This contributor piece by Chinaza Esiaba was first published on TechCabal Insights.
For years, antimicrobial resistance (AMR) in Africa has been described through increasingly stark numbers. AMR happens when bacteria and other microbes evolve to resist the drugs used to treat them, making common infections harder to cure and, in some cases, untreatable. A Lancet analysis estimated that western sub-Saharan Africa had the world’s highest death rate attributable to bacterial AMR in 2019: 27.3 deaths per 100,000 people. The figures establish the scale of the threat. They also expose a paradox: where resistant infections are a serious concern, the laboratory evidence needed to track them is often scarce.
The World Health Organisation (WHO) estimates that one in five laboratory-confirmed bacterial infections in its African Region in 2023 was resistant to antibiotics. That estimate cannot capture infections that are never tested. The visibility gap extends beyond Africa. 48% of countries did not report resistance data to the WHO’s Global Antimicrobial Resistance and Use Surveillance System (GLASS) in 2023, and about half of those that reported lacked systems to produce reliable data.
This is a public health challenge with a health tech dimension. AI diagnostics and prescribing tools depend on laboratories that can test infections, records that link results to patients, and surveillance systems that turn individual tests into evidence about local resistance. For governments and investors, building those connections may be the more immediate opportunity.
Clinicians need diagnostic evidence to prescribe well
The Nigeria Centre for Disease Control and Prevention says that one in two hospitalised patients receiving antibiotics is treated with more than one antibiotic. Watch antibiotics, which have a significant impact on antimicrobial resistance (AMR), such as ceftriaxone, cefuroxime and ciprofloxacin, also account for a large share of prescriptions. Nigerian studies have found high levels of empirical prescribing, that is, starting treatment before laboratory evidence identifies the organism or confirms which antibiotic will work. Dr Ifeyinwa George, a pharmacist and AMR programme manager at DRASA Health Trust, a Nigerian nonprofit focused on infection prevention and public health security, has pointed to limited laboratory capacity as a barrier to detecting and tracking resistant pathogens.
An Africa CDC-led study of 14 countries found that only 1.3% of roughly 50,000 laboratories in participating networks performed bacteriology testing. Of approximately 187,000 samples tested for resistance, 88% lacked clinical information such as the patient’s diagnosis or prior antibiotic use. In a survey of 219 Kenyan health facilities, 61.6% did not offer bacterial culture testing and only 16.9% performed antimicrobial susceptibility testing. As Ghanaian AMR researcher Prof Beverly Egyir put it, “When we do not test, we are essentially flying blind.”
This gap can persist even where testing is available. At Cape Coast Teaching Hospital in Ghana, laboratory reports took an average of 3.4 days from sample receipt to upload into the electronic health system. It is tempting to look at numbers like these and reduce AMR to an antibiotic-overuse problem. Africa’s experience is more complicated: without diagnostic evidence, clinicians may prescribe empirically due to a lack of information, not simply because they disregard stewardship. Giving them better information requires functioning laboratories, timely results, and systems that link those results to patient records.
Medicine quality is another part of the data gap
Resistance surveillance also needs to account for the medicines patients receive. In 2025, Ghana’s Food and Drugs Authority found counterfeit pharmaceutical products worth GH₵42 million ($3.6 million). Additionally, Nigeria’s National Primary Healthcare Development Agency stated that about 70% of medicines distributed in the country were substandard or counterfeit. Substandard medicines with too little active ingredient can also expose bacteria to inadequate concentrations and contribute to resistance.
That is a case for better medicine traceability and reporting. Nigeria’s National Agency for Food and Drug Administration and Control (NAFDAC) uses a Mobile Authentication Service that allows consumers to check medicine codes via text message. Batch tracking, rapid alerts and shared records can help regulators find suspect products and remove them from circulation. The WHO is moving in a similar direction. Its 2026 digital-transformation guidance specifically encourages countries to move from fragmented, paper-based reporting of substandard and falsified medicines to interoperable digital reporting systems. These tools are part of the AMR response because medicine quality changes what treatment a patient actually receives.
When the data infrastructure exists
Some countries are building systems that make more advanced analysis useful. South Africa’s National Institute for Communicable Diseases publishes an AMR surveillance dashboard that draws on laboratory data and helps show which pathogens are becoming resistant. In Ghana, researchers using whole-genome sequencing have studied cholera isolates alongside samples from other African countries to examine resistance genes and how strains are related. These methods can answer sharper public health questions when sample collection and routine data are sufficient to support them.
Kenya provides a practical example of how that foundation grows. According to the WHO’s account of the programme, two model surveillance sites established in 2017 grew into a network of 32 sites across 27 countries. The country now integrates resistance, antibiotic use, and consumption data into a central warehouse and began submitting individual-level data to GLASS in 2025. Susan Githii, Kenya’s GLASS focal person, says the richer data help the team understand resistance trends and guide decisions. The remaining work includes connecting hospital systems and filling missing patient fields.
The investment test
The lesson is not that Africa should abandon AI, rapid diagnostics or clinical decision-support software. These tools need somewhere solid to land. For healthtech investors, the AMR opportunity may lie in systems that make laboratory evidence usable: software that delivers susceptibility results to clinicians, connects data across hospitals and helps regulators trace suspect medicine batches. AI could use that foundation to flag unusual resistance patterns or support treatment decisions. It cannot fill in for infections that were never tested or medicines whose quality is unknown.
The harder question is who keeps that infrastructure running. The EU-backed ARILAC initiative is set to strengthen laboratory and data systems in eight countries over four years. At its launch in July 2026, Africa CDC called for those systems to be included in national budgets. Its 2026–2030 AMR framework also identifies sustainable financing as a priority. Laboratories need steady supplies, maintained equipment, and skilled staff long after a grant ends. Investors need a credible path for health systems to pay for and keep using the tools they fund.
Technology alone will not slow resistance; infection prevention, vaccination, clean water, and responsible antibiotic use remain essential. But the strongest investment case may be in the infrastructure that tells clinicians which treatments still work locally, shows public health teams where resistance is rising, and helps regulators keep poor-quality medicines from reaching patients.
Comments
Post a Comment