Related Experiment Video
Updated: May 22, 2026
05:37
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Summary of the current operational epidemiological modelling landscape
Jeff Schlegelmilch1, Brienne Lenart, Linda Bergonzi King
1Yale New Haven Center for Emergency Preparedness and Disaster Response, 1 Church Street, 5th Floor, New Haven, CT 06510, USA. jeffrey.schlegelmilch@ynhh.org
Journal of Business Continuity & Emergency Planning
|May 12, 2012
Summary
This study identifies needs for a national system to synchronize public health models with disaster response organizations. It explores current gaps to improve emergency decision-making during health crises.
Area of Science:
- Disaster medicine
- Epidemiological modeling
- Public health preparedness
Background:
- Decision-makers need timely epidemiological data during public health emergencies.
- Prospective forecasts from models are crucial for effective response.
- A gap exists in synchronizing US government epidemiological models with response organizations.
Purpose of the Study:
- To determine requirements for a national operational epidemiological modeling process.
- To inform the development of a synchronized national approach.
- To bridge the gap between modeling and response communities.
Main Methods:
- Initiated a study through the National Center for Integrated Civilian-Military Domestic Disaster Medical Response.
- Involved collaboration between Yale New Haven Center for Emergency Preparedness and Disaster Response and US Northern Command.
- Summarized the landscape of modeling and consequence management communities.
Main Results:
- Identified a lack of a formal, synchronized process across US government agencies.
- Highlighted the need for integrated epidemiological modeling for disaster response.
- Characterized the current state of modeling and consequence management.
Conclusions:
- A national operational epidemiological modeling process is required.
- Synchronization between modeling and response is essential for effective public health emergency management.
- Further development is needed to integrate these communities.
Related Concept Videos
01:18Steps in Outbreak Investigation
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:
01:25Statistical Methods for Analyzing Epidemiological Data
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
01:26Introduction to Epidemiology
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
01:27Pharmacodynamic Models: Overview
Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
01:26Principles of Disease Surveillance
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...
01:21Causality in Epidemiology
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...