About: Determining the severity of a novel pathogen in the early stages is difficult in the absence of reliable data. The pattern of outbreaks for COVID-19 across the globe have differed markedly above and below +40N latitudes, suggesting very different levels of severity, but countries worldwide have implemented the same lockdown strategies. Existing methods for estimating severity appear not to have been useful in informing strategic decisions, possibly due to mismatches between the data required and those available, overly sophisticated methods with undesirable biases, or perhaps confusion and uncertainly generated by the wide range of estimates these methods produced early on. The Epidemic Severity Index (ESI) is a simple, robust method for estimating the local severity of novel epidemic outbreaks using early and widely-available data and that does not depend on any estimated values. ESI allows rapid, meaningful comparisons across territories that can be tracked as the outbreaks unfold. The ESI quantifies severity relative to a parameterised baseline rather than attempting to estimate values for infection fatality rates, case fatality rates or transmission rates. The relative nature of the ESI sidesteps any problems of confidence associated with absolute rate estimation methods and offers immediate practical strategic value.   Goto Sponge  NotDistinct  Permalink

An Entity of Type : fabio:Abstract, within Data Space : wasabi.inria.fr associated with source document(s)

AttributesValues
type
value
  • Determining the severity of a novel pathogen in the early stages is difficult in the absence of reliable data. The pattern of outbreaks for COVID-19 across the globe have differed markedly above and below +40N latitudes, suggesting very different levels of severity, but countries worldwide have implemented the same lockdown strategies. Existing methods for estimating severity appear not to have been useful in informing strategic decisions, possibly due to mismatches between the data required and those available, overly sophisticated methods with undesirable biases, or perhaps confusion and uncertainly generated by the wide range of estimates these methods produced early on. The Epidemic Severity Index (ESI) is a simple, robust method for estimating the local severity of novel epidemic outbreaks using early and widely-available data and that does not depend on any estimated values. ESI allows rapid, meaningful comparisons across territories that can be tracked as the outbreaks unfold. The ESI quantifies severity relative to a parameterised baseline rather than attempting to estimate values for infection fatality rates, case fatality rates or transmission rates. The relative nature of the ESI sidesteps any problems of confidence associated with absolute rate estimation methods and offers immediate practical strategic value.
subject
  • Zoonoses
  • Infectious diseases
  • Viral respiratory tract infections
  • COVID-19
  • Occupational safety and health
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 © 2009-2025 OpenLink Software