ABSTRACT
Background: While many studies on the determinants of post-COVID-19 conditions (PCC) have been conducted, little is known about the relationship between SARS-CoV-2 variants and PCC. This study aimed to assess the association between different SARS-CoV-2 variants and the probability of having PCC three months after the infection. Methods: This study was a longitudinal cohort study conducted between April 2021 and September 2022 in Belgium. In total, 8,238 adults with a confirmed SARS-CoV-2 infection were followed up between the time of their infection and three months later. The primary outcomes were the PCC status three months post infection and seven PCC symptoms categories (neurocognitive, autonomic, gastrointestinal, respiratory, musculoskeletal, anosmia and/or dysgeusia, and other manifestations). The main exposure variable was the type of SARS-CoV-2 variants (i.e. Alpha, Delta, and Omicron), extracted from national surveillance data. The association between the different SARS-CoV-2 variants and PCC as well as PCC symptoms categories was assessed using multivariable logistic regression. Results: The proportion of PCC among participants infected during the Alpha, Delta, and Omicron-dominant periods was significantly different and respectively 50%, 50%, and 37%. Participants infected during the Alpha- and Delta-dominant periods had a significantly higher odds of having PCC than those infected during the Omicron-dominant period (OR = 1.61, 95% confidence interval [CI] = 1.33–1.96 and OR = 1.73, 95%CI = 1.54–1.93, respectively). Participants infected during the Alpha and Delta-dominant periods were more likely to report neurocognitive, respiratory, and anosmia/dysgeusia symptoms of PCC. Conclusions: People infected during the Alpha- and Delta-dominant periods had a higher probability of having PCC three months after infection than those infected during the Omicron-dominant period. The lower probability of PCC with the Omicron variant must also be interpreted in absolute figures. Indeed, the number of infections with the Omicron variant being higher than with the Alpha and Delta variants, it is possible that the overall prevalence of PCC in the population increases, even if the probability of having a PCC decreases.
Subject(s)
Dysgeusia , COVID-19ABSTRACT
Background: Recent studies have identified important social inequalities in SARS-CoV-2 infection and related COVID-19 outcomes in the Belgian population. The aim of our study was to investigate the sociodemographic and socioeconomic characteristics associated with the uptake of COVID-19 vaccine in Belgium. Methods: We conducted a cross-sectional analysis of the uptake of a first COVID-19 vaccine dose among 5,342,110 adults ([≥]18 years) in Belgium from December 28th 2020 (official starting date of the vaccination campaign) until August 31st 2021. We integrated data from four national data sources: the Belgian vaccine register (vaccination status), COVID-19 Healthdata (laboratory test results), DEMOBEL (sociodemographic/socioeconomic data), and the Common Base Registry for HealthCare Actors (individuals licensed to practice a healthcare profession in Belgium). We used multivariable logistic regression analysis for identifying characteristics associated with not having obtained a first COVID-19 vaccine dose in Belgium and for each of its three regions (Flanders, Brussels, and Wallonia). Results: During the study period, 10% (536,716/5,342,110) of the Belgian adult population included in our study sample was not vaccinated with a first COVID-19 vaccine dose. A lower COVID-19 vaccine uptake was found among young individuals, men, migrants, single parents, one-person households, and disadvantaged socioeconomic groups (with lower levels of income and education, unemployed). Overall, the sociodemographic and socioeconomic disparities were comparable for all regions. Conclusions: The identification of sociodemographic and socioeconomic disparities in COVID-19 vaccination uptake is critical to develop strategies guaranteeing a more equitable vaccination coverage of the Belgian adult population.
Subject(s)
COVID-19ABSTRACT
BackgroundBy March 2020, COVID-19 cases were confirmed globally. Internationally, variations in estimates relating to the ‘direct’ effect of COVID-19 on population health have been reported. The key to standardising comparisons between nations is to quantify the total effect of COVID-19’s morbidity and mortality, using a standardised methodology. The Burden of Disease (BoD) frameworks achieve this using a summary metric, the ‘Disability-Adjusted- Life- Years’ (DALYs).MethodsOur DALYs are estimates of summing the ‘Years-of-Life-Lost’ (YLLs) and the ‘Years- Lost due to Disability’ (YLD) for the ‘direct’ burden of COVID-19 in the Republic of Ireland (RoI) from March 01, 2020, to February 28, 2021. Life expectancy was based on the Global Burden of Disease (GBD) Study life tables for 2019.ResultsThere were 220,273 cases of COVID-19 and 4,500 related deaths within this study’s parameters. DALYs were estimated to be 51,532.1 (95% Uncertainty Intervals [UI] 50,671.6, 52,294.3). Overall, YLL contributed to 98.7% of the DALYs. Of total symptomatic cases, 6.5% required hospitalisation and of those hospitalised 10.8% required intensive care unit treatment. COVID-19 was likely to be the second highest cause of death over our study’s duration.ConclusionEstimating the burden of a disease at national level is useful for comparing its impact with other diseases in the population and across populations. This work sets out to standardise a COVID-19 BoD methodology framework for the RoI and comparable nations in the EU.
