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

5 min

Decoding the Future of AI: From Disruption to Democratisation and Beyond

The global AI landscape has become a melting pot for innovation, with diverse thinking pushing the boundaries of what is possible. Its application extends beyond just technology, reshaping traditional business models and redefining how enterprises, governments, and societies operate. Advancements in model architectures, training techniques and the proliferation of open-source tools are lowering barriers to entry, enabling organisations of all sizes to develop competitive AI solutions with significantly fewer resources. As a result, the long-standing notion that AI leadership is reserved for entities with vast computational and financial resources is being challenged. This shift is also redrawing the global AI power balance, with a decentralised approach to AI where competition and collaboration coexist across different regions. As AI development becomes more distributed, investment strategies, enterprise innovation and global technological leadership are being reshaped. However, established AI powerhouses still wield significant leverage, driving an intense competitive cycle of rapid innovation. Amid this acceleration, it is critical to distinguish true technological breakthroughs from over-hyped narratives, adopting a measured, data-driven approach that balances innovation with demonstrable business value and robust ethical AI guardrails. Implications of the Evolving AI Landscape The democratisation of AI advancements, intensifying competitive pressures, the critical need for efficiency and sustainability, evolving geopolitical dynamics and the global race for skilled talent are all fuelling the development of AI worldwide. These dynamics are paving the way for a global balance of technological leadership. Democratisation of AI Potential The ability to develop competitive AI models at lower costs is not only broadening participation but also reshaping how AI is created, deployed and controlled. Open-source AI fosters innovation by enabling startups, researchers, and enterprises to collaborate and iterate rapidly, leading to diverse applications across industries. For example, xAI has made a significant move in the tech world by open sourcing its Grok AI chatbot model, potentially accelerating the democratisation of AI and fostering innovation. However, greater accessibility can also introduce challenges, including risks of misuse, uneven governance, and concerns over intellectual property. Additionally, as companies strategically leverage open-source AI to influence market dynamics, questions arise about the evolving balance between open innovation and proprietary control. Increased Competitive Pressure The AI industry is fuelled by a relentless drive to stay ahead of the competition, a pressure felt equally by Big Tech and startups. This is accelerating the release of new AI services, as companies strive to meet growing consumer demand for intelligent solutions. The risk of market disruption is significant; those who lag, face being eclipsed by more agile players. To survive and thrive, differentiation is paramount. Companies are laser-focused on developing unique AI capabilities and applications, creating a marketplace where constant adaptation and strategic innovation are crucial for success. Resource Optimisation and Sustainability The trend toward accessible AI necessitates resource optimisation, which means developing models with significantly less computational power, energy consumption and training data. This is not just about cost; it is crucial for sustainability. Training large AI models is energy-intensive; for example, training GPT-3, a 175-billion-parameter model, is believed to have consumed 1,287 MWh of electricity, equivalent to an average American household’s use over 120 years1. This drives innovation in model compression, transfer learning, and specialised hardware, like NVIDIA’s TensorRT. Small language models (SLMs) are a key development, offering comparable performance to larger models with drastically reduced resource needs. This makes them ideal for edge devices and resource-constrained environments, furthering both accessibility and sustainability across the AI lifecycle. Multifaceted Global AI Landscape The global AI landscape is increasingly defined by regional strengths and priorities. The US, with its strength in cloud infrastructure and software ecosystem, leads in “short-chain innovation”, rapidly translating AI research into commercial products. Meanwhile, China excels in “long-chain innovation”, deeply integrating AI into its extended manufacturing and industrial processes. Europe prioritises ethical, open and collaborative AI, while the APAC counterparts showcase a diversity of approaches. Underlying these regional variations is a shared trajectory for the evolution of AI, increasingly guided by principles of responsible AI: encompassing ethics, sustainability and open innovation, although the specific implementations and stages of advancement differ across regions. The Critical Talent Factor The evolving AI landscape necessitates a skilled workforce. Demand for professionals with expertise in AI and machine learning, data analysis, and related fields is rapidly increasing. This creates a talent gap that businesses must address through upskilling and reskilling initiatives. For example, Microsoft has launched an AI Skills Initiative, including free coursework and a grant program, to help individuals and organisations globally develop generative AI skills. What does this mean for today’s enterprise? New Business Horizons AI is no longer just an efficiency tool; it is a catalyst for entirely new business models. Enterprises that rethink their value propositions through AI-driven specialisation will unlock niche opportunities and reshape industries. In financial services, for example, AI is fundamentally transforming operations, risk management, customer interactions, and product development, leading to new levels of efficiency, personalisation and innovation. Navigating AI Integration and Adoption Integrating AI is not just about deployment; it is about ensuring enterprises are structurally prepared. Legacy IT architectures, fragmented data ecosystems and rigid workflows can hinder the full potential of AI. Organisations must invest in cloud scalability, intelligent automation and agile operating models to make AI a seamless extension of their business. Equally critical is ensuring workforce readiness, which involves strategically embedding AI literacy across all organisational functions and proactively reskilling talent to collaborate effectively with intelligent systems. Embracing Responsible AI Ethical considerations, data security and privacy are no longer afterthoughts but are becoming key differentiators. Organisations that embed responsible AI principles at the core of their strategy, rather than treating them as compliance check boxes, will build stronger customer trust and long-term resilience. This requires proactive bias mitigation, explainable AI frameworks, robust data governance and continuous monitoring for potential risks. Call to Action: Embracing a Balanced Approach The AI revolution is underway. It demands a balanced and proactive response. Enterprises must invest in their talent and reskilling initiatives to bridge the AI skills gap, modernise their infrastructure to support AI integration and scalability and embed responsible AI principles at the core of their strategy, ensuring fairness, transparency and accountability. Simultaneously, researchers must continue to push the boundaries of AI’s potential while prioritising energy efficiency and minimising environmental impact; policymakers must create frameworks that foster responsible innovation and sustainable growth. This necessitates combining innovative research with practical enterprise applications and a steadfast commitment to ethical and sustainable AI principles. The rapid evolution of AI presents both an imperative and an opportunity. The next chapter of AI will be defined by those who harness its potential responsibly while balancing technological progress with real-world impact. Resources Sudhir Pai: Executive Vice President and Chief Technology & Innovation Officer, Global Financial Services, Capgemini Professor Aleks Subic: Vice-Chancellor and Chief Executive, Aston University, Birmingham, UK Alexeis Garcia Perez: Professor of Digital Business & Society, Aston University, Birmingham, UK Gareth Wilson: Executive Vice President | Global Banking Industry Lead, Capgemini 1 https://www.datacenterdynamics.com/en/news/researchers-claim-they-can-cut-ai-training-energy-demands-by-75/?itm_source=Bibblio&itm_campaign=Bibblio-related&itm_medium=Bibblio-article-related

