Many countries are now suffering after years of insufficient attention to warnings about the need for improved pandemic preparedness. The WHO has declared COVID-19 a pandemic, but its underlying factors, vulnerabilities and impacts go far beyond the health sector, and in Sri Lanka, it is overwhelming government and response agencies. This study will address two, inter-related challenges: How will countries cope if a major natural hazard occurs while the COVID-19 pandemic is ongoing? How can pandemic preparedness make use of the existing infrastructure for tackling other hazards? The project team will attempt to understand the potential impact of a pandemic-natural hazard hybrid scenario. It will also seek to improve early warning and preparedness for such an event, as well as the availability of and access to multi-hazard early warning systems (MHEW) and disaster risk information that include pandemic/biological hazards, which is also Target G of the SFDRR [1]. We will address these challenges by examining how public health actors be better included within a MHEW environment and how pandemic threats are integrated within national and local DRR strategies. We will explore the impact of COVID-19 on the response capabilities for other hazards, either multiple simultaneous events, or cascading impacts, and consider how COVID-19 and public health surveillance can be synergised with "the last mile" of MHEW. Pandemic is global, but the preparedness and response is local, and that response is very dependent on governance, laws, culture, risk perception and citizen behaviour. The study has been designed in close collaboration with Sri Lankan health and DRR agencies who identified the key gaps that need exploring. The team will develop and disseminate guidance to better incorporate pandemics and other biological hazards into national and local DRR preparedness and response

Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.

This project aims to develop, and to provide a range of mechanisms to support interdisciplinary collaborations that use and develop new mathematics for understanding climate variability and impact on resilience. Focusing on three scientific themes the project will nurture connections between mathematicians, statisticians, environmental scientists, policy makers and end users working in impact areas to help to identify high-risk and high-return research that will develop collaborations in the areas of the themes. We will do this by a range of tools, including a series of managed events (workshops, sandpits, study groups and e-seminars) that will focus on specific problems to end users as well as promoting novel collaborations in the areas of scientific focus. We will provide a mechanism to solicit, evaluate and fund proposals for feasibility studies that work across this area. This will be informed by an expert panel of researchers as well as an advisory panel taken from national and international groups and end-users.

Infectious disease is the main thing that kills people. Some of the greatest improvements to human health have involved improvements in our understanding and control of germs - from John Snow's pioneering work on cholera in the 19th century to the eradication of smallpox in the 20th century. The 21st century sees a new set of challenges in the understanding and control of infections - while the eradication of polio progresses, we see new influenza strains causing or threatening pandemics, the continued progression of HIV and a massive health burden of often simply but expensively preventable diseases in the developing world.Epidemiology - the science of looking for significant patterns in cases of disease - has always been at the heart of controlling infectious diseases, and mathematics has always been central epidemiology.This project applies advanced mathematics to the science of epidemiology, making use of the large datasets and modern computational resources that are available. New insights about the structure of complex systems offer the promise of making massive advances in this field, through enhanced understanding of transmission routes of infection, risk factors and changes in the disease over time. These insights can in turn be combined with mathematical methods to design optimised interventions against infection so that diseases can be controlled in the most effective way.

UK ENABLE Consortium vision, aims and objectives: Local government is uniquely placed to shape the environmental and social factors which fundamentally influence non-communicable diseases (NCDs) and thus our health and wellbeing. Our vision is for local government to consider the health of local populations in all policy and practice decisions and to have the best possible scientific evidence to support those decisions. We will test our vision by working with five different local authority (LA) based public health systems across the UK, learning what works best, and what can be useful for all LAs across the UK. Our consortium brings together academics, practitioners, policy makers and other stakeholders from across the UK in five centres in NE and SW England, Scotland, Northern Ireland and Wales; each with different models of public health delivery. We will develop and test a process that embeds research capacity and expertise in LAs. Working closely with our partners in each LA, we will identify a current priority for improving the health and wellbeing and reducing inequalities of people living in that area. By building relationships between academics, practitioners and policy makers we will enable the LA to access and create new evidence that is relevant for decision making about the priority issue. Scientific rationale for the proposed research: Evidence-informed policy-making aims to improve decision making by using the best available research. Organisational and cultural barriers within the current system have made this approach difficult to achieve. New methods and approaches are needed which bring together researchers, practitioners and policy makers in local government, where evidence is only one contributing factor to decision-making. Embedded researchers and knowledge brokers can help to ensure evidence is used by building understanding of the context, accessing existing, and co-producing new evidence. Intervention(s) of interest and the potential applications and anticipated benefits of the work: By the end of the project we will: 1. Increase research capacity and 'no how' in each LA, focusing on a local NCD priority issue, enabling access to evidence to inform local decision-making. We will develop and share learning which is generalisable across the UK 2. Build and support new partnerships for active and effective research use with practitioners, policy makers, and academia 3. Build knowledge and skills in local government and universities to maximise use of different kinds of evidence for policy, practice and public decision-making 4. Co-create evidence that addresses local government priorities, with a focus on prevention, by working across sectors and disciplines, utilising novel methodological approaches, including complex systems models 5. Develop a range of health and system interventions that have been co-produced and tested across LA areas 6. Create sustained change in research culture in LAs and academia so that evidence use is embedded across local government 7. Evaluate this new approach and methods to see if we made a difference to the health of people living in each area, related to their priority topic, and whether/how this approach could be rolled out across the UK We anticipate that this work will improve population health and wellbeing and increase the use of scientific research. It aims to improve quality, efficiency and effectiveness of public health interventions and services, reduce waste, and improve staff morale and retention. Consortium management: Our across-UK academic leadership brings together experience of applied translational research in prevention from four of the UKCRC funded Centres of Excellence in Public Health. Senior leaders in local government public health, bring practical experience of putting evidence into action. Other members have expertise in systems thinking, embedded research, knowledge brokerage and other skills essential to our success.