A sequential test for assessing the effectiveness of response strategies during an emerging epidemic

In epidemiology, the fatality rate is an important indicator of disease severity and has been used to evaluate the effects of new treatments. During an emerging epidemic with limited resources, monitoring the changes in fatality rate can also provide signals on the evaluation of government policies...

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Bibliographic Details
Published in:Biometrical journal 2023-01, Vol.65 (1), p.e2100293-n/a
Main Authors: Lam, K.F., Qu, Yuanke
Format: Article
Language:English
Subjects:
Brownian motion
Change detection
Disease Outbreaks
Ebola virus
Ebola virus epidemic
emerging infectious epidemic
Epidemics
Epidemiology
Evaluation
Fatalities
fatality rates
Hemorrhagic Fever, Ebola - diagnosis
Hemorrhagic Fever, Ebola - epidemiology
Humans
Infectious diseases
Public Health
Public policy
sequential test
Sierra Leone - epidemiology
Statistical tests
Test procedures
Viral diseases
Viruses
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Summary:In epidemiology, the fatality rate is an important indicator of disease severity and has been used to evaluate the effects of new treatments. During an emerging epidemic with limited resources, monitoring the changes in fatality rate can also provide signals on the evaluation of government policies and healthcare quality, which helps to guide public health decision. A statistical test is developed in this paper to detect changes in fatality rate over time during the course of an emerging infectious disease. A major advantage of the proposed test is that it only requires the regularly reported numbers of deaths and recoveries, which meets the actual need as detailed surveillance data are hard to collect during the course of an emerging epidemic especially the deadly infectious diseases with large magnitude. In addition, with the sequential testing procedure, the effective measures can be detected at the earliest possible time to provide guidance to policymakers for swift action. Simulation studies showed that the proposed test performs well and is sensitive in picking up changes in the fatality rate. The test is applied to the 2014–2016 Ebola outbreak in Sierra Leone for illustration.
ISSN:0323-3847
1521-4036
DOI:10.1002/bimj.202100293