Clinical Presentation

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By Christian Hoffmann  &
  Bernd Sebastian Kamps

 

After an average incubation time of around 5 days (range: 2-14 days), a typical COVID-19 infection begins with dry cough and low-grade fever (38.1–39°C or 100.5–102.1°F), often accompanied by diminishment of smell and taste. In most patients, COVID-19 remains mild or moderate and symptoms resolve within a week and patients typically recover at home. Around 10% of patients remain symptomatic through the second week. The longer the symptoms persist, the higher the risk of developing more severe COVID-19, requiring hospitalization, intensive care and invasive ventilation. The outcome of COVID-19 is often unpredictable, especially in older patients with comorbidities. The clinical picture ranges from completely asymptomatic to rapidly devastating courses.

In this chapter we discuss clinical presentation, including incubation period and asymptomatic patients, frequent and rare symptoms, laboratory findings and risk factors for severe disease. Radiological findings are described in the diagnostic chapter.

Incubation period

A pooled analysis of 181 confirmed COVID-19 cases with identifiable exposure and symptom onset windows estimated the median incubation period to be 5.1 days with a 95% CI of 4.5 to 5.8 days (Lauer 2020). The authors estimated that 97.5% of those who develop symptoms will do so within 11.5 days (8.2 to 15.6 days) of infection. Fewer than 2.5% of infected persons will show symptoms within 2.2 days, whereas symptom onset will occur within 11.5 days in 97.5%. However, these estimates imply that, under conservative assumptions, 101 out of every 10,000 cases will develop symptoms after 14 days of active monitoring or quarantine. Another analysis of 158 confirmed cases outside Wuhan estimated a very similar median incubation period of 5.0 days (95 % CI, 4.4 to 5.6 days), with a range of 2 to 14 days (Linton 2020). In a detailed analysis of 36 cases linked to the first three clusters of circumscribed local transmission in Singapore, the median incubation period was 4 days with a range of 1-11 days (Pung 2020). Taken together, the incubation period of around 4-6 days is in line with that of other coronaviruses causing SARS or MERS (Virlogeux 2016).

Of note, the time from exposure to onset of infectiousness (latent period) may be shorter. There is little doubt that transmission of SARS-CoV-2 during the late incubation period is possible (Li 2020). In a longitudinal study, the viral load was high 2-3 days before the onset of symptoms, and the peak was even reached 0.7 days before the onset of symptoms. The authors of this Nature Medicine paper estimated that approximately 44% (95% CI 25-69%) of all secondary infections are caused by such presymptomatic patients (He 2020).

Asymptomatic cases

Understanding the frequency of asymptomatic patients and the temporal course of asymptomatic transmission will be very important for assessing disease dynamics. It is important to distinguish those patients who will remain asymptomatic during the whole time of infection and those in which infection is still too early to cause symptoms (presymptomatic).

While physicians need to be aware of asymptomatic cases, the true percentage is difficult to assess. The probably best data come from 3,600 people on board the cruise ship Diamond Princess (Mizumoto 2020) who became involuntary actors in a “well-controlled experiment” where passengers and crew comprised an environmentally homogeneous cohort. Due to insufficient hygienic conditions, >700 people became infected while the ship was quarantined in the port of Yokohama, Japan. After systematic testing, 328 (51.7%) of the first 634 confirmed cases were found to be asymptomatic. Considering the varying of the incubation period between 5.5 and 9.5 days, the authors calculated the true asymptomatic proportion at 17.9% (Mizumoto 2020).

From a total of 565 Japanese citizens evacuated from Wuhan, the asymptomatic ratio was estimated to be 42% (Nishiura 2020). Of 279 close contacts to COVID-19 patients who became PCR positive, 63 (23%) remained asymptomatic throughout their infections. Of note, 29 patients had abnormal CT findings (Wang 2020). In a screening study conducted in Iceland, the number of patients testing positive for SARS-CoV-2 but without symptoms was 44%, although some of these may have been pre-symptomatic (Gudbjartsson 2020). In an observational cohort study of 199 infected patients in a residential treatment center in South Korea, the rate of asymptomatic patients was 26% (Noh 2020). The range of true asymptomatic patients in the studies published to date is still broad and may depend on the population which was analyzed.

Asymptomatic patients may transmit the virus (Bai 2020, Rothe 2020). In a study from Northern Italy viral loads in nasal swabs between asymptomatic and symptomatic subjects did not differ significantly, suggesting the same potential for transmitting the virus (Cereda 2020). Of 63 asymptomatic patients in Chongquing, 9 (14%) transmitted the virus to others (Wang 2020). In an outbreak in a long-term care facility, 13/23 residents who tested positive were asymptomatic or presymptomatic on the day of testing (Kimball 2020). In another skilled nursing facility, of 48 residents, 27 (56%) were asymptomatic at the time of testing positive. Of these, 24 subsequently developed symptoms, with median time to onset of 4 days (Arons 2020). There is some evidence that shedding of RNA and viral load is somewhat shorter in asymptomatic (not presymptomatic!) patients (Noh 2020, Yang 2020).

Taken together, these preliminary studies indicate that around 20-40% of all COVID-19 infected subjects may remain asymptomatic during their infection. But it may well be that we are still quite wrong. Only large-scale field studies on seroprevalence will be able to clarify the exact proportion.

Symptoms

A plethora of symptoms have been described in the past months, clearly indicating that COVID-19 is a complex disease, which in no way consists only of a respiratory infection. Many symptoms are unspecific so that the differential diagnosis encompasses a wide range of infections, respiratory and other diseases. However, different clusters can be distinguished in COVID-19. The most common symptom cluster encompasses the respiratory system: cough, sputum, shortness of breath, and fever. Other clusters encompass musculoskeletal symptoms (myalgia, joint pain, headache, and fatigue), enteric symptoms (abdominal pain, vomiting, and diarrhoea); and less commonly, a mucocutaneous cluster.

Fever, cough, shortness of breath

Symptoms occur in the majority of cases (for asymptomatic patients, see below). In early studies from China (Guan 2020, Zhou 2020), fever was the most common symptom, with a median maximum of 38.3 C; only a few had a temperature of > 39 C. The absence of fever seems to be somewhat more frequent than in SARS or MERS; fever alone may therefore not be sufficient to detect cases in public surveillance. The second most common symptom was cough, occurring in about two thirds of all patients. Among survivors of severe COVID-19 (Zhou 2020), median duration of fever was 12.0 days (8-13 days) and cough persisted for 19 days (IQR 12-23 days). In a meta-analysis of COVID-19 in papers published until February 23, fever (88.7%), cough (57.6%) and dyspnea (45.6%) were the most prevalent clinical manifestations (Rodriguez-Morales 2020). In another review, the corresponding percentages were 88.5%, 68.6% and 21.9%, respectively (Li 2020).

