Featured Post from Aston University

Aston University AI expertise helps estimate daily transmission rates of infections such as Covid

Feb 3, 2023

3 min

Dr Felipe Campelo
  • Model used antibody data collected at blood donation centres
  • Data obtained allowed academics to estimate the proportion of people who were going undiagnosed
  • Current epidemiological models tend not to be as effective at estimating hidden variables such as daily infection rates.


Aston University researchers have helped develop a mathematical model which can estimate daily transmission rates of infections such as Covid by testing for antibodies in blood collected at blood donation centres.


Current epidemiological models that are usually used tend not to be as effective at adjusting quickly to changes in infection levels.


Working with researchers at the Universidade Federal de Minas Gerais in Brazil they conducted a large longitudinal study applying a compartmental model, which is a general modelling technique often applied to the mathematical modelling of infectious diseases, to results obtained from Brazilian blood donor centres. The testing was done by Fundacao Hemominas, one of the largest blood services in Brazil, which covers an area similar to that of continental France.


They used the reported number of SARS-CoV-2 cases along with serology results (diagnostic methods used to identify antibodies and antigens in patients’ samples) from blood donors as inputs and delivered estimates of hidden variables, such as daily values of transmission rates and cumulative incidence rate of reported and unreported cases.


The model discussed in the paper SARS-CoV-2 IgG Seroprevalence among Blood Donors as a Monitor of the COVID-19 Epidemic, Brazil gave the experts the ability to have a more refined view of the infection rates and relative rate of immunity compared to official measurements.


The testing started at the beginning of the pandemic and involved 7,837 blood donors in seven cities in Minas Gerais, Brazil during March–December 2020. At that point testing wasn’t widely available and there was a high proportion of undetected asymptomatic or light symptomatic cases. The data obtained allowed the experts to estimate the proportion of people who were going undiagnosed.


Dr Felipe Campelo, senior lecturer in computer science at Aston University, said:


“Public communication about the COVID-19 epidemic was based on officially reported cases in the community, which strongly underestimates the actual spread of the disease in the absence of widespread testing.


“This difference underscores the convenience of using a model-based approach such as the one we proposed, because it enables the use of measured data for estimating variables such as the total number of infected persons.


“Our model delivers daily estimates of relevant variables that usually stay hidden, including the transmission rate and the cumulative number of reported and unreported cases of infection.”


In Brazil in July 2020 there was a sharp increase in the number of people tested as new infrastructure became available, which allowed the experts to further validate their methodology by observing how officially recorded data became closer to the model predictions once testing became more widespread, including for asymptomatic or mildly symptomatic people.


They applied the model to antibodies found in blood given by donors and used it to estimate the proportion of undiagnosed cases, and to analyse changes in the infection rate, that is, how many people each case infected on average. Previously this has been viewed as a fixed value or a fixed value over a long duration of time, but the dynamics of the spread of Covid change much faster than that. This aspect was very important in early days of the pandemic and could also be applied to similar diseases.


Looking forward, the experts aim to improve the accuracy of the model by introducing changes to account for vaccination effects, waning immunity and the potential emergence of new variants.


The paper SARS-CoV-2 IgG Seroprevalence among Blood Donors as a Monitor of the COVID-19 Epidemic, Brazil has been published in Volume 28, Number 4—April 2022 of Emerging Infectious Diseases.

Connect with:
Dr Felipe Campelo

Dr Felipe Campelo

Senior Lecturer, Computer Science

Dr Campelo works in data science. He creates solution pipelines integrating data mining, optimisation and multicriteria decision support.

OptimisationComputational IntelligenceData MiningData Science

You might also like...

