The leading cause of death is respiratory failure from acute respiratory distress syndrome (ARDS).
The overall pooled mortality rate from ARDS in COVID-19 patients is 39%; however, this varies significantly between countries (e.g., China 69%, Iran 28%, France 19%, Germany 13%).
There is no evidence to suggest worse outcomes (i.e., mechanical ventilator-free days, length of stay in intensive care unit or hospital, or mortality) for patients with COVID-19-related ARDS compared with the general ARDS population.
Risk factors for respiratory failure include older age, male sex, cardiovascular disease, laboratory markers (such as lactate dehydrogenase, lymphocyte count, and C-reactive protein), and high viral load on admission.
Other common causes of death include sepsis or septic shock, sepsis-related multiorgan failure, bacterial or viral co-infections, venous thromboembolism, and cardiac failure.
Mortality rate depends on age and the presence of underlying medical conditions.
People <65 years of age have a very small risk of death even in pandemic epicentres, and deaths in people <65 years of age without any underlying conditions is rare.
Deaths in children and young people are rare. A systematic review and meta-analysis found that 3.3% of children were hospitalised, 0.3% were admitted to the intensive care unit, and 0.02% died in community-based studies (23.9%, 2.9%, and 0.2%, respectively, in hospital-based screening studies.
Approximately 99% of patients who died of COVID-19 had at least one underlying health condition in a US cohort study. The strongest risk factors for death were obesity, anxiety and fear-related disorders, and diabetes, as well as the total number of underlying conditions. The three most prevalent comorbidities in deceased patients were hypertension, diabetes mellitus, and respiratory disease.
Mortality rates are high in critically ill patients.
Global all-cause mortality was 35% in the intensive care unit and 32% in hospital for critically ill patients for the year 2020. However, mortality rates vary between regions. For example, the mortality was as high as 48% in Southeast Asia and as low as 15% in America.
Mortality rates have decreased over time despite stable patient characteristics.
In-hospital mortality decreased from 32.3% to 16.4% between March and August 2020 in a UK cohort study of over 80,000 patients. Mortality declined in all age groups, in all ethnic groups, in men and women, and in patients with and without comorbidities, over and above contributions from declining illness severity. Adjusted in-hospital mortality rates declined during the early part of the first wave in the UK and this was largely maintained during the second wave of the pandemic.
Mortality rates decreased sharply in the US over the first 6 months of the pandemic. In-hospital mortality decreased from 10.6% to 9.3% between March and November 2020 in one US cohort study of over 500,000 patients across 209 acute care hospitals. Among patients with critical illness admitted to an intensive care unit at an academic health system in the US, the mortality rate decreased from 43.5% to 19.2% over the study period.
This may reflect the impact of changes in hospital strategy and clinical processes, and better adherence to evidence-based standard of care therapies for critical illness over time, such as use of corticosteroids, high-flow nasal oxygen to avert intubation, prone positioning, and decreased use of mechanical ventilation. Further studies are needed to confirm these results and investigate causal mechanisms.
Infection fatality rate (IFR)
Defined as the proportion of deaths among all infected individuals including confirmed cases, undiagnosed cases (e.g., asymptomatic or mildly symptomatic cases), and unreported cases. The IFR gives a more accurate picture of the lethality of a disease compared with the case fatality rate.
It has been estimated that approximately 1.5 to 2 billion infections have occurred globally as of February 2021, with an estimated overall IFR of 0.15%. There are substantial differences in IFR and infection spread across continents, countries, and locations. Preprint (not peer reviewed) data suggests that the median IFR in community-dwelling people aged ≥70 years was 2.9% (4.9% in people aged ≥70 years overall), but was much lower at younger ages (median 0.0013%, 0.0088%, 0.021%, 0.042%, 0.14%, and 0.65%, at 0-19, 20-29, 30-39, 40-49, 50-59, and 60-69 years, respectively).
The US Centers for Disease Control and Prevention’s current best estimate of the IFR, according to age:
0 to 17 years – 0.002%
18 to 49 years – 0.05%
50 to 64 years – 0.6%
≥65 years – 9%.
Based on these figures, the overall IFR for people <65 years of age is approximately 0.2%.
