Sensitivity analysis studies the relation between the uncertainty and the uncertainties in the model assumptions.
Sensitivity analysis can play an important role in epidemiology, for example in assessing the influence of the unmeasured confounding on the causal conclusions of a study.
[Ding, Peng; VanderWeele, Tyler J., 2016, Sensitivity Analysis Without Assumptions, Epidemiology, Volume 27 - Issue 3 - p 368-377] It is also important in all mathematical modelling studies of epidemics.
Sensitivity analysis can be used in epidemiology, for example in assessing the influence of the unmeasured confounding on the causal conclusions of a study.
[Joseph AC Delaney, John D Seeger, 2013, Chapter 11, Sensitivity Analysis, in Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide, Velentgas P, Dreyer NA, Nourjah P, et al., editors, Agency for Healthcare Research and Quality (US); Publication No.: 12(13)-EHC099.] The use of
sensitivity analysis
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty ana ...
in
mathematical modelling of infectious disease
Mathematical models can project how infectious diseases progress to show the likely outcome of an epidemic (including in plants) and help inform public health and plant health interventions. Models use basic assumptions or collected statistics alo ...
is suggested in
on the
Coronavirus disease 2019
Coronavirus disease 2019 (COVID-19) is a contagious disease caused by a virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. The disease quickly ...
outbreak. Given the significant
uncertainty
Uncertainty refers to Epistemology, epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially ...
at play, the use of
sensitivity analysis
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty ana ...
to apportion the output uncertainty into input parameters is crucial in the context of
Decision-making
In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either r ...
. Examples of applications of sensitivity analysis to modelling of
COVID-19
Coronavirus disease 2019 (COVID-19) is a contagious disease caused by a virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. The disease quickl ...
are
and.
in particular, the time of intervention time in containing the pandemic spread is identified as a key parameter.
References
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Mathematical modeling
Mathematical analysis
Epidemiology