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It isn’t yet known how the SARS-CoV-2 virus first entered humans. The initial suspect was the ant-eating pangolin, but recent evidence casts some doubt on that theory. Both SARS and MERS are thought to have originated in bats, which are seen as a reservoir for coronaviruses, among other pathogens. Identifying the source of the virus can be important for preventing new outbreaks.
Among humans, SARS-CoV-2 can spread through a variety of routes, including droplets, contaminated surfaces, and possibly fecal-oral routes (the latter of which would increase spread in low-sanitation areas). The vast majority of transmission appears to be through the same routes used by the cold and flu viruses: respiratory droplets and contaminated surfaces. Asymptomatic and presymptomatic patients have been extensively documented; they may serve as a major source of community transmission.
The SARS-CoV-2 virus came to humans from an as-yet-unknown animal. It can spread through a variety of routes that are also typical of the cold and flu viruses.
Coronaviruses are very common throughout the animal world. They are large RNA viruses with spikes on them, making them look vaguely like crowns — hence the name coronavirus, as corona means “crown” in Latin.
The different coronaviruses can have effects ranging from mild to severe. The coronaviruses that affect humans are divided into four main subgroups: alpha, beta, gamma, and delta. SARS-CoV-2 (which causes COVID-19) is a beta-coronavirus, as are SARS-CoV (which causes SARS) and MERS-CoV (which causes MERS). SARS-CoV-2 appears to be more transmissible than SARS.
Transmissibility is captured by the basic reproduction number (known as R0) or the more complex effective reproduction rate (known as Re or Rt). Both aim to estimate how many people one infected person is likely to infect. A virus with an R0 or Rt under one (<1) is likely to die out.
Estimates of the R0 for the novel coronavirus range from a median of 1.95 given by the WHO early on, to a median of 2.28 or 2.79 (with a range of 1.6–4.2) suggested by other studies, depending on the time point and population (e.g., the passengers aboard the Diamond Princess cruise ship versus other populations not on a cruise ship). For comparison, seasonal flu has an R0 of 1.28, H1N1 influenza is in the range of 1.4–1.6, the 1918 influenza pandemic was at around 1.8, and SARS was in the range of 2–5.
An R0 greater than 1 doesn’t mean that a major epidemic is inevitable, or that the virus will spread uncontrolled. Transmission rates can be limited by interventions such as disease surveillance, case isolation, school closure, safety measures at airports, and in the future, possibly immunizations.
COVID-19 appears to be at least as contagious as previous widespread outbreaks, and probably more. The R0 (the number of people likely to catch an infection from someone infected) isn’t yet known with certainty in broader populations, but likely hovers around 2–3.
There is suggestive evidence of asymptomatic/presymptomatic transmission, with numerous cases of spread to multiple people prior to detection. Since CT scans of the lungs of various asymptomatic patients came back positive, respiratory droplets could have been the means of transmission, despite the lack of a cough.
Researchers compared the aerosol and surface stability of SARS-CoV-2 (which causes COVID-19) and SARS-CoV (which causes SARS). The closely related viruses were aerosolized, and SARS-CoV-2 remained viable for 3 hours, with its concentration only declining somewhat.
Air samples were taken from a single infected patient 10 cm from the chin during normal breathing, deep breathing, speaking continuously, and coughing, and viral RNA was not detected. It is possible that the virus isn’t transmitted from the respiratory tract of some people, or that the testing methods were faulty. By contrast, another experiment with 4 infected participants found the virus on Petri dishes places approximately 20 cm from the mouth after coughing, even through surgical and cloth masks. There was no information on normal respiration or talking.
In China, 10 people from 3 families who had eaten at neighboring tables in the same restaurant became ill with the virus. Details of the case support transmission within the restaurant. Tables were roughly one meter apart, and air conditioners blew air in both directions across the 3 tables.
The authors suggest that the main means of spread was through respiratory droplets, aided by the airflow from the air conditioners, despite the lack of coughing or other symptoms. None of the other diners were infected, despite some being at similar distances from the table of origin. They weren’t in the path of the air conditioner. At the same time, the lack of infection of other tables doesn’t preclude travel further than one meter, as the air conditioning could have prevented transmission in other directions.
