Some 5 million people live in flood risk areas in England and Wales, with one in six homes at risk of flooding. In India, similar risks are present: over 40 million hectares (12% of India's land mass) are prone to flooding and river erosion. In this century, the economic losses resulting from damage caused by flooding far outweigh the costs associated with other natural disasters ($21bn in losses from 27 instances in the UK, and $39bn in losses from 128 instances in India). Furthermore, both the frequency and intensity of pluvial and fluvial flooding is expected to increase over time due to climate change - increasing flood risk, financial loss and (human) fatalities. The UK has well-developed emergency planning processes and procedures, and yet there have been a number of recent cases of flooding where the emergency evacuation process has been stretched to its limits and beyond (e.g. Cockermouth and Carlisle). Earlier this year, the Indian Parliament put forward a national action plan under the Disaster Management Act with the aim of substantially decreasing the loss of life, livelihoods and assets, by improving the country's response to disasters. The plan highlights the urgent need for improved (predictive) warning, risk and threat identification and policy assessment, evacuation planning, data collection, information dissemination, cooperation and effective management of the relief operation. At the heart of the management of these issues is developing a good knowledge of the underlying communities and their infrastructure and the state of these endangered systems at critical times, particularly during the onset and development of the flooding event. The deployment and management of unmanned aerial systems (either vertical take-off and landing quad-rotors or small fixed wing aircraft) and of their data product coupled with advanced model prediction capabilities would seem to be a challenging but promising way of supporting emergency planning and management and testing the predicted and actual effects of policy decisions. The project focuses on using instrumented unmanned aerial systems (UASs) to collect and collate pertinent information about an unfolding flooding disaster. The relative ease with which UASs can be deployed (often hand launched) to assess damage across large areas provides emergency responders with the opportunity to assess the situation quickly, allowing the prioritisation of resources and their effective deployment where they are required. One aspect of the research will focus on addressing the challenges associated with flying UASs in such (non-ideal) situations: for example maintaining performance during adverse weather conditions, during intermittent loss of communication with the base station, overcoming the loss of operator visuals, providing the ability to recover the vehicle without a runway and avoiding potential collisions with unexpected obstacles within the flight domain. The project will also consider how the data can be combined with accelerated flood inundation models to generate detailed evacuation plans, and to predict the nature and progress of the flooding to improve allocation of emergency resources, build community flood resilience, save lives and reduce economic damage. The strategy will take into account both the physicality of the flood event itself and the social structures which are subject to the flooding. The concepts will be practically realised by the creation of a prototype decision support system to allow on-the-ground decision makers in the UK and India emergency coordination teams, or government agencies, to better understand the consequences of flooding to help them make timely and better informed decisions. We will also focus on engaging users and building capacity in India and the UK to integrate the use of UASs effectively into current flood response frameworks in a structured way to maximise the benefits they can provide.

Overview & Aim. This project will develop interdisciplinary research methods at the intersection of complex systems, violence, public health interventions, and data visualisation. We aim to evaluate the use of dynamic complex systems modeling to develop interventions for hard-to-reach populations affected by human trafficking and conflict-related violence. The project will address the following questions: What contributions can these novel methods make to the global response to human trafficking and conficlt-related violence? How can evidence-based, accessible and visually powerful complex systems models inform decision-makers working on interventions? Project Justification. Crises, population mobility, violence and exploitation cause deleterious health consequences for millions of individuals, particularly for refugees, low-wage migrant workers and victims of human trafficking [4, 8-10]. Currently, there is limited evidence on effective interventions for these marginalised groups. Scholars emphasise the causal complexity of violence and exploitation, however, most analytical approaches have erroneously assumed linear, average effects of exposures on single outcomes. Experimental approaches to test interventions are often unethical or unfeasible to implement among these hard-to-reach populations. Reductionist research methods, such as traditional epidemiological studies, dangerously oversimplify complex problems, which frequently results in wasted resources and potential harm to already vulnerable groups. Methods. We will invite experts in complexity science, violence research, public health and data visualisation to join the Complexity & Violence Research Network. This Network will jointly design a complex intervention case study that will serve as an evaluated 'proof of concept' for these methods. In brief, our methods will include the following steps: 1. Literature reviews on: 1) complex systems modelling for intervention development, 2) visualising complex systems, and 3) theoretical and epistemological underpinnings of complex systems methods. 2. Joint selection and design of an intervention case study using the Network's existent research on violence and other historical data, empirical data, and theory. 3. Calibrate, visualise and iterate a complex intervention model with dynamic multi-level interactions of exposures, associated harms, and simulated counterfactuals (e.g. intervention). 4. Collaboratively validate the model and evaluate the usefulness, feasibility and ethics of using complex systems methods for intervention development. Evaluation will include Network and Stakeholder reflections and critiques during small in-person meetings and a virtual two-wave Delphi Panel of funders and intervention developers to assess overall methods and usefulness. At every phase, we will critically examine and document the methodological and epistemological contributions, short-comings and risks, and best practice for adopting these methods in interdisciplinary research groups. Outputs. To contribute to our future work and advancements in the field, we will produce: -Academic papers on: 1) the case study findings; and 2) methodological recommendations -Lay guidance on the opportunities and limitations of these methods, with the aim of supporting intervention development, evaluation and policy decisions targeting populations affected by violence, conflict and human trafficking. -A web browser accessible version of the final case study model and visualisations to allow a wide user-audience to engage and play with the model inputs to understand how incorporating dynamic and complex characteristics of a system can explain causal mechanisms and potential effects of interventions. -Articulate future research priorities and identify funding opportunities to pursue longer-term sustainability of the Network and the development of future proposals.