1/7 While transmission data models don’t use case-based surveillance data to predict, they do use data on known epidemiological parameters that influence how #COVID19 spreads, e.g. average # of contacts, duration of infectiousness etc.,
2/7 Together with data on how #publichealth & intervention measures can impact spread. This way the model can show us how different options for intervention might change the epidemic trajectory. #COVID19
3/7 These models can predict numbers of cases but their strength is in guiding planning by illustrating which trajectory is best between e.g. an option A. “do nothing worst case scenario” vs. option “B” or “C” intervention scenarios. #COVID19
4/7 For #COVID19, this type of model is what showed us that if we did “A. nothing” the epidemic would spike over a short period of time w\ maximum hospitalisations & critical cases overwhelming our healthcare system & ⬆️death rates. (Image credit: Drew Harris @drewaharris)
5/7 To avoid this worst-case scenario, modelling experts illustrated how proven effective #publichealth interventions like #PhysicalDistancing, #goodhygiene & #infectioncontrol could #FlattenTheCurve, to maintain health system capacity & ↓ deaths.
6/7 Nevertheless, modelling projections provide a range of possibilities. They are not actual crystal balls because what happens in THE FUTURE DEPENDS ON WHAT WE DO. #COVID19
7/7 That’s why we have to #KeepItUp w\ #PhysicalDistancing, #GoodHygiene , #CoughEtiquette & #TestandTrace other #publichealth measures, because THE FATE OF THE POSSIBILITIES IS UP TO US. #COVID19
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