HealDaawo

International Rescue Committee Inc. (IRC)

HealDaawo

A mobile platform to track substandard antibiotics, creating a first-ever national database on counterfeit medicines and supporting policy development

IRC Somalia is formally registered in Somalia, and our main solution team is based in Mogadishu. The solution’s team will be supported by technical advisors based in IRC’s regional office in Nairobi, and IRC’s global headquarters in New York.

SOM

Nonprofit

Somalia faces widespread availability of substandard and falsified (SF) antimicrobials in the private sector. In the absence of centralized oversight and consistent quality control, antimicrobials are commonly sold in informal markets and small pharmacies—often without prescriptions, standardized labeling, or secure supply chains. This fragmented system makes it difficult for healthcare providers and communities to verify the quality or intended use of the antibiotics they rely on. These gaps contribute to ineffective treatments, medicine misuse, and the growing threat of AMR.  Despite the scale of the problem, Somalia lacks a systematic way to detect, document, or track SF antimicrobials. Community pharmacies, drug sellers, and health workers have no tools to identify questionable products, and policymakers lack the data needed to guide regulatory action or policy reform.  Through IRC’s research and programming in South Sudan and Yemen, we have found this to be a region-wide issue, not limited to Somalia. However, Somalia presents a viable and urgent starting point for piloting a community-led, data-driven solution to identify and understand the spread of SF antibiotics. The work is designed for regional expansion, with next steps planned regionally for countries where IRC works and cross-border efforts can be furthered in Ethiopia. 

IRC is adapting a Somali-led data platform to track substandard drug sales and tackle antimicrobial resistance. The mobile app will be introduced in Somalia for the first time, using data from community pharmacies, healthcare workers, and sellers. The data will include images of antimicrobials sold in the private market (pills and packaging) with metadata (geolocation, type of seller, description), supplemented by laboratory testing of selected pills, and will be displayed on a dashboard (data will be anonymized). The dataset will be used to repeatedly train an AI-driven Vision Language Model (VLM) to identify counterfeit medicines, improve predictive tools, and inform policy. It will ensure seller identities are protected and trust is maintained in the pharmaceutical supply chain. Findings will be displayed on a secure, anonymized dashboard for Somalia’s MoH and AMR researchers. This solution supports a robust, trust-based surveillance model, informed by Institutional Review Board (IRB)-approved AMR research and validated Knowledge, Attitudes, and Practices (KAP) tools for community members and health workers developed in Yemen and South Sudan on community use of antimicrobials, including counterfeit medications. It also protects seller identities to avoid backlash while informing national regulations and laying the groundwork for future regional AMR intervention strategies.

End users: WHO reports nearly one million deaths annually due to prescription of substandard medications. In Somalia, years of prolonged conflict have weakened pharmaceutical regulation, resulting in 70% of medicines being unregulated. This has facilitated the spread of substandard and falsified (SF) drugs, which pose significant health risks. Our mobile app aims to empower community pharmacists, healthcare providers, and drug sellers to identify and report these unsafe medications, ensuring safer consumption and reducing prescription-related mortality rates. In addition, IRC will also conduct awareness campaigns and training sessions to educate healthcare providers on the dangers of substandard medicines and promote responsible purchasing practices. National Regulatory Authorities: We aim to support the MoH and regulatory bodies by designing the app, providing training and tools to detect SF drugs. This data will form the first national database on counterfeit medications, enhancing monitoring and supporting advocacy efforts to pass the pending Medicine Regulation Bill. Collaboration with Kenyan laboratories will facilitate sample testing and ensure compliance. Research Institutions and Universities: The app's data will benefit local researchers and national surveillance systems. Collaborating with researchers and programmers will enhance predictive analytics, improving surveillance and response to substandard drugs.