Effect of Covid-19 Vaccination on Transmission of Alpha and Delta Variants

BACKGROUND: Before the emergence of the B.1.617.2 (delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), vaccination reduced transmission of SARS-CoV-2 from vaccinated persons who became infected, potentially by reducing viral loads. Although vaccination still lowers the risk of infection, similar viral loads in vaccinated and unvaccinated persons who are infected with the delta variant call into question the degree to which vaccination prevents transmission. METHODS: We used contact-testing data from England to perform a retrospective observational cohort study involving adult contacts of SARS-CoV-2–infected adult index patients. We used multivariable Poisson regression to investigate associations between transmission and the vaccination status of index patients and contacts and to determine how these associations varied with the B.1.1.7 (alpha) and delta variants and time since the second vaccination. RESULTS: Among 146,243 tested contacts of 108,498 index patients, 54,667 (37%) had positive SARS-CoV-2 polymerase-chain-reaction (PCR) tests. In index patients who became infected with the alpha variant, two vaccinations with either BNT162b2 or ChAdOx1 nCoV-19 (also known as AZD1222), as compared with no vaccination, were independently associated with reduced PCR positivity in contacts (adjusted rate ratio with BNT162b2, 0.32; 95% confidence interval [CI], 0.21 to 0.48; and with ChAdOx1 nCoV-19, 0.48; 95% CI, 0.30 to 0.78). Vaccine-associated reductions in transmission of the delta variant were smaller than those with the alpha variant, and reductions in transmission of the delta variant after two BNT162b2 vaccinations were greater (adjusted rate ratio for the comparison with no vaccination, 0.50; 95% CI, 0.39 to 0.65) than after two ChAdOx1 nCoV-19 vaccinations (adjusted rate ratio, 0.76; 95% CI, 0.70 to 0.82). Variation in cycle-threshold (Ct) values (indicative of viral load) in index patients explained 7 to 23% of vaccine-associated reductions in transmission of the two variants. The reductions in transmission of the delta variant declined over time after the second vaccination, reaching levels that were similar to those in unvaccinated persons by 12 weeks in index patients who had received ChAdOx1 nCoV-19 and attenuating substantially in those who had received BNT162b2. Protection in contacts also declined in the 3-month period after the second vaccination. CONCLUSIONS: Vaccination was associated with a smaller reduction in transmission of the delta variant than of the alpha variant, and the effects of vaccination decreased over time. PCR Ct values at diagnosis of the index patient only partially explained decreased transmission. (Funded by the U.K. Government Department of Health and Social Care and others.

Modelling decay in effectiveness for evaluation of behaviour change interventions: a tutorial for public health economists

Background and purpose Recent methodological reviews of evaluations of behaviour change interventions in public health have highlighted that the decay in efectiveness over time has been mostly overlooked, potentially leading to suboptimal decision-making. While, in principle, discrete-time Markov chains—the most commonly used modelling approach—can be adapted to account for decay in efectiveness, this framework inherently lends itself to strong model simplifcations. The application of formal and more appropriate modelling approaches has been supported, but limited progress has been made to date. The purpose of this paper is to encourage this shift by ofering a practical guide on how to model decay in efectiveness using a continuous-time Markov chain (CTMC)-based approach. Methods A CTMC approach is demonstrated, with a contextualized tutorial being presented to facilitate learning and uptake. A worked example based on the stylized case study in physical activity promotion is illustrated with accompanying R code. Discussion The proposed framework presents a relatively small incremental change from the current modelling practice. CTMC represents a technical solution which, in absence of relevant data, allows for formally testing the sensitivity of results to assumptions regarding the long-term sustainability of intervention efects and improving model transparency. Conclusions The use of CTMC should be considered in evaluations where decay in efectiveness is likely to be a key factor to consider. This would enable more robust model-based evaluations of population-level programmes to promote behaviour change and reduce the uncertainty surrounding the decision to invest in these public health interventions

Does appropriate empiric antibiotic therapy modify intensive care unit-acquired Enterobacteriaceae bacteraemia mortality and discharge?

