Relevance of transportation to correlations among criticality, physical means of propagation, and distribution of dengue fever cases in the state of Bahia

Saba, Hugo; Moret, Marcelo A.; Barreto, Florisneide Rodrigues; Araújo, Márcio Luís Valença; Jorge, Eduardo Manuel de Freitas; Filho, Aloísio S. Nascimento; Miranda, José García Vivas

doi:10.1016/j.scitotenv.2017.09.047

Cited by 14 publications

(23 citation statements)

References 19 publications

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“…The information regarding the contagion dynamics between municipalities presented in this work is the result of a hybrid model composed of an epidemiological mathematical model of SIR type, which estimates the disease dynamics for each municipality, and of a flow network among municipalities that estimates the spread of cases among them. Previous studies have shown the importance of the transport flow network in the spread of viruses like dengue [14] .…”

Section: Methodsmentioning

confidence: 99%

Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow

Miranda

Silva

Bertolino

et al. 2021

Physica D: Nonlinear Phenomena

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The new Covid-19 pandemic has left traces of suffering and devastation to individuals of almost all countries worldwide and severe impact on the global economy. Understanding the clinical characteristics, interactions with the environment, and the variables that favor or hinder its dissemination help the public authorities in the fight and prevention, leading for a rapid response in society. Using models to estimate contamination scenarios in real time plays an important role. Population compartments models based on ordinary differential equations (ODE) for a given region assume two homogeneous premises, the contact mechanisms and diffusion rates, disregarding heterogeneous factors as different contact rates for each municipality and the flow of contaminated people among them. This work considers a hybrid model for covid-19, based on local SIR models and the population flow network among municipalities, responsible for a complex lag dynamic in their contagion curves. Based on actual infection data, local contact rates ( ) are evaluated. The epidemic evolution at each municipality depends on the local SIR parameters and on the inter-municipality transport flow. When heterogeneity of values and flow network are included, forecasts differ from those of the homogeneous ODE model. This effect is more relevant when more municipalities are considered, hinting that the latter overestimates new cases. In addition, mitigation scenarios are assessed to evaluate the effect of earlier interventions reducing the inter-municipality flux. Restricting the flow between municipalities in the initial stage of the epidemic is fundamental for flattening the contamination curve, highlighting advantages of a contamination lag between the capital curve and those of other municipalities in the territories.

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Section: Methodsmentioning

confidence: 99%

Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow

Miranda

Silva

Bertolino

et al. 2021

Physica D: Nonlinear Phenomena

Self Cite

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“…The inter-cities mobility network serves as a proxy for the transmission network, vital for understanding outbreaks, especially in Brazil, a continental-dimension country 3,4,5,6,7 . The complex network approach 8 emerges as a natural mechanism to handle mobility data computationally, taking areas as nodes (fixed) and movements between origins and destinations as connections (flows).…”

Section: Introductionmentioning

confidence: 99%

The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil

et al. 2020

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The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. We adopt the data from the Brazilian Ministry of Health and the terrestrial flow of people between cities from the Brazilian Institute of Geography and Statistics database in two scales: cities from Brazil, without the North region, and from the São Paulo State. Grounded on the complex networks approach, and considering that the mobility network serves as a proxy for the SARS-CoV-2 spreading, the nodes and edges represent cities and flows, respectively. Network centrality measures such as strength and degree are ranked and compared to the list of cities, ordered according to the day that they confirmed the first case of COVID-19. The strength measure captures the cities with a higher vulnerability of receiving new cases. Besides, it follows the interiorization process of SARS-CoV-2 in the São Paulo State when the network flows are above specific thresholds. Some countryside cities such as Feira de Santana (Bahia State), Ribeirão Preto (São Paulo State), and Caruaru (Pernambuco State) have strength comparable to states’ capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics.

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“…The inter-cities mobility network serves as a proxy for the transmission network, vital for understanding outbreaks, especially in Brazil, a continental-dimension country (5,6,7,8,9) . The complex network approach (10) emerges as a natural mechanism to handle mobility data computationally, taking areas as nodes (fixed) and movements between origins and destinations as connections (flows).…”

Section: Introductionmentioning

confidence: 99%

The correspondence between the structure of the terrestrial mobility network and the emergence of COVID-19 in Brazil

Freitas

Feitosa

Sepetauskas

et al. 2020

Preprint

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BACKGROUND: the inter-cities mobility network serves as a proxy for the SARS-CoV-2 spreading network in a country. OBJECTIVE: to investigate the correspondences between the structure of the mobility network and the emergence of COVID-19 cases in Brazilian cities. METHODS: we adopt the data from the Brazilian Health Ministry and the terrestrial flow of people between cities from the IBGE database in two scales: Brazilian cities without the North region and cities from the Sao Paulo state. Grounded on the complex networks approach, cities are represented as nodes and the flows as edges. Network centrality measures such as strength and degree are ranked and compared to the list of Brazilian cities, ordered according to the day that they confirmed the first case of COVID-19. FINDINGS: The strength presents the best correspondences and the interiorization process of SARS-CoV-2 is captured in the Sao Paulo state when different thresholds are applied to the network flows. MAIN CONCLUSIONS: the strength captures the cities with a higher vulnerability of receiving new cases of COVID-19. Some countryside cities such as Feira de Santana (Bahia state), Ribeirao Preto (Sao Paulo state), and Caruaru (Pernambuco state) have strength comparable to states' capitals, making them potential super spreaders.

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Relevance of transportation to correlations among criticality, physical means of propagation, and distribution of dengue fever cases in the state of Bahia

Cited by 14 publications

References 19 publications

Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow

Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow

The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil

The correspondence between the structure of the terrestrial mobility network and the emergence of COVID-19 in Brazil

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