Among people on board the Diamond Princess cruise ship, a unique situation where an accurate assessment of the IFR in a quarantined population can be made, the IFR was 0.85%. However, all deaths occurred in patients >70 years of age, and the rate in a younger, healthier population would be much lower.
These estimates have limitations and are likely to change as more data emerge over the course of the pandemic, especially in the context of circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants.
Case fatality rate (CFR)
Defined as the total number of deaths reported divided by the total number of detected cases reported. CFR is subject to selection bias as more severe/hospitalised cases are likely to be tested. CFR is a dynamic estimate that changes with time, population, socioeconomic factors, and mitigation measures.
The World Health Organization’s current estimate of the global CFR is 1% (as of 27 November 2022). CFR varies considerably between countries. The pooled CFR in the general population in a systematic review and meta-analysis was 1%. This is much lower than the reported CFR of severe acute respiratory syndrome coronavirus (SARS), which was 10%, and Middle East respiratory syndrome (MERS), which was 37%.
CFR increases with age.
In the US, the majority of deaths were in patients aged ≥65 years. The CFR was highest among patients aged ≥85 years (10% to 27%), followed by those aged 65 to 84 years (3% to 11%), then those aged 55 to 64 years (1% to 3%), and finally those aged 20 to 54 years (<1%).
In China, the majority of deaths were in patients aged ≥60 years. The CFR was highest among patients aged ≥80 years (13.4%), followed by those aged 60 to 79 years (6.4%), and then those aged <60 years (0.32%).
In Italy, the CFR was highest among patients aged ≥80 years (52.5%), followed by those aged 70 to 79 years (35.5%), and then those aged 60 to 69 years (8.5%).
CFR increases with the presence of comorbidities.
In China, the majority of deaths were in patients who had pre-existing underlying health conditions (10.5% for cardiovascular disease, 7.3% for diabetes, 6.3% for chronic respiratory disease, 6% for hypertension, and 5.6% for cancer).
CFR increases with disease severity.
Limitations of IFR/CFR
Estimating the IFR and CFR in the early stages of a pandemic is subject to considerable uncertainties and estimates are likely to change as more data emerges. Rates tend to be high at the start of a pandemic and then trend downwards as more data becomes available.
There is currently no set case definition of a confirmed case, and case definitions vary. A positive polymerase chain reaction (PCR) result is sometimes the only criterion for a case to be recognised; however, a positive PCR test does not necessarily equal a diagnosis of COVID-19, or mean that a person is infected or infectious.
The number of deaths reported on a particular day may not accurately reflect the number of deaths from the previous day due to delays associated with reporting deaths. This makes it difficult to know whether deaths are falling over time in the short term.
Patients who die 'with' COVID-19 and patients who die 'from' COVID-19 may be counted towards the death toll in some countries. For example, in Italy only 12% of death certificates reported direct causality from COVID-19, while 88% of patients who died had at least one comorbidity.
Prognostic factors that have been associated with increased risk of severe disease, hospitalisation or intensive care unit admission, poor outcomes, and mortality include:
Blood type A
Presence of comorbidities
Peripheral artery disease
Chronic respiratory disease (e.g., COPD, obstructive sleep apnoea)
Chronic kidney or liver disease
Bacterial or fungal co-infection
Acute infection or sepsis
Acute kidney, liver, or cardiac injury
Acute respiratory distress syndrome
Liver or kidney impairment
Elevated inflammatory markers (e.g., C-reactive protein, procalcitonin, ferritin, erythrocyte sedimentation rate, tumour necrosis factor-alpha, interferon gamma, interleukins, lactate dehydrogenase)
Elevated creatine kinase
Elevated cardiac markers
PaO₂/FiO₂ ≤200 mmHg
Bilateral pneumonia on chest imaging
Consolidative infiltrate or pleural effusion on chest imaging
High sequential organ failure assessment (SOFA) score.
The most common underlying diseases in deceased patients were hypertension, diabetes, and cardiovascular diseases.
In children and adolescents, congenital heart disease, chronic pulmonary disease, neurological diseases, obesity, multisystem inflammatory syndrome, shortness of breath, acute respiratory distress syndrome, acute kidney injury, gastrointestinal symptoms, and elevated C-reactive protein and D-dimer have been associated with unfavourable prognosis.