Testing of air samples and outlets from rooms in a hospital found evidence of air circulation in the ICU rooms and less commonly in the general ward. Contamination was generally associated with proximity to infected cases and was higher downstream than upstream of infected patients. The authors estimated that the maximum transmission distance was 4 meters and suggested evidence of spread via aerosols.
The study had limitations, however, notably the use of RNA detection and the inability to evaluate concentration versus minimum infective dose. Therefore, it is unclear if the levels detected represent sufficiently infectious doses of live viruses.
Another study didn’t find evidence for air contamination in 3 patients’ rooms, though air outlet fans did test positive. And in one preprint study, the highest virus concentration was found on the air-handling grates in patient-care rooms. Also, personal air samplers were worn and suggested emission of viral aerosol particles even in the absence of cough symptoms.
Finally, two Chinese authors have speculated that there was aerosol transmission between two people living on different floors of a building. However, there are other potential explanations, such as surface contamination.
For example, a cluster-randomized trial suggests a potential for increased infection risk, due to moisture retention, reuse of cloth masks, and poor filtration, but a mathematical model found that, in a population wearing no mask, you can reduce the spread of influenza by 95% if 80% of the population wears homemade (cloth) masks.
Other studies suggest that masks could be useful as part of a broader strategy, including proper hygiene. Masks may also help prevent some people from touching their faces, but conversely some people may readjust their masks or just fiddle with them and thus touch their faces more.
For more information on masks, be sure to visit our dedicated page.
COVID-19 is spread via viral respiratory droplets, and probably to some degree via aerosols, though that is still speculative. Under certain environmental conditions, like wind, air conditioning, or fans, the viral droplets can travel several meters. They can probably be spread without coughing (via loud talking, for instance), though more research is needed before we can be confident in the specifics.
An analysis of 22 studies (none of which was performed on SARS-CoV-2, the virus that causes COVID-19) showed that various coronaviruses can last on various surfaces from 2 hours to 9 days. At room temperature, coronaviruses generally persist for 4–5 days on most surfaces. Higher temperatures, such as 30°C or 40°C, seem to reduce the time, as does 50% humidity compared to 30% humidity. Solutions with 62–71% ethanol, 0.1–0.5% sodium hypochlorite, or 2% glutardialdehyde appear to be the most effective at reducing infectivity.
SARS-CoV-2 was found to persist for up to 72 hours on stainless steel and plastic — it was substantially reduced after 48 hours but still plausibly infectious. Copper had no SARS-CoV-2 after 4 hours, and no SARS-CoV (the virus that causes SARS) after 8 hours, whereas cardboard had no SARS-CoV-2 after 24 hours and no SARS-CoV after 8 hours.
RNA was found on most surfaces of the room of a COVID-19 patient before but not after routine cleaning. The virus could be found on the shoes of medical professionals and on the floors in areas away from the room, but the test wasn’t designed to determine the viability of the virus.
Another paper reported common contamination of surfaces in an ICU with 15 patients with severe COVID-19, and in a general ward with 24 patients with mild COVID-19. While the distance from the infected area is unclear, the paper specifies that other rooms in the hospital were not infected, except for the floors of a nearby pharmacy, with evidence of the virus on the shoes of workers.
SARs-CoV (the virus that causes SARS) remains viable and potentially infectious for hours to days on various surfaces. The degree to which SARS-CoV-2 (the virus that causes COVID-19) is spread via contact with contaminated surfaces is unclear.
A preprint study of the conjunctival swab samples of 63 confirmed cases and 4 suspected cases reported 1 positive case and 2 suspected positives.
A study of 30 COVID-19 patients reported that tears and conjunctival secretions from only 1 patient tested positive. This patient exhibited conjunctivitis.
A study of 37 COVID-19 patients reported viral RNA in the conjunctival sac. Conjunctival secretions only tested positive in 1 of the 37 patients, however. This patient didn’t exhibit conjunctivitis.
RT-PCR, the testing method used in the three studies above, is susceptible to false positives.
Viral RNA in the conjunctiva doesn’t necessarily indicate viral replication, as SARS-CoV-2 can be found in the blood during the acute phase of infection.
