tetano
Editor, Senior Moderator
Infect Dis Model
. 2020 Sep 28;5:766-771.
doi: 10.1016/j.idm.2020.09.006. Online ahead of print.
The SARS-CoV-2 pandemic course in Saudi Arabia: A dynamic epidemiological model
Abdullah Murhaf Al-Khani[SUP] 1 [/SUP], Mohamed Abdelghafour Khalifa[SUP] 1 [/SUP], Abdulrahman Almazrou[SUP] 1 [/SUP], Nazmus Saquib[SUP] 1 [/SUP]
Affiliations
Abstract
Objective: Saudi Arabia ranks second in the number of coronavirus disease 2019 (COVID-19) cases in the Eastern Mediterranean region. It houses the two most sacred religious places for Muslims: Mecca and Medina. It is important to know what the trend in case numbers will be in the next 4-6 months, especially during the Hajj pilgrimage season.
Methods: Epidemiological data on COVID-19 were obtained from the Saudi Arabian Ministry of Health. A susceptible-exposed-infectious-recovered (SEIR) prediction model was constructed to predict the trend in COVID-19 in Saudi Arabia in the next 6 months.
Findings: The model predicts that the number of active cases will peak by 22 May 2020. The cumulative infected cases are predicted to reach 70,321 at that time. The total number of infected individuals is estimated reach to 114,580 by the end of the pandemic.
Conclusion: Our estimates show that by the time the Hajj season commences in Saudi Arabia, the pandemic will be in the midst of its deceleration phase (phase 3). This information will likely be useful to policymakers in their management of the outbreak.
Keywords: COVID-19, coronavirus disease 2019; DCM, deterministic compartmental model; Epidemiology; Infectious disease; MERS-CoV, Middle East respiratory syndrome coronavirus; Modelling; Outbreaks; R0, basic reproduction number; SARS-CoV 2, severe acute respiratory syndrome coronavirus 2; SEIR, susceptible, exposed, infectious and recovered infectious disease prediction model; SIR, susceptible, infectious and recovered infectious disease prediction model; Surveillance; cfr, mortality proportion among the infected; e.dur, duration of the exposed state; e.num, number of exposed; i.dur, duration of the infectious state; i.num, number of infected; p.num, number of protected; r.num, number of recovered; s.num, number of susceptible.
. 2020 Sep 28;5:766-771.
doi: 10.1016/j.idm.2020.09.006. Online ahead of print.
The SARS-CoV-2 pandemic course in Saudi Arabia: A dynamic epidemiological model
Abdullah Murhaf Al-Khani[SUP] 1 [/SUP], Mohamed Abdelghafour Khalifa[SUP] 1 [/SUP], Abdulrahman Almazrou[SUP] 1 [/SUP], Nazmus Saquib[SUP] 1 [/SUP]
Affiliations
- PMID: 33015424
- PMCID: PMC7521407
- DOI: 10.1016/j.idm.2020.09.006
Abstract
Objective: Saudi Arabia ranks second in the number of coronavirus disease 2019 (COVID-19) cases in the Eastern Mediterranean region. It houses the two most sacred religious places for Muslims: Mecca and Medina. It is important to know what the trend in case numbers will be in the next 4-6 months, especially during the Hajj pilgrimage season.
Methods: Epidemiological data on COVID-19 were obtained from the Saudi Arabian Ministry of Health. A susceptible-exposed-infectious-recovered (SEIR) prediction model was constructed to predict the trend in COVID-19 in Saudi Arabia in the next 6 months.
Findings: The model predicts that the number of active cases will peak by 22 May 2020. The cumulative infected cases are predicted to reach 70,321 at that time. The total number of infected individuals is estimated reach to 114,580 by the end of the pandemic.
Conclusion: Our estimates show that by the time the Hajj season commences in Saudi Arabia, the pandemic will be in the midst of its deceleration phase (phase 3). This information will likely be useful to policymakers in their management of the outbreak.
Keywords: COVID-19, coronavirus disease 2019; DCM, deterministic compartmental model; Epidemiology; Infectious disease; MERS-CoV, Middle East respiratory syndrome coronavirus; Modelling; Outbreaks; R0, basic reproduction number; SARS-CoV 2, severe acute respiratory syndrome coronavirus 2; SEIR, susceptible, exposed, infectious and recovered infectious disease prediction model; SIR, susceptible, infectious and recovered infectious disease prediction model; Surveillance; cfr, mortality proportion among the infected; e.dur, duration of the exposed state; e.num, number of exposed; i.dur, duration of the infectious state; i.num, number of infected; p.num, number of protected; r.num, number of recovered; s.num, number of susceptible.