Academics in Durham’s particle physics department are using big data to fight the spread of Covid-19 in the world’s largest refugee camp, Cox’s Bazar. In collaboration with UN agencies, Durham scientists are modelling the movement of people within the refugee camp, in order to understand where and how people interact.
Refugee camps are often overcrowded and lack sanitation facilities. They are also highly dynamic places, making it difficult to monitor demographic patterns and trends. For these reasons, refugee camps are particularly vulnerable to Covid-19.
In order to overcome this challenge, the team used open-source demographic and geographic data to create a digital agent-based model of Cox’s Bazar refugee camp. The model provides a bird’s eye view of where people move from and to on a regular basis. The likelihood of a person with Covid-19 infecting others depends on the type of location they go to, how infectious they are, and the length of time they spend at that location. For example, the model incorporates the fact that men are more likely than women to travel to distribution centres to collect food parcels.
Big data has received heavy investment from the private sector to model consumer habits, but the humanitarian sector has been slow to utilise the potential of big data to inform decision-making. The results of this research will be used to determine the efficacy of different measures against Covid-19, such as mask-wearing or closing down a community centre.
The model has been designed with a high degree of flexibility, allowing new information to be added as it becomes available. It is hoped that such an adaptive algorithm can provide a more accurate analysis of public health in refugee camps, allowing teams on the ground to direct resources where they are needed most.
The Cox’s Bazar settlement is located in Bangladesh and houses 900,000 people. The majority of refugees in the settlement are Rohingya Muslims who have continuously fled targeted violence and discrimination in Myanmar.
Durham’s role in the modelling was led by Joseph Aylett-Bullock, a researcher at the Institute for Particle Physics Phenomenology and a member of the Institute for Data Science, a multidisciplinary research group at Durham University.
Image: Amana Moore