Bridging the gap

Gather vital community-based antibiotic usage data with our open source healthcare tools.

In South Africa, while hospitals have formal antimicrobial surveillance, community-level antibiotic prescriptions, accounting for up to 80% of total usage, lack such monitoring, leading to data underrepresentation. From 2000 to 2010, human antimicrobial consumption surged by 35%, with BRICS countries contributing to 76% of this increase. Moreover, about 60% of acute respiratory infections are treated with antibiotics unnecessarily, underscoring the need for precise data. Community health data collection is challenging due to its non-electronic, decentralized nature, especially in LMICs, relying on resource-intensive methods that seldom produce long-term data.

The Trinity Challenge on Antimicrobial Resistance 

Vikelani was created as a solution to the 2024 Trinity Challenge. By layering healthcare management tools with built-in anonymised antimicrobial-use data collection, Vikelani seeks to gather community-related data on antimicrobial resistance patterns. These data can guide local prescription habits, enable research and be used to influence antimicrobial guidelines and healthcare policy. The solution will be submitted at the end of February 2024.
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Open-source - built on Django, the secure and scalable Python framework
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Free-to-use - the software is free to run with a simple registration and onboarding process
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Rich anonymised datasets - analyse the data we generate with Google's LookerStudio (or use your own analysis software).

Our Solution

Our solution seeks to provide tools that healthcare workers will use for their own sake during routine clinical care to reduce workload and costs, but have the added benefit of generating community-based antibiotic use data.

While hospitals benefit from formal antimicrobial surveillance, up to 80% of antibiotics in South Africa are prescribed at the community level where such surveillance is rare (Brink, 2016). Communities are thus sorely underrepresented when it comes to antimicrobial use data, a concerning situation as antimicrobial use for human consumption increased by 35% between 2000 and 2010 with BRICS countries accounting for 76% of this change (Van Boeckel, 2014). It is additionally estimated that 60% of acute respiratory tract infections are unnecessarily treated with an antibiotic, again highlighting the importance of accurate use data in this setting.

The disparity in available data between hospital- and community-based health practice is because community health data is rarely electronic or centralised, particularly in LMICs. Currently, collection of community antibiotic use data relies on dedicated programs including surveys, exit interviews and antibiotic sales data (Do, 2021). However, such programs require staff, funding, sustained healthcare system engagement and rarely generate longitudinal data.

Our solution seeks to provide tools that healthcare workers will use for their own sake during routine clinical care to reduce workload and costs, but have the added benefit of generating community-based antibiotic use data.