|python Population Modeller Resource1 #685208|
The pyPM.ca software was developed to study and characterize the CoViD-19 epidemic.
It consists of:
- pypmca: a general purpose population modelling engine.
- ipypm: a graphical user interface for pypmca. Based on ipywidgets, it runs in a jupyter notebook.
- models: a repository of CoViD-19 models tuned for different regions.
- data: a repository of regional CoViD-19 data on cases, hospitalizations, and deaths.
- CitationsAdd new citationList by: CiterankMap
|Link Characterizing the spread of CoViD-19|
Author: Dean Karlen
Publication date: 14 July 2020
Publication info: arXiv:2007.07156
Cited by: David Price 2:32 PM 14 September 2022 GMT
Citerank: (2) 685229Dean KarlenR.M. Pearce Professor of Physics, University of Victoria and TRIUMF10019D3ABAB, 690180British Columbia COVID-19 GroupThe BC COVID-19 Modelling Group works on rapid response modelling of the COVID-19 pandemic, with a special focus on British Columbia and Canada.10015D3D3AB
|Excerpt / Summary|
Since the beginning of the epidemic, daily reports of CoViD-19 cases, hospitalizations, and deaths from around the world have been publicly available. This paper describes methods to characterize broad features of the spread of the disease, with relatively long periods of constant transmission rates, using a new population modeling framework based on discrete-time difference equations. Comparative parameters are chosen for their weak dependence on model assumptions. Approaches for their point and interval estimation, accounting for additional sources of variance in the case data, are presented. These methods provide a basis to quantitatively assess the impact of changes to social distancing policies using publicly available data. As examples, data from Ontario and German states are analyzed using this framework. German case data show a small increase in transmission rates following the relaxation of lock-down rules on May 6, 2020. By combining case and death data from Germany, the mean and standard deviation of the time from infection to death are estimated.