Afghanistan's Silent Epidemic: The Overuse of Antibiotics Is Fueling a Public Health Crisis
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Résumé
Afghanistan, long plagued by conflict and economic instability, is now grappling with a less visible but equally dangerous threat: the misuse and overuse of antibiotics. The World Health Organization (WHO) warns that the rise of antimicrobial resistance (AMR) is one of the top 10 global health threats of the 21st century, and Afghanistan is a textbook case of how such problems emerge within fragile health systems [1]. Across both public and private sectors, antibiotics are prescribed at rates far beyond international recommendations. In hospitals under Kabul University of Medical Sciences, 85.5% of inpatients received antibiotics, often without confirmed diagnosis or clear justification [2]. The pattern extends to outpatient care as well. In one district hospital in Kabul, prescriptions during summer showed that 62% of patients were given antibiotics, compared to 50% in winter [3]. Another study found that drugs like ceftriaxone, metronidazole, and amoxicillin are among the most overused medications, fueling resistance [4]. Antibiotic misuse is not only a clinical issue—it is deeply cultural. Many Afghans perceive antibiotics not as targeted treatments but as general “cleaning agents” for the body, a belief documented by Médecins Sans Frontières in Ahmad Shah Baba District Hospital [5]. This mindset extends to dentistry and surgery. A randomized trial in Herat showed that prescribing antibiotics after routine tooth extraction offered no benefit, yet such prescriptions remain common [6]. Unfortunately, this mindset persists despite only moderate public awareness about antibiotic resistance. In a nationwide survey of university students, most participants had heard of the issue, but self-medication with antibiotics was still alarmingly widespread [7]. The roots of this crisis lie in Afghanistan's weakened healthcare infrastructure. Decades of conflict have left the country with scarce diagnostic tools, weak drug regulation, and unreliable supply chains. As a result, many clinicians prescribe empirically, without laboratory confirmation, simply because no alternatives exist [1]. A hospital-based surveillance study involving 6709 patients found that more than half of Escherichia coli infections were resistant to commonly used antibiotics, compared to 7%–8% in Europe. Even standard treatments like amoxicillin–clavulanic acid were largely ineffective [8]. Antibiotic misuse in Afghanistan stems from intertwined factors: weak regulation, cultural beliefs, and limited diagnostics. Over-the-counter sales by undertrained vendors are widespread, and public trust in antibiotics as “quick cures” reinforces demand [3]. Together, these forces sustain excessive use across hospitals, pharmacies, and communities. Some promising tools could help curb misuse. One example is the C-reactive protein (CRP) test, a quick finger prick used to determine whether an infection is likely bacterial or viral. A modeling study in Afghanistan estimated that using CRP tests for malaria-negative patients could reduce unnecessary antibiotic prescriptions by about 12% [9]. While encouraging, the study noted that cost-effectiveness depends on clinicians adhering to test results and on affordability within Afghanistan's health system. Given limited laboratory capacity [10], especially in rural clinics, nationwide use is not yet realistic. However, targeted pilot programs in better-equipped health centers could test feasibility, training needs, and patient outcomes. If successful, these pilots could mark a practical step toward smarter antibiotic use without overpromising what current resources can deliver. Despite the scale of the problem, national responses remain fragmented. Afghanistan still lacks a comprehensive AMR surveillance system. Training in antimicrobial stewardship is limited, and public education campaigns about resistance are rare [1]. To make progress, Afghanistan needs clear, realistic actions suited to its fragile context. First, strengthen hospital-level stewardship programs in major teaching hospitals where clinical leadership and monitoring capacity already exist [11]. Second, enforce pharmacy licensing in provincial centers and restrict antibiotic sales without prescription. Third, pilot mobile health platforms [11] that allow rural clinicians to access standard treatment guidelines and report antibiotic use patterns. Finally, Afghanistan could collaborate with WHO's Global AMR Surveillance System (GLASS) [12] and NGOs such as Médecins Sans Frontières or the French Medical Institute for Mothers and Children [13] to build reliable data systems and community awareness campaigns. Afghanistan has faced many health crises, yet AMR presents a different kind of danger, one that grows quietly and invisibly and is easily overlooked until it becomes irreversible. Addressing it requires policy reform, public engagement, and steady investment in diagnostics and regulation. If ignored, this silent epidemic could erase decades of medical progress in Afghanistan and beyond. Mohammad Masudi, Ali Rahimi, and Nasar Ahmad Shayan conceptualized the manuscript, wrote the original draft, supervised the process, and reviewed and edited the manuscript. We would like to acknowledge the use of ChatGPT-5 Plus (OpenAI) and Paperpal for grammar checking and language refinement during manuscript preparation. The authors have nothing to report. The authors have nothing to report. All authors have reviewed and approved the final manuscript and consent to its publication. The authors declare no conflicts of interest. The authors have nothing to report.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle