Diarrhoeal disease remains a major cause of child morbidity, growth faltering and mortality in low and middle income countries (LMICs), with Campylobacter among the most common causes. The major infection sources in the UK include contaminated food, but transmission routes in LMICs are unknown. This means that transmission among the children at highest risk (85% infected before 1yr in LMICs) is the least studied. House crowding, cohabitation with animals and poor sanitation/food safety are all potential risk factors, but effective interventions depend upon quantitative estimates of infection sources. So why is Campylobacter largely overlooked in LMICs? While the answer to this question, in part, relates to the perceived sub-clinical sporadic nature of infection and difficulties in culturing microaerophilic bacteria, a more unsettling reason is that the countries where people are at the greatest risk have low economic and development status. This realisation led to my decision to devote future research, and the knowledge and resources I have developed, to combat Campylobacter where my skills are most needed, in LMICs.
The epidemiology of campylobacteriosis is poorly understood in LMICs. In pilot studies, we have identified genomic variation in strains that may indicate differences in source, survival, transmission and virulence (compared to the UK). In particular, we have identified globally and locally distributed strains, evidence of within household spread and strains associated with asymptomatic infection and infection with other enteropathogens. Genome sequencing technologies and bioinformatics analysis provide a means for explaining these cryptic disease networks by identifying differences between strains from multiple sources, and tracking their transmission. However, the effective implementation of genomic source attribution relies not only on advanced comparative genomics techniques, but also the deployment of an appropriate sample frame and access to microbiology laboratories. To achieve this I have developed a network of collaborators, through several visits to Africa, that can undertake the required multicentre sampling (consistent with previous national-scale studies) including both broad cross-sectional sampling and sentinel site surveillance allowing calculation of the overall Campylobacter burden as well as case-control comparison to quantify asymptomatic infection. Information will feed into source attribution and monetised decision support models, to allow informed assessment of risk and targeted intervention through public health contacts. If funded, I will re-locate to The Gambia for 3-6 months of each year, at my own expense.
Building on an established collaborative network in the UK and Africa (The Gambia, Ghana, Burkina Faso), we will develop a program of globalized Campylobacter NGS surveillance. Specifically, we will: (i) sample and genome sequence thousands of isolates from animals, food, environmental sources and people (symptomatic, asymptomatic, and matched cases and controls); (ii) develop open-access databases and novel analysis pipelines (association study and machine learning) to characterize Campylobacter population structure and identify source attribution markers; (iii) quantify the relative contribution of different human infection sources; (iv) use a cost-benefit risk models to identify the most effective interventions in the transmission network. This evidence-based approach will enable effective local public health and policy interventions and focus efforts to reducing the burden of diarrhoeal disease in Africa.