A Spatial-Temporal Model for the Evolution of the COVID-19 Pandemic in Spain Including Mobility

Aràndiga, Francesc; Baeza, Antonio; Cordero-Carrión, I.; Donat, Rosa; Martí, Miguel; Mulet, Pep; Yáñez, Dionisio F.

doi:10.3390/math8101677

Cited by 36 publications

(24 citation statements)

References 29 publications

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“…Peixoto et al (42) estimate probabilities of movement between cities which is used to adjust the infected equation in a simple SI model. A more elaborate stochastic approach for estimating the mobility terms in the differential equations is followed in (3).…”

Section: Literature Reviewmentioning

confidence: 99%

A Spatial SEIR Model for COVID-19 in South Africa

Fabris‐Rotelli¹,

Holloway²,

Kimmie³

et al. 2021

Preprint

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The virus SARS-CoV-2 has resulted in numerous modelling approaches arising rapidly to understand the spread of the disease COVID-19 and to plan for future interventions. Herein, we present an SEIR model with a spatial spread component as well as four infectious compartments to account for the variety of symptom levels and transmission rate. The model takes into account the pattern of spatial vulnerability in South Africa through a vulnerability index that is based on socioeconomic and health susceptibility characteristics. Another spatially relevant factor in this context is level of mobility throughout. The thesis of this study is that without the contextual spatial spread modelling, the heterogeneity in COVID-19 prevalence in the South African setting would not be captured. The model is illustrated on South African COVID-19 case counts and hospitalisations.

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Section: Literature Reviewmentioning

confidence: 99%

A Spatial SEIR Model for COVID-19 in South Africa

Fabris‐Rotelli¹,

Holloway²,

Kimmie³

et al. 2021

Preprint

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“…Kamrujjaman et al, 2020 [ 12 ] proposed a quarantined model to provide control measures in different countries in Europe. A SAIR model with mobility within different cities, proposed by Arandiga et al, 2020 [ 13 ], analyzed the outbreak in the different autonomous communities of Spain. More SEIR, modified/extended SEIR, and models with more compartments related to COVID-19 are found in [ 14 , 15 , 16 , 17 , 18 , 19 ] and so on.…”

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 and Rohingya Refugee Camp, Bangladesh: Uncertainty and How the Government Took Over the Situation

Kamrujjaman

Mahmud

Ahmed

et al. 2021

Biology

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Background: Bangladesh hosts more than 800,000 Rohingya refugees from Myanmar. The low health immunity, lifestyle, access to good healthcare services, and social-security cause this population to be at risk of far more direct effects of COVID-19 than the host population. Therefore, evidence-based forecasting of the COVID-19 burden is vital in this regard. In this study, we aimed to forecast the COVID-19 obligation among the Rohingya refugees of Bangladesh to keep up with the disease outbreak’s pace, health needs, and disaster preparedness. Methodology and Findings: To estimate the possible consequences of COVID-19 in the Rohingya camps of Bangladesh, we used a modified Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model. All of the values of different parameters used in this model were from the Bangladesh Government’s database and the relevant emerging literature. We addressed two different scenarios, i.e., the best-fitting model and the good-fitting model with unique consequences of COVID-19. Our best fitting model suggests that there will be reasonable control over the transmission of the COVID-19 disease. At the end of December 2020, there will be only 169 confirmed COVID-19 cases in the Rohingya refugee camps. The average basic reproduction number (R0) has been estimated to be 0.7563. Conclusions: Our analysis suggests that, due to the extensive precautions from the Bangladesh government and other humanitarian organizations, the coronavirus disease will be under control if the maintenance continues like this. However, detailed and pragmatic preparedness should be adopted for the worst scenario.

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“…In addition to the works already considered about SIRD models, interested readers can find a wide variety of models for the study of the COVID-19 pandemic in the scientific literature published in the last months: using Bayesian and stochastic techniques [20][21][22], including mobility [23], confinement and quarantine [15,24], fractional models [25], and logistic models [26], among others.…”

Section: Introductionmentioning

confidence: 99%

A Modified SIRD Model to Study the Evolution of the COVID-19 Pandemic in Spain

Martínez

2021

Symmetry

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In this paper, we use an SIRD model to analyze the evolution of the COVID-19 pandemic in Spain, caused by a new virus called SARS-CoV-2 from the coronavirus family. This model is governed by a nonlinear system of differential equations that allows us to detect trends in the pandemic and make reliable predictions of the evolution of the infection in the short term. This work shows this evolution of the infection in various changing stages throughout the period of maximum alert in Spain. It also shows a quick adaptation of the parameters that define the disease in several stages. In addition, the model confirms the effectiveness of quarantine to avoid the exponential expansion of the pandemic and reduce the number of deaths. The analysis shows good short-term predictions using the SIRD model, which are useful to influence the evolution of the epidemic and thus carry out actions that help reduce its harmful effects.

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A Spatial-Temporal Model for the Evolution of the COVID-19 Pandemic in Spain Including Mobility

Cited by 36 publications

References 29 publications

A Spatial SEIR Model for COVID-19 in South Africa

A Spatial SEIR Model for COVID-19 in South Africa

SARS-CoV-2 and Rohingya Refugee Camp, Bangladesh: Uncertainty and How the Government Took Over the Situation

A Modified SIRD Model to Study the Evolution of the COVID-19 Pandemic in Spain

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