2026, Volume 19, Issue 5, pp 366 – 372

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)

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Authors and Affiliations

* Corresponding author Razan Garwan, Population Health Department, Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia; E-mail: [email protected]

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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About this article

PMC ID: 
PubMed ID: 42487676
DOI: 10.25122/jml-2025-0183

Article Publishing Date (print):
Available Online: 

Journal information

ISSN Printing: 1844-122X
ISSN Online: 1844-3117
Journal Title: Journal of Medicine and Life

Copyright License: Open Access

This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.

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