AFAIK epidemiologists usually measure particular diseases and focus their models on those, whereas LDSL would more be across all species of germs.
I would honestly be interested in any concrete model you build based on this. You don’t necessarily have to compare it against some other field’s existing model, though it does help for credibility’s sake. But I would like to at least be able to compare the model you make against data.
I’m also not sure this is true about epidemiologists, and if it is I’d guess its true to the extent that they have like 4 different parameterizations of different types of diseases (likely having to do with various different sorts of vectors of spread), then they fit one of those 4 different parameterizations to the measured (or inferred) characteristics of a particular disease.
The most central aspect of my model is to explain why it’s generally not relevant to fit quantitative models to data.
I’m also not sure this is true about epidemiologists, and if it is I’d guess its true to the extent that they have like 4 different parameterizations of different types of diseases (likely having to do with various different sorts of vectors of spread), then they fit one of those 4 different parameterizations to the measured (or inferred) characteristics of a particular disease.
Each disease (and even different strands of the same disease and different environmental conditions for the same strand) has its own parameters, but they don’t fit a model that contains all the parameters of all diseases at once, they just focus on one disease at a time.
I would honestly be interested in any concrete model you build based on this. You don’t necessarily have to compare it against some other field’s existing model, though it does help for credibility’s sake. But I would like to at least be able to compare the model you make against data.
I’m also not sure this is true about epidemiologists, and if it is I’d guess its true to the extent that they have like 4 different parameterizations of different types of diseases (likely having to do with various different sorts of vectors of spread), then they fit one of those 4 different parameterizations to the measured (or inferred) characteristics of a particular disease.
The most central aspect of my model is to explain why it’s generally not relevant to fit quantitative models to data.
Each disease (and even different strands of the same disease and different environmental conditions for the same strand) has its own parameters, but they don’t fit a model that contains all the parameters of all diseases at once, they just focus on one disease at a time.