Identifying High-Risk Areas for Dengue Infection Using Mobility Patterns on Twitter

Traditionally, surveillance systems for dengue and other infectious diseases locate each individual case by home address, aggregate these locations to small areas, and monitor the number of cases in each area over time. However, human mobility plays a key role in dengue transmission, especially due to the mosquito day-biting habit, and relying solely on individuals' residential address as a proxy for dengue infection ignores a multitude of exposures that individuals are subjected to during their daily routines.

June 18, 2019

Developing a Prototype Opioid Surveillance System at a 2-Day Virginia Hackathon

At the Governor’s Opioid Addiction Crisis Datathon in September 2017, a team of Booz Allen data scientists participated in a two-day hackathon to develop a prototype surveillance system for business users to locate areas of high risk across multiple indicators in the State of Virginia. We addressed 1) how different geographic regions experience the opioid overdose epidemic differently by clustering similar counties by socieconomic indicators, and 2) facilitating better data sharing between health care providers and law enforcement.

January 25, 2018

Using Scan Statistic to Detect Heroin Overdose Clusters with Hospital Emergency Room Visit Data

Early detection of heroin overdose clusters is important in the current battle against the opioid crisis to effectively implement prevention and control measures. The New York State syndromic surveillance system collects hospital emergency department (ED) visit data, including visit time, chief complaint, and patient zip code. This data can be used to timely identify potential heroin overdose outbreaks by detecting spatial-temporal case clusters with scan statistic.

Objective:

January 25, 2018

Coordinated Enhanced Surveillance with Healthcare Entities for Mass Gathering Events

Mass gatherings can result in morbidity and mortality from communicable and non-communicable diseases, injury, and bioterrorism. Therefore, it is important to identify event-related visits as opposed to community-related visits when conducting public health surveillance. Previous mass gatherings in Virginia have demonstrated the importance of implementing enhanced surveillance to facilitate early detection of public health issues to allow for timelyresponse.

August 21, 2017

Animal Surveillance: Use of Animal Health Data to Improve Global Disease Surveillance

Since the majority of emerging infectious diseases over the past several decades have been zoonotic, animal health surveillance is now recognized as a key element in predicting public health risks. Surveillance of animal populations can provide important early warnings of emerging threats to human populations from bioterrorism or naturally occurring infectious disease epidemics. This study investigated current animal data collection and surveillance systems, isolated major gaps in state and national surveillance capabilities, and provided recommendations to fill those gaps.

July 11, 2017

Monitoring for Local Transmission of Zika Virus using Emergency Department Data

The first travel-associated cases of Zika virus infection in New York City (NYC) were identified in January 2016. Local transmission of Zika virus from imported cases is possible due to presence of Aedes albopictus mosquitos. Timely detection of local Zika virus transmission could inform public health interventions and mitigate additional spread of illness. Daily emergency department (ED) visit surveillance to detect individual cases and spatio-temporal clusters of locally-acquired Zika virus disease was initiated in June 2016. 

Objective

July 16, 2017

Multidimensional Tensor Scan for Drug Overdose Surveillance

Drug overdoses are an increasingly serious problem in the United States and worldwide. The CDC estimates that 47,055 drug overdose deaths occurred in the United States in 2014, 61% of which involved opioids (including heroin, pain relievers such as oxycodone, and synthetics).1 Overdose deaths involving opioids increased 3-fold from 2000 to 2014.1 These statistics motivate public health to identify emerging trends in overdoses, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved).

July 17, 2017

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance [2]. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRAfunded researchers, which are deployed on-demand in the cloud (e.g., Amazon Web Services).

August 10, 2017

Spatio-Temporal Cluster Detection for Legionellosis using Multiple Patient Addresses

The Bureau of Communicable Disease (BCD) at the NYC Department of Health and Mental Hygiene performs daily automated analyses using SaTScan to detect spatio-temporal clusters for 37 reportable diseases. Initially, we analyzed one address per patient, prioritizing home address if available. On September 25, 2015, a BCD investigator noticed two legionellosis cases with similar work addresses. A third case was identified in a nearby residential facility, and an investigation was initiated to identify a common exposure source.

August 10, 2017

Support Vector Subset Scan for Spatial Outbreak Detection

Neill’s fast subset scan2 detects significant spatial patterns of disease by efficiently maximizing a log-likelihood ratio statistic over subsets of locations, but may result in patterns that are not spatially compact. The penalized fast subset scan (PFSS)3 provides a flexible framework for adding soft constraints to the fast subset scan, rewarding or penalizing inclusion of individual points into a cluster with additive point-specific penalty terms.

August 10, 2017

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