How accurate are symptoms and medical examination to diagnose COVID-19?

Key messages

- The results suggest that a single symptom included in this review cannot accurately diagnose COVID-19.

- Loss of sense of taste or smell could be a 'red flag' for the presence of COVID-19. Cough or fever might be useful to identify people who might have COVID-19. These symptoms might be useful to prompt further testing when they are present.

- We need more research to investigate combinations of symptoms and signs with other information such as recent contact or travel history, or vaccination status, and in children, and adults aged 65 years and over.

What are symptoms or signs of COVID-19?

Symptoms are experienced by patients. COVID-19 symptoms include cough, sore throat, high temperature, diarrhoea, headache, muscle or joint pain, fatigue, and loss of sense of smell and taste.

Signs are measured by healthcare workers during clinical examination. They include lung sounds, blood pressure, blood oxygen level and heart rate.

Symptoms and signs of COVID-19 might be important to help people know whether they and the people they come into contact with should isolate at home, undergo testing with a rapid lateral flow test or PCR (laboratory-based) test, or be hospitalised.

What did we want to find out?

Symptoms and signs of COVID-19 are varied and may indicate other diseases, not just COVID-19. We wanted to know how accurate diagnosis of COVID-19 is, based on symptoms and signs from medical examination. We were interested in people with suspected COVID-19, who go to their doctor, outpatient test centres or hospital.

What did we do?

We searched for studies that assessed the accuracy of symptoms and signs to diagnose COVID-19. Studies had to be conducted in general practice, outpatient test centres or hospital outpatient settings only. We only included studies of people in hospital if signs and symptoms were recorded when they were admitted to the hospital, for example through the emergency department.

What did we find?

We focused on 42 studies with 52,608 participants in this review. The studies assessed 96 separate or combined symptoms and signs. Thirty-five studies were conducted in emergency departments or outpatient COVID-19 test centres (46,878 participants), 3 studies in general practice (1230 participants), 2 studies in children’s hospitals (493 in- and outpatients), and 2 studies in nursing homes (4007 participants). The studies were conducted in 18 different countries around the world. Twenty-three studies were conducted in Europe, 8 in North-America, 5 in Asia, and 3 in South-America and 3 in Australia. We didn’t find any studies conducted in Africa. Three focused specifically on children, and only 1 focused on adults aged 65 years and over.

Most studies did not clearly distinguish between mild and severe COVID-19, so we present the results for mild, moderate and severe disease together.

Few studies reported individual signs as diagnostic tests, so we focus mainly on the diagnostic value of symptoms. The most frequently reported symptoms were cough, fever, shortness of breath and sore throat.

According to the studies in our review, in a group of 1000 people with suspected COVID-19 of whom 270 (27%) would actually have COVID-19, around 567 people would have a cough. Of these 567, 168 would actually have COVID-19. Of the 433 who do not have a cough, 102 would have COVID-19. In the same 1000 people, around 283 people would have a fever. Of these 283, 102 would actually have COVID-19. Of the 717 people without fever, 168 would have COVID-19.

Someone who has lost their sense of smell or taste is five times more likely to have COVID-19 than someone who hasn’t.

Other symptoms, such as a sore throat or runny nose, are more likely to indicate the presence of an infectious disease other than COVID-19. In the same 1000 people as described above, around 362 people would have a sore throat. Of these, only 84 would actually have COVID-19. Of the 638 patients without sore throat, 186 would have COVID-19. We found similar figures for having a runny nose.

What are the limitations of the evidence?

The results of this updated review are more reliable than those in previous versions as we included more high-quality studies. However, the accuracy of individual symptoms varied across studies and the diagnostic value of symptoms such as fever, cough or other respiratory symptoms might still be overestimated, as most studies deliberately included participants because they had these symptoms.

The results do not clearly differentiate between people with mild, moderate or severe COVID-19. Only a few studies investigated the symptom-based diagnosis of COVID-19 in children or older adults.

How up to date is this review?

This review updates our previous review. The evidence is up to date to June 2021.

Authors' conclusions: 

Most individual symptoms included in this review have poor diagnostic accuracy. Neither absence nor presence of symptoms are accurate enough to rule in or rule out the disease. The presence of anosmia or ageusia may be useful as a red flag for the presence of COVID-19. The presence of cough also supports further testing. There is currently no evidence to support further testing with PCR in any individuals presenting only with upper respiratory symptoms such as sore throat, coryza or rhinorrhoea.

Combinations of symptoms with other readily available information such as contact or travel history, or the local recent case detection rate may prove more useful and should be further investigated in an unselected population presenting to primary care or hospital outpatient settings.

The diagnostic accuracy of symptoms for COVID-19 is moderate to low and any testing strategy using symptoms as selection mechanism will result in both large numbers of missed cases and large numbers of people requiring testing. Which one of these is minimised, is determined by the goal of COVID-19 testing strategies, that is, controlling the epidemic by isolating every possible case versus identifying those with clinically important disease so that they can be monitored or treated to optimise their prognosis. The former will require a testing strategy that uses very few symptoms as entry criterion for testing, the latter could focus on more specific symptoms such as fever and anosmia.

Read the full abstract...

