have a significant impact on vaccine hesitancy (p < 0.05 for all). ConclusionYounger women, living without multimorbidity (zero or only one health condition), current and former smokers, and those living in the more deprived areas are less likely to have the vaccine, thus, a targeted approach to vaccinations may be required for these groups. Women living with multimorbidity are slightly but significantly less likely to be hesitant about COVID-19 vaccination when pregnant.
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ObjectiveTo estimate vaccine effectiveness (VE) for preventing COVID-19 hospital admission in women first infected with SARS-CoV-2 during pregnancy, and assess how this compares to VE among women of reproductive age who were not pregnant when first infected. DesignPopulation-based cohort study using national, linked Census and administrative data. SettingEngland, United Kingdom, from 8th December 2020 to 31st August 2021. Participants815,4777 women aged 18 to 45 years (mean age, 30.4 years) who had documented evidence of a first SARS-CoV-2 infection in NHS Test and Trace data or Hospital Episode Statistics. Main outcome measuresA hospital inpatient episode where COVID-19 was recorded as the primary diagnosis. Cox proportional hazards models, adjusted for calendar time of infection and sociodemographic factors related to vaccine uptake and risk of severe COVID-19, were used to estimate VE as the complement of the hazard ratio for COVID-19 hospital admission. ResultsCompared with unvaccinated pregnant women, the adjusted rate of COVID-19 hospital admission was 76% (95% confidence interval 69% to 82%) lower for single-vaccinated pregnant women and 83% (75% to 88%) lower for double-vaccinated pregnant women. These estimates were similar to those found for non-pregnant women: 79% (76% to 81%) for single-vaccinated and 82% (80% to 83%) for double-vaccinated. Among those vaccinated more than 90 days before infection, being double-vaccinated was associated with a greater reduction in risk than being single-vaccinated. ConclusionsCOVID-19 vaccination is associated with reduced rates of severe illness in pregnant women infected with SARS-CoV-2, and the reduction in risk is similar to that for non-pregnant women. Waning of vaccine effectiveness occurs more quickly after one dose of a vaccine than two doses. What is already known on this topicBeing pregnant is a risk factor for severe illness and mortality following infection with SARS-CoV-2. Existing evidence suggests that COVID-19 vaccines are effective for preventing severe outcomes in pregnant women. However, research directly comparing vaccine effectiveness between pregnant and non-pregnant women of reproductive age at the population level are lacking. What this study addsOur study provides real-world evidence that COVID-19 vaccination reduces the risk of hospital admission by a similar amount for both women infected with SARS-CoV-2 during pregnancy and women who were not pregnant when infected, during the Alpha and Delta dominant periods in England.
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BackgroundVaccine hesitancy amongst pregnant women has been found to be a concern during past epidemics. ObjectivesThe aims of this study were to 1) estimate COVID-19 vaccination rates among pregnant women in Wales and their association with age, ethnicity, and area of deprivation, using electronic health records (EHR) linkage, and 2) explore pregnant womens views on receiving the COVID-19 vaccine during pregnancy using data from a survey recruiting via social media (Facebook, Twitter), through midwives, and posters in hospitals (Born in Wales Cohort). DesignA mixed methods study utilising routinely collected linked data from the Secure Anonymised Information Linkage (SAIL) (Objective 1) and the Born In Wales Birth Cohort participants (Objective 2). SAIL combines data from general practice, hospital admissions, the national community child health dataset, maternal indicators dataset, and COVID-19 vaccination databases. Setting and participantsObjective 1) All women documented as being pregnant on or after 13th April 2021, aged 18 years or older, and eligible for COVID-19 vaccination were identified in routine health care. They were linked to the vaccination data up to and including 31st December 2021. Objective 2) Separately, a cross-section of pregnant women in Wales were invited to complete an online survey via social media advertising. The survey asked what their views were on having the COVID-19 vaccination during pregnancy, and if they had already received, or intended to receive, the COVID-19 vaccination during their pregnancies. They were also asked to give reasons for their decisions. Outcomes1 (a). Rate of vaccination uptake per month during pregnancy among women eligible for vaccination. 1 (b). Survival analysis was utilised to examine and compare the length of time to vaccination uptake in pregnancy, and variation in uptake by; age, ethnicity, and deprivation area was examined using hazard ratios (HR) from Cox regression. 2.Expectant mothers views of the COVID-19 vaccination during pregnancy. Results Population-level data linkage (objective 1)Within the population cohort, 32.7% (n = 8,203) were vaccinated (at least one dose of the vaccine) during pregnancy, 34.1% (n = 8,572) remained unvaccinated throughout follow-up period, and 33.2% (n = 8,336) received the vaccine postpartum. Younger women (<30 years) were less likely to have the vaccine and those living in areas of high deprivation were also less likely to have the vaccine (HR=0.88, 95% CI 0.82 to 0.95). Asian and other ethnic groups were 1.12 and 1.18 times more likely to have the vaccine in pregnancy compared to women of White ethnicity (HR=1.12, 95% CI 1.00 to 1.25) and (HR=1.18, 95% CI 1.03 to 1.37) respectively. Survey responses (objective 2)69% of participants stated that they would be happy to have the vaccine during pregnancy (n = 207). The remainder, 31%, indicated that they would not have the vaccine during pregnancy (n = 94). Reasons for having the vaccine related to protecting self and baby, perceived risk level, and receipt of sufficient evidence and advice. Reasons for vaccine refusal included lack of research about long-term outcomes for the baby, anxiety about vaccines, inconsistent advice/information, and preference to wait until after the pregnancy. ConclusionPotentially only 1 in 3 pregnant women would have the COVID-19 vaccine during pregnancy, even though 2 in 3 reported they would have the vaccination, thus it is critical to develop tailored strategies to increase its acceptance rate and to decrease vaccine hesitancy. A targeted approach to vaccinations may be required for groups such as younger people and those living in higher deprivation level areas.
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Observational data on COVID-19 including hypothesised risk factors for infection and progression are accruing rapidly, often from non-random sampling such as hospital admissions, targeted testing or voluntary participation. Here, we highlight the challenge of interpreting observational evidence from such samples of the population, which may be affected by collider bias. We illustrate these issues using data from the UK Biobank in which individuals tested for COVID-19 are highly selected for a wide range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the sampling mechanisms that leave aetiological studies of COVID-19 infection and progression particularly susceptible to collider bias. We also describe several tools and strategies that could help mitigate the effects of collider bias in extant studies of COVID-19 and make available a web app for performing sensitivity analyses. While bias due to non-random sampling should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage.
