Operationalizing a Hub-and-Spoke Telemedicine Model for Mpox Surveillance in a High-Alert, Zero-Prevalence Setting: An Observational Study, Real-World Experience From Iran

在高度警戒、零流行地区实施中心辐射式远程医疗模式进行痘苗监测:一项观察性研究,来自伊朗的真实世界经验

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Abstract

BACKGROUND: The global monkeypox (Mpox) outbreak prompted heightened surveillance in regions with significant travel links. Fars Province, Iran, implemented a structured telemedicine response to manage patients presenting with Mpox-like symptoms. OBJECTIVES: This study aimed to describe and evaluate the impact of a tiered, hub-and-spoke telemedicine model on the triage, differential diagnosis, and cost efficiency of managing suspected Mpox cases in a setting with no confirmed Mpox. MATERIALS AND METHODS: In this observational study conducted from August 27 to September 22, 2024, 150 patients presenting with fever and vesiculopustular rash across Fars Province were managed via a mandated protocol. Cases unresolved by local physicians were escalated via asynchronous (store-and-forward) WhatsApp consultations to a central specialist hub. Diagnostic testing, including Orthopoxvirus (Mpox) PCR, varicella zoster virus PCR, and herpes simplex virus testing, was performed based on telemedicine triage. A cost-consequence analysis compared the implemented pathway to a hypothetical standard referral scenario. RESULTS: Among 150 teleconsultations, 28 patients (18.7%) were triaged as high suspicion for Mpox; three had relevant international travel history. No Mpox cases were confirmed. Final diagnoses were varicella (56.7%), herpes zoster (27.3%), herpes simplex (8.0%), and other conditions (8.0%). The telemedicine model prevented 122 (81.3%) unnecessary in-person specialist referrals. The median consultation response time was 95 min. The cost analysis showed a 76% reduction in direct costs, saving an estimated 1,087,500,000 Iranian Rials compared to standard care. CONCLUSION: A tiered telemedicine model proved effective for outbreak preparedness, enabling rapid expert triage, accurate differential diagnosis, and significant resource savings in a high-alert, zero-prevalence setting. This approach might yield a scalable blueprint for managing future alerts of emerging infectious diseases with cutaneous manifestations.

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