Social interaction layers in complex networks for the dynamical epidemic modeling of COVID-19 in Brazil

Scabini, Leonardo F. S.; Ribas, Lucas Correia; Neiva, Mariane Barros; Altamir, G. B.; Farfán, Alex J. F.; Bruno, Odemir Martinez

doi:10.1016/j.physa.2020.125498

Cited by 56 publications

(46 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The current COVID-19 pandemic has attracted the interest of the academic community, giving rise to a growing number of studies on this topic [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] . One of the topics that has raised many discussions is the impact of density on this pandemic.…”

Section: Discussionmentioning

confidence: 99%

Population density impact on COVID-19 mortality rate: A multifractal analysis using French data

Pascoal

Rocha

2022

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

The current COVID-19 pandemic caught everyone off guard and is an excellent case study to investigate the real impact of population density on emerging highly contagious infectious diseases. The relationship between the threat of COVID-19 and population density has been widely debated not only in scientific articles, but also in magazines and reports around the world. It appeared both in the columns of experts and in the speeches of politicians, yet without reaching any consensus. In this study, using COVID-19 data from France, we try to shed light on this debate. An alternative density measure, weighted by population, is used. This novel density measure clearly outperforms the commonly used density in terms of relationship with COVID-19 deaths and proved to be competitive with some of the best known predictors, including population. A multifractal analysis, characterizing different space distributions of population in France, is used to further understand the relation between density and COVID-19 mortality rate.

show abstract

Section: Discussionmentioning

confidence: 99%

Population density impact on COVID-19 mortality rate: A multifractal analysis using French data

Pascoal

Rocha

2022

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

show abstract

“…In general, multi-layer (also known as "multiplex") networks [18] are widely used to study graph diffusion problems [28] and define generalized versions of Pagerank [19]. Recently, multi-layer modelling has also been applied to COVID-19 spread simulation [57] where each layer refers to a potential contamination community, such as school, workplace or transport. Appropriate use of the information on these layers can optimise vaccination strategies as mentioned in [8], by prioritising the populations with high risk and high transmissibility.…”

Section: Multi-layer Modelling Of Scale-free Networkmentioning

confidence: 99%

Real-time Updating of Dynamic Social Networks for COVID-19 Vaccination Strategies

Cheng

Arcucci

Pain

et al. 2021

Preprint

View full text Add to dashboard Cite

Vaccination strategy is crucial in fighting against the COVID-19 pandemic. Since the supply is limited, contact network-based interventions can be most powerful to set an optimal strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamical systems where the contact networks are highly time-variant. Furthermore, numerous mutations of SARS-CoV-2 impact considerably the current infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from the assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamical networks collected in a high school, following by sequential multi-layer networks, generated relying on the Barabasi-Albert model emulating the department of Computing at Imperial College London in the UK as an example.

show abstract

“…As per [22], in the southeast region, 21 beds per 1,00,000 people are available and the northern region accounts much lesser to 9 beds. In [23], the authors studied the modeling of COVID-19 using the complex network approach and presented that the demand for ICU beds might increase 3 times the country's capacity if the growth of the epidemic keeps increasing in steep manner. In India, though the number of deaths has been less compared to those in the USA and Brazil, it did face shortage of bed and ventilators supply.…”

Section: Introductionmentioning

confidence: 99%

Modeling of COVID-19 with limited public health resources: a comparative study of three most affected countries

2021

View full text Add to dashboard Cite

COVID-19 has become a deadly pandemic in the recent times claiming millions of lives worldwide in a grievous manner. Most of the countries in the world have limited number of medical resources (hospitals, beds, ventilators, etc.), and in the case of large outbreak, it becomes very difficult to provide treatment to every infected individual. In this study, we propound a mathematical model where we classify the infected into two subcategories—asymptomatic and symptomatic. This model further accounts for the effect of limited medical resource for infected people and using face masks in combating the pandemic. Focusing on these aspects, we analyze the model and exploit the available data for assessing the pattern in three most affected countries, namely USA, India and Brazil. The developed model is calibrated to fit data for these three countries and estimate the transmission rate of symptomatic, asymptomatic individuals. The rate at which the individuals who are quarantined recover is estimated as well. Along with these estimations, a comparative study based on the basic reproduction number estimated for the three countries is presented. Standard methods of sensitivity analysis are performed to analyze the ways in which basic reproduction number is impacted upon due to changes in different parameters of the model. Further, we obtain disease-free equilibrium and endemic equilibrium of the model. It is observed that backward bifurcation occurs if the capacity of treatment is small and bistable equilibria are shown that makes the system more sensitive to the initial conditions. Sufficient conditions for the local asymptomatic stability of the endemic equilibrium and disease-free equilibrium of the system are obtained. The results of this study imply that to curb the severity of the increasing cases of the disease in these countries, effective strategies to control disease spread should be implemented so that the basic reproduction number can be decreased below the threshold value which is certainly less than unity. The use of protective masks in public is shown to be an important preventive measure to lower disease transmission rate. Also, the quantity of medical resources should increase so that every infected person can get better treatment.

show abstract

Social interaction layers in complex networks for the dynamical epidemic modeling of COVID-19 in Brazil

Cited by 56 publications

References 27 publications

Population density impact on COVID-19 mortality rate: A multifractal analysis using French data

Population density impact on COVID-19 mortality rate: A multifractal analysis using French data

Real-time Updating of Dynamic Social Networks for COVID-19 Vaccination Strategies

Modeling of COVID-19 with limited public health resources: a comparative study of three most affected countries

Contact Info

Product

Resources

About