Support AMR Data Analysis Using R Software
Support AMR data analysis using R software and deliver actionable insights.
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Overview
Support AMR data analysis using R software and deliver actionable insights.
You have:
- Experience in public health, microbiology, epidemiology, nursing, medicine or allied sciences, or data science.
- Proficiency in R programming, especially in data cleaning, visualization, and statistical analysis.
- Familiarity with the AMR R package and its application in health data.
Contract
This is a UNV contract. More about UNV contracts.
With WHO’s support, many hospitals in the Eastern Mediterranean Region are collecting antimicrobial resistance (AMR) surveillance data, but much of it remain underutilized. By volunteering, you will help transform raw data into actionable insights that can guide clinical practice and public health decisions.
This assignment gives you the opportunity to apply your R programming and data analysis skills to a real-world global health challenge. You will also learn from WHO experts and collaborate with professionals across the region, enhancing your experience in AMR and public health data systems.
The three online volunteers will work under the guidance of AMR/IPC Unit Medical Officer, WHO Eastern Mediterranean Regional Office, and willl :
Clean and structure AMR surveillance datasets from selected hospitals.
Generate analytical outputs (tables and visualizations) using the AMR R package.
Summarize key AMR trends and findings in short reports.
Provide virtual support sessions for national focal points and hospital staff on using R for AMR data analysis.
Document the workflow for capacity building and future use.
Final Deliverables:
Cleaned and structured AMR surveillance datasets from selected hospitals.
Analytical outputs using the AMR R package (https://amr-for-r.org/), including tables and visualizations.
A summary report highlighting key AMR trends and findings.
Virtual support sessions for national focal persons and hospital staff on using R for AMR data analysis.
Documentation of the analysis workflow for future reference and capacity building.
Requirements:
Background: Experience in public health, microbiology, epidemiology, nursing, medicine or allied
-Experience in public health, microbiology, epidemiology, nursing, medicine or allied sciences, or data science.
- Proficiency in R programming, especially in data cleaning, visualization, and statistical analysis. -
- Familiarity with the AMR R package and its application in health data.
Potential interview questions
| Can you describe a situation where you used R for data cleaning and the impact it had? | This question assesses your practical experience with R and how it contributes to public health outcomes. | Discuss a specific project, your role, the challenges faced, and the resulting benefits. |
| What strategies do you employ to summarize key trends in large datasets? | Understanding data summarization is crucial for analyzing AMR trends. | Pro members can see the explanation. |
| How do you ensure the datasets you work with are clean and structured? | Pro members can see the explanation. | Pro members can see the explanation. |
| Can you share your experience with documenting analytical workflows for future use? | Pro members can see the explanation. | Pro members can see the explanation. |
| Describe a time you provided support sessions for non-technical users in data analysis. What approach did you take? | Pro members can see the explanation. | Pro members can see the explanation. |
| What challenges have you faced when visualizing data for reporting purposes? | Pro members can see the explanation. | Pro members can see the explanation. |
| How do you stay updated with the latest developments in AMR and related analytical tools? | Pro members can see the explanation. | Pro members can see the explanation. |
| What role does teamwork play in successfully analyzing AMR data? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 9 months ago
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Updated 8 months ago
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Source:
unv.org
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