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Disaster Med Public Health Prep . Impact of the 2018 Western Japan Heavy Rain Disaster on Anti-influenza Virus Drug Prescribing: A Longitudinal Anal

tetano

Editor, Senior Moderator
Disaster Med Public Health Prep


. 2025 Aug 7:19:e223.
doi: 10.1017/dmp.2025.10136. Impact of the 2018 Western Japan Heavy Rain Disaster on Anti-influenza Virus Drug Prescribing: A Longitudinal Analysis Using the National Health Insurance Claims Database

Shu Utsumi[SUP] 1 2 [/SUP], Shuhei Yoshida[SUP] 2 [/SUP], Shinichiro Ohshimo[SUP] 1 [/SUP], Nobuaki Shime[SUP] 1 [/SUP], Masatoshi Matsumoto[SUP] 2 [/SUP]



Affiliations
Abstract

Objectives: No study has evaluated the relationship between heavy rain disasters and influenza by comparing victims and non-victims, and we investigated the association between the 2018 western Japan heavy rain disaster and influenza.
Methods: All patients registered in the National Health Insurance Claims Database and treated in the Hiroshima, Okayama, and Ehime prefectures were included in this retrospective cohort study conducted 1-year post-disaster. A multivariate mixed-effects logistic regression analysis was used to assess the association between the disaster and anti-influenza drug prescribing. A difference-in-differences analysis was conducted to assess anti-influenza drug use for the 4-month period immediately before and every 4 months for a year post-disaster.
Results: This study included 6 176 300 individuals (victims: 36 076 [0.60%]); 2573 (7.1%) and 458 157 (7.4%) in the victim and non-victim groups, respectively, used anti-influenza drugs in the year following the flood. The victims were significantly more likely than non-victims to use anti-influenza drug (risk ratio 1.18; 95% confidence interval [CI] 1.12-1.42). The victims used significantly more anti-influenza drugs in the 4 months immediately post-disaster compared with just before the disaster (odds ratio 3.62; 95% CI 1.77-7.41).
Conclusions: Anti-influenza drug use was higher among victims of the 2018 Western Japan heavy rain disaster than among non-victims.

Keywords: big data; disaster victims; floods; influenza; natural hazards.

 
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