Modeling the Case of Early Detection of Ebola Virus Disease

Diego Chowell (), Muntaser Safan () and Carlos Castillo-Chavez ()
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Diego Chowell: Arizona State University
Muntaser Safan: Arizona State University
Carlos Castillo-Chavez: Arizona State University

A chapter in Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases, 2016, pp 57-70 from Springer

Abstract: Abstract The most recent Ebola outbreak in West Africa highlighted critical weaknesses in the medical infrastructure of the affected countries, including effective diagnostics tools, sufficient isolation wards, and enough medical personnel. Here, we develop and analyze a mathematical model to assess the impact of early diagnosis of pre-symptomatic individuals on the transmission dynamics of Ebola virus disease in West Africa. Our findings highlight the importance of implementing integrated control measures of early diagnosis and isolation. The mathematical analysis shows a threshold where early diagnosis of pre-symptomatic individuals, combined with a sufficient level of effective isolation, can lead to an epidemic control of Ebola virus disease.

Keywords: Ebola virus disease; Pre-symptomatic infection; Early detection; Point-of-care testing (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-40413-4_5

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DOI: 10.1007/978-3-319-40413-4_5

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