Fever and cough do not distinguish between mild and severe cases nor do they predict the course of COVID-19 (Richardson 2020, Petrelli 2020). In contrast, shortness of breath has been identified as a strong predictor of severe disease in larger studies. In a cohort of 1,590 patients, dyspnea was assocoiated with an almost two-fold risk for critical disease (Liang 2020) and mortality (Chen 2020). Others found higher rates of shortness of breath, and temperature of > 39.0 in older patients compared with younger patients (Lian 2020). In the Wuhan study on patients with severe COVID-19, multivariate analysis revealed that a respiratory rate of > 24 breaths per minute at admission was higher in non-survivors (63% versus 16%).

Within the last weeks, huge cohort data from countries outside China have been published. However, almost all data applies to patients who were admitted to hospitals, indicating selection bias towards more severe and symptomatic patients.

  • Among 20,133 patients in the UK who were admitted to 208 acute care hospitals in the UK between 6 February and 19 April 2020, the most common symptoms were cough (69%), fever (72%), and shortness of breath (71%), showing a high degree of overlap (Docherty 2020).
  • Among 5,700 patients who were admitted to any of 12 acute care hospitals in New York between March 1, 2020, and April 4, 2020, only 30.7% had fever of > 38 C. A respiratory rate of > 24 breaths per minute at admission was found in 17.3% (Richardson 2020).
  • Among the first 1,000 patients presenting at the NewYork-Presbyterian/Columbia University (Argenzinao 2020), the most common presenting symptoms were cough (73%), fever (73%), and dyspnea (63%).

Musculoskeletal symptoms

The cluster of musculoskeletal symptoms encompasses myalgia, joint pain, headache, and fatigue. These are frequent symptoms, occurring each in 15-40% of patients (Argenzinao 2020, Docherty 2020, Guan 2020). Although subjectively very disturbing and sometimes foremost in the perception of the patient, these symptoms tell us nothing about the severity of the clinical picture. However, they are frequently overlooked in clinical practice, and headache merits special attention.

According to a recent review (Bolay 2020), headache is observed in 11-34% of hospitalized COVID-19 patients, occurring in 6-10% as presenting symptom. Significant features are moderate-severe, bilateral headache with pulsating or pressing quality in the temporo-parietal, forehead or periorbital region. The most striking features are sudden to gradual onset and poor response to common analgesics. Possible pathophysiological mechanisms include activation of peripheral trigeminal nerve endings by the SARS-CoV-2 directly or through the vasculopathy and/or increased circulating pro-inflammatory cytokines and hypoxia.

Gastrointestinal symptoms

Cell experiments have shown that SARS-CoV and SARS-CoV-2 are able to infect enterocytes (Lamers 2020). Active replication has been shown in both bats and human intestinal organoids (Zhou 2020). Fecal calprotectin as a reliable fecal biomarker allowing detection of intestinal inflammation in inflammatory bowel diseases and infectious colitis, was found in some patients, provides evidence that SARS-CoV-2 infection instigates an inflammatory response in the gut (Effenberger 2020). These findings explain why gastrointestinal symptoms are observed in a subset of patients and why viral RNA can be found in rectal swabs, even after nasopharyngeal testing has turned negative. In patients with diarrhea, stool viral RNA was detected at higher frequency (Cheung 2020).

In the early Chinese studies, however, gastrointestinal symptoms were rarely seen. In a meta-analysis of 60 early studies comprising 4,243 patients, the pooled prevalence of gastrointestinal symptoms was 18% (95% CI, 12%-25%); prevalence was lower in studies in China than other countries. As with otolaryngeal symptoms, it remains unclear whether this difference reflects geographic variation or differential reporting. Among the first 393 consecutive patients who were admitted to two hospitals in New York City, diarrhea (24%), and nausea and vomiting (19%) were relatively frequent (Goyal 2020). Among 18,605 patients admitted to UK Hospitals, 29% of all patients complained of enteric symptoms on admission, mostly in association with respiratory symptoms; however, 4% of all patients described enteric symptoms alone (Docherty 2020).

Otolaryngeal symptoms (including anosmia)

Although upper respiratory tract symptoms such as rhinorrhea, nasal congestion, sneezing and sore throat are relatively unusual, it has become clear within a few weeks that anosmia and hyposmia are important signs of the disease (Luers 2020). Interestingly, these otolaryngological symptoms appear to be much more common in Europe than in Asia. However, it is still unclear whether this is a real difference or whether these complaints in the initial phase in China were not recorded well enough. There is now very good data from Europe: The largest study to date found that 1,754/2,013 patients (87%) reported loss of smell, whereas 1,136 (56%) reported taste dysfunction. Most patients had loss of smell after other general and otolaryngologic symptoms (Lechien 2020). Mean duration of olfactory dysfunction was 8.4 days. Females seem to be more affected than males. The prevalence of self-reported smell and taste dysfunction was higher than previously reported and may be characterized by different clinical forms. Anosmia may not be related to nasal obstruction or inflammation. Of note, only two thirds of patients reporting olfactory symptoms and who had objective olfactory testing had abnormal results.

“Flu plus ‘loss of smell’ means COVID-19”. Among 263 patients presenting in March (at a single center in San Diego) with flu-like symptoms, loss of smell was found in 68% of COVID-19 patients (n=59), compared to only 16% in negative patients (n=203). Smell and taste impairment were independently and strongly associated with positivity (anosmia: adjusted odds ratio 11, 95%CI: 5‐24). Conversely, sore throat was independently associated with negativity (Yan 2020).

Among a total of 18,401 participants from the US and UK who reported potential symptoms on a smartphone app and had undergone a SARS-CoV-2 test, the proportion of participants who reported loss of smell and taste was higher in those with a positive test result (65 vs 22%). A combination of symptoms, including anosmia, fatigue, persistent cough and loss of appetite was appropriate to identify individuals with COVID-19 (Menni 2020).

Taken together, otolarnygeal symptoms do not indicate severity but are important indicators for SARS-CoV-2 infection.

Cardiovascular symptoms and issues

There is growing evidence of direct and indirect effects of SARS-CoV-2 on the heart, especially in patients with pre-existing heart diseases (Bonow 2020). SARS-CoV-2 has the potential to infect cardiomyocytes, pericytes and fibroblasts via the ACE2 pathway leading to direct myocardial injury, but that pathophysiological sequence remains unproven (Hendren 2020). A second hypothesis to explain COVID-19-related myocardial injury centers on cytokine excess and/or antibody mediated mechanisms. It has been also shown that the ACE2 receptor is widely expressed on endothelial cells and that direct SARS-CoV-2 infection of the endothelial cell is possible, leading to diffuse endothelial inflammation (Varga 2020). Post-mortem examination cases indicating a strong virus-induced vascular dysfunction (Menter 2020).

