Systematic review of the prevalence of Long Covid

Woodrow, Mirembe; Carey, Charles; Ziauddeen, Nida; Thomas, Rebecca; Akrami, Athena; Lutje, Vittoria; Greenwood, Darren C.; Alwan, Nisreen A

doi:10.1101/2022.11.06.22281979

Cited by 7 publications

(5 citation statements)

References 136 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Woodrow et al found a prevalence estimate of 42.1% in their systematic review, with values ranging from 0% to 93% in the various studies selected [3]. This result agrees with another meta-analysis estimating a global PCC prevalence of 43% [4], while another paper showed that 80% of individuals with a confirmed COVID-19 diagnosis presented at least one long-term symptom [5].…”

Section: Introductionsupporting

confidence: 65%

The aftermath of Post COVID-19 Condition in Italy and the United States: an ecological comparison

Garlasco,

Nurchis,

Raspolini

et al. 2024

Preprint

View full text Add to dashboard Cite

Post COVID-19 Condition (PCC) is a clinical syndrome following COVID-19 disease. PCC symptoms in adults entail significant productivity loss and reduced quality of life. This study aimed at estimating the epidemiological and economic burden of PCC among the working-age population of Italy and the US. This ecological analysis was conducted on data from January 2020 to April 2023, regarding population aged 18-64. PCC incidence was retrieved for the US, while for Italy it was estimated from COVID-19 cases. Prevalence of factors associated with PCC and parameters to calculate temporary productivity losses (TPL) were retrieved. An estimated Incidence Rate Ratio (eIRR) of PCC incidence in Italy and the US was calculated. TPL for reduced earnings and total Quality-Adjusted Life Years (QALYs) lost were also estimated. The ecological eIRR Italy/US was 0.842 [95%CI: 0.672–1.015], suggesting that, holding COVID-19 cases constant, 15.8% fewer PCC cases have occurred in Italy compared to the US. Overall PCC cases were found to be roughly 12.0 [95%CI: 9.9–14.1] million in the US, with 1.9 [95%CI: 1.6–2.3] million QALYs lost, and around 2.4 [95%CI: 1.8–3.0] million in Italy, with 0.4 [95%CI: 0.3–0.5] million QALYs lost. Up to April 2023, the TPL was estimated to be €4.5 [95%CI: 3.5–6.1] billion in Italy and $41.5 [95%CI: 34.3–48.7] billion in the US. PCC has had a significant epidemiological and economic impact on the working-age population. The findings from this study may be of use for health planning and policy regarding PCC in working-age adults.

show abstract

Section: Introductionsupporting

confidence: 65%

The aftermath of Post COVID-19 Condition in Italy and the United States: an ecological comparison

Garlasco,

Nurchis,

Raspolini

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Some findings from this study show similarities with other Long Covid studies. Most notably, the varying range of symptoms experienced, 4–8 the lack of Long Covid awareness among some population groups, 7,47,48 self‐doubt regarding Long Covid as a cause for illness, 7 symptoms as a barrier to accessing care, 47 problems accessing primary care, 6,10,49 experiences of symptoms being dismissed, 10,32,50 seeking support outside the NHS and making behavioural changes, 6,11,49–51 as well as stigma 6,50,51 and discrimination 49 which can all act as barriers to obtaining support and treatment.…”

Section: Discussionmentioning

confidence: 99%

“…Long Covid can cause varying symptoms and impact on daily life, including, but not limited to, fatigue, breathlessness, headache, cognitive dysfunction, chest pain, muscle/joint pains, cough, disturbed sleep and neuropsychiatric symptoms 1,4–8 . It can have wide‐ranging negative social impacts that include inhibiting the ability to engage in employment and creating financial burdens 4,9–11 …”

Section: Introductionmentioning

confidence: 99%

Barriers to healthcare access and experiences of stigma: Findings from a coproduced Long Covid case‐finding study

