Abstract
To 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.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
No funding received.
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
No IRB or Ethics Committee Approval Necessary
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.
Yes
Data Availability
All data is available both on Github an in the supplemental files.