Insights into COVID-19 data collection and management in Malawi: exploring processes, perceptions, and data
Amelia Taylor1, Thokozani Liwewe2, Jim Todd3
1Malawi University of Business and Applied Sciences, Blantyre, Malawi.
Wellcome Open Research
|August 8, 2024
Summary
COVID-19 surveillance data quality in Malawi was hampered by form design flaws and process issues. Improving form usability and training is crucial for accurate disease surveillance and public health insights.
Area of Science:
- Public Health
- Epidemiology
- Health Informatics
Background:
- COVID-19 surveillance in Malawi relied on case-based forms, but data gaps and inconsistencies impacted usability.
- Significant efforts were made, yet national data quality remained suboptimal.
Purpose of the Study:
- Investigate COVID-19 data collection and reporting processes in Malawi.
- Explore health workers' perceptions of data collection tools and processes.
- Identify factors contributing to data quality issues in surveillance.
Main Methods:
- Conducted Focus Group Discussions and In-Depth Interviews with 75 healthcare professionals.
- Collected views on surveillance form effectiveness, data collection processes, and training needs.
- Utilized MAXQDA for thematic and document analysis.
Main Results:
- Form design issues and challenges with case definitions accounted for 44% of data quality problems.
- Data collection process concerns and training gaps comprised 49% of identified issues.
- Language, privacy, ethical, and cultural factors also impacted data quality.
Conclusions:
- Data quality is intrinsically linked to the design and use of surveillance forms.
- Deficiencies in form format, field order, and lack of guidelines led to errors.
- Reviewing form design is essential for effective integration into surveillance systems.
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