Back

Quantifying Key Parameters of Environmental Transmission and Age-Specific Susceptibility for Mycobacterium avium subspecies paratuberculosis (MAP)

Gao, Y.; Bijma, P.; de Jong, M. C.; Hartemink, N.

2025-03-24 systems biology
10.1101/2024.11.14.623589 bioRxiv
Show abstract

Paratuberculosis is a chronic disease in cows and other ruminants, caused by Mycobacterium avium subspecies paratuberculosis (MAP). We developed an age-specific dose-response model and two environmental transmission models (Model A and B) to estimate key parameters based on previously published experiments for MAP in dairy cows. In the dose-response model, the age-specific susceptibility decrease rate parameter was estimated at 0.0629{square}wk-1, suggesting that a previously used parameter of 0.1{square}wk-1 may have underestimated the infection risks with increasing age. For the transmission models, Model A represents infectivity differences among transiently infectious (I tr), low shedding (Il), high shedding (Ih) individuals by varying transmission rate parameters ([Formula]) with a standardized constant shedding rate parameter of 2.10{square}wk-1, whereas Model B captures these differences by varying shedding rate parameters ([Formula]) with one transmission rate parameter of 0.0299{square}wk-1. Although both models have identical best estimates and AIC values, Model B exhibited wider 95% confidence intervals (95% CI). In both models, the MAP decay rate parameter was estimated at 0.150{square}wk-1, corresponding to a half-life of MAP of approximately 4.61 weeks, which aligns well with previously published values. To better interpret these parameters and understand how different biological assumptions about infectivity influence predicted exposure, we performed scenario analyses examining environmental contamination over time, along with infection probabilities over exposure timing, exposure duration, and the recipients age at exposure. All 95% CI are provided in the main text.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.