Case Study • Data Science

Joint Biosecurity Centre

Modelling the global transmission of COVID-19 and simulating the impact of non-pharmaceutical interventions (NPIs).

COVID-19 Dashboard

Case Study Summary

The Challenge

Provide analysis and insight on the drivers and risk factors of COVID-19 transmission and the likely impact of NPIs.

What We Did

We rapidly designed and built bleeding-edge disease models capable of tracking & predicting the transmission of COVID-19.

Key Outcomes

Data products and predictions directly consumed by SAGE to inform policy-making to better protect public health.


The Joint Biosecurity Centre (JBC) was established in May 2020 to provide evidence-based, objective analysis, assessment and advice to inform local and national decision-making in response to the COVID-19 pandemic. Its immediate term objective was to break the chains of COVID-19 transmission to protect public health as part of the evolving health protection ecosystem in the UK. The JBC brings together and combines internationally-leading epidemiological expertise with data science to provide analysis and insights on the drivers and risk factors of virus transmission.

Joint Biosecurity Centre
Joint Biosecurity Centre Logo

The Challenge

Working with internationally-leading partners (including mathematicians from CERN, AI researchers from The Alan Turing Institute, leading epidemiologists from academia, genomic sequencing SMEs, the NHS, the Office for National Statistics, and major public cloud providers) the JBC sought to provide insights into the factors that affect the spread of COVID-19, to identify the most significant drivers of transmission, and to understand the factors behind localised increases in infection rates and the potential consequences for local health care systems.

COVID-19 surveillance and immunity studies
COVID-19 virus

What We Did

Our founder Jillur Quddus led an expert team responsible for rapidly designing, building, deploying and evaluating bleeding-edge disease models utilising the latest research in statistical modelling and machine learning that were capable of tracking and predicting the transmission of COVID-19 in real-time. Our disease models enabled the Joint Biosecurity Centre to identify both known and previously unknown clusters of COVID-19 outbreaks, along with the ability to understand the key drivers of transmission both within and between localised clusters, and to subsequently simulate the impact of non-pharmaceutical interventions (NPIs) such as local lockdown measures.

Enduring SARS-CoV-2 prevalence risk factors
Map of global COVID-19 cases

Key Outcomes

Our solutions enabled the Joint Biosecurity Centre to meet their immediate term objective of breaking the chains of COVID-19 transmission. The data products that we developed were directly consumed by members of the Scientific Advisory Group for Emergencies (SAGE) and the Chief Medical Officer (CMO) for England to inform evidence-based decision-making and to better protect public health. Furthermore, the designs of our solutions were guided by the principles of reusability and interoperability, meaning that they can be easily reused by the UK's Health Security Agency (UKHSA) in response to future pandemics.

Scientific Advisory Group for Emergencies
COVID-19 public messaging