Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN)

In 2019, a pandemic of the so-called new coronavirus (SARS-COV-II) began, which causes the disease COVID-19. In a short time after the first case appeared, hundreds of countries began to register new cases every day. Mapping and analyzing the flow of people, regardless of the mode of transport, can help us to understand and prevent several phenomena that can affect our society in different ways. Graphs are complex networks made up of points and edges. The (geo)graphs are graphs with known spatial location and, in the case of our study, the edges represent the flow between them. The (geo)graphs proved to be a promising tool for such analyses. In the study region, municipalities that first registered their COVID-19 cases are also municipalities that have the highest mobility indices analyzed: degree, betweenness and weight of edges. © 2022 National Institute for Space Research, INPE. All rights reserved.

Operationalizing Resiliency among Childcare Providers during the COVID-19 Pandemic

Childcare, a critical infrastructure, played an important role to create community resiliency during the COVID-19 pandemic. By finding pathways to remain open, or rapidly return to operations, the adaptive capacity of childcare providers to offer care in the face of unprecedented challenges functioned to promote societal level mitigation of the COVID-19 pandemic impacts, to assist families in their personal financial recoveries, and to provide consistent, caring, and meaningful educational experiences for society's youngest members. This paper assesses the operational adaptations of childcare centers as a key resource and critical infrastructure during the COVID-19 pandemic in the Greater Rochester, NY metropolitan region. Our findings evaluate the policy, provider mitigation, and response actions documenting the challenges they faced and the solutions they innovated. Implications for this research extend to climate-induced disruptions, including fires, water shortages, electric grid cyberattacks, and other disruptions where extended stay-at-home orders or service critical interventions are implemented. © 2022 IEEE.

Geodesign Experience in Florianópolis Metropolitan Region: Practical Planning with Different Professional Backgrounds

The work shows an application of Geodesign for metropolitan region of Florianópolis, at Santa Catarina state, Brazil, with focus on reducing carbon emissions considering the future scenarios of 2035 and 2050. The research took place with students from the discipline of Multipurpose Land Registry and Territorial Planning related to doctoral course of the Post-Graduate Program in Territorial Planning and Social-environmental Development (Programa de Pós-Graduação em Planejamento Territorial e Desenvolvimento Socioambiental – PPGPLAN) from the State University of Santa Catarina - UDESC in the year 2021. The students had different training and performances, but all to a greater or lesser degree had experience in urban planning, with 25% knowing the methods and concepts of Geodesign. Due to the conditions of social distancing imposed by the COVID-19 pandemic, the lessons activities took place remotely. Four official weekly meetings and also daily communication were established to carry on the activities, which were performed by WhatsApp, email or even by extra on-line meeting. To assist decision-making on the GISColab Platform, a spreadsheet was created using Excel software that ensured the organization and systematization of proposals, as well as supporting the spatialization of policies and projects. Due to the students’ professional experience, the biggest challenge was shown in the proposition of ideas that corroborated with the initial goal, that was especially focused on territorial planning integrated in multifactorial parameters. In this sense, remote meetings fulfilled the role of initiating remote participatory discussion, sharing ideas and decisions for proposals adopted and approved in groups, but revealed the lack of specialized critical thinking, difficulties in developing territorial planning and defending ideas based on action and reaction that GISColab platform provides. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Predicting the COVID-19 in the Metropolitan Region (Chile) using a GCN-LSTM neural network

COVID-19 is considered one of the largest pandemics in recent times. Predicting the number of future COVID-19 cases is extremely important for governments in order to make decisions about mobility restrictions, and for hospitals to be able to manage medical supplies, as well as health staff. Most of the predictions of COVID-19 cases are based on mathematical-epidemiological models such as the SEIR and SIR models. In our work, we propose a model of neural networks GCN-LSTM (Graph Convolutional Network - Long Short Term Memory) to predict the spatio-temporal rate incidence of COVID-19 in the Metropolitana Region, Chile. While the GCN network incorporates the spatial correlation in the nearby municipalities, the LSTM network considers the temporal correlation for the prediction over time. To interpolate the missing daily data for the network input, the use of the GAM (Generalized Additive Model) model is proposed. The results show better predictions for some municipalities with higher habitat density. © 2021 IEEE.

Childcare in COVID-19: Assessing resilience of service critical infrastructures

Childcare, a service critical infrastructure, was under stress during the COVID-19 pandemic. The pandemic highlighted the need for robust capacity in childcare to support the function of workers within healthcare and emergency response, both service-based infrastructures;however the national response locking down businesses pushed many children back into the home, reducing demand for childcare and threatening childcare facilities' fiscal viability to remain in business. For many providers, the pandemic and its economic fallout are far from over, meaning the ultimate resiliency of childcare provision is yet to be determined. This paper is part of a larger study that examines the experiences of such childcare providers at the local level in the metropolitan region of Rochester, NY USA. The study provides a method to assess their critical operational capacities, and the longer term findings will assess the effectiveness of their adaptive decision-making to determine whether a specific combination of focused planning, COVID-19 case management strategies, economic decisions, and enrollment capacity resumption promoted recovery and resiliency to sustain the robust level of childcare service provision that communities need in times of crisis and beyond. Implications for this research extend to disruption of all kinds that require human capital, especially climate-induced disruptions, including fires, water shortages, etc. and technological disruptions such as electric grid instability, cyberattacks, and such. © 2021 IEEE.

Effects of the COVID-19 Pandemic on the Air Quality of the Metropolitan Region of São Paulo: Analysis Based on Satellite Data, Monitoring Stations and Records of Annual Average Daily Traffic Volumes on the Main Access Roads to the City

This paper presents an analysis of the effects of the COVID-19 pandemic on the air quality of the Metropolitan Region of São Paulo (MRSP). The effects of social distancing are still recent in the society;however, it was possible to observe patterns of environmental changes in places that had adhered transportation measures to combat the spread of the coronavirus. Thus, from the analysis of the traffic volumes made on some of the main access highways to the MRSP, as well as the monitoring of the levels of fine particulate matter (PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2), directly linked to atmospheric emissions from motor vehicles–which make up about 95% of air polluting agents in the region in different locations–we showed relationships between the improvement in air quality and the decrease in vehicles that access the MRSP. To improve the data analysis, therefore, the isolation index parameter was evaluated to provide daily information on the percentage of citizens in each municipality of the state that was effectively practicing social distancing. The intersection of these groups of data determined that the COVID-19 pandemic reduced the volume of vehicles on the highways by up to 50% of what it was in 2019, with the subsequent recovery of the traffic volume, even surpassing the values from the baseline year. Thus, the isolation index showed a decline of up to 20% between its implementation in March 2020 and December 2020. These data and the way they varied during 2020 allowed to observe an improvement of up to 50% in analyzed periods of the pollutants PM2.5, CO and NO2 in the MRSP. The main contribution of this study, alongside the synergistic use of data from different sources, was to perform traffic flow analysis separately for light and heavy duty vehicles (LDVs and HDVs). The relationships between traffic volume patterns and COVID-19 pollution were analyzed based on time series. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.