COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model

Ahmad, Naim

doi:10.7759/cureus.10452

Cited by 14 publications

(20 citation statements)

References 19 publications

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“…Thereafter, appropriate points of control measures were identified, and effective control measure values were chosen based on the pattern changes and in conjunction with the model fitting. The arrived pattern in the initial stage resembles the pattern proposed in the study of Ahmad [ 13 ]. Specifically, day 90 represents the toughest controls during the Eid 2020 vacation time, wherein there was complete lockdown in Saudi Arabia; this can also be seen from other aggregated indices provided by the OxCGRT (Figure 3 ).…”

Section: Methodssupporting

confidence: 69%

“…The results from this scenario show that by the end of the pandemic, 76.32% of the population would get infected. These numbers are better than the previous study [ 13 ], as the general standard of well-being is being observed more rigorously and getting imbibed in the society in addition to robustness in the results due to this hybrid approach.…”

Section: Discussionmentioning

confidence: 57%

“…For the modification of the SEIR model to represent interventions, studies have incorporated numerous parameters [ 7 , 10 , 11 , 13 ]. This work attempts to employ a single control parameter (σ) to represent the composite of 20 control measures present in the OxCGRT.…”

Section: Methodsmentioning

confidence: 99%

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A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources

Ahmad¹,

Qahmash²

2021

Cureus

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The coronavirus disease 2019 (COVID-19) pandemic has caused the world to operate uncharacteristically for almost the last two years. Governments across the globe have taken different control measures to eradicate it. The Oxford provides open access data for different countries on 20 control measures, including numerous aggregated indices. This paper employs the modified Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiology model to study the COVID-19 pandemic in Saudi Arabia. The modification has been achieved by including control measures and the infectiousness of exposed compartment. A hybrid approach has been used to estimate and incorporate control measures. Initially, a composite control measure has been derived from OxCGRT data to make an attempt to fit the COVID-19 pattern in Saudi Arabia. The derived model has proven to be satisfactory through statistical tests. Nonetheless, the model patterns do not resemble the reported patterns more closely. Hence, a second heuristic approach has been utilized to devise effective control measures from the reported pattern of COVID-19 from the Saudi government agency. A satisfactory model was derived utilizing this approach with successful validation through statistical tests. Also, the model patterns more closely resemble the reported patterns of COVID-19 cases. This hybrid approach proves more robust and ensures the validity of model parameters better. The R naught (R 0 ) value with the current control measures has varied from 0.515 to 1.892, with a mean value of 1.119, and is presently less than 1. The threshold herd immunity, in the absence of any control measure, is estimated to be 47.12% with an R 0 value of 1.89 and would end up infecting 76.32% of the population. The scenario analysis with gradual partial and complete relaxations up to December 31, 2021, shows that the peaks are likely to occur in 2022; therefore, Saudi Arabia must continue to inoculate its population to eradicate COVID-19.

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Section: Methodssupporting

confidence: 69%

Section: Discussionmentioning

confidence: 57%

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A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources

Ahmad¹,

Qahmash²

2021

Cureus

Self Cite

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“…To simulate a pandemic or an epidemic, several models such as Susceptible-Infected-Recovered (SIR) [20] , [21] , [22] , [23] , [24] , Susceptible-Infected- Susceptible (SIS) [25] , Susceptible-Unidentified infected-Confirmed (SUC) [26] , Susceptible-Exposed-Infectious-Recovered (SEIR) [18] , [27] , Susceptible-Exposed-Infected-Quarantine-Recovered (SEIQR) [28] , Susceptible-Vaccinated-Infected-Recovered (SVIR) [29] , and Susceptible–Exposed–Infected–Recovered–Deceased (SEIRD) [30] have been applied. As most of the COVID-19 researchers base their analysis on the SIR [31] , [32] , [33] and SEIR [16] , [17] , [19] , [34] , [35] , [36] , [37] , this paper builds its pandemic model on these two models and demonstrates it in Fig. 1 .…”

Section: Coronavirus Spread and Adopted Policiesmentioning

confidence: 99%

An analysis of the social distancing effects on global economy and international finance using causal loop diagrams

Moradi

2022

Decision Analytics Journal

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This paper investigates the COVID-19 outbreak, explains the policies adopted by governments, and examines the side effects of social distancing on the global economy and international finance. Causal loop diagrams are used to explain the interlinkages amongst the important variables and show the outbreak follows the pattern of a reinforcing loop. Governments strive to balance this loop by adopting a set of policies, of which social distancing has left a tremendous negative impact on the global economy. The side effects of this policy are highlighted in three categories: short-term, midterm, and long-term by explaining the reinforcing loops that require time to get stimulated. The short-term loops result in demand and supply shocks in any economy, and if this policy stays effective for a longer period, the midterm loops get activated, leading to corporate and government debt crises. When the pandemic duration extends, the long-term side effects appear with a deflationary recession and a banking crisis. The quickness of moving from one category to another in an economy depends on the financial strength of firms and their government. Finally, this paper anticipates some changes in future business caused by the pandemic, which can bring insights for managers.

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“…These reports of this worldwide pandemic in Saudi Arabia are attributed to population size, resisted through strategic interventions and mitigation measures characterized by swift community action and hospital preparedness (3,10,26,(28)(29)(30)(31). This aligns with vision 2030 that positions the country as a business and tourism hub (8,32).…”

Section: Introductionmentioning

confidence: 98%

COVID-19 in Saudi Arabia: An Overview

Salam

Al-Khraif

Elsegaey

2022

Front. Public Health

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BackgroundSaudi Arabia, a prominent Arabian country, has 35. 3 million persons living in 2.2 million square kilometers, undergone serious threats recently due to the COVID-19 pandemic. With the built-in infrastructure and disciplined lifestyle, the country could address this pandemic.AimsThis analysis of COVID-19 cases in Saudi Arabia attempts to assess the situation, explore its global percentage share, percentage of population affected, and local distribution from the beginning of infection until recently, tracing historical developments and changes.Data and MethodsThis analysis made use of data released by the Ministry of Health on a daily basis for a number of parameters. They are compiled on an excel sheet on a daily basis: the dataset has undergone rigorous analysis along with the trends and patterns; proportion to the world statistics and geographic distribution.ResultsCOVID-19 spread rapidly in the country with periodic variations, during June-August, 2020. But, recoveries accelerated in the period, thus bridging the gap of increasing infections. In comparison with the world statistics, the country proportions are lower, while the percentage of population affected is similar. It appears that the intensity varied across all 13 administrative areas.ConclusionCOVID-19 transmission since March 2020 is considered to be widespread, creating excess burden on the public health system, delineated into stages (early infection, rapid spread, declining, stabilizing, and second wave). Control measures are set, stage-wise, without impinging upon normal life but to ensure that the proportion of globally affected persons is lesser than the population share: credit goes to the Ministry of Health. Area-wise spread depends largely on population density and development infrastructure dimensions. Ultimately, the disciplined life in compliance with law and order paved the way for effective program implementation and epidemic control.

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COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model

Cited by 14 publications

References 19 publications

A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources

A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources

An analysis of the social distancing effects on global economy and international finance using causal loop diagrams

COVID-19 in Saudi Arabia: An Overview

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