Modelling the evolution of the coronavirus disease (COVID-19) in Saudi Arabia.
J Infect Dev Ctries
; 15(7): 918-924, 2021 07 31.
Article
in English
| MEDLINE | ID: covidwho-1339631
ABSTRACT
INTRODUCTION:
The ongoing COVID-19 pandemic has claimed hundreds of thousands of lives around the world. Health planners are seeking ways to forecast the evolution of the pandemic. In this study, a mathematical model was proposed for Saudi Arabia, the country with the highest reported number of COVID-19 cases in the Arab world.METHODOLOGY:
The proposed model was adapted from the model used for the Middle East respiratory syndrome outbreak in South Korea. Using time-dependent parameters, the model incorporated the effects of both population-wide self-protective measures and government actions. Data before and after the government imposed control policies on 3 March 2020 were used to validate the model. Predictions for the disease's progression were provided together with the evaluation of the effectiveness of the mitigation measures implemented by the government and self-protective measures taken by the population.RESULTS:
The model predicted that, if the government had continued to implement its strong control measures, then the scale of the pandemic would have decreased by 99% by the end of June 2020. Under the current relaxed policies, the model predicted that the scale of the pandemic will have decreased by 99% by 10 August 2020. The error between the model's predictions and actual data was less than 6.5%.CONCLUSIONS:
Although the proposed model did not capture all of the effects of human behaviors and government actions, it was validated as a result of its time-dependent parameters. The model's accuracy indicates that it can be used by public health policymakers.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Public Health
/
COVID-19
/
Models, Theoretical
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
J Infect Dev Ctries
Journal subject:
Communicable Diseases
Year:
2021
Document Type:
Article
Affiliation country:
Jidc.13568
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