Opening the World Cancer Congress in Paris in November 2016, President François Hollande insisted that women should be at the heart of cancer control, “because they are victims of inequality in access to prevention, treatment and screening in every country in the world.” Breast, ovarian and cervical cancers are a major public health problem world-wide. Each year, approximately 2.5 million women are diagnosed with one of these cancers, and 900,000 women die from them, mainly in low- and middle-income countries. The CONCORD programme for global surveillance of cancer survival reported striking differences in survival from these three cancers. Population-based cancer survival is a key measure of the overall effectiveness of health systems in dealing with cancer, from early diagnosis to comprehensive investigation and optimal treatment. I will exploit the CONCORD data base, as follows: • Access primary medical records in selected high- and low-income countries to collect more detailed data on stage at diagnosis, staging investigations, morphology, grade, prognostic bio-markers and treatment, for the most recent year during 2010-2014 for which data are available • Analyse the distributions of stage and treatment (“patterns of care”) • Estimate 1- and 5-year survival trends by stage, histological group and/or molecular subtype • Quantify inequalities in survival as the number of premature deaths that would be avoidable if survival in a given country (region) were equal to that in a neighbouring country with higher survival. This ground-breaking work will show that it is possible (a) to collect high-quality, complete clinical information at population level even in low- and middle-income countries; (b) to explain the striking inequalities in women’s cancer survival world-wide, and (c) to summarise these inequalities in a single number (avoidable deaths) as a powerful tool that motivates policymakers to reduce inequalities in survival.

A rapidly growing body of studies attribute mortality outcomes to thermal exposures, by empirically estimating reduced-form mortality responses to meteorological fields, usually ambient temperature. The research theme proposed in this project is motivated by the awareness that the human thermoregulatory system is a function of not just ambient temperature, but also other environmental parameters such as humidity, radiant temperature and wind. Correct characterization of the environment-related mortality relationship is vital not just in epidemiology, but also for climate-health impacts assessment, understanding the burden on health services, and the potential spill overs to labour productivity and the wider economy. This project will attribute mortality risk to multiple thermal stressors not previously examined in epidemiology and the wider climate-health impacts studies. The project will apply innovative approaches and for the first time, a comprehensive suite of thermal discomfort indicators, both under present climate and contrasting future socio-economic/climate scenarios. The transdisciplinary nature of the project requiring knowledge and training in subjects such as biostatistics, environmental epidemiology, human biometeorology, big data and climate modelling; will involve two-way transfer of knowledge between the researcher and the host institute. Results have the potential to: (i) improve the data and modelling approaches applied in existing environment-related morality studies at a global scale; (ii) facilitate better understanding of the population’s adaptive capacity to thermal exposures, accounting for age and gender; (iii) inform future public health responses at various national/international scales, such as urban planning, healthcare services, and investments in energy-health adaptation; and (iv) assist in government initiated National Adaptation Programmes. The project is in line with the broader EU strategy for ‘Climate, Environment and Health’.

What is Tuberculosis (TB)? How does a person go from infection to disease, and what does this mean at the population level? For a disease that has caused over two billion deaths in human history, and is the biggest cause of death from an infection today, the natural history of TB remains stubbornly elusive. In this ERC award I will challenge current paradigms by exploring the implications of new empirical insights from basic science on our understanding of TB epidemiology and its control using mathematical modelling techniques. My hypothesis is that the prevailing paradigm of TB natural history is overly simple, and one of the key drivers of inaccuracy in projections made by mathematical models thus far. Current models of disease typically account for two distinct stages of infection and disease, with mostly one-directional progression between them. Instead, data has shown that individuals experience a range of stages of disease intensity. Moreover, over time individuals can move between stages through a dynamic interplay between immune induced repression and disease progression. In this ERC award I will first focus on collating the best available data to parameterize a new mathematical model of TB with unprecedented flexibility to capture the required trends. I will settle on the best model structure and understand its behavior. In the second stage, I will use the model to explore critical questions in two areas of TB research that require the detail of the new paradigm: the challenge of addressing latent tuberculosis infection; and incorporating the impact of changes in socio-economic indicators on TB trends. The consequences of such a paradigm shift to better reflect new insights from basic science and epidemiology are important. Initial modelling of intermediate disease states and the potential for progression and regression suggests that the projected impact of diagnostic strategies is substantially reduced, both in the immediate and longer-term.

Secretion systems are evolved machineries enabling bacteria to deliver toxins and virulence factors, called effectors, into target cells to enable the onset of infectious diseases. Uncovering these effectors is essential for the understanding of bacterial pathogenesis and the establishment of appropriate therapeutic strategies to tackle infectious diseases. The recently identified Type Six Secretion System (T6SS) is conserved in environmental and pathogenic Gram-negative bacteria. The T6SS is an organelle structurally akin to an intracellular and membrane-bound contractile phage tail used for the delivery of toxins into prokaryotic and eukaryotic target cells. The importance of this system in the context of infection is highlighted by its ability to not only target eukaryotic cells during bacterial infection, but additionally to target other bacteria co-infecting mammalian and plant hosts. Despite the recent advances made in understanding the mechanisms underlying the T6SS dynamic, very little is known about the T6SS effectors repertoire used by life-threatening pathogens, such as Burkholderia pseudomallei, and for which, vaccine strategies are currently unavailable. In the proposed research, a combination of high-throughput and cross-disciplinary technologies will be used to uncover and characterise novel T6SS effectors in B. thailandensis, a surrogate organism closely related to B. pseudomallei. This will 1) identify new T6SS effectors targeting eukaryotic cells, using a reporter-based transposon screening and 2) identify novel T6SS toxins targeting prokaryotic cells, using a genome-wide saturation mutagenesis strategy. The outcomes of the proposed research will identify the key cellular stages hijacked by the T6SS during the infection of a host, while exposing potential new bacterial targets exploitable for the development of novel antimicrobial strategies.