Among the exploratory spatial data analysis tools, there are indicators of spatial association, which measure the degree of spatial dependence of analysed data and can be applied to quantitative data. Another procedure available is geostatistics, which is based on the variogram, describing quantitatively and qualitatively the spatial structure of a variable. The aim of this paper is to use the concept of the variogram to develop a global indicator of spatial association (Global Spatial Indicator Based on Variogram-G-SIVAR). The G-SIVAR indicator has a satisfactory performance for spatial association, with sensibility for anisotropy cases. Because the indicator is based on geostatistics, it is appropriate for quantitative and qualitative data. The developed indicator is derived from theoretical global variogram, providing more details of the spatial structure of the data. The G-SIVAR indicator is based on spatial dissimilarity, while traditional indexes, such as Moran's I, are based on spatial similarity.
Este texto visa contribuir com o debate atual, valendo-se do seguinte questionamento: qual o impacto inicial da pandemia da covid-19 sobre a mortalidade de trabalhadores e a estrutura ocupacional brasileira? Para se aproximar de possíveis respostas, a pesquisa foi fundamentada a partir de um método de relativização de impactos, isto é, levando-se em consideração o estoque de ocupações e as tendências de mortalidade pré-pandemia, não se prendendo, portanto, somente a números absolutos. Buscou-se, com isso, verificar hipóteses relacionadas à incidência da covid-19 sobre a população ocupada, sem desconsiderar a heterogeneidade estrutural que caracteriza o mercado de trabalho brasileiro e as alterações na própria dinâmica setorial da economia provocada pelas medidas de contenção sanitária.
The COVID-19 pandemic has brought about considerable changes to human mobility. Although circulation restrictions are being lifted worldwide following the mitigation of the crisis, the understanding of its long-term effects is still limited. This paper addresses the situation of business meeting trips made by public officials in Brazil by gauging the level shift in the number of trips, the pace of recovery in the aftermath and whether there is any perspective of returning to a pre-pandemic baseline in the near future. To answer these questions, more than 420,000 trips comprising 5 years of operation of the “TaxiGov” ridesourcing system were evaluated in the framework of a dynamic regression model based on an Interrupted Time Series analysis with Autoregressive Integrated Moving Average errors. We found that the baseline level of meeting trips plummeted more than 80% with the onset of the COVID-19 pandemic, an unprecedented effect that was not matched by any major external shock in recent human history. Based on a counterfactual scenario, more than 138,000 expected trips did not occur considering only the first year of the pandemic (April 2020 to March 2021), which is roughly three times as much as the actual number of trips in the same period. Furthermore, based on the time series’ characteristics, a forecast for the following year indicates that the number of business trips will be still behind the baseline figures of 2018 and 2019. We provide solid evidence that the COVID-19 might have produced longstanding (and perhaps irreversible) effects in business meeting trips in the Brazilian public sector. Important policies implemented throughout this period, such as the regulation of teleworking in the public sector, and the incorporation of new working habits after an extended period of adaptation are probably the main reasons behind these findings. Finally, we emphasize that the reduced environmental impacts ensuing from this decreased mobility could be further expanded by substituting car trips with microbus/van lines serving the main origin-destination trip pairs or by adding ridesharing/carpooling options within the existing ride sourcing system.
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