What is infection fatality rate (IFR)?

IFR is the proportion of all infected people (including asymptomatic cases) who die from the infection. It differs from case fatality rate (CFR), which only counts confirmed cases. IFR is typically much lower than CFR because many infections are never diagnosed.

How accurate is this calculator?

It is a simplified educational model built from published population-level data. Individual outcomes depend on variant circulation, prior infection history, timing of treatment, immune status, frailty, and many other factors that the worksheet cannot capture.

Does this account for COVID variants?

The base IFR values are approximate and represent general risk. Specific variants may have different severity profiles. Omicron variants appear to have lower intrinsic severity than Delta, but the calculator's relative risk factors (age, vaccination, comorbidities) remain valid across variants.

Long COVID (Post-Acute Sequelae of SARS-CoV-2, or PASC) refers to symptoms persisting more than 12 weeks after initial infection. Common symptoms include fatigue, brain fog, shortness of breath, and exercise intolerance. Estimates suggest 5–15% of infections result in long COVID, with vaccination reducing risk by approximately 50%.

Should I get Paxlovid based on my risk score?

This page does not decide whether antiviral treatment is appropriate. Eligibility and treatment choice depend on symptoms, timing, drug interactions, kidney function, current guidance, and clinician review.

How do multiple comorbidities interact?

In this model, comorbidity risks are multiplicative. A patient with both diabetes (1.8×) and CKD (2.5×) has a combined multiplier of 4.5×. In reality, the interaction may be somewhat less than purely multiplicative, but having multiple conditions does substantially compound risk.

COVID-19 Severity Context Calculator

Review age- and comorbidity-based COVID severity context with a simplified educational model for infection fatality, hospitalization, ICU, and long-COVID bands.

⚠️ Medical Disclaimer: This page is an educational population-risk worksheet. Individual outcomes depend on many factors not captured here, including prior infection, variants, timing of treatment, frailty, and immune status.

Age

years

Sex

Vaccination Status

BMI

kg/m²

Smoking Status

Comorbidities (select all that apply):

Risk Level

Low

Estimated infection fatality rate: 0.0260%

Hospitalization Context

0.31%

Illustrative hospitalization band if infected

ICU Context

0.13%

Illustrative ICU band if infected

Illustrative IFR

1 in 3,846

Adjusted infection fatality estimate: 0.0260%

Long-COVID Context

5.3%

Illustrative persistent-symptom band based on the simplified model

Vaccination Effect Used

95% relative reduction

Age-banded base IFR before vaccination adjustment: 0.400%

Age-Based Infection Fatality Rate (Unvaccinated)

Age Group	IFR	1 in...
0–19	0.003%	1 in 33,333
20–29	0.01%	1 in 10,000
30–39	0.03%	1 in 3,333
40–49	0.1%	1 in 1,000
50–59	0.4%	1 in 250
60–69	1.4%	1 in 71
70–79	4.6%	1 in 22
80–89	15%	1 in 7
90+	25%	1 in 4

Comorbidity Risk Multipliers

Condition	Hazard Ratio	Selected
Cardiovascular Disease	2.1×	—
Diabetes	1.8×	—
Chronic Kidney Disease	2.5×	—
COPD / Chronic Lung Disease	1.9×	—
Obesity (BMI ≥ 30)	1.5×	—
Immunocompromised	2.8×	—
Cancer (active)	2.3×	—
Liver Disease	1.7×	—

Planning notes, formulas, and examples

About the COVID-19 Severity Context Calculator

This worksheet translates population-level COVID severity data into a rough context estimate using age, vaccination status, BMI, smoking, and selected comorbidities. It is designed to show how strongly those factors move the background risk picture, not to predict a single person's exact outcome.

Age remains the strongest broad predictor of severe COVID-19, and chronic conditions such as cardiovascular disease, diabetes, kidney disease, cancer, and immunocompromise clearly worsen outcomes. Vaccination, prior exposure history, antivirals, and variant changes can also shift the picture in important ways.