3 min

Aston University’s Professor Ian Maidment to contribute to UK’s first long COVID antiviral drug trials

The £1.25m study, being led by the University of Derby, is trialling antiviral medications as a treatment for symptoms of long COVID Professor Ian Maidment from Aston Pharmacy School is the lead pharmacist and will provide support for the clinical trials It is estimated that more than 2m people in the UK and more than 144m globally live with long COVID Professor Ian Maidment, at Aston Pharmacy School, is the lead pharmacist on a groundbreaking research project looking to find a treatment for symptoms of long COVID, which is being led by the University of Derby. The £1.25m trial, which is the first of its kind in the UK, is exploring whether antiviral medications can be used as an effective treatment option for patients diagnosed with long COVID. It is estimated that more than 2m people in the UK and more than 144m globally live with long COVID and almost a quarter of sufferers have had their symptoms for more than two years. Symptoms are broad and include extreme fatigue and breathlessness, palpitations, and brain fog. The trial, which began in September 2024, is part of a wider programme of groundbreaking research being led by the University of Derby. Involving 72 patients, the research is trialling the use of an antiviral drug that can be given to those admitted to hospital because of a COVID-19 infection. As most people experience a community infection and are not hospitalised, they do not have a way to access this medication. By taking the drug out of the acute admission setting, the researchers are hoping to see whether it can help those living with long COVID and alleviate some of the symptoms that they are living with. During the trial, patients undergo a series of assessments at the University of Derby’s specialist facilities before attending the hospital to receive the antiviral drug intravenously for five consecutive days, delivered in collaboration with experts from University Hospitals of Derby and Burton NHS Foundation Trust. Researchers from the University of Exeter are also involved, and the study is being managed by the University of Plymouth’s Peninsula Clinical Trials Unit. Professor Maidment will provide support for the clinical trials. Patients recruited in Exeter will undertake detailed body scans, which will be analysed to check if the antiviral medication has reduced inflammation, which may occur in people with long COVID. Mark Faghy, professor in clinical exercise science at the University of Derby and the study lead, said: “The impact long COVID has on the lives of patients is huge. For many, it can be debilitating, interfering with work, family life, and socialising, and millions are suffering across the world. Yet, at present, there are no confirmed treatments for the condition. Five years on from the start of the pandemic, long COVID remains a significant health and societal challenge, which is why this project is so important. “This is an ongoing project with various phases and is still in its infancy, but we are excited to have taken the first steps to hopefully improve the quality of life for those living with long COVID.” Professor David Strain, clinical lead based at the University of Exeter Medical School, said: “There is a clear need for people living with long COVID and we hope from this study we can see a reduction in the symptoms people experience. It will be an ongoing project with various phases, but we are excited to be taking the first steps to improve patients' quality of life.” Professor Ian Maidment, Aston Pharmacy School, said: “We need clinical trials to develop new and effective treatments for long COVID. Pharmacy support is critical for the successful delivery of these studies.” Over the past four years, Professor Faghy and his team at the University of Derby have conducted a series of international studies to explore the impacts of acute and long COVID, looking to understand the causes and contributing factors of long COVID by bringing clinical insight together with the lived experience of patients.