Approximately 10% of recovered patients require hospital readmission during the first year after discharge, based on very low-quality evidence. Most hospital readmissions occur within 30 days of discharge. Higher readmission rates have been reported in patients with underlying diseases, but the current evidence is contradictory and comes from studies with a low level of evidence. Higher readmission rates have also been reported in developed countries compared with developing countries, possibly due to the better access to medical services and the higher medical benefits provided in developed countries. The prevalence of post-discharge all-cause mortality of recovered patients was 7.87% within 1 year of discharge.
Persistent infections have been reported in immunocompromised people.
The risk of severe post-acute complications in patients who were not admitted to hospital for the primary infection appears to be low. However, they may be at slightly increased risk of venous thromboembolism, dyspnoea, and initiating bronchodilator or triptan therapy compared with people who tested negative for SARS-CoV-2. These patients visited their general practitioner and outpatient hospital clinics more often after the primary infection than those who tested negative, which may indicate persistent symptoms that do not lead to specific drug treatment or hospital admission.
Reinfection refers to a new infection following previous confirmed infection (i.e., severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] real-time reverse transcription polymerase chain reaction [RT-PCR] positive), and is distinct from persistent infection and relapse. There is currently no standard case definition for SARS-CoV-2 reinfection.
Cases of reinfection are rare.
A systematic review and meta-analysis reported the pooled reinfection rate to be 0.65% in the pre-Omicron period. The rate was higher in high-risk populations (1.6%), and the rate of symptomatic reinfection was lower (0.4%). Across 18 studies, the reinfection risk ranged from 0% to 2.2%, and previous infection reduced the risk for reinfection by 87%. Protection remained above 80% for at least 7 months.
Consider reinfection in the following circumstances:
A repeat positive RT-PCR test 90 days or more after a previous positive RT-PCR test
New symptoms in a patient with previous RT-PCR-positive infection after apparent full recovery (i.e., resolution of previous symptoms) and a repeat positive RT-PCR test (including within 90 days after a previous positive RT-PCR test).
A compatible clinical presentation together with diagnostic evidence (such as a low RT-PCR cycle threshold value) may be sufficient to diagnose reinfection. However, the diagnosis should be made in conjunction with an infectious disease specialist following a risk assessment that involves reviewing available clinical, diagnostic, and epidemiological information to inform whether reinfection is likely. Confirmation of reinfection should be obtained through whole genome sequencing of paired specimens, if available.
Manage patients with suspected reinfection as if they are infectious, as for a new or first infection. Advise the patient to self-isolate pending further investigation and clinical risk assessment. It is important to note that illness due to reinfection may not necessarily follow the same clinical course as the previous episode.
The global population has varied immune histories to SARS-CoV-2 derived from various exposures to infection, virus variants, and vaccination.
The immune response to SARS-CoV-2 involves both cell-mediated and antibody-mediated immunity. Adaptive immunity is thought to occur within the first 7 to 10 days of infection. A robust memory B-cell and plasmablast response is detected early in infection, with secretion of immunoglobulin A (IgA) and IgM antibodies by day 5 to 7, and IgG by day 7 to 10 from the onset of symptoms. T cells are simultaneously activated in the first week of infection and SARS-CoV-2-specific memory CD4+ and CD8+ T cells peak within 2 weeks. Antibody and T-cell response differ among individuals, and depend on age and disease severity.
Approximately 85% to 99% of infected people develop detectable neutralising antibodies within 4 weeks following natural infection. However, this varies depending on disease severity, study setting, time since infection, and method used to measure antibodies.
Moderate-strength evidence suggests that most adults develop detectable levels of IgM and IgG antibodies after infection. IgM levels peak early in the disease course at approximately 20 days and then decline. IgG levels peak later at approximately 25 days after symptom onset and may remain detectable for at least 120 days. Most adults generate neutralising antibodies, which may persist for several months. Some adults do not develop antibodies after infection; the reasons for this are unclear.
Maternal IgG antibodies to SARS-CoV-2 have been found to transfer across the placenta after infection in pregnant women.
Extreme-aged (some over 100 years), frail residents of a long-term care facility have been found to elicit a robust immune response that was capable of neutralising the SARS-CoV-2 virus.
There were some early studies that suggested asymptomatic people may have a weaker antibody response to infection; however, this has not been confirmed.
