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SHUTDOWN - as a Risk Management Tool Is the current Covid 19 pandemic taking Australia into uncharted waters ? Some would believe so but in this brief essay I argue that the well established procedures of Risk Management can enable us to build a road map that can guide everyone through the choice of control options. The destination is to achieve the maximum protection of the asset, i.e. those Australians at greatest risk, via a route that minimises the collateral damage to the rest of the Australian community.


Australian Covid 19 Data For week ending 2nd April 2020 This Table puts the Covid 19 data to date into the perspective of incidences across the whole Australian population

Australian Covid 19 Data For week ending 9th April 2020 This Table puts the Covid 19 data to date into the perspective of incidences across the whole Australian population.

Australian Covid 19 Data For week ending 16th April 2020 This Table puts the Covid 19 data to date into the perspective of incidences across the whole Australian population. Additional data for comparison has been added vz. UK, USA, Sweden and Taiwan. Taiwan has done very well in managing Covid 19 but their success data are being supressed by mainland China. China successfully barred Taiwan from the WHO membership and consequently WHO does not list them as a separate nation state.

Australian Covid 19 Data For week ending 23rd April 2020 This Table puts the Covid 19 data to date into the perspective of incidences across the whole Australian population. Additional data for comparison has been added vz. Motor vehicle accident deaths for 2019

Australian Covid 19 Data For week ending 30th April 2020

Australian Covid 19 Data For week ending 8th May 2020 Includes histogram of ages at time of death of Australian cases.

Australian Covid 19 Data For week ending 15th May 2020



Using Python 3 to Model the COVID-19 Epidemics in Australia and Sweden Fitting epidemic data to a model is attractive because it offers the promise of being able to predict the trajectory of the outbreak forward in time. This short essay provides a Python 3 script and associated 'rule based stochastic modelling' that has proven to be excellent at fitting a model to the initial curve of the outbreak. However, as with all models as the epidemic proceeds from 'cohort' to 'cohort' the model cannot predict that. It does, however, provide excellent agreement with the CDC measurements of R ZERO for Covid 19.

Last Updated 18th May 2020

"Without data you are just another person with an opinion ...."


medlabstats@iinet.net.au

tomhartley850@gmail.com


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