Check out some other posts from Aston University

3 min

Aston University researcher develops new optical technique that could revolutionise medical diagnostics

New light technique could revolutionise non-invasive medical diagnostics Orbital Angular Momentum could be harnessed to improve imaging and data transmission through biological tissues Could eventually have potential to make procedures such as surgery or biopsies unnecessary. An Aston University researcher has developed a new technique using light which could revolutionise non-invasive medical diagnostics and optical communication. The research showcases how a type of light called the Orbital Angular Momentum (OAM) can be harnessed to improve imaging and data transmission through skin and other biological tissues. A team led by Professor Igor Meglinski found that OAM light has unmatched sensitivity and accuracy that could result in making procedures such as surgery or biopsies unnecessary. In addition it could enable doctors to track the progression of diseases and plan appropriate treatment options. OAM is defined as a type of structured light beams, which are light fields which have a tailored spatial structure. Often referred to as vortex beams, they have previously been applied to a number of developments in different applications including astronomy, microscopy, imaging, metrology, sensing, and optical communications. Professor Meglinski in collaboration with researchers from the University of Oulu, Finland conducted the research which is detailed in the paper “Phase preservation of orbital angular momentum of light in multiple scattering environment” which is published in the Nature journal Light Science & Application. The paper has since been named as one of the year’s most exciting pieces of research by international optics and photonics membership organisation, Optica. The study reveals that OAM retains its phase characteristics even when passing through highly scattering media, unlike regular light signals. This means it can detect extremely small changes with an accuracy of up to 0.000001 on the refractive index, far surpassing the capabilities of many current diagnostic technologies. Professor Meglinski who is based at Aston Institute of Photonic Technologies said: “By showing that OAM light can travel through turbid or cloudy and scattering media, the study opens up new possibilities for advanced biomedical applications. “For example, this technology could lead to more accurate and non-invasive ways to monitor blood glucose levels, providing an easier and less painful method for people with diabetes.” The research team conducted a series of controlled experiments, transmitting OAM beams through media with varying levels of turbidity and refractive indices. They used advanced detection techniques, including interferometry and digital holography, to capture and analyse the light's behaviour. They found that the consistency between experimental results and theoretical models highlighted the ability of the OAM-based approach. The researchers believe that their study’s findings pave the way for a range of transformative applications. By adjusting the initial phase of OAM light, they believe that revolutionary advancements in fields such as secure optical communication systems and advanced biomedical imaging will be possible in the future. Professor Meglinski added: "The potential for precise, non-invasive transcutaneous glucose monitoring represents a significant leap forward in medical diagnostics. “My team’s methodological framework and experimental validations provide a comprehensive understanding of how OAM light interacts with complex scattering environments, reinforcing its potential as a versatile technology for future optical sensing and imaging challenges.” ENDS https://www.nature.com/articles/s41377-024-01562-7 Light: Science & Applications volume 13, Article number: 214 (2024) August 2024 https://doi.org/10.1038/s41377-024-01562-7 Authors: Igor Meglinski, Ivan Lopushenko, Anton Sdobnov & Alexander Bykov About Aston University For over a century, Aston University’s enduring purpose has been to make our world a better place through education, research and innovation, by enabling our students to succeed in work and life, and by supporting our communities to thrive economically, socially and culturally. Aston University’s history has been intertwined with the history of Birmingham, a remarkable city that once was the heartland of the Industrial Revolution and the manufacturing powerhouse of the world. Born out of the First Industrial Revolution, Aston University has a proud and distinct heritage dating back to our formation as the School of Metallurgy in 1875, the first UK College of Technology in 1951, gaining university status by Royal Charter in 1966, and becoming The Guardian University of the Year in 2020. Building on our outstanding past, we are now defining our place and role in the Fourth Industrial Revolution (and beyond) within a rapidly changing world. For media inquiries in relation to this release, contact Nicola Jones, Press and Communications Manager, on (+44) 7825 342091 or email: n.jones6@aston.ac.uk

2 min

Aston University researchers to explore using AI and fibre-optic networks to monitor natural hazards and infrastructures

