Vulnerability and COVID-19 infection rates: A changing relationship during the first year of the pandemic.

In the first year of the COVID-19 pandemic, Spain was one of the worst-hit countries, although not all areas and social groups were affected equally. This study focuses on Malaga, a cosmopolitan tourist destination located on the southern Mediterranean coast that has the sixth largest population in Spain. Specifically, it examines the relationship between multidimensional vulnerability and COVID-19 infection rates across the city's census tracts for the period February 2020 to February 2021. The analysis uses high frequency (daily) data on the accumulated incidence of the disease at 14 days and shows that COVID-19 did not spread symmetrically across the census tracts of Malaga but had a greater impact on the most vulnerable neighbourhoods. However, the pattern of this relationship was not uniform in the period examined, with specific contextual factors driving the higher infection rates across time. Our findings show that pandemic containment regulations cannot overlook vulnerability considerations and universal restrictions to reduce the spread of disease should be supplemented by targeted regulations for specific areas.

The daily urban dynamic indicator: Gauging the urban dynamic in Porto during the COVID-19 pandemic.

The SARS-CoV-2 outbreak motivated the development of a myriad of weekly and daily indicators that track economic activity to estimate and predict the consequences of the pandemic. With some exceptions, these indicators are calculated at the country level and are mainly focused on tracking economic factors, disregarding local urban phenomena. To address this, we present the Urban Dynamic Indicator (UDI), a novel composite indicator designed to measure a city's daily urban dynamic. The UDI is applied to Porto municipality, in Portugal, and it corresponds to a latent factor obtained through a factor analysis over seasonal adjusted daily data regarding traffic intensity, public transportation usage, internet usage in public buses, NO2 emissions and noise level. The UDI's values show that, by the end of 2020, despite the approach of economic activity to its pre-pandemic values, as suggested by the Portuguese Daily Economic Indicator (DEI), Porto urban dynamic did not recover completely. The UDI enriches the information available for Porto city planners and policymakers to respond to crisis situations and to gauge the application of local policies that contribute to urban sustainable planning. Furthermore, the methodology defined in this work can be followed for the development of daily urban dynamic indicators elsewhere.

Quantifying Spatiotemporal Changes in Human Activities Induced by COVID-19 Pandemic Using Daily Nighttime Light Data.

The COVID-19 pandemic caused drastic changes in human activities and nighttime light (NTL) at various scales, providing a unique opportunity for exploring the pattern of the extreme responses of human community. This study used daily NTL data to examine the spatial variations and temporal dynamics of human activities under the influence of COVID-19, taking Chinese mainland as the study area. The results suggest that the change in the intensity of NTL is not correlated to the number of confirmed cases, but reflects the changes in human activities and the intensity of epidemic prevention and control measures within a region. During the outbreak period, the major provincial capitals and urban agglomerations were affected by COVID-19 more than smaller cities. During the recovery, different regions showed different recovery processes. The cities in West and Northeast China recovered steadily while the recovery in coastal cities showed relatively greater fluctuations due to an increase in imported cases. Wuhan, the most seriously affected city in China, did not recover until the end of March. Nevertheless, as of 31 March, the overall NTL across China had recovered to an 89.5% level of the same period in the previous year. The high consistency between the big data of travel intensity and NTL further proved the validity of the results of this study. These findings imply that daily NTL data are effective for rapidly monitoring the dynamic changes in human activities, and can help evaluate the effects of control measures on human activities during major public health events.