Work

Spatio-temporal trends in COVID-19 morbidity and mortality due to elderly: a global perspective

Year: 2026

Type: article

Abstract: COVID-19 spread worldwide after emerging at the end of 2020 with a higher spread and death among the elderly and varies across the continent and country. This study aimed to investigate the spatio-temporal trends in COVID-19 morbidity and mortality due to the elderly. COVID-19 infected cases and death data were converted into morbidity and mortality rates per 1,000 population. Thematic maps were used for spatial illustration over time. Linear and Theil-Sen regression models were used to estimate the rate of change in COVID-19 morbidity and mortality due to the elderly. The results revealed a significant relation and change in the global COVID-19 morbidity and mortality rates due to the elderly population (p-value < 0.05). Europe experienced the highest rate of change in COVID-19 morbidity due to the elderly population, followed by Oceania and North America. Moreover, the elderly proportion had the greatest rate of change in COVID-19 mortality in North America, followed by Europe and Africa. The results of this study will enable researchers and experts for data-driven decisions that are more resilient. Moreover, it enables healthcare experts and policymakers to develop guidelines to improve preparedness for future pandemics.

Source: Scientific Reports

DOI: 10.1038/s41598-026-37968-z

Authors: Jeayareeyoh Jeasoh, Apiradee Lim, Rohani Jeharsae, Haris Khurram

Institutions: Prince of Songkla University, National University of Computer and Emerging Sciences

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,690