In the 21st century, AMR has now emerged to be one of the greatest global concerns due to the rapid growth of AMR infections rate that overwhelmed the discovery of new antibiotics to annihilate the resistance. The World Bank estimates that AMR could result in US$ 1 trillion additional healthcare costs by 2050 and US$ 1 trillion to US$ 3.4 trillion gross domestic product (GDP) losses per year by 2030 with the low-income countries in Africa to be most impacted. Given the increasing reports of resistance in both mainstream media and scientific literature, we aim to use Vivli datasets to identify clinical pathogens that are showing high resistance and also have high burden in Africa. Once identified, we will use a reverse vaccinology approach to determine potential vaccine targets for the species with the most prevalent antimicrobial resistance and burden using publicly available whole genome sequences from Africa. One of the most promising ways of curbing antimicrobial resistance is developing vaccines. Although both drugs and vaccines pressure pathogen populations to evolve resistance, drug resistance is common while vaccine resistance is rare. This is due to two main factors: vaccines work prophylactically and target multiple pathogen sites, while drugs work therapeutically and target few. This results in less variation and fewer opportunities for pathogens to develop vaccine resistance. Ultimately, we aim to create an online publicly available repository site that curates potential vaccine targets for major clinically implicated and emerging pathogens. We hope this resource will aid researchers and pharmaceutical industries by scaling down the time needed to develop vaccine, thus helping keep the emergence and spread of antimicrobial resistance at bay.
Center for Global Research Data