Related Experiment Video
Updated: May 31, 2025
14:56
Remote Laboratory Management: Respiratory Virus Diagnostics
Published on: April 6, 2019
33.0K
Data from Emergency Medical Service Activities: A Novel Approach to Monitoring COVID-19 and Other Infectious Diseases
Daniele Del Re1, Luigi Palla2, Paolo Meridiani3
1Department of Physics, Sapienza University of Rome, 00185 Rome, Italy.
Diagnostics (Basel, Switzerland)
|January 25, 2025
Summary
Emergency Medical Service (EMS) call data can effectively monitor COVID-19 spread. Analyzing 7.4 million calls in Lombardy revealed EMS data accurately tracked pandemic trends and seasonal flu outbreaks, offering a novel public health tool.
Area of Science:
- Public Health
- Epidemiology
- Emergency Medicine
Background:
- Lombardy, Italy, faced severe COVID-19 impact.
- Existing COVID-19 monitoring indicators have biases.
- Need for alternative, reliable data sources for disease surveillance.
Purpose of the Study:
- Evaluate Emergency Medical Service (EMS) call data for COVID-19 monitoring.
- Assess EMS data's utility in tracking infectious disease outbreaks.
- Compare EMS data with traditional surveillance metrics.
Main Methods:
- Analyzed 6 million+ emergency calls (112) in Lombardy (2015-2022).
- Filtered calls for respiratory and cardiological symptoms.
- Applied statistical methods to isolate COVID-19 signal from background noise.
Main Results:
- Identified 742,852 relevant records for potential COVID-19 patients.
- EMS data time series strongly correlated with COVID-19 cases and deaths.
- Demonstrated good agreement with seasonal influenza outbreak patterns.
Conclusions:
- EMS call data offers a novel, powerful tool for infectious disease surveillance.
- This approach, with machine learning, can signal outbreaks early.
- Enhances public health response capabilities for epidemics.
Related Concept Videos
01:18Steps in Outbreak Investigation
102
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
102
01:26Principles of Disease Surveillance
67
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
67
01:30Pulse rhythm
754
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
754
01:30Methods of Documentation VII: EMR
823
Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
823
01:12Statistical Software for Data Analysis and Clinical Trials
481
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
481