ArticleData in brief2020
The hidden Markov chain modelling of the COVID-19 spreading using Moroccan dataset.
Article in Data in brief, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Changing Incidence and Characteristics of Photokeratoconjunctivitis During the COVID-19 Pandemic.The western journal of emergency medicine · 2024Observational
- Article
- Vulture-Based AdaBoost-Feedforward Neural Frame Work for COVID-19 Prediction and Severity Analysis System.Interdisciplinary sciences, computational life sciences · 2022Article
- Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset.Data in brief · 2022Article
- Predicting the trend of indicators related to Covid-19 using the combined MLP-MC model.Chaos, solitons, and fractals · 2021Article
- Article
- Exploring Household Food Dynamics During the COVID-19 Pandemic in Morocco.Frontiers in nutrition · 2021Article
- Health-related quality of life and behavior-related lifestyle changes due to the COVID-19 home confinement: Dataset from a Moroccan sample.Data in brief · 2020Article
- Impact of the COVID-19 lockdown on the epidemiologic and clinic profiles of domestic accidents in children.African journal of paediatric surgery : AJPSArticle
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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