Calibrating an Epidemic Compartment Model to Seroprevalence Survey Data
Keyword(s):
New York
◽
AbstractTo date, the Covid-19 epidemic has produced tremendous cost and harm. However, to date, many epidemic models are not calibrated to seroprevalence survey(s). This paper calibrates a relatively simple, SIR plus confirmed cases (“SIRX”) model against seroprevalence survey data released by the State of New York. The intention of this paper is to demonstrate a potentially new technique of calibration for epidemic models used by scientists, public health officials and governments. The technique can then be incorporated in other more complex models. Open source code is included to assist model developers.
Keyword(s):
2010 ◽
Keyword(s):
2021 ◽
pp. 207-221