The hidden Markov chain modelling of the COVID-19 spreading using Moroccan dataset
Abdelghafour Marfak,
Doha Achak,
Asmaa Azizi,
Chakib Nejjari,
Khalid Aboudi,
Elmadani Saad,
Abderraouf Hilali,
Ibtissam Youlyouz-Marfak
Affiliations
Abdelghafour Marfak
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco; Higher Institute of Nursing Professions and Health Technology of Rabat, Morocco; Corresponding author.
Doha Achak
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
Asmaa Azizi
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
Chakib Nejjari
Epidemiology, Clinical Research and Community Health, Faculty of Medicine and Pharmacy of Fez, University Sidi Mohammed Ben Abdellah, Fez, Morocco; International School of Public Health, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco
Khalid Aboudi
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
Elmadani Saad
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
Abderraouf Hilali
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
Ibtissam Youlyouz-Marfak
Laboratory of Health Sciences and Technology, Higher Institute of Health Sciences, Hassan First University of Settat, Morocco
The World Health Organization (WHO) declared in March 12, 2020 the COVID-19 disease as pandemic. In Morocco, the first local transmission case was detected in March 13. The number of confirmed cases has gradually increased to reach 15,194 on July 10, 2020. To predict the COVID-19 evolution, statistical and mathematical models such as generalized logistic growth model [1], exponential model [2], segmented Poisson model [3], Susceptible-Infected-Recovered derivative models [4] and ARIMA [5] have been proposed and used. Herein, we proposed the use of the Hidden Markov Chain, which is a statistical system modelling transitions from one state (confirmed cases, recovered, active or death) to another according to a transition probability matrix to forecast the evolution of COVID-19 in Morocco from March 14, to October 5, 2020. In our knowledge the Hidden Markov Chain was not yet applied to the COVID-19 spreading. Forecasts for the cumulative number of confirmed, recovered, active and death cases can help the Moroccan authorities to set up adequate protocols for managing the post-confinement due to COVID-19. We provided both the recorded and forecasted data matrices of the cumulative number of the confirmed, recovered and active cases through the range of the studied dates.