Clinically, COVID-19 can manifest with an acute cardiovascular syndrome (termed “ACovCS”). Numerous cases with ACovCS have been described, not only with typical thoracic complaints, but also with very diverse cardiovascular manifestations. Troponin is an important parameter (see below). In a case series of 18 COVID-19 patients who had ST segment elevation, there was variability in presentation, a high prevalence of nonobstructive disease, and a poor prognosis. 6/9 patients undergoing coronary angiography had obstructive disease. Of note, all 18 patients had elevated D-dimer levels (Bangalore 2020).

In patients with a seemingly typical coronary heart syndrome, COVID-19 should also be considered in the differential diagnosis, even in the absence of fever or cough (Fried 2020, Inciardi 2020). For more information, see the chapter comorbidities.

Thrombosis, embolism

Coagulation abnormalities occur frequently in association with COVID-19, complicating clinical management. Numerous studies have reported on an incredibly high number of venous thromboembolism (VTE), especially in those with severe COVID-19. The initial coagulopathy of COVID-19 presents with prominent elevation of D-dimer and fibrin/fibrinogen degradation products, while abnormalities in prothrombin time, partial thromboplastin time, and platelet counts are relatively uncommon (excellent review: Connors 2020). Coagulation test screening, including the measurement of D-dimer and fibrinogen levels, is suggested.

But what are the mechanisms? Some studies have found pulmonary embolism with or without deep venous thrombosis, as well as presence of recent thrombi in prostatic venous plexus, in patients with no history of VTE, suggesting de novo coagulopathy in these patients with COVID-19. Others have highlighted changes consistent with thrombosis occurring within the pulmonary arterial circulation, in the absence of apparent embolism (nice review: Deshpande 2020). Some studies have indicated severe hypercoagulability rather than consumptive coagulopathy (Spezia 2020).

Some of the key studies are listed here:

  • Of 240 patients (109 critically ill) admitted to US hospitals, VTE was diagnosed in 31 patients (28%) 8 ± 7 days after admission. The authors conclude that routine chemical VTE prophylaxis may be inadequate (Maatman 2020).
  • In a single-center study from Amsterdam on 198 hospitalized cases, the cumulative incidences of VTE at 7 and 21 days were 16% and 42%. In 74 ICU patients, cumulative incidence was 59% at 21 days, despite thrombosis prophylaxis. Authors recommend performing screening compression ultrasound in the ICU every 5 days (Middeldorp 2020).
  • Of 143 patients hospitalized with COVID-19, 66 patients developed lower extremity deep venous thrombosis (46%), among them 23 with proximal DVT (Zhang 2020). Patients with DVT were older and had a lower oxygenation index, a higher rate of cardiac injury, and worse prognosis. Multivariate analysis found CURB-65 score 3-5 (OR 6.1), Padua prediction score ≥ 4 (OR 4.0), and D-dimer >1.0 μg/ml (OR 5.8) to be associated with DVT.
  • Among the first 107 COVID-19 patients admitted to the ICU for pneumonia in Lille, France, the authors identified 22 (21%) cases of pulmonary embolism (PE). At the time of diagnosis, 20/22 were receiving prophylactic antithrombotic treatment (UFH or LWMH) according to the current guidelines in critically ill patients.
  • In 100 patients with severe COVID-19, a high prevalence of 23% was found for pulmonary embolus (PE) (Grillet 2020). PE was diagnosed at a mean of 12 days from symptom onset. In multivariable analysis, requirement for mechanical ventilation remained associated with acute pulmonary embolus.
  • In a prospective study from France, 64/150 (43%) patients were diagnosed with clinically relevant thrombotic complications. The authors argue for higher anticoagulation targets in critically ill patients (Helms 2020).
  • Autopsy findings from 12 patients, showing that 7/12 had deep vein thrombosis. Pulmonary embolism was the direct cause of death in four cases (Wichmann 2020).
  • Careful examination of the lungs from deceased COVID-19 patients with lungs from 7 patients who died from ARDS secondary to influenza A showed distinctive vascular features. COVID-19 lungs displayed severe endothelial injury associated with the presence of intracellular virus and disrupted cell membranes. Histologic analysis of pulmonary vessels showed widespread thrombosis with microangiopathy. Alveolar capillary microthrombi and the amount of vessel growth were 9 and almost 3 times as prevalent as in influenza, respectively (Ackerman 2020)
  • Five cases of large-vessel stroke occurring in younger patients (age 33-49, 2 without any risk factors) (Oxley 2020).
  • Five cases with profound hemodynamic instability due to the development of acute cor pulmonale, among them 4 younger than 65 years of age (Creel-Bulos 2020).

There is a very controversial debate about a possible correlation between the use of ibuprofen and the increased risk of VTE development. According to a recent review (Arjomandi 2020), the causation between the effects of ibuprofen and VTE remains speculative. The role of ibuprofen on a vascular level remains unclear as well as whether ibuprofen is able to interact with SARS-CoV-2 mechanistically. However, the authors recommend careful considerations on avoiding high dosage of Ibuprofen in subjects at particular risk of thromboembolic events.

Neurologic symptoms

Neuroinvasive propensity has been demonstrated as a common feature of human coronaviruses. Viral neuroinvasion may be achieved by several routes, including trans-synaptic transfer across infected neurons, entry via the olfactory nerve, infection of vascular endothelium, or leukocyte migration across the blood-brain barrier (review: Zubair 2020). With regard to SARS‐CoV‐2, early occurrences such as olfactory symptoms (see above) should be further evaluated for CNS involvement. Potential late neurological complications in cured COVID-19 patients are possible (Baig 2020). A retrospective, observational case series found 78/214 patients (36%) with neurologic manifestations, ranging from fairly specific symptoms (loss of sense of smell or taste, myopathy, and stroke) to more non-specific symptoms (headache, low consciousness, dizziness, or seizure). Whether these more non-specific symptoms are manifestations of the disease itself remains to be seen (Mao 2020).

There are several observational series of specific neurological features such as Guillain–Barré syndrome (Toscano 2020) or Miller Fisher Syndrome and polyneuritis cranialis (Gutierrez-Ortiz 2020).

