Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 7 de 7
Filter
2.
Nat Med ; 28(7): 1476-1485, 2022 07.
Article in English | MEDLINE | ID: covidwho-1830084

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization and pandemic preparedness are critical to minimize population-wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.


Subject(s)
COVID-19 , Aged , Aged, 80 and over , Bayes Theorem , Brazil/epidemiology , COVID-19/epidemiology , Hospitals , Humans , SARS-CoV-2
3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-312959

ABSTRACT

Background: The multiple efficacious vaccines authorised for emergency use worldwide represent the first preventative intervention against coronavirus disease 2019 (COVID-19) that does not rely on social distancing measures. The speed at which data are emerging and the heterogeneities in study design, target populations, and implementation make it challenging to interpret and assess the likely impact of vaccine campaigns on local epidemics. We reviewed available vaccine efficacy and effectiveness studies to generate working estimates that can be used to parameterise simulation studies of vaccine impact. Methods: We searched MEDLINE, the World Health Organization’s Institutional Repository for Information Sharing, medRxiv, and vaccine manufacturer websites for studies that evaluated the emerging data on COVID-19 vaccine efficacy and effectiveness. Studies providing an estimate of the efficacy or effectiveness of a COVID-19 vaccine using disaggregated data against SARS-CoV-2 infection, symptomatic disease, severe disease, death, or transmission were included. We extracted information on study population, variants of concern (VOC), vaccine platform, dose schedule, study endpoints, and measures of impact. We applied an evidence synthesis approach to capture a range of plausible and consistent parameters for vaccine efficacy and effectiveness that can be used to inform and explore a variety of vaccination strategies as the COVID-19 pandemic evolves. Results: Of the 602 articles and reports identified, 53 were included in the analysis. The availability of vaccine efficacy and effectiveness estimates varied by vaccine and were limited for VOCs. Estimates for non-primary endpoints such as effectiveness against infection and onward transmission were sparse. Synthesised estimates were relatively consistent for the same vaccine platform for wild-type, but was more variable for VOCs. Conclusions: : Assessment of efficacy and effectiveness of COVID-19 vaccines is complex. Simulation studies must acknowledge and capture the uncertainty in vaccine effectiveness to robustly explore and inform vaccination policies and policy around the lifting of non-pharmaceutical interventions.

4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-320841

ABSTRACT

Background: Health-related quality of life (HRQL) is important for evaluating the impact of a disease in the longer term across the physical and psychological domains of human functioning. The aim of this study is to evaluate HRQL in COVID-19 survivors in Italy using the short form 36-items questionnaire (SF-36). Methods: This is an observational study involving adults discharged home following a coronavirus disease 2019 (COVID-19)-related hospital admission. Baseline demographic and clinical data including the Cumulative Illness Rating Scale (CIRS) and the Hospital Anxiety and Depression Scale (HADS) were collected. The validated Italian version of SF-36 was administered cross-sectionally. The SF-36 contains eight scales measuring limitations in physical and social functioning, the impact on roles and activities, fatigue, emotional well-being, pain and general health perception. Results: A total of 35 patients, with a mean age of 60 years, completed the SF-36. The results showed difficulties across the physical and psychological domains, particularly affecting the return to previous roles and activities. A higher burden of co-morbidities as well as a more severe muscle weakness was associated to a lower physical functioning. Younger age, rather than older, correlated to a perceived greater limitation in physical functioning and vitality. Conclusions: COVID-19 survivors particularly the ones of working age may need support for resuming their premorbid level of functioning and returning to work.

5.
Lancet ; 398(10313): 1825-1835, 2021 11 13.
Article in English | MEDLINE | ID: covidwho-1492790

ABSTRACT

BACKGROUND: England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories. METHODS: This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions. FINDINGS: The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness. INTERPRETATION: Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. FUNDING: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/organization & administration , SARS-CoV-2 , Vaccination Coverage/organization & administration , COVID-19/epidemiology , COVID-19/mortality , England/epidemiology , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Humans , Models, Theoretical , Patient Admission/statistics & numerical data
6.
Diabetes Care ; 44(1): 50-57, 2021 01.
Article in English | MEDLINE | ID: covidwho-1067598

ABSTRACT

OBJECTIVE: To describe the relationship between type 2 diabetes and all-cause mortality among adults with coronavirus disease 2019 (COVID-19) in the critical care setting. RESEARCH DESIGN AND METHODS: This was a nationwide retrospective cohort study in people admitted to hospital in England with COVID-19 requiring admission to a high dependency unit (HDU) or intensive care unit (ICU) between 1 March 2020 and 27 July 2020. Cox proportional hazards models were used to estimate 30-day in-hospital all-cause mortality associated with type 2 diabetes, with adjustment for age, sex, ethnicity, obesity, and other major comorbidities (chronic respiratory disease, asthma, chronic heart disease, hypertension, immunosuppression, chronic neurological disease, chronic renal disease, and chronic liver disease). RESULTS: A total of 19,256 COVID-19-related HDU and ICU admissions were included in the primary analysis, including 13,809 HDU (mean age 70 years) and 5,447 ICU (mean age 58 years) admissions. Of those admitted, 3,524 (18.3%) had type 2 diabetes and 5,077 (26.4%) died during the study period. Patients with type 2 diabetes were at increased risk of death (adjusted hazard ratio [aHR] 1.23 [95% CI 1.14, 1.32]), and this result was consistent in HDU and ICU subsets. The relative mortality risk associated with type 2 diabetes decreased with higher age (age 18-49 years aHR 1.50 [95% CI 1.05, 2.15], age 50-64 years 1.29 [1.10, 1.51], and age ≥65 years 1.18 [1.09, 1.29]; P value for age-type 2 diabetes interaction = 0.002). CONCLUSIONS: Type 2 diabetes may be an independent prognostic factor for survival in people with severe COVID-19 requiring critical care treatment, and in this setting the risk increase associated with type 2 diabetes is greatest in younger people.


Subject(s)
COVID-19/complications , COVID-19/mortality , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/mortality , Adolescent , Adult , Aged , Aged, 80 and over , Cohort Studies , Comorbidity , Critical Care/statistics & numerical data , England/epidemiology , Female , Hospital Mortality , Hospitalization , Humans , Intensive Care Units , Kidney Failure, Chronic/complications , Male , Middle Aged , Prognosis , Proportional Hazards Models , Retrospective Studies , Risk Factors , SARS-CoV-2 , Young Adult
7.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-1250

ABSTRACT

Background:The importance of diabetes as a prognostic factor in people admitted to hospital critical care with COVID-19 is poorly understood and has not been qu

SELECTION OF CITATIONS
SEARCH DETAIL