Ecological and socio-economic factors impacting maintenance and dissemination of antibiotic resistance in the Greater Serengeti Ecosystem

Advances in antibiotic treatment are continually challenged by the evolution and dissemination of antibiotic resistance leaving medical practitioners with dwindling options for cost-effective therapies. Though the molecular scale mechanisms underpinning antibiotic resistance are generally understood, current understanding of how resistance persists at the population scale - the scale at which interventions must be planned and implemented - is weak. Critical to the development of effective public health and management tools is a unified understanding of the overall ecology of antibiotic resistance in both human and animal populations and the socio-economic factors that influence evolution and dissemination of antibiotic resistance. This project will gather data and build understanding that explicitly addresses this knowledge gap.

Our long-term goal is to identify the ecological and socio-economic drivers that contribute to maintenance and dissemination of antibiotic resistance. We will develop a community-scale model of antibiotic resistance epidemiology that integrates molecular and phenotypic data with ecological modeling, and use this model to investigate the relationship between ecological patterns of antibiotic resistance and socio-economic drivers.

This strategy of combining both ecological and socio-economic drivers will be applied to study antibiotic resistance traits amongst three host populations (human, livestock, and wildlife) and across three distinct ecological zones in Tanzania. We selected the greater Serengeti ecosystem for our study in part because (i) the close proximity and contact between potential reservoir populations provides a tractable system for developing models to test hypotheses that are relevant to both industrialized and resource-constrained countries; (ii) the local unregulated access to antibiotics provides a robust opportunity to test our central hypothesis (see below) in the presence of drug selection pressure; (iii) socio-economic conditions vary across space and time with on-going changes occurring in the region regarding adoption of new livestock production systems, greater reliance on tourism and growing human populations alongside antibiotic use patterns and human-animal interactions in rural communities; and (iv) the spread of antibiotic resistance in Tanzania is directly relevant to local communities. Because Tanzania is undergoing rapid urbanization, our findings will have implications for other countries experiencing similar socio-economic changes.

Using statistical and ecological modelling, we will determine the relative contribution of transmission pathways and ecological reservoirs to the persistence of antibiotic resistance in bacteria from humans and animal populations and integrate the contribution of community knowledge, attitudes and practices to model the socio-economic contribution to antibiotic resistance. By linking the ecological dynamics with the socio-economic survey data, we will be able to identify modifiable risks (e.g., antibiotic usage patterns, waste management, livestock management and contact patterns) and also predict the potential impact on resistance of changes in population mobility, socio-economic status and livestock production type. The understanding of behavioural drivers (e.g., knowledge, education and social affiliation) will guide the most appropriate modes of communication with stakeholders. Together, the biological, epidemiological and socio-economic analyses will allow development of a framework that incorporates technical, economic and social outcomes of drivers that promote and maintain antibiotic resistance. The framework will allow identification of positive, neutral and negative aspects of antibiotic use in communities to guide policy development in broader societal context of matching safe and stable food supply and sustainable livestock farming with human health.

We will develop a novel approach, extending the study of antibiotic resistance from the molecular to the community level, where resistance is least well understood, and focusing on broad patterns of resistance and dissemination of resistance to multiple communities, rather than on patterns of antibiotic resistance for specific pathogens.

Underpinning our approach is the use of ecological diversity measures to quantify the distribution of resistance - an approach pioneered by the UK applicants (Matthews, Haydon, Mather) and successfully applied to the analysis of antibiotic resistance patterns. Diversity of resistance phenotypes is quantified using a continuum of ecological diversity measures related to Rényi's entropy measures, that differentially weight the abundance of rare antibiotic resistance phenotypes. The resulting diversity profiles provide a population 'fingerprint' that allows robust comparison of diversity between populations.

For the current project we will develop mathematical models that capture the observed patterns of resistance and use them to test our hypotheses about the roles of antibiotic usage versus transfer of resistance within and between reservoir populations as drivers of the observed resistance patterns.

Our analyses will: (i) quantify the diversity of resistance profiles; (ii) characterise the connectivity of isolates across different communities and spatio-temporal scales; (iii) identify risk factors for resistance prevalence and diversity; (iv) develop simple dynamic models for the generation and transfer of resistance between populations, and; (v) link socio-economic variables to the modeling outputs to identify differences in household characteristics (e.g., socio-economic status, livestock type and production system) proximity to wildlife, antibiotic usage, and contact patterns that impact on the relative balance between generation and transfer of resistance, thereby identifying modifiable risks.

The beneficiaries and users of our research comprise:
- Doctors and veterinary practitioners
- Policy makers, including those in government and in NGOs
- Organisations that regulate trade, such as the FAO
- Pharmaceutical industries ie the producers of antibiotic drugs
- Livestock in developing and developed countries
- The public in developing and developed countries
- Post-doctoral researchers and PhD students employed on the project

In the short term, this research will be immediately useful to the Tanzanian communities being studied, providing local medical and veterinary practitioners the opportunity to advise the community on the avoidance of practices that enhance the spread of resistance. In the longer term, an improved recognition of the multiple routes by which resistance can enter communities could impact on prescribing practices in the developed world.

In the longer term, our research will ensure that policy makers, at international and national levels, in government and NGOs, will be better informed about the requirements for and scope of regulatory frameworks for antibiotic distribution. An improved understanding of the linkages between resistance in livestock and in humans will also allow organisations, such as the FAO, who are responsible for overseeing trade in animals and animal products to make better informed policy decisions.

Pharmaceutical industries will be able to make use of the work as it will help them identify the timescales and mechanisms over which pathogens may develop resistance, thus providing them with information about the length of commercial usefulness of their product, and the opportunity to improve labelling and other guidelines concerning the distribution and usage of their products.

Via our enhanced understanding of the mechanisms of persistence of antibiotic resistance, this project will inform the development of effective and practical intervention strategies, which will improve the health and welfare of both humans and livestock worldwide.

The PhD students and post-doctoral researchers trained during the course of this project will be specific beneficiaries of the project. They will have the opportunity to develop skills in the planning and implementation of a field study (in Tanzania), in molecular characterisation (WSU), mathematical modelling (Glasgow) and in the design and analysis of socio-economic surveys, the specific suite of skills selected being appropriate to their motivations, background and interests. The provision of such multidisciplinary training will help promote the long-term sustainability of interdisciplinary research. They will also gain transferable skills in project management, teamwork, document writing, communication and presentation, computer and programming skills and survey design and analysis.