Because those factors interact in ways no simple bedside model can fully capture, the output here should be read as educational population context only. It is not a validated individualized mortality or long-COVID prediction tool.

When This Page Helps

This worksheet helps turn broad COVID-19 severity data into a rough context estimate that is easier to interpret. It is best used to compare how age, vaccination, and comorbidities change the background risk picture rather than to make a personal prediction.

How to Use the Inputs

Enter your age in years.
Select your biological sex (males have ~30% higher mortality risk).
Select your vaccination status (unvaccinated through boosted).
Enter your BMI (obesity significantly increases risk).
Select your smoking status.
Click all applicable comorbidities from the list.
Review your personalized risk estimates and reference tables.

Formula used

Illustrative model used on this page:
- Start with an age-banded infection-fatality estimate
- Apply simplified multipliers for sex, vaccination status, BMI, smoking, and selected comorbidities
- Derive rough hospitalization, ICU, and long-COVID context bands from that adjusted base

This is a site-defined educational worksheet, not a validated individual prediction equation.

Example Calculation

Result: Illustrative IFR context: about 1 in 5,291 — Moderate worksheet band

Base IFR for ages 60–69 starts at 1.4% in this educational model. The page then applies simplified sex, vaccination, diabetes, and BMI multipliers to show how the background risk picture changes. The result is a worksheet estimate only, not a personalized clinical forecast.

Tips & Best Practices

Vaccination is the single most effective risk reduction — boosted status reduces mortality by ~95%.
BMI ≥ 30 increases risk by ~50%; BMI ≥ 40 increases risk by ~150%. Weight loss before infection improves outcomes.
Males have ~30% higher mortality risk than females, likely due to immune response differences and ACE2 expression.
Comorbidity risks are multiplicative — having 2+ conditions compounds your risk substantially.
Early antiviral treatment (Paxlovid within 5 days of symptoms) reduces hospitalization by ~89% in high-risk patients.
Long COVID risk decreases by ~50% with vaccination and by ~25% with early antiviral treatment.

What This Worksheet Is Good For

This page is useful for showing how strongly age, vaccination, and chronic disease shift the background severity picture. It is a way to organize population-level factors, not a way to know what will happen in one specific infection.

Why The Output Stays Approximate

COVID outcomes depend on more than age and chronic disease. Prior infection, circulating variants, immune status, frailty, pregnancy, treatment timing, and healthcare access all matter, and the exact interaction between those factors is not simple or fixed.

Best Use

Read the output as a rough context estimate that helps explain why layered prevention and early medical review matter more for some people than for others. It should not be used as a substitute for current clinical guidance.

Sources & Methodology

Last updated: March 28, 2026

Methodology

This page uses age-banded infection-fatality estimates as a starting point, then applies simplified multipliers for vaccination status, smoking, BMI, and selected comorbidities to show how population-level risk changes when those factors are present. It also derives rough hospitalization, ICU, and long-COVID context bands from the same simplified framework.

This is not a validated individual prediction model. The output is an educational population-context estimate only, and it cannot account for current variants, prior infection history, timing of vaccine doses, antivirals, frailty, pregnancy, immune status, or the exact interaction between multiple conditions.

Sources

Age-specific mortality and immunity patterns of SARS-CoV-2 (PubMed / Nature) — Foundational paper for age-stratified infection-fatality estimates.
Underlying Conditions and the Higher Risk for Severe COVID-19 (Centers for Disease Control and Prevention) — CDC summary of underlying conditions associated with more severe COVID-19 outcomes.
Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis (PubMed / International Journal of Infectious Diseases) — Meta-analysis supporting the role of obesity, diabetes, cardiovascular, respiratory, kidney, and other chronic conditions in severe or fatal COVID outcomes.

Frequently Asked Questions

IFR is the proportion of all infected people (including asymptomatic cases) who die from the infection. It differs from case fatality rate (CFR), which only counts confirmed cases. IFR is typically much lower than CFR because many infections are never diagnosed.