It seems possible for conjunctival secretions to carry the virus. Even so, it probably isn’t very common, and it’s unclear what risk conjunctival secretions carry.
Out of 31 serum samples from 9 patients, none tested positive for the virus, the earliest test being 3 days post-onset of symptoms. Another report found small amounts of viral RNA in a small number of blood donations, though it wasn’t able to assess infectivity. Out of 76 patients, there wasn’t evidence of the virus in blood samples. Another report found positive results in 1 of 5 patients, for the first 3 days of testing, which were days 7-9 of having symptoms. Yet another paper found viral RNA in 3/10 severe cases and 2/13 mild cases, the difference between them not being statistically significant.
One report found that 9 patients who received blood transfusions from those who were positive with COVID-19 failed to develop the disease themselves. The information is ambiguous, and the specific timelines of infection and donation are unclear but failed to confirm blood transmissibility. The authors note that blood transmissibility hasn’t been confirmed in SARS-CoV-1 or MERS-CoV, though low levels of viral RNA has been detected in those cases.
There isn't yet evidence for active SARS-CoV-2 in the blood of patients. There have been several reports of positive viral RNA tests, but the implications for infectivity are unknown. One report suggested a lack of transmission from blood donors, though more research is needed to confirm this.
Four reports found evidence of viral RNA in feces in 55-80% of cases, most of which persisted after nasopharyngeal testing had become negative for over a week, while another found similar findings in one child. Yet another paper found the virus in fecal samples of 44 of 153 patients. It’s plausible that SARS-CoV-2 can infect the gastrointestinal symptoms via ACE2 receptors, and diarrhea has been found in a high percentage of patients in some studies, though not in all studies, and much more research is needed to determine if this is genuine.
Some researchers worry that fecal aerosols from pipes could cause mass infection, as was suspected to happen in the SARS-CoV-1 outbreak. Other authors express concern about contamination through multiple types of wastewater, from baths to plumming.
The authors of one study found that although viral RNA was highly prevalent in stool, these samples didn’t produce viable cultures, suggesting a lack of infectivity.
While there isn’t current evidence of transmission through feces, viral RNA of SARS-CoV-2 is frequently present in fecal samples, even more than a week after respiratory tests are negative. One study failed to find compelling evidence for infective viruses in stool, though more research is needed.
In one study of 12 patients with confirmed infections, 11 were found to harbor the virus. In the first specimens, the median viral load was 3.3 x 106 copies/ml, with a range of 9.9 x 102 to 1.2 x 108. Of the 6 patients, only 1 still tested positive 11 days after hospital admission (though there was evidence of rebounding: tests were negative and then positive days later).
In one study of 23 patients with confirmed infections, the median viral load out of 173 specimens was 5.2 log10 (158,489) copies/mL, with an interquartile range of 4.1–7.0. 7/21 had detectable viral RNA for 20 days or longer after their initial symptom onset, and there was evidence of rebounding. There was a general decline with time, with the highest levels in the first week.
In both studies, the patients were asked to cough out saliva from their throats, so there was a potential influence (contamination) from the lower respiratory tract.
The virus was not found in the semen of 12 participants, 11 of which had tested negative for nucleic acid in pharyngeal swabs, whereas one was positive during the time of testing, though had been positive for 40 days prior to the test. There was also a negative result for testicular biopsy performed on a deceased patient. More research on newly infected participants is needed to determine whether or not the virus is present in semen or testes at any time during the infection.
Other studies have found low rates of 4/58, 1/9, and 3/48, which could be false positives, though transcription-polymerase chain reaction (RT-PCR, the most common testing method) for COVID-19 is highly specific and unlikely to produce very many false positives. Contamination may be a cause, though there is a possibility that there’s a narrow window of time in which urine may contain the virus during infection. It’s also not clear what the infectivity of positive urine might be.
A small percentage of urine tests have been positive for the virus, though it’s unclear why this is was the case or if the virus would be infectious when in urine.
The virus was not found in tests of vaginal swabs inserted 2-3 cm, taken from patients with severe COVID-19 17 to 40 days after the onset of the infection. More research during earlier stages of the infection is needed.
