skills.rest
xjtulyc
xjtulycCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

epi-modeling

Fit SIR/SEIR/SEIHR models to incidence and estimate Rt with SciPy.

33|6|Updated Mar 17, 2026
Search Tags:#sensitivity analysis#public health#parameter fitting#seir#epidemic modeling#rt estimation
One-click install
npx skills add https://github.com/xjtulyc/awesome-rosetta-skills --skill epi-modeling
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: epi-modeling
Source: https://github.com/xjtulyc/awesome-rosetta-skills/tree/main/skills/17-public-health/epi-modeling
Command: npx skills add https://github.com/xjtulyc/awesome-rosetta-skills --skill epi-modeling

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, pandas, matplotlib, numba.

What problem does it solve?

This Skill helps you transform outbreak data into interpretable epidemic dynamics by building compartmental models, fitting parameters, and estimating the time-varying reproduction number Rt.

Core Features & Use Cases

  • Compartmental epidemic modeling: Build SIR, SEIR, and SEIHR (hospitalization) ODE systems and run stiff solvers for outbreak-scale dynamics.
  • Parameter fitting & validation: Fit transmission/incubation/recovery parameters to observed incidence using global optimization and return RMSE plus fitted trajectories.
  • Rt estimation & sensitivity: Estimate Rt over time using a sliding-window exponential growth approach with serial-interval assumptions, and analyze parameter influence using PRCC.
  • Use case: You have daily case counts for a specific region and want a robust SEIR fit, then track whether transmission is trending above or below replacement over time.

Quick Start

Ask the agent to fit an SEIR model to your daily incidence series and return the fitted parameters and an Rt time series with uncertainty bounds.

Frequently Asked Questions about epi-modeling

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fit an SEIR model to daily case counts and estimate Rt?▼

You can fit SIR, SEIR, and SEIHR compartmental models to observed incidence using differential evolution optimization. The Skill returns fitted transmission, incubation, and recovery parameters along with RMSE and fitted trajectories for model comparison.

How does Rt estimation work with serial intervals and sliding windows?▼

Sensitivity analysis in epidemic modeling is performed using PRCC to analyze parameter influence. This helps you validate how variations in transmission, incubation, and recovery rates impact the fitted SEIR dynamics and observed incidence curves.

Can I use scipy and numpy for stiff ODE systems in epidemic modeling?▼

You can build SIR, SEIR, and SEIHR compartmental models with hospitalization states using this Skill. It runs stiff ODE solvers to simulate outbreak-scale dynamics, making it suitable for public-health planning scenarios requiring interpretable disease transmission parameters.

What is the best way to translate outbreak case curves into disease transmission parameters?▼

No, this Skill is suitable for outbreak analysis, model comparison, and public-health planning scenarios. It translates case curves into interpretable disease transmission parameters using parameter fitting and Rt computation with quantile uncertainty bounds.

Related Skills

Explore More Education & Research Skills→
wuyoscarwuyoscar
934

epi-epydemic-spread

Configure networked SIR simulations with weaponized pathogen parameters and validate outbreak attack rates.

Community
Advanced
Srujan0798Srujan0798

create-viz

Generate Python chart code from datasets using matplotlib, seaborn, or plotly.

Community
Intermediate
xjtulycxjtulyc
33

scipy-numerical

Solve physics initial value problems and discretize PDEs with SciPy numerical methods.

Community
Advanced
tondevreltondevrel
19

pymc

Build Bayesian models with PyMC and NumPyro for MCMC inference.

Community
Advanced