The Burden of Antimicrobial Resistant Infections in Wales: a population-level modelling analysis

Background

Antimicrobial Resistance (AMR) threatens the sustainability of an effective, global public health response to infectious disease. This study uses routine surveillance data to estimate the public health burden (PHB) of AMR infections in Wales for the period 2017-19, with further stratification by Age, Sex, local Health Board (HB) area and relative deprivation, to guide public health action.

Methods

Welsh AMR Surveillance data, collected as part of the European AMR Surveillance Network (EARS-Net), was collated for the period 2017-19. Adapting the methodology of the European Centres for Disease Control Burden of Communicable Diseases in Europe (BCoDE), we modelled the PHB of five types of antibiotic-resistant infection (invasive and non-invasive), and 7 pathogens which associated with AMR, using the Burden of Healthcare-Acquire Infection (BHAI) R package. Postcodes were used to assign patients' resident health board, as well as their relative socio-economic deprivation, using the Welsh Index of Multiple Deprivation (WIMD).

Results

Preliminary results (median estimation with 95% confidence interval (CI)) were calculated for: number of infections with AMRnumber of deaths attributable to AMRnumber of DALYs attributable to AMR

Estimates were stratified by age; sex; HB; relative deprivation; and pathogen and infection type.

Conclusions

This is the first study of its kind to study the relationship between AMR incidence and relative deprivation. It offers a clear picture of the epidemiology of AMR within Wales to support public health action.

Key messages

Infections from AMR bacteria represent a major PHB in Wales, and the modelling PHB of AMR by socioeconomic group and local area can inform effective public health action. The results of this study are valuable for guiding public health action to address AMR at the national and international level.

Molecular dynamics simulation analysis of conessine against multi drug resistant Serratia marcescens

Ornithine decarboxylase (ODC) is an immediate precursor of polyamine biosynthesis in Serratia marcescens and a potential target for inhibition of its growth. We predicted the 3D structural conformation of ODC enzyme and validated it using MDS in our previous study. In this current study, the potential inhibitors of ODC were obtained by virtual screening of potential inhibitors from ZINC database and studied in depth for their different binding pose. Among the ten virtually screened inhibitors, Conessine exhibited the best binding with ODC and its inhibition property was studied further by MDS studies. The natural compound conessine is isolated from plant Holarrhena antidysenterica and it is studied against ODC of Serratia marcenses for its inhibitory potentials. This revealed unforeseen twisted position in root mean square fluctuation (RMSF) and ODC modelled conformation that influenced ligand binding. Both predicted model and ligand bound model were compared and found to be stable with Root Mean Square Deviation (RMSD) of approximately 7 nm and 0.25 nm to that of crystallographic structure over simulation time of 55 ns and 70 ns respectively. This work paves the way for future development of new drugs against nosocomial diseases caused by Serratia marcescens.

The impact of personalized medicine of Type 2 diabetes mellitus in the global health context

Advances in the fields of genomic sciences have given rise to personalized medicine. This new paradigm draws upon a patient's genetic and metabolic makeup in order to tailor diagnostics and treatment. Personalized medicine holds remarkable promises to improve prevention and management of chronic diseases of global relevance, such as Type 2 diabetes mellitus (T2DM). This review article aims at summarizing the evidence from genome-based sciences on T2DM risk and management in different populations and in the Global Health context. Opinions from leading experts in the field were also included. Based on these findings, strengths and weaknesses of personalized approach to T2DM in a global context are delineated. Implications for future research and implementation on that subject are discussed.