People with diabetes are, in general, at a higher risk for a variety of infectious diseases.
In a study of 280 patients, those with endocrine system diseases (34 total, unclear proportions of diabetes, and other diseases) had a higher risk of severe COVID-19 than mild COVID-19 (33.73% vs. 3.05%) which was statistically significant. However, this wasn’t adjusted for any confounding factors.
In a cohort of 799 patients with 113 deaths and 161 recoveries at the time of analysis one month after beginning the study, diabetes (47 total cases) was a little more common in patients who died (21%) than those who didn’t (14%). However, this wasn’t adjusted for confounding factors.
In a meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in diabetes patients was found; odds ratio (95% CI) 2.47 (1.67, 3.66). Another meta-analysis found that diabetic patients were more likely to be admitted to the ICU than non-diabetic patients (odds ratio 2.79, 95 % CI 1.85–4.22) based on 1382 patients. These figures are preliminary and more studies that make efforts to adjust for confounding factors are needed in future research. One study of 1590 patients reported on the relationship of COVID-19 and diabetes, finding a hazard ratio (95% CI) of 1.586 (1.028, 2.449) for participants with diabetes having severe COVID-19, as defined by admission to the ICU, invasive ventilation, or death, when adjusted for age and smoking status.(preprint)
Specifically, when it comes to mortality, one of the aforemention meta-analyses found that diabetes patients were more likely to die (odds ratio 3.21, 95 % CI 1.82–5.64) based on 4 studies for each and a combined 471 patients. A study performed in Italy found that 128 of the 355 patients who did had diabetes, which is greater than the general population. Another report from China found that 56/191 patients evaluated died, and of the 56, 36 had diabetes. The same criticisms apply to these studies. Further, in 339 elderly patients with 65 deaths, patients with hypertension (54 total) had a comparable incidence of mortality (hazard ratio 1.088 with 95% CI 0.568 to 2.084) though this wasn’t adjusted for confounding factors. In one study, of 102 patients with 17 deaths, diabetes was present in 35.3% of non-survivors, and 5.9% of survivors, the difference being statistically significant. This isn’t adjusted for confounding factors and is limited by its small sample and a lack of measures to reduce bias.
Diabetes is a notable risk factor, though the research is still preliminary and it's unclear how much of a unique risk it poses, as opposed to its covariates.
In one study of 102 patients with 17 deaths, cardiovascular disease (general) was present in 17.6% of non-survivors, and 2.4% of survivors, the difference being statistically significant. This isn't adjusted for confounding factors and was limited by its small sample and a lack of measures to reduce bias.
In 339 elderly patients with 65 deaths, patients with cardiovascular disease (53 total) had a greater incidence of mortality (hazard ratio 1.858 with 95% CI 1.58 to 3.261) when adjusted for age.
In a study of 280 patients, those with cardiovascular and cerebrovascular diseases (34 total, unclear proportions of each and lumped together) had a higher risk of severe COVID-19 than mild COVID-19 (51.81% vs 7.11%) which was statistically significant, though this wasn't adjusted for any confounding factors.
In a cohort of 799 patients with 113 deaths and 161 recoveries at the time of analysis one month after beginning the study, diabetes (47 total cases) was a little more common in patients who died (14%) than those who didn't (4%). However, this wasn't adjusted for confounding factors.
In a meta-analysis on studies from China, from 4 studies with 1,416 patients, that recorded baseline cardiovascular disease and COVID-19 severity found that those who had cardiovascular disease had higher odds of having severe COVID-19 as opposed to non-severe (odds ratio 3.42, 95% CI 1.88, 6.22). However, this isn't adjusted for confounding factors. In another meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in cardiovascular disease patients was found; odds ratio (95% CI) 2.93 (1.73, 4.96). This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
In one study of 102 patients with 17 deaths, cerebrovascular disease (general) was present in 17.6% of non-survivors, and 3.5% of survivors, the difference not being statistically significant (p=0.09). This isn't adjusted for confounding factors and is limited by its small sample and a lack of measures to reduce bias.
In 339 elderly patients with 65 deaths, patients with cerebrovascular disease (21 total) had a greater incidence of mortality (hazard ratio 1.379 with 95% CI 0.650 to 2.926) when adjusted for age.