Aston University is leading a new £5.5 million EU research project Will focus on converting fibre-optic cables into sensors to detect natural hazards Could identify earthquakes and tsunamis and assess civil infrastructure. Aston University is leading a new £5.5 million EU research project to explore converting existing telecommunication fibre-optic cables into sensors which can detect natural hazards, such as earthquakes and tsunamis, and assess the condition of civil infrastructure. The project is called ECSTATIC (Engineering Combined Sensing and Telecommunications Architectures for Tectonic and Infrastructure Characterisation) and is part of the Horizon Europe Research and Innovation Action (RIA), which aims to tackle global challenges and boost the continent’s industrial competitiveness. Converting telecom fibres into sensors requires new digital signal processing to overcome the limited data storage and processing capabilities of existing communication networks. To address this the project will use localised, high performance digital processing that will integrate artificial intelligence and machine learning. The researchers’ goal is to minimise algorithms’ complexity while providing extremely accurate real-time sensing of events and network condition. The new laser interrogation and signal processing technologies will be tested using existing fibre optic networks, including those underwater, in cities, and along railway infrastructure to assess their potential. Delivered by a consortium of 14 partners across seven countries, from academic and non-academic sectors, the research will start in February 2025 and will last three and a half years. The Europe-wide team will be led by Professor David Webb who is based in the Aston Institute of Photonic Technologies (AIPT). Professor Webb said: “There are more than five billion kilometres of installed data communications optical fibre cable, which provides an opportunity to create a globe-spanning network of fibre sensors, without laying any new fibres. “These traverse the seas and oceans - where conventional sensors are practically non-existent - and major infrastructures, offering the potential for smart structural health monitoring.” Professor Webb will be joined by fellow researchers Professor Sergei Turitsyn, Dr Haris Alexakis and Dr Pedro Freire. For media inquiries in relation to this release, contact Nicola Jones, Press and Communications Manager, on (+44) 7825 342091 or email: n.jones6@aston.ac.uk

3 min

EU-UK Trade Deal continues to stifle trade with 27% drop in exports since 2021

New report shows persistent stifling effects of the impact of the Trade and Cooperation Agreement on UK-EU trade relations Monthly data show a 27% drop in UK exports and a 32% reduction in imports to and from the EU between 2021 and 2023 Recommendations for policy interventions include to negotiate sector-specific deals, engage with individual EU countries, and work on reducing non-tariff barriers A comprehensive analysis by researchers at the Centre for Business Prosperity at Aston University reveals that negative impacts of the UK-EU Trade and Cooperation Agreement (TCA) have intensified over time. The new report, Unbound: UK Trade Post Brexit, also shows a 33% reduction in the variety of goods exported, with the agricultural, textiles, clothing and materials sectors most affected. To assess the impact of the UK-EU TCA, the authors analysed monthly import and export between the UK and the EU, from January 2017 to December 2023 and separated into pre- and post-January 2021 when the agreement came into force. The monthly data shows a 27% drop in UK exports and a 32% decline in imports from the EU. Lead author, Professor Jun Du of Aston University says: “The Trade and Cooperation Agreement introduced substantial barriers and there are ongoing and marked declines in the value and variety of UK exports and imports. Without urgent policy interventions, the UK’s economic position and place in the global market will continue to weaken.” The UK-EU TCA redefined trade and investment rules and market access between the UK and the EU. Since it came into force, the UK government has negotiated several trade agreements, but the EU remains the UK’s largest trade partner. Exports for most sectors have decreased since January 2021, although the impact is varied. Agrifood, textile and clothing and material-based manufacturing have been among the hardest hit, with substantial declines in both export value and the variety of products exported. At the same time, some sectors such as tobacco, railway and aircraft manufacturing have seen modest increases in varieties of products exported. On the import side, most sectors have shrunk in both value and variety, particularly agrifood products, optical, textile and material-based manufacturing. A few sectors, for example, ships and furniture, have demonstrated noticeable increases in import product variety. The large variations across different goods categories and EU trade partners underscore the uneven effects of Brexit and the TCA on UK-EU trade dynamics, highlighting the need to understand the nuances and come up with tailored strategies that address the unique challenges of each sector within the new regulatory environment. The researchers make recommendations, outlining how sector-specific negotiations, streamlining customs procedures with digital technologies and reducing regulatory divergence could mitigate some of the impacts. Dr Oleksandr Shepotylo, the report’s co-author says: “Our findings indicate a decoupling of the UK from key EU final goods markets, accompanied by a shift in UK supply chains toward geographically closer EU trading partners for exports and smaller countries for imports. “This shift raises concerns and underscores the urgent need for a strategic reconfiguration of UK supply chains to maintain competitiveness.” Professor Du continues: “The TCA has introduced considerable barriers to UK-EU trade, particularly through increased Non-tariff measures (NTMs). “Addressing these issues through targeted improvements to the TCA is crucial to ensuring that UK businesses remain competitive in the European market. A structured, multi-faceted approach is necessary.” To find out more about these findings, click here.

View all posts
Powered by