Papers › Estimating the household secondary attack rate with the Incomplete Chain Binomial model

Estimating the household secondary attack rate with the Incomplete Chain Binomial model

6 Mar 2024arXiv:2403.03948links table onlyarchive 2025-07-28

Jonas Christoffer Lindstrøm, Terese Bekkevold, Cathinka Halle Julin, Anna Hayman Robertson, Lisbeth Meyer Næss

The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.

The Secondary Attack Rate (SAR) is a measure of how infectious a communicable disease is, and is often estimated based on studies of disease transmission in households. The Chain Binomial model is a simple model for disease outbreaks, and the final size distribution derived from it can be used to estimate the SAR using simple summary statistics. The final size distribution of the Chain Binomial model assume that the outbreaks have concluded, which in some instances may require long follow-up time. We develop a way to compute the probability distribution of the number of infected before the outbreak has concluded, which we call the Incomplete Chain Binomial distribution. We study a few theoretical properties of the model. We develop Maximum Likelihood estimation routines for inference on the SAR and explore the model by analyzing two real world data sets.

PaperPDFCode

Code

opisthokonta/chainbinomial officialmentioned in paper report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections