One of the main challenges in the assessment of socioeconomic impacts is data availability. Although there is a myriad of statistics from different sources for varying locations and time frames, they are never available from the same source, for each location, in every period of time. Our approach to discover and improve the understanding of the socioeconomic impacts is to develop and deploy a measure that is available on a daily basis, from local to global, using only open source data and that is flexible enough to capture different aspects from COVID-19 pandemics in a timely manner.
The theoretical support of our project comes from the economic concept of social welfare, which represents and measures individual and social preferences regarding to alternative social states (Deaton & Muellbauer, 2009, pp. 214-239). Social welfare can be measured by the average real (equivalent) per capita total expenditure (the bigger the better). But the inequality in its distribution reduces the social welfare to a level that is lower than its maximum (the lower the better).
Elvidge et al. (2012) analyzed the relation between nocturnal lighting and social development, proposing an index for the co-distribution of nocturnal light and people to evaluate differences in development within countries. The shortcoming is that, in order to update the index, the spatial distribution of people has to be known. To overcome this limitation, we propose the use of the spatial distribution of nocturnal light solely, instead.
Social distancing, either voluntary or compulsory, has been one of the most controversial measures adopted in the global effort to restrain coronavirus dissemination. While experts indicate that as the most effective way to counter the pandemics, the socioeconomic externalities of such initiatives raised concerns about the most vulnerable people. Many lost their jobs or had their job contract suspended. Many weren’t allowed to work anymore, since they performed activities not classified as essential. Throughout the world, legislators, companies, NGOs and volunteers articulated countless actions towards a compensation. In Brazil, for example, besides an emergency financial aid, low-income population was also granted a waiver on water and electricity bills.
In order to offer a way to monitor the socioeconomic impacts of the pandemics, we integrated the concept of social welfare, a measurement of distribution inequality and data from NASA's Black Marble (Román et al., 2018). Using QGIS and Python, we calculated the average light radiance for various pairs of consecutive days for different locations and, then, calculated the Gini coefficient for the spatial distribution of the nocturnal light.
For the sake of comparison, we applied the metrics for two consecutive days, in three different time windows with the same lunar phase. The reference date is the beginning of quarantine in the selected regions: Sao Paulo - Rio de Janeiro (https://images.spaceappschallenge.org/stream-images/HPGckz-T29OVfw_SAXUUpKre8Ig=/7171/width-800/) and Para (https://images.spaceappschallenge.org/stream-images/x-78KDdytsujQDR5Mn2WNb_ELsI=/7180/width-800/).
The metric is sensitive to differences within and between regions, but inference is compromised by the presence of clouds, fires and other specifities of satellite images that are out of the scope of this project. The use of NASA's Black Marble HD image would not only enhance the quality of the images, but would also provide scientifically valid results. As a next step, Silver Lining team is very curious about deploying a system with the collaboration of AWS and Tableau, making the results available for legislators and researchers worldwide.
Deaton, A., Muellbauer, J. (2009). Economics and consumer behavior. New York: Cambridge University Press, 450 p.
Elvidge, C.D., Baugh, K.E., Anderson, S.J., Sutton, P.C., Ghosh, T. (2012). The Night Light Development Index (NLDI): a spatially explicit measure of human development from satellite data. Soc. Geogr., 7, 23–35. doi:10.5194/sg-7-23-2012
Román, M.O., Wang, Z., Sun, Q., Kalb, V., Miller, S.D., Molthan, A., Schultz, L., Bell, J., Stokes, E.C., Pandey, B. and Seto, K.C., et al. (2018). NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment 210, 113-143. doi:10.1016/j.rse.2018.03.017.