On the usefulness of set-membership estimation in the epidemiology of infectious diseases | Zendy

Andreas Widder | Zendy

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On the usefulness of set-membership estimation in the epidemiology of infectious diseases

Author(s) -

Andreas Widder

Publication year - 2017

Publication title -

mathematical biosciences and engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.451

H-Index - 45

eISSN - 1551-0018

pISSN - 1547-1063

DOI - 10.3934/mbe.2018006

Subject(s) - estimation , infectious disease (medical specialty) , ebola virus , outbreak , epidemiology , mathematical modelling of infectious disease , set (abstract data type) , population , data set , computer science , econometrics , confidence interval , disease , statistics , mathematics , data mining , medicine , virology , environmental health , engineering , pathology , systems engineering , programming language

We present a method, known in control theory, to give set-membership estimates for the states of a population in which an infectious disease is spreading. An estimation is reasonable due to the fact that the parameters of the equations describing the dynamics of the disease are not known with certainty. We discuss the properties of the resulting estimations. These include the possibility to determine best- or worst-case-scenarios and identify under which circumstances they occur, as well as a method to calculate confidence intervals for disease trajectories under sparse data. We give numerical examples of the technique using data from the 2014 outbreak of the Ebola virus in Africa. We conclude that the method presented here can be used to extract additional information from epidemiological data.

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