ABSTRACT
Objectives Burden of Disease frameworks facilitate estimation of the health impact of diseases to be translated into a single measure, such as the Disability-Adjusted-Life-Year (DALY). Methods DALYs were calculated as the sum of Years of Life Lost (YLL) and Years Lived with Disability (YLD) directly associated with COVID-19 in the Republic of Ireland (RoI) from March 01, 2020, to February 28, 2021. Life expectancy is based on the Global Burden of Disease (GBD) Study life tables for 2019. Results There were 220,273 confirmed cases with a total of 4,500 deaths as a direct result of COVID-19. DALYs were estimated to be 51,532.1 (95% Uncertainty Intervals [UI] 50,671.6, 52,294.3). Overall, YLL contributed to 98.7% of the DALYs. Of total symptomatic cases, 6.5% required hospitalisation and of those hospitalised 10.8% required intensive care unit treatment. COVID-19 was likely to be the second highest cause of death over our study's duration. Conclusion Estimating the burden of a disease at national level is useful for comparing its impact with other diseases in the population and across populations. This work sets out to standardise a COVID-19 BoD methodology framework for the RoI and comparable nations in the EU.
Subject(s)
Movement Disorders , Aphasia , COVID-19 , Death , DiseaseABSTRACT
COVID-19 has affected all countries. Its containment represents a unique challenge for India due to a large population (>1.38 billion) across a wide range of population densities. Assessment of the COVID-19 disease burden is required to put the disease impact into context and support future pandemic policy development. Here, we present the national-level burden of COVID-19 in India in 2020 that accounts for differences across urban and rural regions and across age groups. Disability-adjusted life years (DALY) due to COVID-19 were estimated in the Indian population in 2020, comprised of years of life lost (YLL) and years lived with disability (YLD). Scenario analyses were conducted to account for excess deaths not recorded in the official data and for reported COVID-19 deaths. The direct impact of COVID-19 in 2020 in India was responsible for 14,106,060 (95% uncertainty interval [UI] 14,030,129–14,213,231) DALYs, consisting of 99.2% (95% UI 98.47–99.64%) YLLs and 0.80% (95% UI 0.36–1.53) YLDs. DALYs were higher in urban (56%; 95% UI 56–57%) than rural areas (44%; 95% UI 43.4–43.6) and in males (64%) than females (36%). In absolute terms, the highest DALYs occurred in the 51–60-year-old age group (28%) but the highest DALYs per 100,000 persons were estimated for the 71-80 year old age group (5,481; 95% UI 5,464–5,500 years). There were 4,823,791 (95% UI 4,760,908–4,924,307) DALYs after considering reported COVID-19 deaths only. The DALY estimations have direct and immediate implications not only for public policy in India, but also internationally given that India represents one sixth of the world’s population.
Subject(s)
COVID-19ABSTRACT
Objective. Scrutiny of COVID-19 mortality in Belgium over the period 8 March-9 May 2020 (Weeks 11-19), using number of deaths per million, infection fatality rates, and the relation between COVID-19 mortality and excess death rates. Data. Publicly available COVID-19 mortality (2020); overall mortality (2009-2020) data in Belgium and demographic data on the Belgian population; data on the nursing home population; results of repeated sero-prevalence surveys in March-April 2020. Statistical methods. Reweighing, missing-data handling, rate estimation, visualization. Results. Belgium has virtually no discrepancy between COVID-19 reported mortality (confirmed and possible cases) and excess mortality. There is a sharp excess death peak over the study period; the total number of excess deaths makes April 2020 the deadliest month of April since WWII, with excess deaths far larger than in early 2017 or 2018, even though influenza-induced January 1951 and February 1960 number of excess deaths were similar in magnitude. Using various sero-prevalence estimates, infection fatality rates (IFRs; fraction of deaths among infected cases) are estimated at 0.38-0.73% for males and 0.20-0.39% for females in the non-nursing home population (non-NHP), and at 0.79-1.52% for males and 0.88-1.31% for females in the entire population. Estimates for the NHP range from 38 to 73% for males and over 22 to 37% for females. The IFRs rise from nearly 0% under 45 years, to 4.3% and 13.2% for males in the non-NHP and the general population, respectively, and to 1.5% and 11.1% for females in the non-NHP and general population, respectively. The IFR and number of deaths per million is strongly influenced by extensive reporting and the fact that 66.0% of the deaths concerned NH residents. At 764 (our re-estimation of the figure 735, presented by "Our World in Data"), the number of COVID-19 deaths per million led the international ranking on May 9, 2020, but drops to 262 in the non-NHP. The NHP is very specific: age-related increased risk; highly prevalent comorbidities that, while non-fatal in themselves, exacerbate COVID-19; larger collective households that share inadvertent vectors such as caregivers and favor clustered outbreaks; initial lack of protective equipment, etc. High-quality health care countries have a relatively older but also more frail population [1], which is likely to contribute to this result.