Exposure to natural disasters and vaccination indicators: a systematic review and directions for future research.

VaccineOct 27, 2026 (epub)

Brittany Shea, Jeffrey Shaman

✦ AI-curated · Sources linked

In 30 seconds

This systematic review examined peer-reviewed research on exposure to natural disasters and vaccination indicators, including vaccine administration, coverage, and rates. Searches of four databases identified 17 eligible studies covering several disaster types and age groups. Sixteen of the 17 studies (94.12%) reported a connection or association between disaster exposure and reduced vaccination indicators; 13 of 17 (76.47%) focused on early-childhood vaccination. The review also found that some studies assessed vulnerability by exposure level, location, and socioeconomic status, while highlighting the need for stronger research to quantify effects across disaster types and over time.

Key findings

  • Sixteen of 17 studies (94.12%) identified a connection or association between natural-disaster exposure and reduced vaccination indicators.
  • Thirteen of 17 studies (76.47%) focused on early-childhood vaccinations.
  • Studies covered cyclones or hurricanes, droughts, earthquakes, flooding, heat waves, and multiple disaster types.

Why it matters

Disaster-related disruption may undermine vaccination and leave populations more vulnerable to vaccine-preventable diseases. The review brings together evidence across disaster types and vaccination measures, while showing that the evidence base is limited and often focused on young children. Better measurement of effects and vulnerability could help clarify where and how immunization services are most affected during and after disasters.

What to keep in mind

The review reports that well-designed studies quantifying the effects of disaster exposure on vaccination indicators are limited; the included studies varied in disaster types and populations.

Source

Published in Vaccine. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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