BACKGROUND: Conflicting results have been found regarding outcomes of intensive care unit (ICU)-acquired Enterobacteriaceae bacteraemia and the potentially modifying effect of appropriate empiric antibiotic therapy. AIM: To evaluate these associations while adjusting for potential time-varying confounding using methods from the causal inference literature. METHODS: Patients who stayed more than two days in two general ICUs in England between 2002 and 2006 were included in this cohort study. Marginal structural models with inverse probability weighting were used to estimate the mortality and discharge associated with Enterobacteriaceae bacteraemia and the impact of appropriate empiric antibiotic therapy on these outcomes. FINDINGS: Among 3411 ICU admissions, 195 (5.7%) ICU-acquired Enterobacteriaceae bacteraemia cases occurred. Enterobacteriaceae bacteraemia was associated with an increased daily risk of ICU death [cause-specific hazard ratio (HR): 1.48; 95% confidence interval (CI): 1.10-1.99] and a reduced daily risk of ICU discharge (HR: 0.66; 95% CI: 0.54-0.80). Appropriate empiric antibiotic therapy did not significantly modify ICU mortality (HR: 1.08; 95% CI: 0.59-1.97) or discharge (HR: 0.91; 95% CI: 0.63-1.32). CONCLUSION: ICU-acquired Enterobacteriaceae bacteraemia was associated with an increased daily risk of ICU mortality. Furthermore, the daily discharge rate was also lower after acquiring infection, even when adjusting for time-varying confounding using appropriate methodology. No evidence was found for a beneficial modifying effect of appropriate empiric antibiotic therapy on ICU mortality and discharge

Symptoms and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Positivity in the General Population in the United Kingdom

BACKGROUND: “Classic” symptoms (cough, fever, loss of taste/smell) prompt severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) testing in the United Kingdom. Studies have assessed the ability of different symptoms to identify infection, but few have compared symptoms over time (reflecting variants) and by vaccination status. METHODS: Using the COVID-19 Infection Survey, sampling households across the United Kingdom, we compared symptoms in PCR-positives vs PCR-negatives, evaluating sensitivity of combinations of 12 symptoms (percentage symptomatic PCR-positives reporting specific symptoms) and tests per case (TPC) (PCR-positives or PCR-negatives reporting specific symptoms/ PCR-positives reporting specific symptoms). RESULTS: Between April 2020 and August 2021, 27 869 SARS-CoV-2 PCR-positive episodes occurred in 27 692 participants (median 42 years), of whom 13 427 (48%) self-reported symptoms (“symptomatic PCR-positives”). The comparator comprised 3 806 692 test-negative visits (457 215 participants); 130 612 (3%) self-reported symptoms (“symptomatic PCR-negatives”). Symptom reporting in PCR-positives varied by age, sex, and ethnicity, and over time, reflecting changes in prevalence of viral variants, incidental changes (eg, seasonal pathogens (with sore throat increasing in PCR-positives and PCR-negatives from April 2021), schools reopening) and vaccination rollout. After May 2021 when Delta emerged, headache and fever substantially increased in PCR-positives, but not PCR-negatives. Sensitivity of symptom-based detection increased from 74% using “classic” symptoms, to 81% adding fatigue/weakness, and 90% including all 8 additional symptoms. However, this increased TPC from 4.6 to 5.3 to 8.7. CONCLUSIONS: Expanded symptom combinations may provide modest benefits for sensitivity of PCR-based case detection, but this will vary between settings and over time, and increases tests/case. Large-scale changes to targeted PCR-testing approaches require careful evaluation given substantial resource and infrastructure implications

Ct threshold values, a proxy for viral load in community SARS-CoV-2 cases, demonstrate wide variation across populations and over time