3 min

Myanmar’s earthquake crisis demands international humanitarian intervention - before it’s too late

We are at a crossroads. Will the international community intervene in Myanmar to save lives, or will it once again retreat into silence until it is too late? In the shadow of disaster, silence is complicity. The devastating earthquake that recently struck Myanmar, registering a magnitude of 7.7 and claiming over a thousand lives with the potential for fatalities to rise into the tens of thousands, is far more than a natural calamity - it is a preventable humanitarian catastrophe. The international community must confront a difficult question: How many more lives must be lost before the world steps in? As someone who has studied disaster governance for over two decades, I can say with a heavy heart that what we are witnessing in Myanmar is a textbook case of systemic failure - of national crisis management, of international humanitarian coordination and, most disturbingly, of disaster diplomacy. A Crisis Exacerbated by Inaction The situation on the ground is dire. Entire villages lie in ruins across Shan State and Mandalay. Liquefaction, caused by the shifting of tectonic plates, has turned many areas into unstable wetlands, with water seeping through the ground continuously. With countless bodies left unrecovered and proper sanitation systems overwhelmed, the risk of cholera and other waterborne diseases looms large. In past disasters - be it Haiti in 2010, Nepal in 2015 or the Turkey-Syria earthquake of 2023 - we saw the tragic consequences of slow and politicised humanitarian responses. But Myanmar’s case is uniquely perilous. The country is not only facing a natural disaster but also the aftermath of years of civil conflict, military rule and geopolitical paralysis. The ruling junta’s statements and figures are unreliable at best and disinformation is hampering coordinated international support. When Aid Needs Armour The reality is that humanitarian intervention in Myanmar now requires more than blankets and bottled water - it needs boots on the ground. Given the multiplicity of armed rebel groups and the entrenched conflict dynamics, any aid convoy risks becoming a pawn in a larger power struggle. We need an international peacekeeping force, mandated strictly for humanitarian purposes, to ensure safe and unfettered access to affected populations. This must be a neutral, apolitical force, equipped to operate in a complex, high-risk environment - not to take sides, but to protect lives. Without such security guarantees, humanitarian agencies cannot function, and the crisis will evolve into famine, mass migration, and possibly regional instability across Southeast Asia. A Crisis of Leadership The United Nations, ASEAN, WHO and other key global institutions have yet again fallen short of timely action. The ineffectiveness of their response should prompt a critical reevaluation of their governance structures and crisis leadership models. The deeper issue is not just logistical - it’s moral. In the absence of strong, scientifically-informed and transparent leadership, international aid becomes another layer of dysfunction. We need a new generation of disaster governance professionals - leaders trained not only in logistics and law, but in negotiation, ethics and diplomacy. The Cost of Indifference Myanmar’s crisis will not remain confined within its borders. Already, we are seeing early signs of mass displacement towards India, Thailand and Bangladesh. If left unchecked, these flows will eventually extend to Europe, the UK and beyond, burdening an already overstretched global refugee system. The longer we delay, the greater the consequences - not just for Myanmar, but for the world. A Call for Science, Transparency and Regional Solidarity As academics and practitioners in the field of Disaster Risk Reduction (DRR), we must hold ourselves to the highest standard of integrity. DRR in regions like South and Southeast Asia must be built on inclusive science, open data, regional collaboration and local knowledge. Taiwan and Singapore offer examples of how early warning systems and data transparency can save lives - why aren't we replicating these models more widely? If this disaster teaches us anything, it is that sovereignty cannot be used as a shield for inaction. A disaster of this magnitude transcends politics. It is a test of our global conscience.

View all posts
Powered by