AttributesValues
type
value
  • 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 (%22SIRX%22) 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.
Subject
  • Zoonoses
  • Serology
  • Epidemics
  • Epidemiology
  • Viral respiratory tract infections
  • Health policy
  • COVID-19
  • Biological hazards
  • Occupational safety and health
  • New York (state)
part of
is abstract of
is hasSource of
Faceted Search & Find service v1.13.91 as of Mar 24 2020


Alternative Linked Data Documents: Sponger | ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data]
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software