Especially in patients with severe COVID-19, neurological symptoms are common. In an observational series of 58 patients, ARDS due to SARS-CoV-2 infection was associated with encephalopathy, prominent agitation and confusion, and corticospinal tract signs. Patients with COVID-19 might experience delirium, confusion, agitation, and altered consciousness, as well as symptoms of depression, anxiety, and insomnia (review: Rogers 2020). It remains unclear which of these features are due to critical illness–related encephalopathy, cytokines, or the effect or withdrawal of medication, and which features are specific to SARS-CoV-2 infection (Helms 2020).

Dermatological symptoms

Numerous studies have reported on cutaneous manifestations seen in the context of COVID-19. The most prominent phenomenon, the so-called “COVID toes”, are chilblain-like lesions which mainly occur at acral areas. These lesions can be painful (sometimes itchy, sometimes asymptomatic) and may represent the only symptom or late manifestations of SARS-CoV-2 infection. Of note, in most patients with “COVID toes”, the disease is only mild to moderate. It is speculated that the lesions are caused by inflammation in the walls of blood vessels, or by small micro-clots in the blood. However, whether “COVID toes” represent a coagulation disorder or a hypersensitivity reaction is not yet known. In addition, in many patients, SARS-CoV-2 PCR was negative (or not done) and serology testings (to prove the relationship) are still pending. Key studies:

  • Two different patterns of acute acro-ischemic lesions can overlap (Fernandez-Nieto 2020). The chilblain-like pattern was present in 95 patients (72.0%). It is characterized by red to violet macules, plaques and nodules, usually at the distal aspects of toes and fingers. The erythema multiform-like pattern was present in 37 patients (28.0%).
  • Five clinical cutaneous of lesions are described (Galvan 2020): acral areas of erythema with vesicles or pustules (pseudo-chilblain) (19%), other vesicular eruptions (9%), urticarial lesions (19%), maculopapular eruptions (47%) and livedo or necrosis (6%). Vesicular eruptions appear early in the course of the disease (15% before other symptoms). The pseudo-chilblain pattern frequently appears late in the evolution of the COVID-19 disease (59% after other symptoms).
  • In a case series on 22 adult patients with varicella-like lesions (Marzano 2020), typical features were constant trunk involvement, usually scattered distribution and mild/absent pruritus, the latter being in line with most viral exanthems but not like true varicella. Lesions generally appeared 3 days after systemic symptoms and disappeared by day 8.
  • Three cases of COVID-19 associated ulcers in the oral cavity, with pain, desquamative gingivitis, and blisters (Martin-Carreras 2020).

Other case reports include digitate papulosquamous eruption (Sanchez 2020), petechial skin rash (Diaz-Guimaraens 2020 Quintana-Castanedo 2020). However, it should be kept in mind that not all rashes or cutaneous manifestations seen in patients with COVID-19 can be attributed to the virus. Coinfections or medical complications have to be considered. Comprehensive mucocutaneous examinations, analysis of other systemic clinical features or host characteristics, and histopathologic correlation, will be vital to understanding the pathophysiologic mechanisms of what we are seeing on the skin (Review: Madigan 2020).

Kidneys and liver

SARS-CoV-2 has an organotropism beyond the respiratory tract, including the kidneys and the liver. Researchers have quantified the SARS-CoV-2 viral load in precisely defined kidney compartments obtained with the use of tissue microdissection from 6 patients who underwent autopsy (Puelles 2020). Three of these 6 patients had a detectable SARS-CoV-2 viral load in all kidney compartments examined, with preferential targeting of glomerular cells. Renal tropism is a potential explanation of commonly reported new clinical signs of kidney injury in patients with COVID-19, even in patients with SARS-CoV-2 infection who are not critically ill (Zhou 2020). Recent data indicate that renal involvement is more frequent than described in early studies. Of the first 1,000 patients presenting at the NewYork-Presbyterian-Columbia University, 236 were admitted or transferred to intensive care units (Argenziano 2020). Of these, 78.0% (184/236) developed acute kidney injury and 35.2% (83/236) needed dialysis. Concomitantly, 13.8% of all patients and 35.2% of patients in intensive care units required in-patient dialysis, leading to a shortage of equipment needed for dialysis and continuous renal replacement therapy.

One of the largest studies, evaluating liver injury in 2,273 SARS-CoV-2 positive patients, found that 45% had mild, 21% moderate, and 6.4% severe liver injury. In multivariable analysis, severe acute liver injury was significantly associated with elevated inflammatory markers including ferritin and IL‐6. Peak ALT was significantly associated with death or discharge to hospice (OR 1.14, p=0.044), controlling for age, body mass index, diabetes, hypertension, intubation, and renal replacement therapy (Phipps 2020).

Ocular and atypical manifestations

Ocular manifestations are also common. In a case series from China, 12/38 patients (32%, more common in severe cases) had ocular manifestations consistent with conjunctivitis, including conjunctival hyperemia, chemosis, epiphora, or increased secretions. Two patients had positive PCR results from conjunctival swabs (Wu 2020). The retina can also be affected, as has been shown using optical coherence tomography (OCT), a non-invasive imaging technique that is useful for demonstrating subclinical retinal changes. Twelve adult patients showed hyper-reflective lesions at the level of the ganglion cell and inner plexiform layers more prominently at the papillomacular bundle in both eyes (Marinho 2020).

Other new and sometimes puzzling clinical presentations have emerged (and will emerge) in the current pandemic. There are case reports of non-specific symptoms, especially in the elderly population, underlining the need for extensive testing in the current pandemic (Nickel 2020).

Laboratory findings

The most evident laboratory findings in the first large cohort study from China (Guan 2020) are shown in Table 1. On admission, lymphocytopenia was present in 83.2% of the patients, thrombocytopenia in 36.2%, and leukopenia in 33.7%. In most patients, C-reactive protein was elevated to moderate levels; less common were elevated levels of alanine aminotransferase, and D-dimer. Most patients have normal procalcitonin on admission.