In a study of 280 patients, those with cardiovascular and cerebrovascular diseases (34 total, unclear proportions of each and lumped together) had a higher risk of severe COVID-19 than mild COVID-19 (51.81% vs 7.11%) which was statistically significant, though this wasn't adjusted for any confounding factors.
In a meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in cerebrovascular disease patients was found; odds ratio (95% CI) 3.89 (1.64, 9.22). This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
In a study of 1591 patients in Italy, hypertension was more common in patients who died in the ICU (195 of 309) as compared with those in the ICU who were discharged (84 of 212) (difference of 23%, 95% CI, 15%-32%). However, they were also somewhat older, and age and other confounding factors weren't adjusted for, so a high level of caution is warranted.
In one study of 102 patients with 17 deaths, hypertension was present in 64.7% of non-survivors and 20% of survivors, the difference being statistically significant. This isn't adjusted for confounding factors and is limited by its small sample and a lack of measures to reduce bias.
In 339 elderly patients with 65 deaths, patients with hypertension (138 total) had a greater incidence of mortality (hazard ratio 1.494 with 95% CI 0.915 to 2.438) though this wasn't adjusted for confounding factors.
In a cohort of 799 patients with 113 deaths and 161 recoveries at the time of analysis one month after beginning the study, hypertension (94 total cases) was more common in patients who died (48%) than those who didn't (24%). However, this wasn't adjusted for confounding factors.
In a meta-analysis on studies from China, from 4 studies with 1,416 patients, that recorded baseline hypertension and COVID-19 severity found that those who had hypertension had higher odds of having severe COVID-19 as opposed to non-severe (odds ratio 2.36, 95% CI 1.46-3.83). However, this isn't adjusted for confounding factors. In another meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in hypertensive patients was found; odds ratio (95% CI) 2.29 (1.69, 3.10). This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
In a meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in patients with malignancies was found; odds ratio (95% CI) 2.29 (1.00, 5.23). This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
In one study of 102 patients with 17 deaths, hypertension was present in 17.6 of non-survivors and 1.2% of survivors, the difference being statistically significant. This isn't adjusted for confounding factors and is limited by its small sample and a lack of measures to reduce bias.
In a meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in renal disease patients was found; odds ratio (95% CI) 2.51 (0.93, 6.78), though this wasn't statistically significant. This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
In a meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a lower risk of exacerbation in patients with liver disease was found; odds ratio (95% CI) 20.67 (0.30, 1.49), but this wasn't statistically significant. This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
It's not clear if liver disease is or isn't a risk factor. More research is needed.
In one study of 102 patients with 17 deaths, chronic liver disease (general) was present in 23.5% of non-survivors, and 7.1% of survivors, the difference not being statistically significant (P=0.101). This isn't adjusted for confounding factors and is limited by its small sample and a lack of measures to reduce bias.
In 339 elderly patients with 65 deaths, patients with COPD (21 total) had a greater incidence of mortality (hazard ratio 2.240 with 95% CI 1.115 to 4.497) when adjusted for age.
In a meta-analysis on studies from China, from 4 studies with 1,416 patients, that recorded baseline respiratory system disease and COVID-19 severity found that those who had respiratory system diseases had higher odds of having severe COVID-19 as opposed to non-severe (odds ratio 2.46, 95% CI 1.76-3.44). However, this isn't adjusted for confounding factors. In another meta-analysis of 6 retrospective studies that involved medical data of 1558 COVID-19 patients, a higher risk of exacerbation in COPD patients was found; odds ratio (95% CI) 5.97 (2.49, 14.29). This figure is preliminary, and more studies, a more standardized way of measuring symptoms, and efforts to reduce confounding are needed in future research.
A preprint meta-analysis of 12 papers that recorded smoking behavior of COVID-19 patients found that, based on 9,025 patients, 495 had a history of smoking Including past-smokers), and 18% experienced disease progression while 9.3% of never-smoking patients did (odds ratio of 2.25, with 95% CI 1.49-3.39). There wasn't notable heterogeneity or publication bias. However, it should be noted that these reports are preliminary and at general risk of bias. There was a low rate of smoking in these reports compared with the general population, which may be due to bias. Furthermore, most of the studies didn't adjust for confounding factors, though the one that did found a higher risk for smokers after adjustment.