COVID-19 illness is highly variable, ranging from infection with no symptoms through to pneumonia and life-threatening consequences. Symptoms such as fever, cough, or loss of sense of smell (anosmia) or taste (ageusia), can help flag early on if the disease is present. Such information could be used either to rule out COVID-19 disease, or to identify people who need to go for COVID-19 diagnostic tests. This is the second update of this review, which was first published in 2020.


To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19.

Search strategy: 

We undertook electronic searches up to 10 June 2021 in the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We used artificial intelligence text analysis to conduct an initial classification of documents. We did not apply any language restrictions.

Selection criteria: 

Studies were eligible if they included people with clinically suspected COVID-19, or recruited known cases with COVID-19 and also controls without COVID-19 from a single-gate cohort. Studies were eligible when they recruited people presenting to primary care or hospital outpatient settings. Studies that included people who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.

Data collection and analysis: 

Pairs of review authors independently selected all studies, at both title and abstract, and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and assessed risk of bias using the QUADAS-2 checklist, and resolved disagreements by discussion with a third review author. Analyses were restricted to prospective studies only. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic (ROC) space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary prospective studies were available, and whenever heterogeneity across studies was deemed acceptable.

Main results: 

We identified 90 studies; for this update we focused on the results of 42 prospective studies with 52,608 participants. Prevalence of COVID-19 disease varied from 3.7% to 60.6% with a median of 27.4%. Thirty-five studies were set in emergency departments or outpatient test centres (46,878 participants), three in primary care settings (1230 participants), two in a mixed population of in- and outpatients in a paediatric hospital setting (493 participants), and two overlapping studies in nursing homes (4007 participants). The studies did not clearly distinguish mild COVID-19 disease from COVID-19 pneumonia, so we present the results for both conditions together.

Twelve studies had a high risk of bias for selection of participants because they used a high level of preselection to decide whether reverse transcription polymerase chain reaction (RT-PCR) testing was needed, or because they enrolled a non-consecutive sample, or because they excluded individuals while they were part of the study base. We rated 36 of the 42 studies as high risk of bias for the index tests because there was little or no detail on how, by whom and when, the symptoms were measured. For most studies, eligibility for testing was dependent on the local case definition and testing criteria that were in effect at the time of the study, meaning most people who were included in studies had already been referred to health services based on the symptoms that we are evaluating in this review.

The applicability of the results of this review iteration improved in comparison with the previous reviews. This version has more studies of people presenting to ambulatory settings, which is where the majority of assessments for COVID-19 take place. Only three studies presented any data on children separately, and only one focused specifically on older adults.

We found data on 96 symptoms or combinations of signs and symptoms. Evidence on individual signs as diagnostic tests was rarely reported, so this review reports mainly on the diagnostic value of symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. RT-PCR was the most often used reference standard (40/42 studies).

Only cough (11 studies) had a summary sensitivity above 50% (62.4%, 95% CI 50.6% to 72.9%)); its specificity was low (45.4%, 95% CI 33.5% to 57.9%)). Presence of fever had a sensitivity of 37.6% (95% CI 23.4% to 54.3%) and a specificity of 75.2% (95% CI 56.3% to 87.8%). The summary positive likelihood ratio of cough was 1.14 (95% CI 1.04 to 1.25) and that of fever 1.52 (95% CI 1.10 to 2.10). Sore throat had a summary positive likelihood ratio of 0.814 (95% CI 0.714 to 0.929), which means that its presence increases the probability of having an infectious disease other than COVID-19.

Dyspnoea (12 studies) and fatigue (8 studies) had a sensitivity of 23.3% (95% CI 16.4% to 31.9%) and 40.2% (95% CI 19.4% to 65.1%) respectively. Their specificity was 75.7% (95% CI 65.2% to 83.9%) and 73.6% (95% CI 48.4% to 89.3%). The summary positive likelihood ratio of dyspnoea was 0.96 (95% CI 0.83 to 1.11) and that of fatigue 1.52 (95% CI 1.21 to 1.91), which means that the presence of fatigue slightly increases the probability of having COVID-19.

Anosmia alone (7 studies), ageusia alone (5 studies), and anosmia or ageusia (6 studies) had summary sensitivities below 50% but summary specificities over 90%. Anosmia had a summary sensitivity of 26.4% (95% CI 13.8% to 44.6%) and a specificity of 94.2% (95% CI 90.6% to 96.5%). Ageusia had a summary sensitivity of 23.2% (95% CI 10.6% to 43.3%) and a specificity of 92.6% (95% CI 83.1% to 97.0%). Anosmia or ageusia had a summary sensitivity of 39.2% (95% CI 26.5% to 53.6%) and a specificity of 92.1% (95% CI 84.5% to 96.2%). The summary positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.55 (95% CI 3.46 to 5.97) and 4.99 (95% CI 3.22 to 7.75) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The summary positive likelihood ratio of ageusia alone was 3.14 (95% CI 1.79 to 5.51).

Twenty-four studies assessed combinations of different signs and symptoms, mostly combining olfactory symptoms. By combining symptoms with other information such as contact or travel history, age, gender, and a local recent case detection rate, some multivariable prediction scores reached a sensitivity as high as 90%.