RapidSOS Data Lab

Analyzing a year of 911 calls for data insights

2 months ago


The emergency 911 system serves as a critical lifeline for individuals facing crises, providing rapid response and assistance.

A recent survey carried out by the International Academies of Emergency Dispatch (IAED) and the National Association of State 911 Administrators (NASNA) reveals that the shortage of 911 staff impacts call centers big and small, spanning every region and touching all states.

This research paper thoroughly examines data from 911 calls gathered over a year to identify trends that could help enhance staffing and operational efficiency in emergency response systems.

Data Collection

The dataset for this analysis comprises anonymized 911 call records spanning 12 months that passed through the RapidSOS Intelligent Safety Platform. The data for each call includes timestamps, geographic information, and other additional information (e.g., demographic, health, medical, telematics, etc.)


Descriptive statistics examined the frequency and distribution of call times, types, and geographic variations. Datasets were normalized per 100 thousand habitants to both ensure privacy and help identify trends and correlations. 

911 Call Volume Key Findings

By Time of DayLowest between 4:00-5:00 am, peaks at 5:00 pm.

By Day of the WeekSaturday had the highest number of 911 calls, and Tuesday had the lowest.

By MonthApril through June had the highest 911 call volume, and December through February had the lowest.

By StateWashington D.C. had the highest volume of calls to 911 centers, and Vermont had the lowest.

By Federal HolidayNew Year’s Eve had the highest call volume from the federal holidays, and Thanksgiving had the lowest.

Call Volume

The analysis revealed variations in call frequency throughout different times of the day, week, and month.

On an average day, adjusted for time zones, 911 call volume is the lowest between 4 – 5 am and peaks at 5 pm. There is a sharp increase between 5 am to 8 am and then calls increase more slowly between 8 am and 5 pm.

Looking at call volume by day of the week, Saturday had the highest number of 911 calls while Tuesday had a much lower rate than other days of the week.

Seasonal trends by month were also identified. The period between April through June had the highest 911 call volume in the year. December through February had the lowest.

Call Volume by Time of Day
911 Call Volume by Day of the Week
911 Call Volume by Month

Geographic Variations

The geospatial analysis also uncovered regional variations in call patterns. On average across the year, Washington D.C. had the highest volume of calls to 911 centers, while Vermont had the lowest.

911 Call Volume by State

Holiday Analysis

Call volume analysis highlighted call patterns across federal holidays. New Year’s Eve had the highest call volume from the federal holidays while Thanksgiving had the lowest. Call volume varied across states when comparing across federal holidays. New Year’s Eve had an increase of +319% in the number of calls as compared to the average day in the year.

911 Call Volume by Federal Holiday


The findings from this analysis lay the groundwork for meaningful conversations about enhancing the efficiency and staffing of emergency response operations. Leveraging this data can guide the strategic allocation of resources and the improvement of emergency services in areas of high demand.

This study highlights the complex nature of 911 emergency call patterns and their significance for effective crisis management. Through the application of data-driven approaches, there is an opportunity to significantly improve how emergency services cater to community needs. Continued research and collaboration between stakeholders are crucial for the ongoing improvement of emergency response systems.

Future research could focus on incorporating data from multiple years to track evolving patterns and trends. Additionally, exploring the integration of emerging technologies, such as artificial intelligence and predictive analytics, could further enhance the efficiency of emergency response systems.


Hodgkiss, W., Baru, C., Fountain, T., Reich, D., Warner, K., & Glasscock, M. (2005). Spatiotemporal analysis of 9-1-1 call stream data. In Proceedings of the 2005 national conference on Digital government research (pp. 293-294).

Jasso, H., Fountain, T., Baru, C., Hodgkiss, W., Reich, D., & Warner, K. (2007). Prediction of 9-1-1 call volumes for emergency event detection. In Proceedings of the 8th annual international conference on digital government research: bridging disciplines & domains (pp. 148-154).

Cramer, D., Brown, A. A., & Hu, G. (2012). Predicting 911 calls using spatial analysis. Software engineering research, management and applications 2011, 15-26.

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