Background The state of Ceará (Northeast Brazil) has shown a high incidence of coronavirus disease (COVID-19), and most of the cases that were diagnosed during the epidemic originated from the capital Fortaleza. Monitoring the dynamics of the COVID-19 epidemic is of strategic importance and requires the use of sensitive tools for epidemiological surveillance, including consistent analyses that allow the recognition of areas with a greater propensity for increased severity throughout the cycle of the epidemic. This study aims to classify neighborhoods in the city of Fortaleza according to their propensity for a severe epidemic of COVID-19 in 2020. Methods We conducted an ecological study within the geographical area of the 119 neighborhoods located in the city of Fortaleza. To define the main transmission networks (infection chains), we assumed that the spatial diffusion of the COVID-19 epidemic was influenced by population mobility. To measure the propensity for a severe epidemic, we calculated the infectivity burden (ItyB), infection burden (IonB), and population epidemic vulnerability index (PEVI). The propensity score for a severe epidemic in the neighborhoods of the city of Fortaleza was estimated by combining the IonB and PEVI. Results The neighborhoods with the highest propensity for a severe COVID-19 epidemic were Aldeota, Cais do Porto, Centro, Edson Queiroz, Vicente Pinzon, Jose de Alencar, Presidente Kennedy, Papicu, Vila Velha, Antonio Bezerra, and Cambeba. Importantly, we found that the propensity for a COVID-19 epidemic was high in areas with differing socioeconomic profiles. These areas include a very poor neighborhood situated on the western border of the city (Vila Velha), neighborhoods characterized by a large number of subnormal agglomerates in the Cais do Porto region (Vicente Pinzon), and those located in the oldest central area of the city, where despite the wealth, low-income groups have remained (Aldeota and the adjacent Edson Queiroz). Conclusion Although measures against COVID-19 should be applied to the entire municipality of Fortaleza, the classification of neighborhoods generated through this study can help improve the specificity and efficiency of these measures.

Um dos principais desafios na modelagem microscópica de vias urbanas é a estimação dos valores dos parâmetros dos modelos comportamentais do condutor. O principal objetivo deste artigo é propor um método de calibração dos modelos comportamentais do VISSIM para modelagem do tráfego de vias arteriais urbanas, com foco na estimação da velocidade média do tráfego de automóveis e de ônibus. O método foi aplicado em dois corredores urbanos da cidade de Fortaleza, resultando em erros de calibração de 10% e 13% e de validação de 19% e 9%. O segundo objetivo deste artigo foi comparar a calibração apresentada, do tipo sequencial, na qual os parâmetros são calibrados separadamente, seguindo uma sequência pré-estabelecida, com a calibração simultânea, na qual todos os parâmetros são calibrados em conjunto com base na medida de desempenho do tráfego que se deseja estimar. A calibração sequencial resultou em melhores estimativas para os parâmetros comportamentais, pois ela diminui a chance de se obter combinações de valores irreais para os parâmetros.

Background: The state of Ceará (Northeast Brazil) has shown a high incidence of coronavirus disease (COVID-19), and most of the cases that were diagnosed during the epidemic originated from the capital Fortaleza. Monitoring the dynamics of the COVID-19 epidemic is of strategic importance and requires the use of sensitive tools for epidemiological surveillance, including consistent analyses that allow the recognition of areas with a greater propensity for increased severity throughout the cycle of the epidemic. This study aims to classify neighborhoods in the city of Fortaleza according to their propensity for a severe epidemic of COVID-19 in 2020. Methods: We conducted an ecological study within the geographical area of the 119 neighborhoods located in the city of Fortaleza. To define the main transmission networks (infection chains), we assumed that the spatial diffusion of the COVID-19 epidemic was influenced by population mobility. To measure the propensity for a severe epidemic, we calculated the infectivity burden (ItyB), infection burden (IonB), and population epidemic vulnerability index (PEVI). The propensity score for a severe epidemic in the neighborhoods of the city of Fortaleza was estimated by combining the IonB and PEVI. Results: The neighborhoods with the highest propensity for a severe COVID-19 epidemic were Aldeota, Cais do Porto, Centro, Edson Queiroz, Vicente Pinzon, Jose de Alencar, Presidente Kennedy, Papicu, Vila Velha, Antonio Bezerra, and Cambeba. Importantly, we found that the propensity for a COVID-19 epidemic was high in areas with differing socioeconomic profiles. These areas include a very poor neighborhood situated on the western border of the city (Vila Velha), neighborhoods characterized by a large number of subnormal agglomerates in the Cais do Porto region (Vicente Pinzon), and those located in the oldest central area of the city, where despite the wealth, low-income groups have remained (Aldeota and the adjacent Edson Queiroz).Conclusion: Although measures against COVID-19 should be applied to the entire municipality of Fortaleza, the classification of neighborhoods generated through this study can help improve the specificity and efficiency of these measures.