 

Table 2. Percentage of symptoms in first larger cohort study from China (Guan 2020). Disease severity was classified according to American Thoracic Society (Metlay 2019) guidelines
Clinical symptoms All Severe Disease Non-
Severe
Fever,% 88.7 91.9 88.1
Cough,% 67.8 70.5 67.3
Fatigue,% 38.1 39.9 37.8
Sputum production,% 33.7 35.3 33.4
Shortness of breath,% 18.7 37.6 15.1
Myalgia or arthralgia,% 14.9 17.3 14.5
Sore throat,% 13.9 13.3 14.0
Headache,% 13.6 15.0 13.4
Chills,% 11.5 15.0 10.8
Nausea or vomiting,% 5.0 6.9 4.6
Nasal congestion,% 4.8 3.5 5.1
Diarrhea,% 3.8 5.8 3.5
Radiological findings      
Abnormalities on X-ray,% 59.1 76.7 54.2
Abnormalities on CT,% 86.2 94.6 84.4
Laboratory findings      
WBC <4,000 per mm3,% 33.7 61.1 28.1
Lymphocytes <1,500 per mm3,% 83.2 96.1 80.4
Platelets <150,000 per mm3,% 36.2 57.7 31.6
C-reactive protein ≥10 mg/L,% 60.7 81.5 56.4
Lactate dehydrogenase ≥250 U/L,% 41.0 58.1 37.1
AST >40 U/L,% 22.2 39.4 18.2
D-dimer ≥0.5 mg/L,% 46.6 59.6 43.2

 

Inflammation

Parameters indicating inflammation such as elevated CRP and procalcitonin are very frequent findings. They have been proposed to be important risk factors for disease severity and mortality (Chen 2020). For example in a multivariate analysis of a retrospective cohort of 1,590 hospitalized subjects with COVID-19 throughout China, a procalcitonin > 0.5 ng/ml at admission had a HR for mortality of 8.7 (95% CI:3.4-22.3). In 359 patients, CRP performed better than other parameters (age, neutrophil count, platelet count) in predicting adverse outcome. Besides, admission serum CRP level was identified as a moderate discriminator of disease severity (Lu 2020). Of 5,279 cases confirmed in a large medical center in New York, 52% of them admitted to hospital, a CRP > 200 was more strongly associated (odds ratio 5.1) with critical illness than age or comorbidities (Petrilli 2020).

In a retrospective observational study of 69 patients with severe COVID-19, the decrease of interleukin-6 (IL-6) levels was closely related to treatment effectiveness, while the increase of IL-6 indicated disease exacerbation. The authors concluded that the dynamic change of IL-6 levels can be used as a marker in disease monitoring in patients with severe COVID-19 (Liu 2020). High levels of IL-6 and IL-8 during treatment were observed in patients with severe or critical disease and correlated with decreased lymphocyte count in another study on 326 patients from China (Zhang 2020). The determinants of disease severity seemed to stem mostly from host factors such as age, lymphocytopenia, and its associated cytokine storm.

Hematological: Lymphocytes, platelets

Lymphocytopenia and transient but severe T cell depletion is a well-known feature of SARS (He 2005). In COVID-19, lymphopenia is also among the most prominent hematological features. Lymphopenia may be predictive for progression (Ji 2020) and patients with severe COVID-19 present with lymphocytopenia of less than 1500/µl in almost 100% (Guan 2020). It’s not only the total lymphocyte count. There is growing evidence for a transient depletion of T cells. Especially the reduced CD4+ and CD8+ T cell counts upon admission was predictive of disease progression in a larger study (Zhang 2020). In another large study on COVID-19 patients, CD3+, CD4+ and CD8+ T cells but also NK cells were significantly decreased in COVID-19 patients and related to the severity of the disease. According to the authors, CD8+ T and CD4+ T cell counts can be used as diagnostic markers of COVID-19 and predictors of disease severity (Jiang 2020).

Another common hematological finding is low platelet counts that may have different causes (Review: Xu 2020). Cases of hemorrhagic manifestation and severe thrombocytopenia responding to immunoglobulins fairly quickly with a sustained response over weeks have been reported (Ahmed 2020).

Cardiac: Troponin

Given the cardiac involvement especially in severe cases (see above), it is not surprising that cardiac parameters are frequently elevated. A meta-analysis of 341 patients found that cardiac troponin I levels are significantly increased only in patients with severe COVID-19 (Lippi 2020). In 179 COVID-19 patients, cardiac troponin ≥ 0.05 ng/mL was predictive for mortality (Du 2020). In a huge cohort study from New York, troponin was strongly associated with critical illness (Petrilli 2020). However, it remains to be seen whether troponin levels can be used as a prognostic factor. A comprehensive review on the interpretation of elevated troponin levels in COVID-19 was recently published (Chapman 2020).

Coagulation: D-Dimer, aPTT

Several studies have evaluated the coagulation parameter D-dimer in the progression of COVID-19. Among 279 patients in whom D-dimer was measured for ten consecutive days after admission, dynamicly changes positively correlated with the prognosis (Li 2020). In the Wuhan study, all patients surviving had low D-dimer during hospitalization, whereas levels in non-survivors tended to increase sharply at day 10. In a multivariate analysis, D-dimer of > 1 µg/mL remained the only lab finding which was significantly associated with in-hospital death, with an odds ratio of 18.4 (2.6-129, p=0.003). However, D-dimer has a reported association with mortality in patients with sepsis and many patients died from sepsis (Zhou 2020).

In a considerable proportion of patients, a prolonged aPTT can be found. Of 216 patients with SARS-CoV-2, this was the case in 44 (20%). Of these, 31/34 (91%) had positive lupus anticoagulant assays. As this is not associated with a bleeding tendency, it is recommended that prolonged aPTT should not be a barrier to the use of anticoagulation therapies in the prevention and treatment of venous thrombosis (Bowles 2020). Another case series of 22 patients with acute respiratory failure present a severe hypercoagulability rather than consumptive coagulopathy. Fibrin formation and polymerization may predispose to thrombosis and correlate with a worse outcome (Spieza 2020).

Lab findings as risk factor

It is not very surprising that patients with severe disease had more prominent laboratory abnormalities than those with non-severe disease. It remains unclear, how a single parameter can be of clinical value as almost all studies were retrospective and uncontrolled. Moreover, the numbers of patients were low in many studies. However, there are some patterns which may be helpful in clinical practice. Lab risk factors are:

  • Elevated CRP, procalcitonin, interleukin-6 and ferritin
  • Lymphocytopenia, CD4 T cell and CD8 T cell depletion, leukocytosis
  • Elevated D-dimer and troponin
  • Elevated LDH

Clinical classification

There is no broadly accepted or valid clinical classification for COVID-19. The first larger clinical study distinguished between severe and non-severe cases (Guan 2020), according to the Diagnosis and Treatment Guidelines for Adults with Community-acquired Pneumonia, published by the American Thoracic Society and Infectious Diseases Society of America (Metlay 2019). In these validated definitions, severe cases include either one major criterion or three or more minor criteria. Minor criteria are a respiratory rate > 30 breaths/min, PaO2/FIO2 ratio <250, multilobar infiltrates, confusion/disorientation, uremia, leukopenia, low platelet count, hypothermia, hypotension requiring aggressive fluid resuscitation. Major criteria comprise septic shock with need for vasopressors or respiratory failure requiring mechanical ventilation.

