<b>EpiModel</b>: An <i>R</i> Package for Mathematical Modeling of Infectious Disease over Networks

Jenness, Samuel M.; Goodreau, Steven M.; Morris, Martina

doi:10.18637/jss.v084.i08

Cited by 139 publications

(73 citation statements)

References 40 publications

(68 reference statements)

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“…Therefore, the goal of the public health interventions in Cameroon will be to progressively reduce the number of exposures (we will simulate using 12, 6, and 2 exposures per day) and the probability of infection (we will simulate using 5%, 2.5%, and 1%). The simulation was done using the R EpiModel package with a population of size N = 1,000 for computational matters [18]. Fig 8 gives the results.…”

Section: Plos Onementioning

confidence: 99%

Simulating the progression of the COVID-19 disease in Cameroon using SIR models

et al. 2020

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This paper analyses the evolution of COVID-19 in Cameroon over the period March 6-April 2020 using SIR models. Specifically, we 1) evaluate the basic reproduction number of the virus, 2) determine the peak of the infection and the spread-out period of the disease, and 3) simulate the interventions of public health authorities. Data used in this study is obtained from the Cameroonian Public Health Ministry. The results suggest that over the identified period, the reproduction number of COVID-19 in Cameroon is about 1.5, and the peak of the infection should have occurred at the end of May 2020 with about 7.7% of the population infected. Furthermore, the implementation of efficient public health policies could help flatten the epidemic curve.

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Section: Plos Onementioning

confidence: 99%

Simulating the progression of the COVID-19 disease in Cameroon using SIR models

et al. 2020

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“…The analytic component of this paper was carried out using the EpiModel ( Jenness, Goodreau, & Morris, 2018 ) package in the R statistical programming language, version 3.6.3 (R Foundation for Statistical Computing). Microsoft Excel 2016 was used for data storage and management.…”

Section: Methodsmentioning

confidence: 99%

The SARS-CoV-2 pandemic course in Saudi Arabia: A dynamic epidemiological model

Al-Khani¹,

Khalifa²,

Almazrou³

et al. 2020

Infectious Disease Modelling

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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.

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“…Besides, we can observe a decrease in the percentage of the population infected by the virus and the disease lasts for a shorter period. 10 We used the R EpiModel package to simulate public interventions with a population of size N = 1,000 for computational matters (Jenness et al 2018).…”

Section: Simulating Public Health Interventionsmentioning

confidence: 99%

Simulating the progression of the COVID-19 disease in Cameroon using SIR models

Nguemdjo¹,

Meno²,

Dongfack

et al. 2020

Preprint

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This paper analyses the evolution of COVID 19 disease in Cameroon over the period March 6 April 2020 using SIR model. Specifically, 1) we evaluate the basic reproduction number of the virus. 2) Determine the peak of the infection and the spread-out period of the disease. 3) Simulate the interventions of public health authorities. Data used in this study is obtained from the Ministry of Health of Cameroon. The results suggest that over the period, the reproduction number of the COVID 19 in Cameroon is about 1.5 and the peak of the infection could occur at the end of May 2020 with about 7.7% of the population infected. Besides, implementation of efficient public health policies could help flattens the epidemic curve.

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EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks

Cited by 139 publications

References 40 publications

Simulating the progression of the COVID-19 disease in Cameroon using SIR models

Simulating the progression of the COVID-19 disease in Cameroon using SIR models

The SARS-CoV-2 pandemic course in Saudi Arabia: A dynamic epidemiological model

Simulating the progression of the COVID-19 disease in Cameroon using SIR models

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