A Spatial Biosurveillance Synthetic Data Generator in R

To develop a spatially accurate biosurveillance synthetic data generator for the testing, evaluation, and comparison of new outbreak detection techniques.

June 09, 2017

Evaluation of the Malaria Surveillance System in Kaduna State, Nigeria 2016

Malaria is a parasitic disease caused by Plasmodium falciparum. About 3.2 billion people worldwide are at risk of malaria. Children and pregnant women are particularly vulnerable to the disease. Sub- Saharan Africa carries a high share of the global malaria burden. Effective malaria surveillance system is essential in the control and elimination of malaria. Worldwide, there were an estimated 198 million cases of malaria in 2013 and 584,000 deaths. 

Objective

June 11, 2017

Estimating spatial patterning of dietary behaviors using grocery transaction data

Unhealthy diet is becoming the most important preventable cause of chronic disease burden. Dietary patterns vary across neighborhoods as a function of policy, marketing, social support, economy, and the commercial food environment. Assessment of community-specific response to these socio-ecological factors is critical for the development and evaluation policy interventions and identification of nutrition inequality.

July 27, 2017

Factors associated with immunization of children in Kaduna State, Nigeria, 2016

Immunization is one of the safest and most effective interventions to prevent disease and early child death. Although, about three quarters of the world’s child population is reached with the required vaccines, only half of the children in Sub-Saharan Africa get access to basic immunization. A substantial number of children worldwide do not complete immunization schedules because neither health services nor conventional communication mechanisms regularly reach their communities.

June 19, 2017

Better, Stronger, Faster: Making the Case for Adding Data Fields to Syndromic Surveillance, NJ 2015

NJDOH created a custom classification in EpiCenter to detect synthetic cannabinoid-related ED visits using chief complaint data. DOH staff included the keywords black magic, black mamba, cloud 9, cloud 10,incense, k2, legal high, pot potpourri, spice, synthetic marijuana, voodoo doll, wicked x, and zombie which were obtained from the New York City Department of Health and Mental Hygiene. Staff also included the keywords, agitation, k-2, moon rocks, seizure, skunk, and yucatan to characterize the related event.

September 25, 2017

A Bayesian Hierarchical Model for Estimating Influenza Epidemic Severity

Timely monitoring and prediction of the trajectory of seasonal influenza epidemics allows hospitals and medical centers to prepare for, and provide better service to, patients with influenza. The CDC’s ILINet system collects data on influenza-like illnesses from over 3,300 health care providers, and uses this data to produce accurate indicators of current influenza epidemic severity. However, ILINet indicators are typically reported at a lag of 1-2 weeks. Another source of severity data, Google Flu Trends, is calculated by aggregating Google searches for certain influenza related terms.

August 07, 2017

Evaluation of National Influenza Sentinel Surveillance System in Nigeria, Jan-Dec 2014

National Influenza Sentinel Surveillance (NISS) was established in Nigeria in 2006 to monitor influenza occurrence in humans in Nigeria and provide a foundation for detecting outbreaks of novel strains of influenza. Surveillance for influenza-like illness (ILI) and severe acute respiratory infection (SARI) is carried out in 4 sentinel sites. Specimens and epidemiological data are collected and transported 4 days a week from the sentinel sites to the National Influenza Reference Laboratory.

August 31, 2017

Acute Gastroenteritis: Contribution of SOS Médecins Network

In France, the surveillance of GE is performed by several complementary systems including specific and syndromic surveillance systems.

August 07, 2017

Performance of Early Outbreak Detection Algorithms in Public Health Surveillance from a Simulation Study

Early detection of outbreaks is crucial in public health surveillance in order to enable rapid control measures. Statistical methods are widely used for outbreak detection but no study has proposed to evaluate and compare thoroughly the performance of these methods.

Objective

Evaluate the performance of 8 statistical methods for outbreak detection in health surveillance with historical data.

September 01, 2017

Alcohol-Related ED Visits and Ohio State Football: Putting the O-H in ETOH

According to the Center for Disease Control (CDC), binge drinking causes over half of the 88,000 excessive alcohol use deaths and costs approximately $149 billion dollars annually in the United States. Additionally, excessive alcohol use can increase the risk of many other health problems, including injuries and cancer, placing a large burden on public health. In Franklin County, Ohio, The Ohio State University (OSU) football games are an occasion of binge drinking for the student body and Columbus population alike.

August 07, 2017

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