Effects on lungs are highly variable, seeming to be more diverse than initially anticipated. On x-rays and CT scans, “ground-glass” opacities are commonly seen in the lungs, referring to fluid buildup or thickening of tissue where air spaces should normally be. Additional patterns in the lungs that suggest pneumonia as a cause of tissue injury are also appearing.
COVID-19 seems to have especially deletorious impacts on the lower respiratory tract. That’s because the main human receptor for the SARS S glycoprotein, called human angiotensin-converting enzyme 2 (ACE2), is mainly found in the lower respiratory tract.
There appears to be three major manifestions of lung symptoms: mild illness with upper respiratory tract symptoms; pneumonia that isn’t life-threatening, and severe pneumonia with acute respiratory distress syndrome (ARDS). The latter course can start with mild symptoms for around a week and then progress rapidly to much difficulty breathing, requiring life support.
Some patients with COVID-19 who are sick enough to be admitted to hospital develop inflammation of the heart (myocarditis) fairly late in the illness, which can lead to lethal heart arrhythmias. It is unclear if this is due to infection of the heart itself, or if it is secondary to myocardial suppression due to cytokine storm.
Studies have found that instances of liver injury range from 14.8-53% in infected patients, according to ALT/AST levels. The proportion of people with severe cases having liver damage was significantly higher than in mild cases, and reached as high as 58.06% and 78% in certain preprint reports. Unpublished data suggested that gamma-glutamyl transferase (GGT) increased in severe cases while alkaline phosphatase was normal during both mild and severe cases. It was noted that the ACE2 receptors that it uses to infect the body are are found on liver cells and bile duct cells, with the latter having a higher expression and comparable to alveolar type 2 cells in the lungs. The possibility of reverse causality and medication used during treatment causing liver damage can't be ruled out at present.
Loss of sense of smell (anosmia) as well as taste seem to be common symptoms, around 30% of patients in South Korea having at least one of those symptoms, and some even having that as their only notable symptom.
Out 40/59 of those with COVID-19 evaluated reported olfactory impairment while 42/59 reported gustatory impairment, compared with 16% and 17% respectively for those without COVID-19 with the odds ratio being unaffected when adjusted for various other symptoms. 29/40 reported improvement by 4 weeks after the survey, with 18% improving in less than a week, 37.5% by 1-2 and 18% by 2-4.
In another study, 417 patients with a mean age of 36.9 ± 11.4 years (range 19–77) filled out a questionnaire devised for the purpose of the study and 357 (85.6%) reported some sort of olfactory dysfunction, with 284 (79.6%) being deemed anosmic and 73 (20.4%) having microsmia. 33% of patients with microsmia recovered in 1-4 days, 39.6% in 5-8 days, 24.2 in 9-14 days and 3.3% in more than 15 days. 342 patients (88.8%) were deemed to have gustatory disorders according to impaired sense of taste for salty, sweet, bitter, or sour foods. The dysfunction for both was constant and unchanged in 72.8% of patients and fluctuated in 23.4%. There wasn’t a significant association between comorbidities and the development of olfactory or gustatory dysfunctions. It’s unclear which questions were asked for the sake of diagnosis of anosmia, and the definition could be considerably different than that for the other studies.
A study subjected 60 hospitalized COVID-19 patients and 60 age/sex-matched controls to the University of Pennsylvania Smell Identification Test (UPSIT) which asks 40 questions accompanied by scratch-and-sniff strips with a variety of scents in order to assess olfactory dysfunction. They found that 59/60 of the COVID-19 patients had some degree of olfactory dysfunction, with 15 being anosmic (loss of ability to smell), 20 having severe microsmia (reduced ability to smell), 16 having moderate microsmia and 8 had mild microsmia. In the control group, 49/60 had a normal sense of smell and 11/60 with only mild microsmia. 14 of the COVID-19 patients reported taste loss, while none of the control group did. The COVID-19 group had fewer smokers (2 as compared with 11) but more patients with diabetes (8 vs. 0), though diabetes didn’t seem to influence their sense of smell, and patients were considerably less likely to self-report smell loss than to have it as evaluated by the test. It should be noted that this study didn’t select its participants in a randomized manner, though didn’t likely have reliable information about the patients’ sense of smell prior to the study.
