Conducting operational research during outbreaks to improve preparedness and response

Each significant outbreak and epidemic raises questions that must be answered in order to better inform future preparedness and response efforts, such as:

January 25, 2018

Data-Driven Computational Model to Assess the Risk of Epidemics in Global Mass Gatherings

Global Mass gatherings (MGs) such as Olympic Games, FIFA World Cup, and Hajj (Muslim pilgrimage to Makkah), attract millions of people from different countries. The gathering of a large population in a proximity facilitates transmission of infectious diseases. Attendees arrive from different geographical areas with diverse disease history and immune responses. The associated travel patterns with global events can contribute to a further disease spread affecting a large number of people within a short period and lead to a potential pandemic.

January 25, 2018

A Suite of Mechanistic Epidemiological Decision Support Tools

We present the EpiEarly, EpiGrid, and EpiCast tools for mechanistically-based biological decision support. The range of tools covers coarse-, medium-, and fine-grained models. The coarse-grained, aggregated time-series only data tool (EpiEarly) provides a statistic quantifying epidemic growth potential and associated uncertainties. The medium grained, geographically-resolved model (EpiGrid) is based on differential equation type simulations of disease and epidemic progression in the presence of various human interventions geared toward understanding the role of infection control, early vs.

January 25, 2018

Web Search Query Data to Monitor Dengue Epidemics: a New Model for Dengue Surveillance

With an estimated 500 million people infected each year, dengue ranks as one of the most significant mosquito-borne viral human diseases, and one of the most rapidly emerging vectorborne diseases. A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses.

May 02, 2019

Severe Influenza Pneumonia Surveillance: Clinical and Translational Epidemiology

The threat of epidemics due to non-human strains of influenza A viruses is ever present1. Surveillance is a critical aspect of pandemic preparedness for early case detection2. Identification of the index cases of a pandemic virus can trigger public health mitigation efforts3. To develop an appropriate surveillance process, it is important to understand the two possibilities of pandemic evolution. A new pandemic may begin with mild cases, during which surveillance should be concentrated on work/school absenteeism and in physician offices.

May 02, 2019

Crowdout: When do other events hinder informal disease surveillance?

Informal surveillance systems like HealthMap are effective at the early detection of outbreaks. However, reliance on informal sources such as news media makes the efficiency of these systems vulnerable to newsroom constraints, namely high-profile disease events drawing reporting resources at the expense of other potential outbreaks and diminished staff over weekends and holidays. To our knowledge, this effect on informal or syndromic surveillance systems has yet to be studied.



May 02, 2019

Reducing the Delay in Detecting an Influenza Epidemic with More Sensitive Case Detection Algorithms

Measures aimed at controlling epidemics of infectious diseases critically benefit from early outbreak recognition [1]. SSS seek early detection by focusing on pre-diagnostic symptoms that by themselves may not alarm clinicians. We have previously determined the performance of various Case Detector (CD) algorithms at finding cases of influenza-like illness (ILI) recorded in the electronic medical record of the Veterans Administration (VA) health system.

July 30, 2018

Radiographic Surveillance in Children: A System for Monitoring Epidemics Associated with Prominent Respiratory Symptoms

Yearly epidemics of respiratory diseases occur in children. Early recognition of these and of unexpected epidemics due to new agents or as acts of biological/chemical terrorism is desirable. In this study, we evaluate the ordering of chest radiographs as a proxy for early identification of epidemics of lower respiratory tract disease. This has the potential to act as a sensitive real-time surveillance tool during such outbreaks.


Create a tool for monitoring respiratory epidemics based on chest radiograph ordering patterns.

July 30, 2018

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