Travel and Work-Associated Malaria in a Non-Endemic Country: A Mongolian Case Series (2012–2024)

Abstract

Background: Malaria is a tropical disease transmitted by infected Anopheles mosquitoes and
remains a major global health problem in endemic regions. Mongolia is a non-endemic
country but it continues to report imported cases associated with travel and work in endemic
areas. Imported malaria poses challenges in Mongolia due to low clinical suspicion, delayed
diagnosis. Although local transmission is currently absent, imported cases highlight the need
for early detection and prevention strategies.
Methods: A retrospective descriptive study was conducted at the National Center for
Communicable Diseases of Mongolia. A total of 10 imported malaria cases from 2012 to
2024 were initially identified. Data were obtained from medical records, including clinical
presentation, temperature charts, diagnostic methods, species identification, and treatment.
Laboratory parameters were excluded. Data were analyzed using IBM SPSS Statistics 27.
Results: Among the 10 patients, 70% were male and 30% female. The mean age was 33.80 ±
9.47 years, and the mean body mass index was 23.88 ± 2.68 kg/m². The mean duration of
hospitalization was 11.50 ± 5.06 days. Malaria diagnosis was confirmed by blood smear and
rapid diagnostic test. The most common species was Plasmodium falciparum (50%),
followed by mixed infections. Fever and gastrointestinal symptoms were present in all
patients. Other symptoms included sweating, headache, chills, respiratory and neurological
symptoms. Fever pattern showed predominantly unclassifiable patterns (70%). A total of 4
patients required intensive care unit admission, with a mean ICU stay of 7 ± 2.16 days.
Conclusion: Malaria in this cohort was characterized by non-specific clinical features and
predominantly irregular or unclassifiable fever patterns. Plasmodium falciparum was the
most frequently identified species. The findings highlight the challenges of retrospective
clinical diagnosis and the limitations of incomplete medical records in long-term data
collection.