Impact of Weather Variability on Emergency Medical Service Activity in Semarang City

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Vol. 23 No. 1 (2026): Jurnal Kesehatan Lingkungan Volume 23 No. 1, Januari 2026
Published: Jan 27, 2026
Keywords:
Weather variability,
Emergency medical services,
Extreme temperature,
Relative humidity,
Rainfall

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Jevita Sri Nurhayati Loleh
Public Health Study Program, Faculty of Health Sciences, Universitas Dian Nuswantoro, Semarang, Indonesia
Eti Rimawati
Public Health Study Program, Faculty of Health Sciences, Universitas Dian Nuswantoro, Semarang, Indonesia
Ahmad Zaini
Semarang City Health Office, Central Java, Indonesia
Wisnu Wardhana
Semarang City Health Office, Central Java, Indonesia
Siwi Praptining Wijayanti
Semarang City Health Office, Central Java, Indonesia

Abstract

Weather variability influences the occurrence of medical emergencies that require rapid response, particularly in urban areas with high population density. This study aimed to analyze the effects of temperature, relative humidity, and rainfall on the number of daily PSC 119 calls in Semarang City. An ecological time-series design was applied using daily call records and meteorological data collected over 365 days in 2024, analyzed with a Distributed Lag Non-linear Model combined with quasi-Poisson regression to estimate risks across lag periods. The results show that both low and high temperatures substantially increased the risk of PSC 119 calls compared with the reference temperature. Moderate humidity was associated with higher risk, while very high humidity demonstrated a protective effect. Rainfall, particularly no-rain to light-rain conditions, also contributed to increased call frequency. Most weather-related effects occurred within 0–3 days, indicating an acute pattern of influence. These findings highlight the importance of integrating weather prediction into emergency preparedness systems to support workforce planning, resource allocation, and operational response. Further studies incorporating call-type classifications and additional environmental variables are recommended to improve understanding of weather-related emergency service demand.

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