DOI: 10.25934/pr00009029
title: Data Challenge - Ten-year Trends In Antimicrobial Resistance Amongst Pathogens Isolated From Clinical Samples.

description: My name is Egunjobi Tunde, and I am very interested in participating in the Vivli AMR Surveillance Open Data Re-use Challenge, funded by Wellcome. I have been an Advocate of Antimicrobial Stewardship in my local community and on Social Media for about a decade now, and this Data Challenge is a step in the right direction. Other related researches particularly in the Area of AMR that I have been involved in can be found on ResearchGate and Orcid.  

The outcomes of the proposed study could help:
1. Track resistance frequency. This would make it easier to communicate a location's current level of resistance and allow for more appropriate treatment decisions. Such a surveillance report would inform public health professionals of emerging pathogens and encourage the adoption of control measures.

2. Promote context-specific antimicrobial stewardship programs. This is critical because the factors that contribute to the spread of AMR differ based on location. Intravenous to oral switch therapy, education regarding AMR, policies for infection prevention and control, policies for antibiotic quality control, increased microbiology laboratory capacity, and the creation of a national action plan are a few examples of these programs.

3. Guide legislators in Passing laws regulating the use of specific antibiotics and ensuring the proper removal of these antimicrobials from hospital systems to stop pathogens found in the soil, like Acinetobacter, from acquiring resistance in the environment.

The ability of the healthcare provider to prescribe more effectively would be greatly improved by making the study's data available to them. The results of this proposed study would ultimately help save lives and lower the financial burden of healthcare.

Aim:
To determine the Ten-year trends in antimicrobial resistance (AMR) amongst pathogens isolated from clinical samples.

Objectives:
1. To determine the trends in AMR amongst pathogens isolated from clinical samples by year.

2. To determine the trends in AMR amongst pathogens isolated from clinical samples by types of sample.

3. To determine the trends in AMR amongst pathogens isolated from clinical samples by organisms.

4. To determine the trends in AMR amongst pathogens isolated from clinical samples by antimicrobial agents.

5. To determine the trends in AMR amongst pathogens isolated from clinical samples by patients' sex.

6. To determine the trends in AMR amongst pathogens isolated from clinical samples by patients' age.

Hypotheses:
1. H1: The burden of AMR increases yearly.

2. H1: The rate of isolation of resistant pathogens is more in certain clinical samples.

3. H1: Antimicrobial resistance is found more among certain organisms.

4. H1: Microorganisms show resistance more to certain antimicrobial agents.

5. H1: The burden of AMR is high among male patients.

6. H1: The burden of AMR is high among the paediatrics.

Statistical Analysis:
Data received will be sorted by year, type of clinical sample, organism, antimicrobial agent, and patients' demographics (if available). The data will be analyzed using Epi Info 7.2. and/or SPSS (Statistical Package for the Social Sciences). Categorical variables will be presented as percentages and Continuous data as mean ± standard deviation (where applicable). A P-value less than 0.05 will be considered significant.

Please feel free to contact me via email at tunde.egunjobi@iuokada.edu.ng. I look forward to hearing from you! Thank you for your time and consideration.

Best Regards,
Egunjobi Tunde