Some authors (Wang 2020) have used the following classification including four categories:

  1. Mild cases: clinical symptoms were mild without pneumonia manifestation through image results
  2. Ordinary cases: having fever and other respiratory symptoms with pneumonia manifestation through image results
  3. Severe cases: meeting any one of the following: respiratory distress, hypoxia (SpO2 ≤ 93%), abnormal blood gas analysis: (PaO2 < 60mmHg, PaCO2 > 50mmHg)
  4. Critical cases: meeting any one of the following: Respiratory failure which requires mechanical ventilation, shock, accompanied by other organ failure that needs ICU monitoring and treatment.

In the report of the Chinese CDC, estimation of disease severity used almost the same categories (Wu 2020) although numbers 1 and 2 were combined. According to the report, there were 81% mild and moderate cases, 14% severe cases and 5% critical cases. There are preliminary reports from the Italian National Institute of Health, reporting on 24.9% severe and 5.0% critical cases (Livingston 2020). However, these numbers are believed to strongly overestimate the disease burden, given the very low number of diagnosed cases in Italy at the time. Among 7,483 US heath care workers with COVID-19, a total of 184 (2.1–4.9%) had to be admitted to ICUs. Rate was markedly higher in HCWs older 65 of age, reaching 6.9–16.0% (CDC 2020).

Outcome

We are facing rapidly increasing numbers of severe and fatal cases in the current pandemic. The two most difficult but most frequently asked clinical questions are 1. How many patients end up with severe or even fatal courses of COVID-19? 2. What is the true proportion of asymptomatic infections? We will learn more about this shortly through serological testing studies. However, it will be important that these studies are carefully designed and carried out, especially to avoid bias and confounding.

Case fatality rates

The case fatality rates (CFR) or infection fatality rates (IFR) are both difficult to assess in such a dynamic pandemic. CFR can be biased upwards by underreporting of cases and downwards by insufficient follow up or unknown outcome. A downward trend may also indicate improvements in epidemiological surveillance. COVID-19 fatality is likely overestimated and especially early estimates are susceptible to uncertainty about asymptomatic or subclinical infections and several biases, including biases in detection, selection or reporting (Niforatos 2020).

Dividing the number of deaths by the number of total confirmed cases is not appropriate. For example, on May 30, the CFR between the 30 most affected countries (in terms of absolute numbers) ranged from 0.07 (Singapore) to 16.7 (Belgium). Within the 10 most affected countries, the range was 1.15 (Russia) to 15.3 (France).

The picture is much more complex and these simple calculations certainly do not reflect the true mortality in each country without taking into factor three other issues:

  1. The testing policies (and capacities) in a country. This is the most important factor. The fewer people you test (all people, only symptomatic patients, only those with severe symptoms) the higher the mortality. In Germany, testing systems and high lab capacities were established rapidly (Stafford 2020).
  2. Age of the infected population and especially of the population which is affected first. For example, in Italy, higher percentages of older people became infected during the first weeks, compared to Germany (where many people acquired SARS-CoV during ski holidays or carnival sessions). Especially if high-risk sites (such as retirement homes) are affected, death cases in the country will increase considerably. For example, a single outbreak in Washington has led to 34 deaths among 101 residents of a long-term care facility (McMichael 2020) – this is exactly the same number of death cases which Australia has reported as whole country on April 4, among a total of 5,635 confirmed COVID-19 cases.
  3. Stage of the epidemic. Some countries have experienced their epidemic grow early, some are still a few days or weeks behind. Death rates only reflect the infection rate of 2-3 weeks previously. In the large retrospective study from Wuhan, the time from illness onset to death was 18.5 days (IQR 15-22 days).

The “death rates” for some selected countries, based on the number of deaths and tests, is shown in Figure 1. These curves reflect test readiness and test capacities. A country such as Sweden, which initially relied on “herd immunity”, differs significantly from countries in which a lot has been tested from the beginning of the epidemic, such as Germany. The USA is still at the beginning, in Korea the outbreak was stopped relatively quickly by intensive tracking measures.

 

Figure 1. People who tested positive (among 1 million inhabitants, dashed) and deaths (among 10 million inhabitants). “Mortality” reaches 10% at the point where the curves intersect. This has happened for countries such as UK, Italy or Sweden, but is unlikely for others like Germany, Switzerland or USA.

CFR among health care workers and among well-defined populations

In well-monitored populations in which underreporting is unlikely or can be largely determined, the mortality rates may better reflect the “true” CFR of COVID-19. This applies to healthcare workers (HCW) but also to populations of “well-defined” (limited) outbreaks. The low mortality rates in these populations are remarkable.

In large study of 3,387 HCW from China infected with SARS-CoV-2, only 23 have died, corresponding to a mortality of 0.68%. The median age was 55 years (range, 29 to 72), and 11 of the 23 deceased HCW had been reactivated from retirement (Zhan 2020). Current studies in the USA have found similar rates, mortality estimates were 0.3-0.6% (CDC 2020). Of the 27 HCW who have died from COVID-19 until mid-April, 18 were over 54 years of age. The overall low mortality rates were probably due to the fact that HCWs were younger and healthier, but also that they had been tested earlier and more frequently.

We will also learn more from limited outbreaks affecting homogeneous populations, such as cruise ships and aircraft carriers. Outbreaks on these floating microcosms are unfortunate but informative experiments, they tell us a lot about transmission and the natural course of the disease in well-defined populations. Two large “involuntary field studies” are currently taking place: around 1,140 sailors were infected on the US aircraft carrier Theodore Roosevelt (one soldier has already died, nine were hospitalized), and more than 1,080 COVID-19 patients on the French aircraft carrier Charles de Gaulle. These populations are probably young, healthy and correspond more to the general population. Detailled investigations will follow.

The most valid data seem to come from the Diamond Princess. As of May 31, the total number of infected reached 712, and 13 patients have died from the disease leading to a CFR of 1.8%. However, this rate may yet increase, as at least 4 patients were in serious condition (Moriarty 2020). Of note, around 75% of the patients on the Diamond Princess were of 60 years or older, many of them in their eighties. Projecting the Diamond Princess case fatality rate onto the age structure of the general population, it is obvious that the mortality rate may be much lower in other broader populations. Mortality would be in a range of 0.2-0.4 %.

Older Age

From the beginning of the epidemic, older age has been identified as an important risk factor for disease severity (Huang 2020, Guan 2020). In Wuhan, there was a clear and considerable age dependency in symptomatic infections (susceptibility) and outcome (fatality) risks, by multiple folds in each case (Wu 2020). The summarizing report from the Chinese CDC found a death rate of 2.3%, representing 1,023 among 44,672 confirmed cases (Wu 2020). Mortality increased markedly in older people. In the cases aged 70 to 79 years, CFR was 8.0% and cases in those aged 80 years older had a 14.8% CFR.

