
🚀 SIMPLICITY v2.2.4: Heterogeneous Populations This major release marks the integration of the long-shedders branch, evolving SIMPLICITY from an acute-infection model into a framework capable of handling population heterogeneity. ✨ Highlights & New Features Heterogeneous Population Modeling: Added full support for mixed populations containing both "Standard" and "Long-Shedder" host types. The model now features distinct infectiousness windows, detectability profiles, and lineage capacities for each sub-population. Evolutionary Calibration: This accounts for the compound evolutionary pressure generated by the continuous emergence of intra-host lineages ($k_v$) over time in distinct host types. Automated Calibration Pipeline 🧹 Housekeeping & Archiving (Important!) To keep the root and scripts/ directories clean for version 2.0+, we performed a massive repository cleanup: Paper Archive: All specific figure-generating scripts and legacy experiments used for the original SIMPLICITY publication have been safely moved to scripts/00_SIMPLICITY_paper_archive/. Test Suite: Removed obsolete tests and added new, robust test files (e.g., tests/test_diag_mut_rates.py) to validate the new parameterization logic.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