Current evidence suggests that the immune responses remain robust and protective against reinfection in most people for at least 10 months after infection. A cross-sectional study of unvaccinated adults found evidence of natural immunity up to 20 months after infection, although it is unclear how antibody levels correlate with future protection, particularly with emerging variants.
Some SARS-CoV-2 variants with key changes in the spike protein have a reduced susceptibility to neutralisation by antibodies. However, cellular immunity elicited by natural infection also targets other viral proteins, which tend to be more conserved across variants than the spike protein.
The majority of people develop a strong and broad T-cell response with both CD4+ and CD8+ T cells, and some have a memory phenotype.
Evidence suggests that natural infection with SARS-CoV-2 is likely to confer high protective immunity against reinfection.
Robust antibody and T-cell immunity against SARS-CoV-2 is present in the majority of recovered patients 12 months after moderate to critical infection. Neutralising antibodies diminished between 6 and 12 months after infection, mostly in older people and critical patients. However, memory T-cells retained the ability to mediate cellular immunity in patients who had lost their neutralising antibody responses. Memory T-cell responses to the original SARS-CoV-2 strain were not disrupted by new variants. Convalescent critically ill patients consistently generated substantial adaptive and humoral immune responses against SARS-CoV-2 for more than 1 year after hospital discharge.
A UK Health Security Agency study found that naturally acquired immunity, as a result of past infection, provides 84% protection against reinfection compared with people who have not had the disease previously, and protection appeared to last for at least 7 months.
Similarly, a population-level observational study among 4 million PCR-tested people in Denmark found protection against repeat infection in the population to be 80% or higher in those younger than 65 years of age, and 47% in those older than 65 years of age. There was no evidence of waning protection over time.
A registry-based study from Sweden found that natural immunity was associated with a 95% lower risk of reinfection and an 87% lower risk of hospitalisation compared with no immunity, for up to 20 months. Vaccination appeared to further decrease the risk of both outcomes for up to 9 months, although the differences in absolute numbers were small.
A cohort study across six US states found that unvaccinated people with prior symptomatic COVID-19 had an 85% lower risk of acquiring COVID-19 than unvaccinated individuals without prior COVID-19, and suggests that natural immunity was associated with similar protection against both mild and severe disease.
An observational study from Lombardy, Italy, found that natural immunity appears to confer a protective effect for at least 1 year; however, the study ended before SARS-CoV-2 variants began to spread, and it is unknown how well natural immunity to the wild-type virus will protect against these variants.
Pre-existing immunity to SARS-CoV-2
Testing of blood samples taken before the COVID-19 pandemic has shown that some people already have immune cells that recognise SARS-CoV-2. Studies have reported T-cell reactivity against SARS-CoV-2 in 20% to 50% of people with no known exposure to the virus. Approximately 5% of uninfected adults and 62% of uninfected children aged 6 to 16 years had antibodies that recognise SARS-CoV-2 in one study.
This may be a consequence of true immune memory derived in part from previous infection with common cold coronaviruses, or from other unknown animal coronaviruses. However, further research into whether there is pre-existing immunity to SARS-CoV-2 in the human population is required.
Natural versus vaccine-induced immunity
Protection after natural infection appears to be comparable to that estimated for vaccine efficacy.
Evidence suggested that natural immunity may confer at least equal or longer-lasting and stronger protection against infection, symptomatic disease, and hospitalisation caused by the Delta variant compared with vaccine-induced immunity.
Protection of natural infection waned with time after primary infection and reached approximately 70% by the 16th month (pre-Omicron period). This is similar to vaccine immunity, but occurs at a slower rate. Immune evasion of Omicron subvariants reduced the overall protection of pre-Omicron natural immunity and accelerated its waning, again, similar to vaccine immunity but at a slower rate. Protection of natural infection against severe reinfection remains strong with no evidence for waning (regardless of variant) for over 14 months after primary infection.
Previous natural infection has been associated with a lower incidence of infection, regardless of the variant, compared with the primary series of mRNA vaccination.
Immunity and the Omicron variant
Infection with the Omicron variant has been found to induce strong immune protection against a subsequent Omicron infection, regardless of the subvariant. An additional earlier infection with a non-Omicron variant has been found to strengthen this protection against a subsequent Omicron infection in one study.
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