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National audience; I calibrate a Multiple‐Risk Susceptible–Infected–Recovered model on the covid pandemic to analyze the impact of the age‐specific confinement and polymerase chain reaction (PCR) testing policies on incomes and mortality. Two polar strategies emergeas potentially optimal. The suppression policy would crush the curve by confining 90% of the population for 4 months to eradicate the virus. The flatten‐thecurvepolicy would reduce the confinement to 30% of the population for 5 months, followed by almost 1 year of free circulation of the virus to attain herd immunity without overwhelming hospitals.Both strategies yield a total cost of around 15% of annualgross domestic product (GDP) when combining the economic cost of confinement with the value of lives lost. I show that hesitating between the two strategies can have a huge societal cost, in particular if the suppression policy is stopped too early. Becauseseniors are much more vulnerable, a simple recommendation emerges to shelter them as one deconfines young and middle‐aged people to build our collective herd immunity. By doing so, one reduces the death toll of the pandemic together with the economic cost of the confinement, and the total cost is divided by a factor 2. I also show that expandingthe mass testing capacity to screen people sent back to work has a large benefit under various scenarios.This analysis is highly dependent upon deeply uncertain epidemiologic, sociological, economic, and ethical parameters.

Understanding the human cytotoxic T lymphocyte (CTL) biology is crucial to develop novel strategies aiming at maximizing their lytic capacity against cancer cells. Here we introduce an agent-based model, calibrated on population-scale experimental data that allows quantifying human CTL per capita killing. Our model highlights higher individual CTL killing capacity at lower CTL densities and fits experimental data of human melanoma cell killing. The model allows extending the analysis over prolonged time frames, difficult to investigate experimentally, and reveals that initial high CTL densities hamper efficacy to control melanoma growth. Computational analysis forecasts that sequential addition of fresh CTL cohorts improves tumor growth control. In vivo experimental data, obtained in a mouse melanoma model, confirm this prediction. Taken together, our results unveil the impact that sequential adjustment of cellular densities has on enhancing CTL efficacy over long-term confrontation with tumor cells. In perspective, they can be instrumental to refine CTL-based therapeutic strategies aiming at controlling tumor growth.