In recent weeks, this has been seen and confirmed by almost all studies published throughout the world. In almost all countries, age groups of 80 years of older contribute to more than 90% of all death cases.

  • In a large registry analysing the epidemic in the UK in 20,133 patients, the median age of the 5,165 patients (26%) who died in hospital from COVID-19 was 80 years (Docherty 2020).
  • Among 1,591 patients admitted to ICU in Lombardy, Italy, older patients (> 63 years) had markedly higher mortality than younger patients (36% vs 15%). Of 362 patients older than 70 years of age, mortality was 41% (Grasselli 2020).
  • According to the Italian National Institute of Health, an analysis of the first 2,003 death cases, median age was 80.5 years. Only 17 (0.8%) were 49 years or younger, and 88% were older than 70 years (Livingston 2020).
  • Detailed analysis of all-cause mortality at Italian hot sports showed that the deviation in all-cause deaths compared to previous years during epidemic peaks was largely driven by the increase in deaths among older people, especially in men (Piccininni 2020, Michelozzi 2020).
  • In 5,700 patients admitted to New York hospitals, there was a dramatic increase of mortality among older age groups, reaching 61% (122/199) in men and 48% (115/242) in women over 80 years of age (Richardson 2020).
  • In an outbreak reported from King County, Washington, a total of 167 confirmed cases were observed in 101 residents (median age 83 years) of a long-term care facility, in 50 healthcare workers (HCW, median age 43 years), and 16 visitors. The case fatality rate for residents was 33.7% (34/101) and 0% among HCW (McMichael 2020).

There is no doubt that older age is by far the most important risk factor for mortality. Countries failing to protect their elderly population for different reasons (such as Italy, Belgium or Sweden) are facing higher CFR, while those without many older patients infected by SARS-CoV-2 (such as the Republic of Korea, Singapore, Australia) have markedly lower rates.

Other risk factors for severe disease

Besides older age, many risk factors for severe disease and mortality have been evaluated in the current pandemic. Early studies from China found comorbidities such as hypertension, cardiovascular disease and diabetes to be associated with severe disease and death (Guan 2020). Among 1,590 hospitalised patients from mainland China, after adjusting for age and smoking status, COPD (hazard ratio, 2.7), diabetes (1.6), hypertension (1.6) and malignancy (3.5) were risk factors of reaching clinical endpoints (Guan 2020). Dozens of further studies have also addressed risk factors (Shi 2020, Zhou 2020). The risk scores that have been mainly proposed by Chinese researchers are so numerous that they cannot be discussed here. They were mainly derived from uncontrolled data, their clinical relevance remains limited.

During recent weeks, several studies conducted outside China have found obesity to be an important risk factor (Goyal 2020, Petrilli 2020). Among the first 393 consecutive patients who were admitted to two hospitals in New York City, obese patients were more likely to require mechanical ventilation. Obesity was also an important risk factor in France (Caussy 2020) or in Singapore, especially in younger patients (Ong 2020). Smoking as a risk factor is under discussion, as well as COPD, kidney diseases and many others (see comorbidity chapter). Among 1,150 adults who were admitted to two NYC hospitals with COVID-19 in March, older age, chronic cardiac disease (adjusted HR 1.76) and chronic pulmonary disease (2.94) were independently associated with in-hospital mortality (Cummings 2020).

The hitherto largest registry data from different parts of the world are shown in Table 3. A striking finding of these studies is the lower mortality in female patients, running through almost all available data. There is some evidence that there are sex-specific differences in clinical characteristics and prognosis and that the presence of comorbidities is of less impact in females (Meng 2020). It has been speculated that the higher vulnerability in men is due to the presence of subclinical systemic inflammation, blunted immune system, down-regulation of ACE2 and accelerated biological aging (Bonafe 2020).

The main problem of all studies published to date is that their uncontrolled data is subject to confounding and that they do not prove causality. Even more importantly: The larger the numbers, the more imprecise the definition of a given comorbidity. What is a “chronic cardiac disease”? A mild and well-controlled hypertension or a severe cardiomyopathy? The clinical manifestation and the relevance of a certain comorbidity may be very heterogeneous (see also the comorbidity chapter).

There is growing evidence that sociodemographic factors play a role. Many studies did not adjust for these factors. For example, in a large cohort of 3,481 patients in Louisiana, public insurance (Medicare or Medicaid), residence in a low-income area, and obesity were associated with increased odds of hospital admission (Price-Haywood 2020). A careful investigation of the NYC epidemic revealed that the Bronx, which has the highest proportion of racial/ethnic minorities, the most persons living in poverty, and the lowest levels of educational attainment, had higher rates (almost two-fold) of hospitalization and death related to COVID-19 than the other 4 NYC boroughs Brooklyn, Manhattan, Queens and Staten Island (Wadhera 2020).

Taken together, large registry studies have found slightly elevated Hazard Ratios of mortality for multiple comorbidities (Table 3). It seems, however, that most patients with preexisting conditions are able to control and eradicate the virus. Comorbidities play a major role in those who do not resolve and who fail to limit the disease to an upper respiratory tract infection and who develop pneumonia. Facing the devastation that COVID-19 can inflict not only on the lungs but on many organs, including blood vessels, heart and kidneys (nice review: Wadman 2020), it seems plausible that a decreased cardiovascular and pulmonary capacity ameliorate clinical outcome in these patients.

However, at this time, we can only speculate about the precise role of comorbidities and their mechanisms to contribute to disease severity.

Is there a higher susceptibility? In a large, population-based study from Italy, patients with COVID-19 had a higher baseline prevalence of cardiovascular conditions and diseases (hypertension, coronary heart disease, heart failure, and chronic kidney disease). The incidence was also increased in patients with previous hospitalizations for cardiovascular or noncardiovascular diseases (Mancia 2020). A large UK study found some evidence of potential sociodemographic factors associated with a positive test, including deprivation, population density, ethnicity, and chronic kidney disease (Lusignan 2020). However, even these well perfomed studies cannot completely rule out the (probably strong) diagnostic suspicion bias. Patients with comorbidities could be more likely to present for assessment and be selected for SARS-CoV-2 testing in accordance with guidelines. Given the high number of nosocomial outbreaks, they may also at higher risk for infection, just due to higher hospitalization rates.

