ArticleJournal of medicine and life2026
Seasonal patterns in nine notifiable communicable diseases and the epidemic dynamics of COVID-19 at Johns Hopkins Aramco Healthcare: a six-year review (2019-2024).
Article in Journal of medicine and life, 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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Abstract
Seasonal variation influences the transmission dynamics of communicable diseases, yet limited evidence describes these patterns in the Eastern Province of Saudi Arabia. This retrospective study analyzed surveillance data from Johns Hopkins Aramco Healthcare (JHAH) over 6 years (2019-2024) to describe temporal and monthly patterns in nine common notifiable communicable diseases (influenza, salmonellosis, respiratory syncytial virus [RSV], chlamydia, campylobacteriosis, varicella [chickenpox], gonorrhea, scabies, and animal bites) and to describe the epidemic patterns of COVID-19 (analyzed separately from March 2020 to December 2024). The cases were organized by weekly epidemiological data and visualized through monthly line plots, illustrating temporal patterns. Descriptive statistics were used to determine annual totals, peak years and months, and case fatality rates for COVID-19. Results indicated 2,518 cases of nine notifiable diseases, predominantly influenza (686 cases), followed by salmonellosis (592), RSV (293), chlamydia (250), and campylobacter (240). Temporal trends suggestive of seasonal variations were noted, with influenza, RSV, campylobacter, and scabies peaking in winter, while salmonellosis and chickenpox peaked in October. The incidence of chlamydia, gonorrhea, and animal bites was highest in late spring and early summer. From March 2020 to December 2024, there were 36,280 COVID-19 cases and 718 deaths, with three epidemic waves and a decline in monthly cases post-2023. This exploratory study underscores the potential association of climatic and behavioral factors with disease transmission and provides preliminary observations to support public health strategies, including vaccination timing, surveillance, and further research into predictive modeling.
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