SEAHIR: A Specialized Compartmental Model for COVID-19

Alexandros Leontitsis, Abiola Senok, Alawi Alsheikh-Ali, Younus Al Nasser, Tom Loney and Aamena Alshamsi
Additional contact information
Alexandros Leontitsis: Smart Dubai Department, Dubai Design District, Building 1A, Dubai P.O. Box 555995, United Arab Emirates
Abiola Senok: College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Building 14, Dubai Healthcare City, Dubai P.O. Box 505055, United Arab Emirates
Alawi Alsheikh-Ali: College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Building 14, Dubai Healthcare City, Dubai P.O. Box 505055, United Arab Emirates
Younus Al Nasser: Smart Dubai Department, Dubai Design District, Building 1A, Dubai P.O. Box 555995, United Arab Emirates
Tom Loney: College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Building 14, Dubai Healthcare City, Dubai P.O. Box 505055, United Arab Emirates
Aamena Alshamsi: Smart Dubai Department, Dubai Design District, Building 1A, Dubai P.O. Box 555995, United Arab Emirates

IJERPH, 2021, vol. 18, issue 5, 1-11

Abstract: The SEIR (Susceptible-Exposed-Infected-Removed) model is widely used in epidemiology to mathematically model the spread of infectious diseases with incubation periods. However, the SEIR model prototype is generic and not able to capture the unique nature of a novel viral pandemic such as SARS-CoV-2. We have developed and tested a specialized version of the SEIR model, called SEAHIR (Susceptible-Exposed-Asymptomatic-Hospitalized-Isolated-Removed) model. This proposed model is able to capture the unique dynamics of the COVID-19 outbreak including further dividing the Infected compartment into: (1) “Asymptomatic”, (2) “Isolated” and (3) “Hospitalized” to delineate the transmission specifics of each compartment and forecast healthcare requirements. The model also takes into consideration the impact of non-pharmaceutical interventions such as physical distancing and different testing strategies on the number of confirmed cases. We used a publicly available dataset from the United Arab Emirates (UAE) as a case study to optimize the main parameters of the model and benchmarked it against the historical number of cases. The SEAHIR model was used by decision-makers in Dubai’s COVID-19 Command and Control Center to make timely decisions on developing testing strategies, increasing healthcare capacity, and implementing interventions to contain the spread of the virus. The novel six-compartment SEAHIR model could be utilized by decision-makers and researchers in other countries for current or future pandemics.

Keywords: compartmental models; COVID-19; Erlang distribution; predictive modelling; SARS-CoV-2; SEIR (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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