Evaluating the impacts of tiered restrictions introduced in England in December 2020 on covid-19 hospitalisations: a synthetic control study. (preprint)

Objectives To assess the impact of Tier 3 covid-19 restrictions implemented in December 2020 in England on covid-19 hospital admissions compared to Tier 2 restrictions, and its potential variations by neighbourhood deprivation levels and the prevalence of the Alpha variant (B.1.1.7). Design Observational study utilising a synthetic control approach. Comparison of changes in weekly hospitalisation rates in Tier 3 areas to a synthetic control group derived from Tier 2 areas. Setting England between 4th October 2020 and 21st February 2021. Participants 23 million people under Tier 3 restrictions, compared to a synthetic control group derived from 29 million people under Tier 2 restrictions. Interventions Implementation of Tier 3 covid-19 restrictions in designated areas on 7th December 2020, with additional constraints on indoor and outdoor meetings and the hospitality sector compared to less stringent Tier 2 restrictions. Main Outcome Measures Weekly covid-19 related hospital admissions for neighbourhoods in England over a 12-week period following the interventions. Results The introduction of Tier 3 restrictions was associated with a 17% average reduction in hospital admissions compared to Tier 2 areas (95% CI 13% to 21%; 8158 (6286 to 9981) in total)). The effects were similar across different levels of neighbourhood deprivation and prevalence of the Alpha variant (B.1.1.7). Conclusions Regionally targeted Tier 3 restrictions in England had a moderate but significant effect on reducing hospitalisations. The impact did not exacerbate socioeconomic inequalities during the pandemic. Our findings suggest that regionally targeted restrictions can be effective in managing infectious diseases.

A systematic review of the prevalence of persistent gastrointestinal symptoms and incidence of new gastrointestinal illness after acute SARS-CoV-2 infection (preprint)

It is known that SARS-CoV-2 infection can result in gastrointestinal symptoms. For some, these symptoms may persist beyond acute infection, in what is known as post-COVID syndrome. We conducted a systematic review to examine the prevalence of persistent gastrointestinal symptoms and the incidence of new gastrointestinal illness following acute SARS-CoV-2 infection. We searched scientific literature using MedLine, SCOPUS, Embase, Europe PubMed Central, medRxiv and Google Scholar from December 2019 to October 2022. Two reviewers independently identified 28 eligible articles which followed participants for various gastrointestinal outcomes after acute SARS-CoV-2 infection. Study quality was assessed using the Joanna Briggs Institute Critical Appraisal Tools. The weighted pooled prevalence for persistent gastrointestinal symptom of any nature and duration was 10.7%, compared to 4.9% in healthy controls. For six studies at a low risk of methodological bias, the symptom prevalence ranged from 0.2% to 24.1% with a median follow-up time of 13 weeks. We also identified the presence of functional gastrointestinal disorders in historically SARS-CoV-2 exposed individuals. Our review has shown that, from a limited pool of mostly low-quality studies, previous SARS-CoV-2 exposure may be associated with ongoing gastrointestinal symptoms and the development of functional gastrointestinal illness. Furthermore, we show the need for high-quality research to better understand the SARS-CoV-2 association with gastrointestinal symptoms, particularly as population exposure to enteric infections returns to pre-COVID-19-restriction levels.

Pregnant women's attitudes and behaviours towards antenatal vaccination against Influenza and COVID-19 in the Liverpool City Region, United Kingdom: cross-sectional survey (preprint)

Objectives Influenza poses a serious health risk to pregnant women and their babies. Despite this risk, influenza vaccine uptake in pregnant women in the UK is less than 50%. Little is known about how COVID-19 affects pregnant women, but its management may affect attitudes and behaviours towards vaccination in pregnancy. The study objectives were to establish attitudes and knowledge of pregnant women towards influenza disease and influenza vaccination and to compare these to attitudes and knowledge about COVID-19 and COVID-19 vaccination. Design A cross-sectional survey was conducted using an online questionnaire distributed through local advertisement and social media outlets. Information was sought on attitudes and knowledge of influenza and COVID-19 and their respective vaccines. Participants and setting Pregnant women residing in Liverpool City Region, UK Results Of the 237 respondents, 73.8% reported receiving an influenza vaccine. Over half (56.5%) perceived themselves to be at risk from influenza, 70.5% believed that if they got influenza, their baby would get ill, and 64.6% believed getting influenza could hurt their baby, 60.3% believed that the influenza vaccine would prevent their baby from getting ill, and 70.8% believed it would protect their baby. Only 32.9% of respondents stated they would receive the COVID-19 vaccine if it were available to them. However, 80.2% stated they would receive a COVID-19 vaccine if they were not pregnant. Most of the women stated that they would accept a vaccine if recommended to them by healthcare professionals. Conclusions Acceptance of the influenza and COVID-19 vaccines during pregnancy seems to be more related to the safety of the baby rather than the mother. Women perceived their child to be more at risk than themselves. Information about influenza and COVID-19 vaccine safety as well as healthcare provider recommendations play an important role in vaccine uptake in pregnant women.

Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19 (preprint)

Background: COVID-19 pandemic has developed rapidly and the ability to stratify the most vulnerable patients is vital. However, routinely used severity scoring systems are often low on diagnosis, even in non-survivors. Therefore, clinical prediction models for mortality are urgently required. Methods: We developed and internally validated a multivariable logistic regression model to predict inpatient mortality in COVID-19 positive patients using data collected retrospectively from Tongji Hospital, Wuhan (299 patients). External validation was conducted using a retrospective cohort from Jinyintan Hospital, Wuhan (145 patients). Nine variables commonly measured in these acute settings were considered for model development, including age, biomarkers and comorbidities. Backwards stepwise selection and bootstrap resampling were used for model development and internal validation. We assessed discrimination via the C statistic, and calibration using calibration-in-the-large, calibration slopes and plots. Findings: The final model included age, lymphocyte count, lactate dehydrogenase and SpO2 as independent predictors of mortality. Discrimination of the model was excellent in both internal (c=0.89) and external (c=0.98) validation. Internal calibration was excellent (calibration slope=1). External validation showed some over-prediction of risk in low-risk individuals and under-prediction of risk in high-risk individuals prior to recalibration. Recalibration of the intercept and slope led to excellent performance of the model in independent data. Interpretation: COVID-19 is a new disease and behaves differently from common critical illnesses. This study provides a new prediction model to identify patients with lethal COVID-19. Its practical reliance on commonly available parameters should improve usage of limited healthcare resources and patient survival rate.