Impact of COVID-19 outbreak on the seasonality and incidence of type 1 diabetes mellitus: A nationwide cohort study

The observed increase in new-onset T1DM cases and the disruption of its typical seasonal pattern during the COVID-19 pandemic suggest a potential association between respiratory virus exposure and the development of T1DM.

Authors

Institutions

Publication Details

Journal
World Journal of Diabetes
Published
2025-08-14
DOI
https://doi.org/10.4239/wjd.v16.i8.108724
Citations
2
Primary Topic
Diabetes and associated disorders
Type
article
Field-Weighted Citation Impact
3.63
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of COVID-19 outbreak on the seasonality and incidence of type 1 diabetes mellitus: A nationwide cohort study

Guy Hazan, David Shaki, Alon Haim, Eli Hershkovitz et al.
2 citations
World Journal of Diabetes
Diabetes and associated disorders
3.63
article

Impact of COVID-19 outbreak on the seasonality and incidence of type 1 diabetes mellitus: A nationwide cohort study

Guy Hazan, David Shaki, Alon Haim, Eli Hershkovitz, Yoav Bachar, Lior Carmon, Neta Loewenthal, Amit Shira Babiev, Itai Hazn
article en
2 citations

Abstract

The observed increase in new-onset T1DM cases and the disruption of its typical seasonal pattern during the COVID-19 pandemic suggest a potential association between respiratory virus exposure and the development of T1DM.

World Journal of DiabetesVol. 16(8)
Ben-Gurion University of the Negev (IL), Soroka Medical Center (IL)
Openalex Percentile: Top 7%
Diabetes and associated disorders
3.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.