 

Table 3. Age and comorbidities in a large registry study (Docherty 2020), providing multivariate analyses and Hazard Ratios.
  UK, n = 15,194  
Hazard Ratio (95% CI) Death  
Age 50-59 vs < 50 2.63 (2.06-3.35)  
Age 60-69 vs < 50 4.99 (3.99-6.25)  
Age 70-79 vs < 50 8.51 (6.85-10.57)  
Age > 80 vs < 50 11.09 (8.93-13.77)  
Female 0.81 (0.75-0.86)  
Chronic cardiac disease 1.16 (1.08-1.24)  
Chronic pulmonary disease 1.17 (1.09-1.27)  
Chronic kidney disease 1.28 (1.18-1.39)  
Hypertension    
Diabetes 1.06 (0.99-1.14)  
Obesity 1.33 (1.19-1.49)  
Chronic neurological disorder 1.18 (1.06-1.29)  
Dementia 1.40 (1.28-1.52)  
Malignancy 1.13 (1.02-1.24)  
Moderate/severe liver disease 1.51 (1.21-1.88)  
     

 

Predisposition

COVID-19 shows an extremely variable course, from completely asymptomatic to fulminantly fatal. In some cases it affects young and apparently healthy people, for whom the severity of the disease is neither caused by age nor by any comorbidities – just think of the Chinese doctor Li Wenliang, who died at the age of 34 from COVID-19 (see chapter Timeline). So far, only assumptions can be made. The remarkable heterogeneity of disease patterns from a clinical, radiological, and histopathological point of view has led to the speculation that the idiosyncratic responses of individual patients may be in part related to underlying genetic variations (von der Thusen 2020). Some preliminary reports suggest that this is the case.

  • For example, a report from Iran describes three brothers aged 54 to 66 who all died of COVID-19 after less than two weeks of fulminating progress. All three had previously been healthy, without underlying illnesses (Yousefzadegan 2020).
  • In a post-mortem examination of 21 COVID-19 cases, 65% of the deceased patients had blood group A. Blood group A may be associated with the failure of pulmonary microcirculation and coagulopathies. Another explanation could be the direct interaction between antigen A and the viral S protein, thus facilitating virus entry via ACE2 (Menter 2020).
  • Researchers from UK have investigated the associations between ApoEe4 alleles and COVID-19 severity, using the UK Biobank data (Kuo 2020). ApoEe4e4 homozygotes were more likely to be COVID-19 test positives (Odds Ratio 2.31, 95% CI: 1.65-3.24) compared to e3e3 homozygotes. The ApoEe4e4 allele increased risks of severe COVID-19 infection, independent of pre-existing dementia, cardiovascular disease, and type 2 diabetes. This interesting observation needs to be confirmed (and explained).

In addition to the genetic predisposition, other potential reasons for a severe course need to be considered: the amount of viral exposure (probably high for Li Wenliang?), the route by which the virus enters the body, ultimately also the virulence of the pathogen and a possible (partial) immunity from previous viral diseases. If you inhale large numbers of virus deeply, leading rapidly to a high number of virus in the pulmonary system, this may be much worse than smearing a small amount of virus on your hand to the nose. In this case, the immune system in the upper respiratory tract may have much more time to limit further spread into the lungs and other organs. But this is still speculation and will have to be investigated in the coming months.

Overburdened health care systems

Mortality may be also higher in situations where hospitals are unable to provide intensive care to all the patients who need it, in particular ventilator support. Mortality would thus also be correlated with health-care burden. Preliminary data show clear disparities in mortality rates between Wuhan (>3%), different regions of Hubei (about 2.9% on average), and across the other provinces of China (about 0.7% on average). The authors have postulated that this is likely to be related to the rapid escalation in the number of infections around the epicenter of the outbreak, which has resulted in an insufficiency of health-care resources, thereby negatively affecting patient outcomes in Hubei, while this has not yet been the situation in other parts of China (Ji 2020). Another study estimated the risk of death in Wuhan as high as 12% in the epicentre and around 1% in other more mildly affected areas (Mizumoto 2020)­.

The nightmare of insufficient ressources is currently the reality in Northern Italy. In Italy, on March 15, the cumulative death numbers exceeded for the first time those of admissions to intensive care units – a clear sign for a collapsing health care system. Other countries or regions will face the same situation soon.

Reactivations, reinfections

There are several reports of patients who become positive again after negative PCR tests (Lan 2020, Xiao 2020, Yuan 2020). These reports have gained much attention, because this could indicate both reactivations as well as reinfections. After closer inspection of these reports, however, there is no good evidence for reactivations or reinfections, and other reasons are much more likely. Methodological problems of PCR always have to be considered; the results can considerably fluctuate (Li 2020). Insufficient material collection or storage are just two examples of many problems with PCR. Even if everything is done correctly, it can be expected that a PCR could fluctuate between positive and negative at times when the values ​​are low and the viral load drops at the end of an infection (Wölfel 2020). It also depends on the assay used, the detection limit is between a few hundred and several thousand virus copies/mL (Wang 2020).

The largest study to date found a total of 25 (14.5%) of 172 discharged COVID-19 patients who had a positive test at home after two negative PCR results at hospital (Yuan 2020). On average, the time between the last negative and the first positive test was 7.3 (standard deviation 3.9) days. There were no differences to patients who remained negative. This and the short period of time suggest that in these patients, no reactivations are to be expected.

In addition, animal studies suggest that re-infection is very unlikely (Chandrashekar 2020). Following initial viral clearance and on day 35 following initial viral infection, 9 rhesus macaques were re-challenged with the same doses of virus that were utilized for the primary infection. Very limited viral RNA was observed in BAL on day 1, with no viral RNA detected at subsequent timepoints. These data show that SARS-CoV-2 infection induced protective immunity against re-exposure in nonhuman primates.

Reactivations as well as rapid new infections would be very unusual, especially for coronaviruses. If a lot of testing is done, you will find a number of such patients who become positive again after repeated negative PCR and clinical convalescence. The phenomenon is likely to be overrated. Most patients get well anyway; moreover, it is unclear whether renewed positivity in PCR is synonymous with infectiousness.

Outlook

Over the coming months, serological studies will give a clearer picture of the true number of asymptomatic patients and those with unusual symptoms. More importantly, we have to learn more about risk factors for severe disease, in order to adapt prevention strategies. Older age is the main but not the only risk factor. Recently, a 106-year-old COVID-19 patient recently recovered in the UK. The precise mechanisms how comorbidities (and comedications) may contribute to an increased risk for a severe disease course have to be elucidated. Genetic and immunological studies have to reveal susceptibility and predisposition for both severe and mild courses. Who is really at risk, who is not? Quarantining only the old is too easy.

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