Background: Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Methods: We included all positive nose and throat swabs 26 April 2020 to 13 March 2021 from the UK’s national COVID-19 Infection Survey, tested by RT-PCR for the N, S, and ORF1ab genes. We investigated predictors of median Ct value using quantile regression. Results: Of 3,312,159 nose and throat swabs, 27,902 (0.83%) were RT-PCR-positive, 10,317 (37%), 11,012 (40%), and 6550 (23%) for 3, 2, or 1 of the N, S, and ORF1ab genes, respectively, with median Ct = 29.2 (~215 copies/ml; IQR Ct = 21.9–32.8, 14–56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity, and age. Single-gene positives almost invariably had Ct > 30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4808 (78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody negative. Conclusions: Marked variation in community SARS-CoV-2 Ct values suggests that they could be a useful epidemiological early-warning indicator. Funding: Department of Health and Social Care, National Institutes of Health Research, Huo Family Foundation, Medical Research Council UK; Wellcome Trust

Effect of Delta variant on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK

The effectiveness of the BNT162b2 and ChAdOx1 vaccines against new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections requires continuous re-evaluation, given the increasingly dominant B.1.617.2 (Delta) variant. In this study, we investigated the effectiveness of these vaccines in a large, community-based survey of randomly selected households across the United Kingdom. We found that the effectiveness of BNT162b2 and ChAdOx1 against infections (new polymerase chain reaction (PCR)-positive cases) with symptoms or high viral burden is reduced with the B.1.617.2 variant (absolute difference of 10–13% for BNT162b2 and 16% for ChAdOx1) compared to the B.1.1.7 (Alpha) variant. The effectiveness of two doses remains at least as great as protection afforded by prior natural infection. The dynamics of immunity after second doses differed significantly between BNT162b2 and ChAdOx1, with greater initial effectiveness against new PCR-positive cases but faster declines in protection against high viral burden and symptomatic infection with BNT162b2. There was no evidence that effectiveness varied by dosing interval, but protection was higher in vaccinated individuals after a prior infection and in younger adults. With B.1.617.2, infections occurring after two vaccinations had similar peak viral burden as those in unvaccinated individuals. SARS-CoV-2 vaccination still reduces new infections, but effectiveness and attenuation of peak viral burden are reduced with B.1.617.2

The challenge of antimicrobial resistance: What economics can contribute

BACKGROUND: Antimicrobial resistance (AMR) is increasing, driven by widespread antibiotic use. The wide availability of effective antibiotics is under threat, jeopardizing modern health care. Forecasts of the economic costs are similar to those of a 2°C rise in global average surface temperature, above preindustrial levels. AMR is becoming an urgent priority for policy-makers, and pressure is mounting to secure international commitments to tackle the problem. // ADVANCES: Estimating the value of interventions to reduce antibiotic use requires predictions of future levels of antibiotic resistance. However, modeling the trajectory of antibiotic resistance, and how marginal changes in antibiotic consumption contribute to resistance, is complex. The challenge of estimating the resulting impact on health and the economy is similarly daunting. As with the cost of climate change, estimates of total AMR costs are fraught with uncertainty and may be far too low. Much of the uncertainty arises from the complexity of estimating the cost of changes in overall resistance levels. This cost depends on various factors: which drug and pathogen are involved, the mechanism of antibiotic resistance, the prevalence of that pathogen, the types of infections it causes and their level of transmissibility, the health burden of those infections, and whether alternative treatments are available. Effective new antibiotics are urgently needed. However, without government intervention, R&D for antibiotics is rarely profitable, and most major pharmaceutical companies have left the field. New ways are needed to make antibiotic development profitable, decoupling profits from volumes sold. // OUTLOOK: Analogies can be drawn between climate change and AMR, both of which have been described as a global “tragedy of the commons.” There is some consensus that we should treat carbon emissions reduction as an insurance policy against the possibility of a catastrophic climate outcome—and avoid waiting for a definitive optimum-abatement policy. A similar paradigm shift is needed to incentivize both the introduction and valuation of interventions to reduce antibiotic use and R&D of new antibiotics. Rather than taxing the price and letting the market dictate the quantity of antibiotics supplied, an alternative may be to establish a regulatory body that issues prescribers tradable permits and to allow the market to determine the price. Such an approach could create a predictable revenue stream through more-foreseeable licensing fees for important antibiotics by decoupling the return on investment from the volume used. Approaches such as this could incentivize industry to develop new antibiotics for which there would otherwise be too small a market to provide a sufficient return on investment. Reducing inappropriate antibiotic use while expanding essential access is a difficult challenge, especially in low- and middle-income countries. However, policy-makers and philanthropists are alert to the importance of AMR and increasingly are making substantial research funds available, with much of these funds devoted to the social sciences. We need economists, across many different fields, to engage with this pressing global problem

