Evidence map›Paper›PMID 42769947›Full record

ArticleJournal of pharmaceutical policy and practice2026

Antibiotic and antiviral prescribing patterns among hospitalised patients with COVID-19 pneumonia in Mongolia: a real-world descriptive retrospective study.

Narangarav Nyamdag, Nina Muratkhan, Munkhbat Sukhee, Erdenetuya Myagmarsuren

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Article in Journal of pharmaceutical policy and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Narangarav NyamdagSchool of Pharmacy, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.ORCID https://orcid.org/0009-0008-7501-9861
Nina MuratkhanSchool of Pharmacy, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.ORCID https://orcid.org/0009-0000-2457-4330
Munkhbat SukheeSchool of Pharmacy, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.ORCID https://orcid.org/0000-0002-6587-2227
Erdenetuya MyagmarsurenSchool of Pharmacy, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia.ORCID https://orcid.org/0000-0002-9519-9010

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: During the COVID-19 pandemic, Mongolia, like many low- and middle-income countries, faced major healthcare delivery challenges due to limited system readiness, resource constraints, geopolitical vulnerabilities, and prolonged border closures. These factors caused shortages of laboratory reagents and globally recommended therapeutics, including remdesivir and tocilizumab, prompting clinicians to use alternative antivirals and empirical broad-spectrum antibiotics. Objective: To evaluate and compare real-world prescribing patterns of antibiotics and antivirals among hospitalised patients with COVID-19 pneumonia at Mongolia's two largest tertiary referral facilities: Mongolia-Japan Hospital (MJH) and the National Center for Communicable Diseases (NCCD). Methods: This retrospective cross-sectional study analysed anonymised medical charts and electronic health records of 1012 adults with PCR-confirmed COVID-19 pneumonia hospitalised between 18 April and 31 December 2021. Demographics, comorbidities, laboratory markers, and pharmacological treatments were systematically extracted and compared between the two institutions. Results: Antibiotics were prescribed to 87.6% (887/1012) of patients. Cephalosporins were the most frequently prescribed class (89.3%, 904/1012), followed by macrolides (36.5%, 369/1012) and fluoroquinolones (33.5%, 339/1012). Multi-drug empiricism was common, with beta-lactam, macrolide, and quinolone combinations accounting for 70.8% (68/96) of triple-antibiotic regimens. Antivirals were administered to over 90% of patients, predominantly umifenovir (52.2%) and favipiravir, supported by domestic stockpiles and Eurasian trade networks. Remdesivir was rarely used, while tocilizumab was administered to only 2 patients (0.2%). Hypertension and diabetes were significantly more frequent in the MJH cohort, reflecting differences in catchment populations and screening practices. Conclusion: The high rate of empirical broad-spectrum antibiotic use and reliance on alternative antivirals reflect pragmatic clinical adaptations to diagnostic reagent shortages and therapeutic supply inequities. These findings highlight the need for national antimicrobial stewardship programmes, strengthened microbiological diagnostic capacity, and digitised clinical registries to improve healthcare system resilience in resource-constrained settings.

Indexed as

antibiotic prescribingantibiotic stewardshipCOVID-19 pneumoniahealth system resiliencelow- and middle-income countries (LMICs)

Identifiers

PMID42769947
PMCPMC13591967

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.