By Vinod Kumar, CEO, Vodafone Business
It has been over a year now since Wuhan went into the world’s first coronavirus lockdown.
Since last January, over 200 countries have reported cases and many have been using physical distancing policies to contain the spread. While this has proven effective, we’re yet to fully understand the consequences of these prolonged lockdowns and the impact that physical distancing measures have had on society.
What we do know is that the number of children who are hungry, isolated, abused and living in poverty has increased1. An extra 142 million children are expected to be living in monetary-poor households due to the pandemic – a setback that threatens to damage an entire generation.
This is where UNICEF is striving to make a difference and they are using data insights to help them do it.
The role of data
At the start of the pandemic, we realised quite quickly that Vodafone and UNICEF could work together to support governments and local authorities to understand the suitability and sustainability of lockdown restrictions, particularly when looking at impoverished areas.
Partnering with Vodafone Foundation, UNICEF was able to access funding to develop cutting edge tools to support their understanding and response to the pandemic. While Vodafone’s international Big Data and AI team has, within our “Big Data for Social Good” initiative, used anonymised and aggregated data collected from our networks to provide the organisation with mobility insights.
Insights that show the population’s anonymised and aggregated movements via maps, both at national and regional levels, for several markets in Europe and South Africa.
This has been critical in allowing UNICEF to compare different indicators across geographies, showing the direct impact of physical distancing, from how socio-economic inequalities can impact daily travel patterns to the effectiveness of policies.
For example, the daily insights we provide about changes in travel distance and changes in time spent at home have helped us identify that people living in poorer areas are less likely to reduce their movements.
Aggregated data from Portugal has shown that mobility variations also exist in-country between those living in poorer parts of the country to those living in wealthier locations.
This may be because they aren’t able to carry out their jobs remotely. For this same reason, they may find it more difficult to stay home and look after their children while schools are closed.
Receiving real-time, large analytical capacity for an unexpected event like COVID-19 would normally take time and be expensive to gather.
Using our existing mobile phone customers, we already had access to a large volume of data across the globe and permission from users to share location information in an aggregated and anonymised way.
Having access to this sought-after data, UNICEF can focus on actioning these insights on the ground instead. Providing up-to-date analysis of the situation as it unfolds, as well as informed advice on a very complex landscape, that can help mitigate the impact of COVID-19 control measures and give support to affected communities so that they may recover more quickly.
One size doesn’t fit all
During the hard times of COVID-19, when many governments have faced tough decisions and had to implement strong measures in the midst of many uncertainties, UNICEF’s goal has been to build tools and analyses that can help governments make informed decisions.
Enabling them to assess critical questions such as suitability or sustainability of approaches and policies, with a special focus on vulnerable populations.
Sharing data supported by the Big Data and AI teams across Portugal, Germany, UK, Czech Republic and South Africa so far, UNICEF has been able to gain valuable insight into how movement patterns have changed across different regions and socio-economic backgrounds, as well as how different Big Data and AI technologies can be used to capture such changes.
In addition, funding from Vodafone Foundation has enabled UNICEF to provide advice and support to colleagues in-country in their work with local governments.
For example, UNICEF Indonesia developed real-time daily dashboards looking at population mobility and disease transmission dynamics to help prevent spreading at the earliest possible stage.
Working alongside University of Cuenca, UNICEF Ecuador has developed various models to monitor mortality and analyse the effects of schools closing on transmission rates to inform the safe reopening of schools.
This collaboration has shown that when we understand data better, we have the opportunity to improve the way we do just about anything.