Methods to Determine the End of an Infectious Disease Epidemic: A Short Review
Hiroshi Nishiura ()
Additional contact information
Hiroshi Nishiura: Hokkaido University
A chapter in Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases, 2016, pp 291-301 from Springer
Abstract:
Abstract Deciding the end of an epidemic is frequently associated with forthcoming changes in infectious disease control activities, including downgrading alert level in surveillance and restoring healthcare workers’ working shift back to normal. Despite the practical importance, there have been little epidemiological and laboratory methods that were proposed to determine the end of an epidemic. This short review was aimed to systematically discuss methodological principles of a small number of existing techniques and understand their advantages and disadvantages. Existing epidemiological methods have been mostly limited to a single-and-brief exposure setting, while the application to human-to-human transmissible disease epidemic with stochastic dependence structure in the observed case data has remained to be a statistical challenge. In veterinary applications, a large-scale sampling for laboratory testing has been commonly adapted to substantiate a freedom from disease, but such study has only accounted for binomial sampling process in estimating the error probability of elimination. Surveillance and mathematical modeling are two complementary instruments in the toolbox of epidemiologists. Combining their strengths would be highly beneficial to better define the end of an epidemic.
Keywords: Epidemic; Ebola; Epidemic elimination; Incubation period; Exposure; Polio; Heuristic method (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-40413-4_17
Ordering information: This item can be ordered from
http://www.springer.com/9783319404134
DOI: 10.1007/978-3-319-40413-4_17
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().