WAAW 2025: The future of AMR action lies in decentralised, technology-enabled stewardship

World Antimicrobial Awareness Week (WAAW) 2025 will take place from November 18 to 24, 2025.

Antimicrobial resistance (AMR) is often described as a global health crisis. But for most countries in the Global South, AMR is not an abstract threat, it is a visible reality in outpatient departments, primary health centres, informal clinics and pharmacies that form the backbone of healthcare for millions. The real challenge lies here, at the last mile, where health workers face overwhelming patient loads, limited diagnostics and enormous pressure to “do something”. Too often, that “something” is an antibiotic.

The persistent overuse and misuse of antibiotics is not simply a behavioural problem. It reflects a deeper structural gap: Peripheral health systems lack the tools, data and decision-support mechanisms needed to rationalise prescriptions. Without objective measures to guide clinical decisions, the safest and quickest response is to prescribe empirically. This structural vacuum perpetuates AMR.

If we want to meaningfully shift the AMR trajectory, our solutions must reach the point of care — where clinical decisions are made within minutes, not in tertiary hospitals or policy rooms. And the most powerful enabler for this shift is technology.

AI-enabled tools as the next frontier

Over the last decade, digital health has rapidly matured in low- and middle-income countries (LMIC). Telemedicine, electronic medical records and supply chain systems have transformed many aspects of care delivery. Yet AMR has remained stubbornly resistant to decentralisation because diagnostic and clinical decision-support technologies have not penetrated the front lines.

This is now changing.

Emerging AI-enabled tools can give frontline providers objective signals they never previously had access to, helping them reduce unnecessary antibiotic use, refer patients appropriately and manage uncertainty with confidence.

1. Automated ambient listening and AI-assisted scribing

In primary care settings, clinicians often struggle to balance patient volumes with thorough clinical assessments. History-taking becomes hurried, symptoms are incompletely documented and subtle cues are missed. This leads to defensive antibiotic prescribing.

AI-driven ambient listening tools — already being piloted in LMIC settings — automatically capture, summarise and structure clinical encounters. They ensure that cough duration, fever pattern, comorbidities, red flags and prior antibiotic exposure are recorded reliably.

When combined with simple clinical decision support systems (CDSS), these tools can flag viral syndromes, guide watchful waiting and prompt clinicians when antibiotics are not indicated. Such tools introduce much-needed discipline into clinical reasoning, without demanding extra time from overstretched health workers.

2. Cough characterisation through AI: differentiating viral and bacterial illness

One of the most promising technological advances for AMR is AI-based cough analysis. Early studies show that cough acoustics — captured via a mobile phone — carry distinct signatures that can help differentiate viral and bacterial lower respiratory infections.

For primary care, this could be transformative.

Imagine a health worker equipped with a cough-analysis tool on a smartphone. Within seconds, the tool indicates whether the cough pattern is suggestive of a viral infection, reducing unnecessary antibiotic initiation. Combined with symptom screening, this can create an objective triage layer that has never existed before in rural or low-resource clinics.

Research is underway to validate such systems across diverse geographies, ages and comorbidity patterns. If scaled responsibly, cough-AI could become one of the most accessible diagnostic aids for antibiotic stewardship globally.

3. Ultra-portable X-rays and AI for lung health: moving beyond tuberculosis

Digital radiography has undergone a quiet revolution. Ultra-portable machines weighing less than 10 kg are now deployed in thousands of screening camps across Asia and Africa. When paired with AI algorithms, they have proven extremely effective for tuberculosis (TB) triage.

This same ecosystem can now be leveraged for AMR.

Pneumonia remains a major driver of irrational antibiotic use, particularly in children. AI-powered chest X-ray interpretation can support frontline clinicians by identifying radiological patterns suggestive of viral versus bacterial pneumonia. While still evolving, these tools open the possibility of objective differentiation at the point of care, reducing empirical antibiotic use.

Importantly, the infrastructure already exists — TB programmes, mobile vans, district hospitals, community outreach units. Expanding indications from TB to broader lung health is a natural next step.

4. Point-of-care ultrasound and AI-driven lung ultrasound interpretation

Point-of-care ultrasound (POCUS) is now a standard tool in many maternal health programmes. The same technology, when applied to lung ultrasound, has significant potential for AMR stewardship.

Clinical literature already shows that lung ultrasound can help differentiate viral and bacterial pneumonia with high accuracy. What has been missing is scalability: frontline workers are not trained radiologists.

AI-assisted interpretation is closing this gap.

Ongoing research in LMIC settings is focused on building open-source datasets of lung ultrasound images and training AI models for pneumonia differentiation. If successful, POCUS plus AI could become the most affordable, decentralised respiratory diagnostic — usable in primary health centres, conflict settings or internally displaced persons (IDP) camps.

Technology as a critical amplifier

Technology alone will not solve AMR. Stewardship requires regulation, behaviour change, supply chain reforms and strong governance. But without technologies that help peripheral providers make safer clinical decisions, we will continue to treat AMR as a policy problem instead of the frontline emergency it truly is.

The Global South has a unique opportunity: unlike high-income countries, LMICs have rapidly leapfrogged into digital health adoption. If we integrate AI, clinical decision systems and point-of-care diagnostics into primary care pathways, we can fundamentally reshape antibiotic-use patterns for generations.

AMR action must move closer to the patient. Technology can get us there, faster, more cheaply and more equitably than ever before.

Shibu Vijayan is Chief Medical Officer for Global Health, Qure.ai Views expressed are the author’s own and don’t necessarily reflect those of Down To Earth