Background: The state of Ceará (Northeast Brazil) has shown a high incidence of coronavirus disease (COVID-19), and most of the cases that were diagnosed during the epidemic originated from the capital Fortaleza. Monitoring the dynamics of the COVID-19 epidemic is of strategic importance and requires the use of sensitive tools for epidemiological surveillance, including consistent analyses that allow the recognition of areas with a greater propensity for increased severity throughout the cycle of the epidemic. This study aims to classify neighborhoods in the city of Fortaleza according to their propensity for a severe epidemic of COVID-19 in 2020. Methods: We conducted an ecological study within the geographical area of the 119 neighborhoods located in the city of Fortaleza. To define the main transmission networks (infection chains), we assumed that the spatial diffusion of the COVID-19 epidemic was influenced by population mobility. To measure the propensity for a severe epidemic, we calculated the infectivity burden (ItyB), infection burden (IonB), and population epidemic vulnerability index (PEVI). The propensity score for a severe epidemic in the neighborhoods of the city of Fortaleza was estimated by combining the IonB and PEVI. Results: The neighborhoods with the highest propensity for a severe COVID-19 epidemic were Aldeota, Cais do Porto, Centro, Edson Queiroz, Vicente Pinzon, Jose de Alencar, Presidente Kennedy, Papicu, Vila Velha, Antonio Bezerra, and Cambeba. Importantly, we found that the propensity for a COVID-19 epidemic was high in areas with differing socioeconomic profiles. These areas include a very poor neighborhood situated on the western border of the city (Vila Velha), neighborhoods characterized by a large number of subnormal agglomerates in the Cais do Porto region (Vicente Pinzon), and those located in the oldest central area of the city, where despite the wealth, low-income groups have remained (Aldeota and the adjacent Edson Queiroz).Conclusion: Although measures against COVID-19 should be applied to the entire municipality of Fortaleza, the classification of neighborhoods generated through this study can help improve the specificity and efficiency of these measures.

Background: The state of Ceará (Northeast Brazil) has shown a high incidence of coronavirus disease (COVID-19), and most of the cases that were diagnosed during the epidemic originated from the capital Fortaleza. Monitoring the dynamics of the COVID-19 epidemic is of strategic importance and requires the use of sensitive tools for epidemiological surveillance, including consistent analyses that allow the recognition of areas with a greater propensity for increased severity throughout the cycle of the epidemic. This study aims to classify neighborhoods in the city of Fortaleza according to their propensity for a severe epidemic of COVID-19 in 2020. Methods: We conducted an ecological study within the geographical area of the 119 neighborhoods located in the city of Fortaleza. To define the main transmission networks (infection chains), we assumed that the spatial diffusion of the COVID-19 epidemic was influenced by population mobility. To measure the propensity for a severe epidemic, we calculated the infectivity burden (ItyB), infection burden (IonB), and population epidemic vulnerability index (PEVI). The propensity score for a severe epidemic in the neighborhoods of the city of Fortaleza was estimated by combining the IonB and PEVI. Results: The neighborhoods with the highest propensity for a severe COVID-19 epidemic were Aldeota, Cais do Porto, Centro, Edson Queiroz, Vicente Pinzon, Jose de Alencar, Presidente Kennedy, Papicu, Vila Velha, Antonio Bezerra, and Cambeba. Importantly, we found that the propensity for a COVID-19 epidemic was high in areas with differing socioeconomic profiles. These areas include a very poor neighborhood situated on the western border of the city (Vila Velha), neighborhoods characterized by a large number of subnormal agglomerates in the Cais do Porto region (Vicente Pinzon), and those located in the oldest central area of the city, where despite the wealth, low-income groups have remained (Aldeota and the adjacent Edson Queiroz).Conclusion: Although measures against COVID-19 should be applied to the entire municipality of Fortaleza, the classification of neighborhoods generated through this study can help improve the specificity and efficiency of these measures.