Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis

BackgroundSeasonal influenza activity showed a sharp decline in activity at the beginning of the emergence of COVID-19. Whether there is an epidemiological correlation between the dynamic of these 2 respiratory infectious diseases and their future trends needs to be explored. ObjectiveWe aimed to as...

Full description

Saved in:
Bibliographic Details
Main Authors: Qing Wang (Author), Mengmeng Jia (Author), Mingyue Jiang (Author), Wei Liu (Author), Jin Yang (Author), Peixi Dai (Author), Yanxia Sun (Author), Jie Qian (Author), Weizhong Yang (Author), Luzhao Feng (Author)
Format: Book
Published: JMIR Publications, 2023-06-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000 am a22000003u 4500
001 doaj_1c381e66a0ab458fb8c3a6fb49d588e3
042 |a dc 
100 1 0 |a Qing Wang  |e author 
700 1 0 |a Mengmeng Jia  |e author 
700 1 0 |a Mingyue Jiang  |e author 
700 1 0 |a Wei Liu  |e author 
700 1 0 |a Jin Yang  |e author 
700 1 0 |a Peixi Dai  |e author 
700 1 0 |a Yanxia Sun  |e author 
700 1 0 |a Jie Qian  |e author 
700 1 0 |a Weizhong Yang  |e author 
700 1 0 |a Luzhao Feng  |e author 
245 0 0 |a Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis 
260 |b JMIR Publications,   |c 2023-06-01T00:00:00Z. 
500 |a 2369-2960 
500 |a 10.2196/44970 
520 |a BackgroundSeasonal influenza activity showed a sharp decline in activity at the beginning of the emergence of COVID-19. Whether there is an epidemiological correlation between the dynamic of these 2 respiratory infectious diseases and their future trends needs to be explored. ObjectiveWe aimed to assess the correlation between COVID-19 and influenza activity and estimate later epidemiological trends. MethodsWe retrospectively described the dynamics of COVID-19 and influenza in 6 World Health Organization (WHO) regions from January 2020 to March 2023 and used the long short-term memory machine learning model to learn potential patterns in previously observed activity and predict trends for the following 16 weeks. Finally, we used Spearman correlation coefficients to assess the past and future epidemiological correlation between these 2 respiratory infectious diseases. ResultsWith the emergence of the original strain of SARS-CoV-2 and other variants, influenza activity stayed below 10% for more than 1 year in the 6 WHO regions. Subsequently, it gradually rose as Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the following period, the activity of each disease increased as the other decreased, alternating in dominance more than once, with each alternation lasting for 3 to 4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation, with coefficients above -0.3 in WHO regions, especially during the Omicron pandemic and the following estimated period. The diseases had a transient positive correlation in the European region of the WHO and the Western Pacific region of the WHO when multiple dominant strains created a mixed pandemic. ConclusionsInfluenza activity and past seasonal epidemiological patterns were shaken by the COVID-19 pandemic. The activity of these diseases was moderately or greater than moderately inversely correlated, and they suppressed and competed with each other, showing a seesaw effect. In the postpandemic era, this seesaw trend may be more prominent, suggesting the possibility of using one disease as an early warning signal for the other when making future estimates and conducting optimized annual vaccine campaigns. 
546 |a EN 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n JMIR Public Health and Surveillance, Vol 9, p e44970 (2023) 
787 0 |n https://publichealth.jmir.org/2023/1/e44970 
787 0 |n https://doaj.org/toc/2369-2960 
856 4 1 |u https://doaj.org/article/1c381e66a0ab458fb8c3a6fb49d588e3  |z Connect to this object online.