Monitoring populations at increased risk for SARS-CoV-2 infection in the community using population-level demographic and behavioural surveillance

BACKGROUND: The COVID-19 pandemic is rapidly evolving, with emerging variants and fluctuating control policies. Real-time population screening and identification of groups in whom positivity is highest could help monitor spread and inform public health messaging and strategy. METHODS: To develop a real-time screening process, we included results from nose and throat swabs and questionnaires taken 19 July 2020-17 July 2021 in the UK's national COVID-19 Infection Survey. Fortnightly, associations between SARS-CoV-2 positivity and 60 demographic and behavioural characteristics were estimated using logistic regression models adjusted for potential confounders, considering multiple testing, collinearity, and reverse causality. FINDINGS: Of 4,091,537 RT-PCR results from 482,677 individuals, 29,903 (0·73%) were positive. As positivity rose September-November 2020, rates were independently higher in younger ages, and those living in Northern England, major urban conurbations, more deprived areas, and larger households. Rates were also higher in those returning from abroad, and working in healthcare or outside of home. When positivity peaked December 2020-January 2021 (Alpha), high positivity shifted to southern geographical regions. With national vaccine roll-out from December 2020, positivity reduced in vaccinated individuals. Associations attenuated as rates decreased between February-May 2021. Rising positivity rates in June-July 2021 (Delta) were independently higher in younger, male, and unvaccinated groups. Few factors were consistently associated with positivity. 25/45 (56%) confirmed associations would have been detected later using 28-day rather than 14-day periods. INTERPRETATION: Population-level demographic and behavioural surveillance can be a valuable tool in identifying the varying characteristics driving current SARS-CoV-2 positivity, allowing monitoring to inform public health policy. FUNDING: Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research

Seasonality of urinary tract infections in the United Kingdom in different age groups: longitudinal analysis of The Health Improvement Network (THIN)

Evidence regarding the seasonality of urinary tract infection (UTI) consultations in primary care is conflicting and methodologically poor. To our knowledge, this is the first study to determine whether this seasonality exists in the UK, identify the peak months and describe seasonality by age. The monthly number of UTI consultations (N = 992 803) and nitrofurantoin and trimethoprim prescriptions (N = 1 719 416) during 2008-2015 was extracted from The Health Improvement Network (THIN), a large nationally representative UK dataset of electronic patient records. Negative binomial regression models were fitted to these data to investigate seasonal fluctuations by age group (14-17, 18-24, 25-45, 46-69, 70-84, 85+) and by sex, accounting for a change in the rate of UTI over the study period. A September to November peak in UTI consultation incidence was observed for ages 14-69. This seasonality progressively faded in older age groups and no seasonality was found in individuals aged 85+, in whom UTIs were most common. UTIs were rare in males but followed a similar seasonal pattern than in females. We show strong evidence of an autumnal seasonality for UTIs in individuals under 70 years of age and a lack of seasonality in the very old. These findings should provide helpful information when interpreting surveillance reports and the results of interventions against UTI

