Academics and data scientists from Durham University and UN Global Pulse (UNGP) have developed an agent-based model to simulate the spread of COVID-19 in the Cox’s Bazar refugee settlement in Bangladesh.
The researchers analysed a number of operational interventions by modelling the interactions of over 900,000 Rohingya refugees and found that mask wearing is highly effective to slow the spread of COVID-19.
Researchers also established that handling of positive cases in isolation and treatment centres have little impact on the spread of COVID-19 in comparison to home isolation for individuals with mild symptoms, mainly due to the exceptionally high population density in the settlement and many facilities being communal that poses increased risk of coronavirus transmission.
Furthermore, at the time of the study, the simulation results indicated that the reopening of learning centres could lead to a higher infection rate in the refugee settlement, where social distancing is nearly impossible. This led the researchers to explore various mitigation strategies.
The study adapted the JUNE epidemic model to the settlement setting. The team took a scenario-based approach that focused on simulating the relative effectiveness of the above-mentioned interventions in the settlement.
The modelling followed a three-step process of (1) building a ‘digital twin’ of the Cox’s Bazar refugee settlement that (2) simulated the possible movement and interaction patterns among the residents and (3) implementation of operational interventions to simulate its effects on the spread of COVID-19 in the settlement.
Virtual individuals were included into the model with different demographic attributes that mirrored real world statistics. A simulation engine was designed by the researchers that captured movement and interaction patterns of the people in the model.
Full results of the study have been published in the journal PLOS Computational Biology.
The study findings have allowed decision makers in the refugee settlement to set up new contingency plans for high case numbers and develop policies on safe opening of various indoor spaces.
A mask-wearing strategy was rolled out, which included mask-making, and communication and engagement campaigns to increase correct mask usage, as the model showed how this could significantly reduce the spread of COVID-19 over time.
The model has been informed by data from UNHCR, the UN’s Refugee Agency, on geography, demographics, comorbidities, physical infrastructure, and other parameters obtained from real-world observations.
The study results were presented in a series of reports that provided crucial insights and limitations relevant to this modelling approach to the World Health Organisation and UNHCR public health professionals operating in the settlement on the potential effectiveness of interventions to curb the spread of COVID-19.
Chris Earney, Deputy Director of UNGP said: “The project has fulfilled its operational objectives successfully and the team are aiming to scale the model implementation further with future applications and partnerships.”
The JUNE open-source modelling framework has been developed by the researchers during the pandemic and was originally applied to simulating the spread of COVID-19 in England.
Professor Frank Krauss of Durham University said: “The work with the UN and the WHO is super-exciting and a very good example for the calibre of our PhD students. It is great to see their enthusiasm, skills and drive: this project started from zero, and within months we had a highly competitive COVID simulation for the UK, all while they also collaborated with international agencies to apply this to a completely new setting. This is nothing short of a truly excellent achievement!”
The research conducted by UNGP has been supported by the Government of Sweden, and the William and Flora Hewlett Foundation and the PhD students were supported by the UKRI-STFC grant.
ENDS
Media Information
Dr Joseph Aylett-Bullock, Researcher and Data Scientist at UNGP, is available for interview and can be contacted on joseph@unglobalpulse.org .
For interview requests with UNGP officials, please contact Theresa Schwarz, Communications and Partnerships, UNGP Finland on theresa.schwarz@un.org .
Alternatively, please contact Durham University Communications Office for interview requests on communications.team@durham.ac.uk .
Photographs
Associated images are available via the following link: https://www.dropbox.com/sh/morwt3sg8o2k4k0/AAAkOsWV2mlJu9r1ssTB5qmla?dl=0
Images should be credited to UNHCR/Amos Halder.
Source Information
“Operational response simulation tool for epidemics within refugee and IDP settlements”, Joseph Aylett-Bullock, Carolina Cuesta-Lazaro, Arnau Quera-Bofarull, Anjali Katta, Katherine Homann Pham, Benjamin Hoover, Hendrik Strobelt, Rebeca Moreno
Jimenez, Aidan Sedgewick, Egmond Samir Evers, David Kennedy, Sandra Harlass, Allen Gidraf Kahindo Maina, Ahmad Hussien and Miguel Luengo-Oroz, to be published in PLOS Computational Biology and can be accessed via this link following embargo lift: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009360
A copy of this paper (embargoed until 1900 GMT on Thursday, 28 th October 2021) is available from Durham University Communications Office. Please email Communications Office on communications.team@durham.ac.uk .
Useful Web Links
Dr Joseph Aylett-Bullock staff profile: https://www.durham.ac.uk/staff/j-p-bullock/
Department of Physics, Durham University: https://www.durham.ac.uk/departments/academic/physics/
Institute for Data Science, Durham University: https://www.dur.ac.uk/idas/
JUNE open-source framework: https://www.durham.ac.uk/news-events/latest-news/2021/09/new-model-helps-covid-19-planning/
UNGP epidemic modelling of COVID-19: https://www.unglobalpulse.org/microsite/epidemic-modelling-in-settlements/
About UN Global Pulse
UN Global Pulse (UNGP) is the innovation lab of the Secretary-General of the United Nations (UN). UNGP is a seasoned innovator and thought leader for the UN System and is uniquely positioned to assist UN partners in leveraging technology for the public good. Over the last ten years, UNGP has developed and adapted numerous machine learning and mathematical models and tools to the needs of entities inside the UN. The UNGP team consists of researchers, data scientists, engineers, designers, social scientists, humanitarians, data privacy and ethics experts.
About UNHCR
UNHCR, the UN Refugee Agency, is a global organisation dedicated to saving lives, protecting rights and building a better future for people forced to flee their homes because of conflict and persecution.
We lead international action to protect refugees, forcibly displaced communities and stateless people.
We deliver life-saving assistance, help safeguard fundamental human rights, and develop solutions that ensure people have a safe place called home where they can build a better future. We also work to ensure that stateless people are granted a nationality.
We work in over 130 countries, using our expertise to protect and care for millions.
About UNHCR’s Innovation Service
The UN Refugee Agency's Innovation Service supports new and creative approaches to address the growing humanitarian needs of today and the future. UNHCR’s Innovation Service is committed to creating an enabling environment for innovation to flourish in UNHCR by equipping staff with the knowledge, resources, and skills needed to ensure that they can increasingly draw on structured innovation to solve the most pressing challenges.
About Durham University
Durham University is a globally outstanding centre of teaching and research based in historic Durham City in the UK.
We are a collegiate university committed to inspiring our people to do outstanding things at Durham and in the world.
We conduct boundary-breaking research that improves lives globally and we are ranked as a world top 100 university with an international reputation in research and education (QS World University Rankings 2022).
We are a member of the Russell Group of leading research-intensive UK universities and we are consistently ranked as a top 10 university in national league tables (Times and Sunday Times Good University Guide, Guardian University Guide and The Complete University Guide).
For more information about Durham University visit: www.durham.ac.uk/about/
END OF MEDIA RELEASE – issued by Durham University Communications Office.
PLOS Computational Biology
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009360
Computational simulation/modeling