Olfactory and gustatory dysfunction are quite common in COVID-19, though it's unclear how common they truly are due to small sample sizes and potentially misleading questionnaires.
Patients with COVID-19 commonly have low levels of lymphocytes, which may be associated with mortality and symptom severity.
COVID-19, along with MERS and SARS, all showed exceptionally high levels of proinflammatory cytokines in serum, including IL1B, IFNγ, IP10, and MCP1. Cytokine storm, which is a massive overproduction of immune cells in response to infection, appears to be associated with the severity of COVID-19. Elevated serum ferritin (usually a measure of the body’s iron stores, but also an acute phase reactant) is a common lab test finding that can be used to diagnose cytokine storm syndrome (CSS). A 10-fold or more elevation in CRP levels is common in patients admitted to hospitals for COVID-19.
Contrasting with earlier reports of lower gastrointestinal involvement, analysis of data from Hubei Province in China suggests that COVID-19 patients can have primarily digestive system complaints (diarrhea being the most common problem). In some patients, diarrhea was the only presenting symptoms, and these patients tended to have worse outcomes.
Certain patients with COVID-19 display symptoms related to the nervous system, including headaches and nausea. It appears possible for the SARS-CoV-2 virus to infect humans (and experimental animals) outside of the respiratory tract, including the central nervous system. This could partially explain the exacerbation of respiratory symptoms to acute respiratory failure in some patients.
The case fatality rate of COVID-19 is uncertain, and constantly being updated with new evidence by international and national health agencies. It appears to be somewhere around 2%.
Preliminary research (preprints, do not consider this research alone) in China found that out of 200 cases (363 dead), there was no statistically significant difference in mortality between smokers and non-smokers, or males and females. Those aged less than 50 years were significantly less likely to die than those older, and >70 years was especially associated with risk for mortality.
There was a statistically significantly greater risk ratio for those who had comorbidities, pulmonary disease in particular, while diabetes, hypertension, hepatic diseases, and other diseases showed nonsignificant increases in risk.
Oxygenation index below 200 was associated with an extremely elevated risk, and 200–300 with an elevated risk compared with over 300.
High AST/ALT ratio, serum urea nitrogen, total bilirubin, and lactate dehydrogenase were associated with significantly higher mortality.
Patients with two or more comorbidities appear to have an increased risk of being admitted to an intensive care unit (ICU), receiving invasive ventilation, or dying compared to those with a single comorbidity or none.
Currently, based on a very limited number of cases, there doesn’t appear to be evidence for virus transmission from mother to newborn child. In a case series of nine mothers with COVID-19, there was no virus present in Amniotic fluid, cord blood, or neonatal throat swabs. However, not only is the sample very small, but the mothers were infected late in pregnancy. So the effects of an earlier infection are unknown.
An updated analysis of 38 pregnant women, including the aforementioned 9 in China with COVID-19 found no maternal deaths. It also didn't find cases of intrauterine transmission from mothers, and all pregnancies resulted in live births. Yet another paper describing two pregnancies failed to find intrauterine transmissions, or deaths of mothers or infants.
A systematic review of all case reports/series from February 12 to April 4, 2020, found that out of 108 pregnant women with COVID-19, there were no maternal deaths, while 3 women required admission to the ICU. Out of 86 deliveries reported, one neonate died, though this didn’t appear to be due to COVID-19. Six neonates required admission to intensive care units, all due to shortness of breath, and with a variety of other symptoms. There was one case of intrauterine fetal death from a woman who had multiple organ dysfunction syndrome with acute respiratory distress syndrome which led to the emergency Cesarean section. No clear evidence for mother-fetus transmission of COVID-19 has been found. There have been reports of newborns with elevated SARS-CoV-2 IgM antibodies, but testing for SARS-CoV-2 itself was negative, and it’s possible that these were false positives.
In the aforementioned case series, no virus was present in breastmilk samples.