Sustained collaboration between demand-side agencies and supply-side partners to leverage the power of MBD analytics can save our planet
When COVID-19 hit the world, mobile industry association, GSMA’s (Artificial Intelligence) AI for Impact (AI4I) initiative immediately sprang into action, to extract actionable intelligence from Mobile Big Data (MBD) to support government efforts to tackle the rapidly spreading pandemic. Their efforts led to well-planned lockdowns, and other restrictive measures to stop the spread of the virus. From Nigeria to France, Sweden, to Democratic Republic of Congo MBD analytics helped governments to understand the trajectory of the pandemic and take proactive measures using AI.
The rapid transmission rate of the virus threatened to overwhelm the Democratic Republic of Congo (DRC) which had a long history of infectious disease outbreaks and endemic malaria, making it particularly vulnerable to persistent public health emergencies. The AI4I COVID-19 response in the DRC aimed to help the government understand the country’s vulnerability to the pandemic, inform response measures and strengthen the provision of healthcare services. The GSMA established an ecosystem of diverse partners from the public and private sectors to work together in a virtual “Mobile Big Data Control Room.”
Figure 1:Mobile big data analysis use cases for COVID-19 response; Source:GSMA
MBD analytics provided DRC health authorities with insights into how movement patterns changed in response to government measures and other factors, such as economic pressures. Specifically, government agencies have used these insights for evaluating lockdown compliance – Kinshasa’s Gombe district saw a 70% drop in the total flow of mobile subscribers travelling to the district in the weeks after lockdown was enforced. Highlighted unintended consequences of lockdowns and border closures – locations with increases in population mixing and potential future disease hotspots were identified. MBD helped assess the risk of viral transmission on resumption of economic activity – The insights enabled visibility of population movement from Kinshasa’s most affected districts to other parts of the city and other provinces in the country as mining activities resumed.
When several countries were figuring out their response strategies, South African mobile operator MTM teamed up with the Nigeria Governors Forum, a coalition of the 36 state governors, to enable data-driven insights to shape resource planning and response measures.
In the first phase they developed a model to predict the worst-case scenario for infections in each state. This was used to support the health committees with local resource planning decisions. The predictive analysis utilizedanonymized and aggregated mobile network data, combined with geospatial reference datasets from open-source public data repositories, and applied to an epidemiological model.
The second phase focused on understanding where the population at greatest socioeconomic risk from the impact of the disease was clustered geographically. Lockdown measures, which were designed to reduce population movement and interaction to halt transmissions, meant many subsistence/daily paid workers lost their source of income and ability to buy essential food supplies. The MBD solution was able to identify the geographies with the most vulnerable population through the application of anonymized and aggregated mobile money transactions, as a proxy indicator for economic status.
This was validated by third-party economic indicators and layered with infrastructure insights from geospatial reference datasets. This insight went on to form the basis of the geographical targeting for the HelpNow crowdfunding platform, an initiative developed by a coalition of partners, which has been designed to collect and disperse crowd-sourced donations to the most vulnerable in Lagos state. People and families located in the vulnerable areas are encouraged to apply for grants through the HelpNow initiative.
Figure 2:MBD analytics can support various stages of COVID-19 response
Telia, the Finland-based mobile operator, worked with the Public Health Agency of Sweden to understand how groups of people move in society amid the pandemic. The analysis established that even without a formal lockdown instruction from the government, mobility reduced by 20% in March 2020, compared to the first week of the previous month.
The French multinational telecom company, Orange worked with the French National Institute for Health and Medical Research (Inserm) early on, to help prepare and evaluate lockdown measures. The analysis showed a 65% reduction in journeys during lockdown and how this was particularly effective in reducing work and recreational trips.
Since January 2020, Telenor has been providing mobility data on movement between Norway’s 356 municipalities to the Norwegian Institute of Public Health’s COVID-19 task force. Telenor’s mobility data has been utilized to inform modelling of the potential spread of the virus, to develop predicted incidence in each municipality and to simulate the number of hospitalizations, intensive care patients and deaths.
In 2020, as COVID-19 emerged, institutions and governments started to explore how mobile big data solutions could help track, contain, and predict the spread of the virus. Many mobile operators formed partnerships with governments to help manage the crisis, but this was only the beginning. Leveraging those insights would require technical expertise, a deep knowledge of local policy and collaboration between public- and private-sector partners. Today, mobile broadband networks cover nearly 95% of the global population and are the only form of connectivity available to many people in LMICs (Low- & Medium-Income Countries). During the pandemic, mobile networks have become a lifeline, allowing many economic activities to continue and for people to maintain social interactions.
Figure 3: MBD analytics helped governments answer key questions on various use cases around the pandemic
The GSMA AI for Impact (AI4I) initiative was well positioned to meet the challenge. AI4I launched in 2017, bringing together a global task force of 21 mobile network operators and an advisory panel of 12 United Nations agencies to raise awareness and develop best practices on the use of aggregated, anonymized mobility data to address global challenges. GSMA AI4I initiative develops global partnerships to accelerate action on the use of MBD analytics and AI as powerful forces to transform business and society and achieve impact in alignment with the UN SDGs.
The pandemic has been a turning point for mobile big data analytics. A watershed moment in which mobile operators, governments and international agencies have worked together on a remarkable number of projects globally to develop effective response measures. Mobile operators have helped with efforts to better understand and respond to the virus in at least 40 countries.
The everyday use of mobile networks generates enormous amounts data, often referred to as mobile big data (MBD). Through mobile operators’ MBD analytics and AI expertise, MBD can be aggregated, anonymized, analysed, combined with data and information from other relevant sources, and packaged into valuable products and services, such as reports and dashboards. These can be powerful support tools for decision-making across a wide range of problems – such as determining how to respond to epidemics and natural disasters, mitigating pollution, planning infrastructure deployment, or allocating scarce resources.
With social and travel restrictions put in place to curb the spread of the virus, mobile connectivity has emerged as a lifeline, allowing many everyday activities to continue. Mobile networks also generate enormous amounts of data, often referred to as mobile big data (MBD), which can provide unique insights on population mobility patterns and socioeconomic indicators when aggregated, anonymized, analysed and combined with relevant data and information from other sources.
Insights from MBD analytics products and services support evidence-based decision-making by helping governments and other stakeholders to:
- monitor the effectiveness of lockdown enforcements and their impact on infection rates
- understand how the pandemic may spread, given the potential for travellers to take diseases from areas with high infection rates to areas of low incidence
- locate and identify vulnerable population groups that could be adversely impacted by lockdowns and social distancing measures
- optimize the supply of medical facilities and personnel in areas of greatest need
- plan how to safely resume social and economic activities, and
- optimise the provision of public services amid changes in usage patterns.
Looking ahead, MBD analytics holds the promise of helping governments around the world to better prepare for future disease outbreaks and tackle various local and global challenges, in line with the UN Sustainable Development Goals (SDGs). When adopted early, MBD analytics products and services can play a key role in helping governments implement response measures more effectively and efficiently. This requires continued collaboration between demand-side agencies – including governments, development agencies and donors – and supply-side partners to leverage the power of MBD analytics to address the challenges faced by societies, economies, and the planet.