Antimicrobial resistance (AMR) is one of the most serious and rapidly growing public health threats in the world today and already accounts for hundreds of thousands of deaths each year. The problem of AMR is particularly severe in many developing countries in Southeast Asia where regulation and biocontainment measures are limited and levels of antibiotic use in both human populations and animal production systems are high .
While the transmission of AMR in hospital settings has been studied intensively , outside hospital settings our understanding of how antibiotic use selects for resistance in many important bacterial pathogens is far more limited. For bacteria colonizing humans, direct use of antibiotics to treat infections is a major driver of AMR, and indirect exposure to antibiotics and antibiotic-resistant bacteria associated with animal production systems may, in some settings, play an important role (e.g. through direct contact with animals, preparation and consumption of foods of animal origin, and environmental dissemination through animal waste). Such exposures are likely to be highly variable in space and time. Simple models suggest that not just total volume of antibiotic use but spatial and temporal patterns of antibiotic use can be important determinants of the emergence, spread and maintenance of resistance.
This DPhil project, which will be based at the Oxford research unit in in Thailand (Mahidol Oxford Tropical Medicine Research Unit, MORU), will look at how these heterogeneities impact on the evolutionary and ecological dynamics of AMR. The project, which will focus in AMR in Enterobacteriaceae, will make use of rich local data sources to inform the development of mechanistic mathematical models for the spread of AMR within human populations, accounting for important heterogeneities in contact patterns and patterns of antibiotic exposure. The student will develop models and use them to evaluate the likely effect of interventions to reduce unnecessary antibiotic use (e.g. through vaccination against respiratory pathogens , education, and improved sanitation).
We will provide a comprehensive in-house training programme in advanced mathematical and statistical modelling techniques. There will also be opportunities to attend relevant external short courses.
The research will be will be highly collaborative in nature and will involve interactions with veterinarians, microbiologists, pharmacists, modellers, statisticians and epidemiologists.
The project also benefits from extensive collaborative links both with other Oxford researchers and departments and internationally. Students will be expected to publish their work, present findings at international meetings, attend local and external training courses, and attend weekly group meetings, journal clubs and departmental seminars.
This DPhil project would be suitable for a highly motivated student with excellent quantitative skills, strong computer programming ability and a passion for understanding complex biological systems.
Project reference number: 989
|Professor Ben Cooper||Tropical Medicine||Oxford University, Bangkok||THA||Ben@tropmedres.ac|
|Assistant Professor Wirichada Pan-ngum||Tropical Medicine||Oxford University, Bangkok||THAfirstname.lastname@example.org|
|Professor Nicholas PJ Day FMedSci FRCP||Tropical Medicine||Oxford University, Bangkok||THAemail@example.com|
Southeast Asia, a vibrant region that has recently undergone unprecedented economic development, is regarded as a global hotspot for the emergence and spread of antimicrobial resistance (AMR). Understanding AMR in Southeast Asia is crucial for assessing how to control AMR on an international scale. Here we (i) describe the current AMR situation in Southeast Asia, (ii) explore the mechanisms that make Southeast Asia a focal region for the emergence of AMR, and (iii) propose ways in which Southeast Asia could contribute to a global solution. Hide abstract
is an important and increasing cause of life-threatening disease in hospitalized neonates. Third generation cephalosporin resistance (3GC-R) is frequently a marker of multi-drug resistance, and can complicate management of infections. 3GC-R is hyper-endemic in many developing country settings, but its epidemiology is poorly understood and prospective studies of endemic transmission are lacking. We aimed to determine the transmission dynamics of 3GC-R in a newly opened neonatal unit (NU) in Cambodia and to address the following questions: what is the diversity of 3GC-R both within- and between-host; to what extent is high carriage prevalence driven by ward-based transmission; and to what extent can environmental contamination explain patterns of patient acquisition. We performed a prospective longitudinal study between September and November 2013. Rectal swabs from consented patients were collected upon NU admission and every 3 days thereafter. Morphologically different colonies from swabs growing cefpodoxime-resistant were selected for whole-genome sequencing (WGS). One hundred and fifty-eight samples from 37 patients and 7 environmental sites were collected. 32/37 (86%) patients screened positive for 3GC-R and 93 colonies from 119 swabs were successfully sequenced. Isolates were resistant to a median of six (range 3-9) antimicrobials. WGS revealed high diversity; pairwise distances between isolates from the same patient were either 0-1 SNV or >1,000 SNVs; 19/32 colonized patients harbored colonies differing by >1000 SNVs. Diverse lineages accounted for 18 probable importations to the NU and nine probable transmission clusters involving 19/37 (51%) of screened patients. Median cluster size was five patients (range 3-9). Seven out of 46 environmental swabs (15%) were positive for 3GC-R Environmental sources were plausible sources for acquisitions in 2/9 transmission clusters, though in both cases other patients were also plausible sources. The epidemiology of 3GC-R was characterized by multiple introductions, high within- and between host diversity and a dense network of cross-infection, with half of screened neonates part of a transmission cluster. We found no evidence to suggest that environmental contamination was playing a dominant role in transmission. Hide abstract
BACKGROUND: Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly. METHODS AND FINDINGS: We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups. CONCLUSIONS: Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries. Hide abstract