How the POPGRID Data Community is Responding to COVID-19
As communities around the world grapple with the devastating effects of COVID-19, the importance of timely, disaggregated, and accurate data has never been clearer. It is vital that we understand where populations are located, the available infrastructure, and their access to critical services to ensure that everyone can understand their risk and take appropriate action. From new platforms, analysis, and available datasets, read more on how participants in the POPGRID Data Collaborative are helping to fight this pandemic.
CIESIN (Center for International Earth Science Information Network)
In May 2020, CIESIN released the Global COVID-19 Viewer through the NASA Socioeconomic Data and Applications Center (SEDAC). The platform provides COVID-19 case data at country and subnational levels (where available) along with data on population density and age and sex distribution. Users can draw circles and polygons on the map to obtain data on the age and sex distribution of the population in those areas, which appear to relate to the risks of mortality (e.g. populations over age 65). Population density is also linked to transmission risk. The age and sex data are seamlessly available for any geography, including across national borders. The population data are from SEDAC's Gridded Population of the World (GPW) Basic Demographic Characteristics, v4.11, and the COVID-19 data are from the Johns Hopkins University & Medicine (JHU) Coronavirus Resource Center.
CIESIN, through the BMGF GRID3 project, is supporting countries in developing improved demographic data in Africa for COVID-19 response, as well as improved mapping of health facilities (with support from the global vaccine alliance or GAVI).
Users can access the Viewer here: https://sedac.ciesin.columbia.edu/mapping/popest/covid-19/. An improved version with additional functions is currently in testing.
CUNY-CIDR (City University of New York Institute for Demographic Research)
CUNY-CIDR has reviewed and responded to the New York Department of Health’s epidemiological models and worked with them to understand how to incorporate population density. The team has also compared data for Italy, Wuhan, and New York City, to demonstrate the density distributions that could be used in modeling.
Esri has analyzed daily data from the JHU COVID-19 map and is working on integrating population data into the JHU map. They are also analyzing rates of testing, affected populations, and human movement, as well as providing modeling assistance to research groups. Additionally, the team has conducted trend analysis on the rates of new cases in the U.S. and stratified countries into five different levels.
Users can access a summary of analyses here: https://storymaps.arcgis.com/stories/a5190c7fd6db422f9a1bab6dac024b99
Facebook is working on COVID-19 disaster mapping and disease prevention maps that analyze the impacts of stay-at-home orders and other prevention and response measures. The team is collaborating with humanitarian and other partners on technical concepts, including efforts around privacy and contact tracing. In addition, to support response efforts, Facebook is using new 2020 Maxar data to update their high-resolution population data sets.
ImageCat is in conversation with CIESIN and Planet to use high resolution data and SARS data to look at economic impacts and recovery.
JRC (European Commission Joint Research Center)
The JRC is advising the Commission’s policy Director Generals on using data and models for monitoring and analysis of the COVID-19 outbreak. Two web portals have been developed to share analyses and news. The Global Human Settlement Layer (GHSL) team is providing data used in model development, including population distribution (GHS-POP), settlement classification (GHS-SMOD) and tourism distribution. Demographics, urban/rural characteristics, public transport, and other issues are also being considered in both epidemiological modelling and socioeconomic modelling to analyze policy scenarios and socioeconomic impacts.
Users can access the portals here:
https://drmkc.jrc.ec.europa.eu/overview/COVID-19#documents/972/list
https://covid-statistics.jrc.ec.europa.eu/
ORNL (Oak Ridge National Laboratory)
ORNL’s LandScan USA product is now permanently available through Homeland Infrastructure Foundation-Level Data (HIFLD) Open Data on the GeoPlatform. This will allow for the broadest access in support of the COVID-19 response and beyond. LandScan USA is a high resolution and spatiotemporal population distribution model that captures diurnal variation of the U.S. population by producing night-time (residential) and daytime population data at 3 arc-second (approximately 90m) resolution and can be used for rapid assessment, estimation, and visualization of populations at risk of Covid-19. It can also be easily integrated into risk and impact assessment models.
Users can access LandScan data here: https://geoplatform.maps.arcgis.com/home/item.html?id=e431a6410145450aa56606568345765b
In response to the current health crisis, TReNDS is deepening their work to address emerging issues, including data governance and public-private data partnerships, encouraging epistemic communities (like the POPGRID Data Collaborative) to establish standards and share best practices, reorienting their research in response to country needs, and offering practical advice and advocacy, including the value of timely population data for critical decision-making. Additionally, TReNDS’ new report on behalf of POPGRID highlights how gridded population data can be used in a variety of applications, including infectious disease and COVID-19, disaster response, and more.
Users can read the new report here: https://www.sdsntrends.org/leaving-no-one-off-the-map
WorldPop has contributed to epidemiological modeling in China and examining disease-oriented types of issues in the country in response to the pandemic. They plan to expand this model when more data are available from other countries. Additionally, the team is working with colleagues at Facebook to produce European-based models with call data records to support governments in their effort to respond to COVID-19, particularly African governments involved in the Georeferenced Infrastructure and Demographic Data for Development (GRID3) project. Also, to help better understand the link between demographic characteristics and fatality or hospitalization rates, WorldPop developed a tool to make their disaggregated population data (by age and sex) for subnational census/administrative units more accessible through the WorldPop Demographics Platform.
Users can access the Platform here: https://www.portal.worldpop.org/demographics/
For more information and to collaborate, email ciesin.info@ciesin.columbia.edu.
