How do I simulate a tumor growth?

Open this page and use the live Epidemic Response Model tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.

Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.

Can I use my own numbers?

Absolutely — every input is adjustable, and with data import you can drive a tumor growth from your own measurements.

Use case · powered by Epidemic Response Model

Epidemic Response Model for a tumor growth

Simulate a tumor growth live in your browser. This runs the real Epidemic Response Model solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

For:Students Researchers Educators Engineers Hobbyists & Makers K-12 Students First Responders

SIR Model

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SIR Epidemic ModelLive

compartmental disease dynamics

Controls

Presets

Basic reproduction R₀

Infectious period (days)

Initial immune (vaccinated)

The SIR model splits a population into Susceptible, Infected, and Recovered and lets them flow between compartments. R₀ — the average number infected by one case — sets whether an outbreak grows. Vaccinating above the herd-immunity threshold 1−1/R₀ prevents an epidemic outright.

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Data Inspector

Peak infected0.0%

Total infected0.0%

Herd immunity60%

Governing equation

\frac{d S}{d t} = - β S I, \frac{d I}{d t} = β S I - γ I, \frac{d R}{d t} = γ I; β = 0.357, γ = 0.143, R_{0} = \frac{β}{γ} = 2.50

Reading this result: R₀ = 2.50 > 1 with only 0% immune, so infections grow into an epidemic. You would need to immunize 60% (the herd-immunity threshold 1−1/R₀) to stop it; the current effective reproduction number is 2.50.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Epidemic Network

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Epidemic on a NetworkLive

agent-based SIR on a contact graph

Controls

Speed1×

Infection spreads along the contact network (red = infected, blue = susceptible, green = recovered). Tune transmission, recovery, and connectivity.

Presets

Transmission β

Recovery γ

Contact radius

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Data Inspector

Susceptible0

Infected0

Recovered0

Edges0

Governing equation

R_{0} = \frac{β ⟨ k ⟩}{γ} = \frac{0.06 \times 0.0}{0.01} \approx 0.0

Reading this result: Spread outpaces recovery by 6.0-to-1 — an epidemic grows, but whether it reaches everyone hinges on the contact radius wiring nodes together.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Evacuation

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Building Evacuation / EgressLive

crowd flow through exits

Controls

Presets

Occupants

Exits

Walk speed

Speed1×

Occupants head for the nearest exit while pushing apart in crowds, so bottlenecks and congestion form at doorways — the effect that drives real egress times. Add or remove exits to see how total clearance time responds. Planning aid only.

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Data Inspector

Evacuated0 / 150

Clear time0.0 s

Exits2

Social-force velocity

v = 1.3 \overset{e}{^}_{exit} + 2.2 j \sum f_{ij}, \frac{N}{exits} = \frac{150}{2} = 75

Reading this result: Around 75 per exit — congestion starts to build at the doors, and adding an exit usually helps more than speeding people up.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Triage

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START TriageLive

mass-casualty triage algorithm

Triage category

YELLOW

Delayed

Controls

Can the patient walk?

Is the patient breathing?

Presets

Respirations / min

24 /min

Perfusion (radial pulse / cap refill <2s)

Mental status (obeys commands)

Simple Triage And Rapid Treatment sorts mass-casualty patients in under 60 seconds each using RPM: Respirations, Perfusion, Mental status. Training reference only — follow your agency protocol and medical direction.

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Data Inspector

RR trigger>30/min

Perfusioncap refill 2s

StandardSTART adult

Triage criterion

RR = 24 \leq 30 \Rightarrow not RED by RR

Reading this result: RPM checks pass (RR 24/min, perfusion adequate, follows commands), so the patient is DELAYED (YELLOW).

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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About this simulation

The full Epidemic Response Model tool models a tumor growth with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

More you can do with Epidemic Response Model

Epidemic Response Model for a bacterial growth Epidemic Response Model for a predator-prey cycle Epidemic Response Model for a neuron firing Epidemic Response Model for a heartbeat Epidemic Response Model for a virus spread Epidemic Response Model for a gene expression Epidemic Response Model for a protein fold Epidemic Response Model for a muscle contraction

Other ways to simulate a tumor growth

Dynamical Systems for a tumor growth Epidemic Network for a tumor growth Spatial Predator–Prey for a tumor growth SIR Epidemic for a tumor growth Hodgkin-Huxley Neuron for a tumor growth Lotka-Volterra for a tumor growth

Frequently asked questions

How do I simulate a tumor growth?: Open this page and use the live Epidemic Response Model tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?: Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?: Absolutely — every input is adjustable, and with data import you can drive a tumor growth from your own measurements.