2020
DOI: 10.1101/2020.10.19.20214494
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Attributes and predictors of Long-COVID: analysis of COVID cases and their symptoms collected by the Covid Symptoms Study App

Abstract: Reports of "Long-COVID", are rising but little is known about prevalence, risk factors, or whether it is possible to predict a protracted course early in the disease. We analysed data from 4182 incident cases of COVID-19 who logged their symptoms prospectively in the COVID Symptom Study app. 558 (13.3%) had symptoms lasting >28 days, 189 (4.5%) for >8 weeks and 95 (2.3%) for >12 weeks. Long-COVID was characterised by symptoms of fatigue, headache, dyspnoea and anosmia and was more likely with increa… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

26
255
4
23

Year Published

2020
2020
2022
2022

Publication Types

Select...
7
3

Relationship

0
10

Authors

Journals

citations
Cited by 238 publications
(308 citation statements)
references
References 17 publications
26
255
4
23
Order By: Relevance
“…During this period there was evidence of a downturn in daily infections from the national surveillance data on symptomatic cases ("Pillar 1 and 2") [1] and from the coronavirus symptom app (Zoe app) [12] , and a plateau in data from the Office for National Statistics Coronavirus (COVID-19) Infection Survey [13] . Despite differences between these data streams in their recruitment strategy including whether this is influenced by symptom status [1,12], all four are broadly consistent in identifying an inflection point towards the end of our study period.…”
Section: Discussionmentioning
confidence: 99%
“…During this period there was evidence of a downturn in daily infections from the national surveillance data on symptomatic cases ("Pillar 1 and 2") [1] and from the coronavirus symptom app (Zoe app) [12] , and a plateau in data from the Office for National Statistics Coronavirus (COVID-19) Infection Survey [13] . Despite differences between these data streams in their recruitment strategy including whether this is influenced by symptom status [1,12], all four are broadly consistent in identifying an inflection point towards the end of our study period.…”
Section: Discussionmentioning
confidence: 99%
“…The survey asked respondents to detail their experience of a subset of 66 symptoms over time. Respondents indicated whether each of these symptoms was present during a series of time intervals following the onset of their first symptoms: week 1 (days 1-7), week 2 (days [8][9][10][11][12][13][14], week 3 (days 15-21), week 4 (days [22][23][24][25][26][27][28][29][30], month 2 (days 31-60), month 3 (days 61-90), month 4 (days 91-120), month 5 (days 121-150, month 6 (days 151-180), and month 7 (days 181-210).…”
Section: Symptom Time Course Estimationmentioning
confidence: 99%
“…Symptoms of illness persisting after resolution of acute SARS-CoV-2 infection are common, yet incompletely described. A prospective observational cohort of 4,182 people positive for SARS-CoV-2 in Great Britain, the US, and Sweden revealed persistent symptoms for more than 28 days (long COVID LC28) in 13.3% of study volunteers ( Sudre et al., 2020 ). The proportion of people with obesity was higher in the LC28 cohort relative to the cohort reporting shorter duration of symptoms.…”
Section: Long-covid Syndrome and Indirect Consequences Of Covid-19mentioning
confidence: 99%