Background The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. Methods In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1•5, 2•0, and 3•0 at differing infection rate scenarios, including full suppression (0•001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. Findings We included 3 862 012 individuals (1 957 935 [50•7%] women and 1 904 077 [49•3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13•7% were older than 70 years and 6•3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4•46% (95% CI 4•41-4•51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1•5, four with an RR of 2•0, and seven with an RR of 3•0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1•5, 36 749 with an RR of 2•0, and 73 498 with an RR of 3•0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1•5, 293 991 with an RR of 2•0, and 587 982 with an RR of 3•0. Interpretation We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indir...

SummaryBackgroundInvasive community-onset staphylococcal disease has emerged worldwide associated with Panton-Valentine leucocidin (PVL) toxin. Whether PVL is pathogenic or an epidemiological marker is unclear. We investigate the role of PVL in disease, colonisation, and clinical outcome.MethodsWe searched Medline and Embase for original research reporting the prevalence of PVL genes among Staphylococcus aureus pneumonia, bacteraemia, musculoskeletal infection, skin and soft-tissue infection, or colonisation published before Oct 1, 2011. We calculated odds ratios (ORs) to compare patients with PVL-positive colonisation and each infection relative to the odds of PVL-positive skin and soft-tissue infection. We did meta-analyses to estimate odds of infection or colonisation with a PVL-positive strain with fixed-effects or random-effects models, depending on the results of tests for heterogeneity.ResultsOf 509 articles identified by our search strategy, 76 studies from 31 countries met our inclusion criteria. PVL strains are strongly associated with skin and soft-tissue infections, but are comparatively rare in pneumonia (OR 0·37, 95% CI 0·22–0·63), musculoskeletal infections (0·44, 0·19–0·99), bacteraemias (0·10, 0·06–0·18), and colonising strains (0·07, 0·01–0·31). PVL-positive skin and soft-tissue infections are more likely to be treated surgically than are PVL-negative infections, and children with PVL-positive musculoskeletal disease might have increased morbidity. For other forms of disease we identified no evidence that PVL affects outcome.InterpretationPVL genes are consistently associated with skin and soft-tissue infections and are comparatively rare in invasive disease. This finding challenges the view that PVL mainly causes invasive disease with poor prognosis. Population-based studies are needed to define the role of PVL in mild, moderate, and severe disease and to inform control strategies.FundingNone.

Background The effectiveness of SARS-CoV-2 vaccines in older adults living in long-term care facilities is uncertain. We investigated the protective effect of the first dose of the Oxford-AstraZeneca non-replicating viral-vectored vaccine (ChAdOx1 nCoV-19; AZD1222) and the Pfizer-BioNTech mRNA-based vaccine (BNT162b2) in residents of long-term care facilities in terms of PCR-confirmed SARS-CoV-2 infection over time since vaccination. Methods The VIVALDI study is a prospective cohort study that commenced recruitment on June 11, 2020, to investigate SARS-CoV-2 transmission, infection outcomes, and immunity in residents and staff in long-term care facilities in England that provide residential or nursing care for adults aged 65 years and older. In this cohort study, we included long-term care facility residents undergoing routine asymptomatic SARS-CoV-2 testing between Dec 8, 2020 (the date the vaccine was first deployed in a long-term care facility), and March 15, 2021, using national testing data linked within the COVID-19 Datastore. Using Cox proportional hazards regression, we estimated the relative hazard of PCR-positive infection at 0-6 days, 7-13 days, 14-20 days, 21-27 days, 28-34 days, 35-48 days, and 49 days and beyond after vaccination, comparing unvaccinated and vaccinated person-time from the same cohort of residents, adjusting for age, sex, previous infection, local SARS-CoV-2 incidence, long-term care facility bed capacity, and clustering by long-term care facility. We also compared mean PCR cycle threshold (Ct) values for positive swabs obtained before and after vaccination. The study is registered with ISRCTN, number 14447421. Findings 10 412 care home residents aged 65 years and older from 310 LTCFs were included in this analysis. The median participant age was 86 years (IQR 80-91), 7247 (69•6%) of 10 412 residents were female, and 1155 residents (11•1%) had evidence of previous SARS-CoV-2 infection. 9160 (88•0%) residents received at least one vaccine dose, of whom 6138 (67•0%) received ChAdOx1 and 3022 (33•0%) received BNT162b2. Between Dec 8, 2020, and March 15, 2021, there were 36 352 PCR results in 670 628 person-days, and 1335 PCR-positive infections (713 in unvaccinated residents and 612 in vaccinated residents) were included. Adjusted hazard ratios (HRs) for PCR-positive infection relative to unvaccinated residents declined from 28 days after the first vaccine dose to 0•44 (95% CI 0•24-0•81) at 28-34 days and 0•38 (0•19-0•77) at 35-48 days. Similar effect sizes were seen for ChAdOx1 (adjusted HR 0•32, 95% CI 0•15-0•66) and BNT162b2 (0•35, 0•17-0•71) vaccines at 35-48 days. Mean PCR Ct values were higher for infections that occurred at least 28 days after vaccination than for those occurring before vaccination (31•3 [SD 8•7] in 107 PCR-positive tests vs 26•6 [6•6] in 552 PCR-positive tests; p<0•0001).Interpretation Single-dose vaccination with BNT162b2 and ChAdOx1 vaccines provides substantial protection against infection in older adults from 4-7 weeks after vaccination and might reduce SARS...

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Antibiotics underpin all of modern medicine, from routine major surgery through to caesarean sections and modern cancer therapies. These drugs have revolutionized how we practice medicine, but we are in a constant evolutionary battle to evade microbial resistance and this has become a major global public health problem. We have overused and misused these essential medicines both in the human and animal health sectors and this threatens the effectiveness of antimicrobials for future generations. We can only address the threat of antimicrobial resistance (AMR) through international collaboration across human and animal health sectors integrating social, economic and behavioural factors. Our global organizations are rising to the challenge with the recent World Health Assembly resolution on AMR and development of the Global Action plan but we must act now to avoid a return to a pre-antibiotic era.