An extended SEIARD model for COVID-19 vaccination in Mexico: analysis and forecast

Pérez, Ángel; Oluyori, David A.

doi:10.5206/mase/14233

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…For the Pfizer-BioNTech, 10 references indicated a 21-day difference between the first and second dose [ 69 , 100 , 133 , 134 , 217 , 302 , 303 , 335 , 342 , 383 ], while one reference indicated a 28-day difference [ 173 ]. Different intervals were identified for the AstraZeneca vaccine: 70 days [ 139 ], 84 days [ 99 ], and 28, 56, 84, 112, and 140 days [ 350 ].…”

Section: Resultsmentioning

confidence: 99%

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

Espinosa,

Mora,

Sanabria

et al. 2024

Syst Rev

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Background The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19). Methodology PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542. Findings In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias. Interpretation The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

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Section: Resultsmentioning

confidence: 99%

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

Espinosa,

Mora,

Sanabria

et al. 2024

Syst Rev

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Analysis of an ongoing epidemic: Advantages and limitations of COVID-19 modeling

Santana-Cibrian¹,

Acuña-Zegarra²,

Tocto-Erazo³

et al. 2023

Mathematical Modelling, Simulations, and AI for Emergent Pandemic Diseases

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Modeling the Transmission of the SARS-CoV-2 Delta Variant in a Partially Vaccinated Population

León

Ávila-Vales

Huang

2022

Viruses

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In a population with ongoing vaccination, the trajectory of a pandemic is determined by how the virus spreads in unvaccinated and vaccinated individuals that exhibit distinct transmission dynamics based on different levels of natural and vaccine-induced immunity. We developed a mathematical model that considers both subpopulations and immunity parameters, including vaccination rates, vaccine effectiveness, and a gradual loss of protection. The model forecasted the spread of the SARS-CoV-2 delta variant in the US under varied transmission and vaccination rates. We further obtained the control reproduction number and conducted sensitivity analyses to determine how each parameter may affect virus transmission. Although our model has several limitations, the number of infected individuals was shown to be a magnitude greater (~10×) in the unvaccinated subpopulation compared to the vaccinated subpopulation. Our results show that a combination of strengthening vaccine-induced immunity and preventative behavioral measures like face mask-wearing and contact tracing will likely be required to deaccelerate the spread of infectious SARS-CoV-2 variants.

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An extended SEIARD model for COVID-19 vaccination in Mexico: analysis and forecast

Cited by 4 publications

References 26 publications

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

Analysis of an ongoing epidemic: Advantages and limitations of COVID-19 modeling

Modeling the Transmission of the SARS-CoV-2 Delta Variant in a Partially Vaccinated Population

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