Prof. Dean Everett

The ticking time-bomb: The hidden extent of the AMR landscape and the potential untreatable hospital ESKAPE infections across the UAE: A Phenotypic and Genotypic profiling and mapping study.

In 2020, the World Health Organization (WHO) announced its top global health challenges (https://www.who.int/news-room/photo-story/photo-story-detail/urgent-health-challenges-for-the-next-decade). Of the 13 threats to humankind identified up until 2030, 5 were infectious disease related and 1 specifically Antimicrobial Resistance (AMR) related. AMR is one of humankind’s biggest global challenges. 

This study will i) Retrospectively define AMR phenotypic and genotypic diversity over a 14-year period (2010-2024) across ALL major pathogens; ii) Characterize genomic-determinants of antimicrobial resistance of these isolates and undertake expanded sensitivity screening beyond currently available antimicrobials in order to inform local and national future treatment policy; iii) Prospectively define the prevalence of ESKAPE pathogens in adult and pediatric in-patients admitted to hospitals across the UAE and to trace cases back to the community; iv) Identify the source and/or spread of infection and/or hotspots; v) Employ whole genome sequencing to assess dissemination of AMR clones within the population and by demographics; vi) Assess antibiotic consumption and correlate this to antimicrobial resistance profiles to inform local policy of antibiotic use; vii) Assess temporal-spatial contexts for these key pathogens in the UAE through molecular epidemiological analyses to find out how they are contributing to local and global rising trends of antimicrobial resistance; and viii) Define clinical associations and outcome of AMR infection.

The Abu Dhabi Brain Infection Study 

Brain infections and particularly, clinical meningitis, remains a significant global health concern. Despite vaccinations being readily available for a number of associated pathogens, it is associated with high case-fatality, outbreaks and leads to lifelong disability among survivors. Timely appropriate diagnosis and treatment to avoid death and disability is crucial. In the MENA region there remains limited meningitis data reported and even less research undertaken. Published data on meningitis remains scarce in the United Arab Emirates (UAE), with no new studies since 2007. Our study will generate significant data that will contribute to prevention, treatment and elimination of bacterial meningitis as well as reduce morbidity and mortality from clinical meningitis cases - all in support of the WHO Roadmap to Defeat Meningitis by 2030.

This study will (i) Define the clinical and genomic epidemiology of meningitis in Abu Dhabi; (ii) Develop prognostic imaging markers for causative pathogens relevant to this setting; (iii) Identify the localization of the most vulnerable brain regions to meningitis; (iv) Describe mechanisms of pathogen invasion across the blood-brain barrier; (v) Determine the association of inflammatory and other immunologic factors with meningitis pathogens; and (vi) Identify genomic markers associated with invasion of the blood-brain barrier, through the use of comparative genomics.

Abu Dhabi Pregnancy Risk Assessment Monitoring System (AD-PRAMS)

AD-PRAMS is a population-based surveillance system that provides information on women that have recently given birth and their newborn. AD-PRAMS is a partnership between the Early Childhood Authority (ECA), The Abu Dhabi Public Health Center (ADPHC), and Khalifa University College of Medicine and Health Sciences. The goal of AD-PRAMS is to provide information that will help improve the health of mothers and babies, and to reduce the number of infant deaths in Abu Dhabi. It will sample >10% of Abu Dhabi births and plans to collect data on at least 3600 mothers and their child every calendar year. 

One Health AMR Molecular Biosecurity Programme

The development of antimicrobial resistance (AMR) is one the of the top 10 global threats to human health in the 21st Century. The One Health AMR Programme will combine cutting-edge metagenomic technologies applied at scale with innovative AI and big data epidemiology approaches to implement a world first molecular One Health epidemiological analysis of AMR at a national scale. This world leading project will pioneer the molecular epidemiological approach to One Health AMR. This will enhance national health biosecurity in the UAE and lead global thinking implementation of the One Health approach. Innovative data mining of metagenomic data will demonstrate proof of concept for metagenomic data to address wider human health and societal challenges. Project outputs will feed directly into the UAE AMR National Action Plan and provide international policy guidance.

Deciphering the impact of mask and other non-pharmacological interventions on epidemiology and seasonality of Influenza

Human Influenza viruses cause significant morbidity and mortality worldwide. They are the major cause of acute respiratory diseases in humans, causing several serious global pandemics because of their transmission dynamics and great antigenic variability. Pandemic influenza is usually caused by influenza A virus, due to its rapid antigenic variation, strong replication capacity, and transmission ability associated with genetic reassortment. Influenza B virus, often neglected, has been circulating and, in some seasons, has predominated over influenza A, particularly among children. Vaccines against influenza A/H1N1 and A/H3N2 have been used effectively for more than 20 years for controlling and preventing potential pandemics.

The overall aim of this study is to utilize the already in place outstanding influenza virus sentinel surveillance system in UAE to fully characterize that population both clinically and demographically and use this information to define the impact of Covid-19 prevention measures on Influenza. The study will i) Define the impact of Mask and other non-pharmacological interventions on epidemiology and seasonality of Influenza; ii) Characterize incoming and circulating influenza strains; iii) Define genomic and epidemiological associations with circulating viruses; and iv) Create and test epidemiological models of influenza for future public health surveillance and interventions.