Later this week, the International Science Council will join the UN Sustainable Development Solutions Network’s Thematic Research Network on Data and Statistics (SDSN TReNDS), together with a panel of experts, for a webinar on the use of gridded population data in a variety of applications, including infectious disease and disaster response; survey planning; sea-level rise; water availability, and more. The webinar follows the recent publication of the TReNDS report, Leaving No One Off The Map: A Guide For Gridded Population Data For Sustainable Development. To find out more, we caught up with report co-author Hayden Dahmm.
Hayden Dahmm
SDSN TReNDS Analyst
Why is the issue of gridded population data so important right now? What does the report aim to do?
With the Sustainable Development Goals and the multiple ongoing crises that we now face, understanding how populations are distributed is more important than ever. Being able to identify where vulnerable communities are based is critical to providing services such as identifying potential disease hotspots, and gridded population data is an important tool in trying to approach these issues.
At the same time, each of the gridded population data products now available employ different assumptions and different underlying data, which help to enrich our overall understanding, but these are differences that need to be considered when selecting between the available data sets. An understanding of these products is essential to their effective and informed use, and so that’s what we aim to provide in this report: to give not only an introduction to the topic of gridded population data, but also to help potential users navigate these differences between the available data sets.
How can gridded population data be used in crisis situations and emergencies?
In the report, we highlight how the UN World Food Programme (WFP) has employed gridded population data as part of its routine for responding to natural disasters. If an earthquake strikes, or if there is a tropical storm approaching, they’re able to apply a real-time estimation of the impact zone for these disasters and overlay that with population data to then automatically estimate how many people are impacted and where they are generally located. This enables the WFP to quickly determine the volume of resources that are required and where they need to be deployed. They can then provide this information to their other collaborators in the humanitarian sector, and it allows them to mobilize rapidly rather than having to wait to determine the potential scope of the crisis. They can immediately get at least some sense of what the impact might be. Once they’re on the ground, they can improve these estimates with additional sources of data, but having the gridded population data available in a standard format that can be combined with other forms of information is necessary to enabling this type of response.
Understanding how populations are distributed is also significant when responding to disease outbreaks. It has been suggested that one of the critical issues encountered during the Ebola crisis from 2013 to 2016 was a lack of detailed data about where communities were located in West Africa, which made it challenging to then perform testing and to distribute medical resources appropriately. As part of the COVID response, gridded population data has been used by researchers to estimate the potential spread, or calculate the impact of various containment measures. The Center for International Earth Science Information Network (CIESEN) at Columbia University, which produces the Gridded Population of the World (GPW) collection, have created an online viewer of gridded population data from a number of different available products, in combination with data about COVID cases, which makes it easier to evaluate potential outbreaks. You can use their platform to immediately calculate different incidences in specific geographic areas of your own selection.
You’ve mentioned that this kind of gridded population data is being used by NGOs and researchers. Is it also being used by policy-makers or other groups?
As an example, I know that USAID regularly uses gridded population data, and specifically LandScan, which is produced by the US Federal Government. They rely on this data set when responding to disaster scenarios, including earthquakes and hurricanes, in a similar way to the UN World Food Programme.
Part of our research involved collaboration with the Global Partnership for Sustainable Development Data, which conducted a survey of different partner countries and looked at ways that they are using population data. The results of that survey suggest that there is still not widespread awareness of gridded population data within governments, or at least not in the set of developing countries that were surveyed. One of the aims of this report is to try to increase general awareness so that these products can be applied in a wider range of situations, both for emergency planning but also for policy planning and assessing future scenarios.
What have reactions to the report been like?
It’s been extremely encouraging. We’ve received direct feedback from a number of policy-makers, especially individuals in statistical departments from around the world, who’ve complimented the report for being a valuable and informative resource. SDSN TReNDS works to mobilize scientific and technical understanding around data and statistics to support sustainable development, and a key audience that we seek to address is policy-makers. Knowing that our report is reaching that audience and is hopefully having an impact is highly motivating.
In addition, there’s been some media coverage. We feel as though this report is helping to achieve broader awareness of the different data products that are currently available. All these data products are known within certain circles of academia, where they’re used for a whole variety of interesting studies, but this information is not necessarily widely known by the non-academic audience. The whole purpose of the report was to try to bring attention to these issues for that wider, non-academic, audience.
How is gridded population data currently being used to support implementation of the Sustainable Development Goals?
Gridded population data has been actively incorporated into the measurement for a few of the SDG indicators. One instance is the rural access index (indicator 9.1.1), which is reported by the World Bank. They are using gridded population data to estimate the proportion of rural residents who live within walking distance of a roadway. This was previously measured at the national level, and was only available intermittently. Now that a new methodology is available, we can begin to understand at a more local level how issues of roadway access impact various communities, and this could begin to direct the conversation around what the particular priorities should be.
Likewise, gridded population data has been used for assessing particulate matter exposure and for measuring the growth rate of cities, both of which fall under SDG11 on sustainable cities. This shows the potential of using innovative methods and gridded population data together to advance our understanding of key sustainability challenges. In our review of the SDG indicators, we identified at least 73 that require population data, and for many of these we do not have high-resolution estimates available. By combining gridded population data with satellite imagery and other types of data collected on the ground, we may have means available to obtain estimates at a more local level.
What’s required to get to a stage where gridded population data is being used to its full potential for the Sustainable Development Goals?
First of all, the sustainable development community needs to have a wider understanding of what gridded population data products are available, and an understanding of when they can be most appropriately applied. We’d likely also need to have strengthened procedures for estimating other types of indicators, for example the availability of fresh water or transportation. If these are things that could be measured in combination with population, we could achieve a localized measurement, but other methodologies need to be advanced as well.
You’re a presenter in the webinar about this report later this week. What do you hope to get out of the discussion, and why should someone reading this piece join in?
The webinar is going to involve discussion with the attendees, and so my hope is to engage with a wider audience in order to help increase awareness around the potential and various considerations that need to be taken into account for the use of gridded population data. In particular, I’m curious to hear about experiences that people may have already had with this data product and what sorts of successes or challenges they may have encountered. I would encourage people to join in and learn about the innovative applications and technical aspects of population data that they might find helpful in their own work.
Register to join the webinar.
Photo by Scott Webb on Unsplash