Awareness of appropriate antibiotic use in primary care for influenza-like illness: Evidence of improvement from UK population-based surveys

Supplementary Materials: The following are available online at https://www.mdpi.com/2079-6382/9/10/690/s1, Figure S1: Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals who would go to the GP with ILI by population subgroup; Figure S2. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals would ask for antibiotics by population subgroup; Figure S3. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals that have taken antibiotics for ILI in the past 12 months by population subgroup; Figure S4. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals that would go to GP with a child with ILI by population subgroup; Figure S5. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals that would ask for antibiotics for a child with ILI by population subgroup; Figure S6. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals that think antibiotics would help for a child with ILI by population subgroup; Figure S7. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals for which child has taken an antibiotic for ILI in the past 12 months by population subgroup; Figure S8. Changes from Survey 1 (red) to Survey 3 (blue) in the percentage of individuals for which AMR information was surprising/new by population subgroup.Copyright © 2020 by the authors. Influenza-like illnesses (ILI) account for a significant portion of inappropriate antibiotic use. Patient expectations for antibiotics for ILI are likely to play a substantial role in ‘unnecessary’ antibiotic consumption. This study aimed to investigate trends in awareness of appropriate antibiotic use and antimicrobial resistance (AMR). Three sequential online surveys of independent representative samples of adults in the United Kingdom investigated expectations for, and consumption of, antibiotics for ILI (May/June 2015 (n = 2064); Oct/Nov 2016 (n = 4000); Mar 2017 (n = 4000)). Respondents were asked whether they thought antibiotics were effective for ILI and about their antibiotic use. Proportions and 95% confidence intervals (CI) were calculated for each question and interactions with respondent characteristics were tested using logistic regression. Over the three surveys, the proportion of respondents who believed antibiotics would “definitely/probably” help an ILI fell from 37% (95% CI 35–39%) to 28% (95% CI 26–29%). Those who would “definitely/probably” visit a doctor in this situation fell from 48% (95% CI 46–50%) to 36% (95% CI 34–37%), while those who would request antibiotics during a consultation fell from 39% (95% CI 37–41%) to 30% (95% CI 29–32%). The percentage of respondents who found the information we provided about AMR “new/surprising” fell from 34% (95% CI 32–36%) to 28% (95% CI 26–31%). Awareness improved more among black, Asian and minority ethnic (BAME) than white people, with little other evidence of differences in improvements between subgroups. Whilst a degree of selection bias is unavoidable in online survey samples, the results suggest that awareness of AMR and appropriate antibiotic use has recently significantly improved in the United Kingdom, according to a wide range of indicators.The research was funded by the National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford in partnership with Public Health England (PHE) [grant numbers HPRU-2012-10041 and NIHR200915], and the NIHR HPRU in Evaluation of Interventions at the University of Bristol, also in partnership with PHE [grant number HPRU-2012-10026]. Michele Peters is an Associate Professor supported by the NIHR funded Policy Research Unit on Quality, Safety and Outcomes (QSO), a collaboration between the Universities of Kent and Oxford, the London School of Hygiene and Tropical Medicine, the Hull-York Medical School and the Picker Institute. Laurence S. J. Roope, James Buchanan, Derrick W. Crook, Tim Peto, A. Sarah Walker and Sarah Wordsworth are partly funded by the Oxford NIHR Biomedical Research Centre. Tim Peto, Christopher C. Butler and A. Sarah Walker are NIHR Senior Investigators. Enrique Castro-Sánchez is affiliated with the NIHR HPRU in Healthcare Associated Infection and Antimicrobial Resistance at Imperial College London in partnership with Public Health England [grant number HPRU-2012-10047], is a National Institute for Health Research Senior Nurse and Midwife Research Leader and acknowledges the support of the BRC. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the National Institute for Health Research (NIHR), the Department of Health, or Public Health England (PHE)