Clutterbuck,

Ramasawmy,

Pantelic

et al. 2024

Health Expectations

View full text Add to dashboard Cite

Background and AimLong Covid is often stigmatised, particularly in people who are disadvantaged within society. This may prevent them from seeking help and could lead to widening health inequalities. This coproduced study with a Community Advisory Board (CAB) of people with Long Covid aimed to understand healthcare and wider barriers and stigma experienced by people with probable Long Covid.MethodsAn active case finding approach was employed to find adults with probable, but not yet clinically diagnosed, Long Covid in two localities in London (Camden and Merton) and Derbyshire, England. Interviews explored the barriers to care and the stigma faced by participants and were analysed thematically. This study forms part of the STIMULATE‐ICP Collaboration.FindingsTwenty‐three interviews were completed. Participants reported limited awareness of what Long Covid is and the available pathways to management. There was considerable self‐doubt among participants, sometimes reinforced by interactions with healthcare professionals (HCPs). Participants questioned their deservedness in seeking healthcare support for their symptoms. Hesitancy to engage with healthcare services was motivated by fear of needing more investigation and concerns regarding judgement about the ability to carry out caregiving responsibilities. It was also motivated by the complexity of the clinical presentation and fear of all symptoms being attributed to poor mental health. Participants also reported trying to avoid overburdening the health system. These difficulties were compounded by experiences of stigma and discrimination. The emerging themes reaffirmed a framework of epistemic injustice in relation to Long Covid, where creating, interpreting and conveying knowledge has varied credibility based on the teller's identity characteristics and/or the level of their interpretive resources.ConclusionWe have codeveloped recommendations based on the findings. These include early signposting to services, dedicating protected time to listening to people with Long Covid, providing a holistic approach in care pathways, and working to mitigate stigma. Regardless of the diagnosis, people experiencing new symptoms must be encouraged to seek timely medical help. Clear public health messaging is needed among communities already disadvantaged by epistemic injustice to raise awareness of Long Covid, and to share stories that encourage seeking care and to illustrate the adverse effects of stigma.Patient or Public ContributionThis study was coproduced with a CAB made up of 23 members including HCPs, people with lived experience of Long Covid and other stakeholders.

show abstract

“…With the lack of a consensus clinical definition of Long COVID, 20 assessment of the true accuracy of algorithms like ours is challenging. Moreover, the lack of a consistent estimate for Long COVID’s prevalence 21 makes it difficult to determine an appropriate model threshold using real-world evidence. Assessing performance using the U09.9 label as ground truth is the most readily available option, but the inconsistency of the code’s use by providers and its late availability 4 mean that many patients with Long COVID lack the label.…”

Section: Discussionmentioning

confidence: 99%

Reengineering a machine learning phenotype to adapt to the changing COVID-19 landscape: A study from the N3C and RECOVER consortia

Crosskey,

McIntee,

Preiss

et al. 2023

Preprint

View full text Add to dashboard Cite

BackgroundIn 2021, we used the National COVID Cohort Collaborative (N3C) as part of the NIH RECOVER Initiative to develop a machine learning (ML) pipeline to identify patients with a high probability of having post-acute sequelae of SARS-CoV-2 infection (PASC), or Long COVID. However, the increased home testing, missing documentation, and reinfections that characterize the latter years of the pandemic necessitate reengineering our original model to account for these changes in the COVID-19 research landscape.MethodsOur updated XGBoost model gathers data for each patient in overlapping 100-day periods that progress through time, and issues a probability of Long COVID for each 100-day period. If a patient has known acute COVID-19 during any 100-day window (including reinfections), we censor the data from 7 days prior to the diagnosis/positive test date through 28 days after. These fixed time windows replace the prior model’s reliance on a documented COVID-19 index date to anchor its data collection, and are able to account for reinfections.ResultsThe updated model achieves an area under the receiver operating characteristic curve of 0.90. Precision and recall can be adjusted according to a given use case, depending on whether greater sensitivity or specificity is warranted.DiscussionBy eschewing the COVID-19 index date as an anchor point for analysis, we are now able to assess the probability of Long COVID among patients who may have tested at home, or with suspected (but untested) cases of COVID-19, or multiple SARS-CoV-2 reinfections. We view this exercise as a model for maintaining and updating any ML pipeline used for clinical research and operations.

show abstract

Systematic review of the prevalence of Long Covid

Cited by 7 publications

References 136 publications

The aftermath of Post COVID-19 Condition in Italy and the United States: an ecological comparison

The aftermath of Post COVID-19 Condition in Italy and the United States: an ecological comparison

Barriers to healthcare access and experiences of stigma: Findings from a coproduced Long Covid case‐finding study

Reengineering a machine learning phenotype to adapt to the changing COVID-19 landscape: A study from the N3C and RECOVER consortia

Contact Info

Product

Resources

About