Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

CDC Innovation Fund Project Spotlight

NIOSH- Mini Baghouse Technology to Control Worker Exposure to Silica Dust at Hydraulic Fracturing Sites

Eric Esswein of the CDC National Institute of Safety & Health (NIOSH) is shown next to the mini baghouse technology he designed to reduce worker exposure to silica dust at hydraulic fracturing sites.

Esswein’s team designed bag assemblies to reduce worker exposure to silica dust at hydraulic fracturing locations. The National Institute for Occupational Safety and Health (NIOSH) mini-baghouse assembly mounts to the top of sand movers used in the hydraulic fracturing process. The assembly was field tested in 2016 with industry partners at two locations. Esswein obtained a patent on the technology in February 2017. Industry partners have expressed interest in supporting further field testing.

Eric Esswein of NIOSH designed mini baghouse technology to reduce worker exposure to silica dust. CDC NIOSH photo, Randy Nitz.

ATSDR- Development of a portable multi-sensor device

In the photo, Greg Zarus builds and tests inexpensive battery-powered air sampling devices for pollution events.

Communities and local officials often request the Agency for Toxic Substances and Disease Registry (ATSDR) to investigate hazardous air pollution that they believe is harming their health. Using new sensor technology, Greg Zarus’s ATSDR team is building and testing inexpensive battery-powered air sampling devices that can detect multiple chemicals under a variety of atmospheric conditions, turn on a separate more accurate sampling device, collect samples, and turn off, for multiple air pollution events.

Zarus’s team is partnering with NIOSH to field test two separate networks of robotic samplers with NIOSH in summer 2017. His project is also partnered with Georgia Institute of Technology faculty and students through their Capstone program. One of his team’s interns developed a lesson plan to use the sensors to teach STEM in high schools, and plans to find school hosting sites to adopt the sensor programming—making schools a possible future crowdsource for pollution data.

Greg Zarus builds and tests inexpensive battery-powered air sampling devices for pollution events. CDC photo, Greg Zarus.

NCBDDD- Reinventing autism surveillance with machine learning

The photo shows a CDC-developed data algorithm that aims to predict whether a child meets Autism Spectrum Disorder (ASD) criteria using the words in a child’s evaluations.
Matt Maenner’s team, composed of scientists from the National Center on Birth Defects and Developmental Disabilities (NCBDDD) and the Center for Surveillance, Epidemiology, and Laboratory Services (CSELS), seeks to reduce the labor needed to estimate the prevalence of autism spectrum disorder (ASD) among children. CDC produces the most widely used estimate of ASD prevalence in the United States, but the system is very labor intensive. It involves having clinicians manually review developmental evaluations to look for symptoms of ASD. Maenner’s team wants to use machine learning to automate parts of this process, improving the efficiency and timeliness of the system. Their algorithm uses the software Random Forest and aims to predict whether a child meets ASD criteria using the words in a child’s evaluations. This project is co-funded through the HHS Ventures Fund program.

A CDC-developed algorithm aims to predict whether a child meets Autism Spectrum Disorder (ASD) criteria using the words in a child’s evaluations. CDC photo, Matt Maenner.

CGH- Counterfeit Drug Identifier (CoDI)

CDC’s Mike Green has designed a counterfeit drug identifier to detect falsified, degraded, and expired drugs. The project has focused on testing antimalarial tablets.

Mike Green in CDC’s Center for Global Health (CGH) has designed a simple and cheap device to detect falsified/degraded/expired drugs. His team has successfully tested a prototype in Ghana and is using iFund dollars to engineer an improved prototype. The project’s focus has been on testing antimalarial tablets. A provisional patent application was filed. The CoDI is participating in an upcoming Drug Quality Field Methods evaluation project in spring 2017. The study will compare different field methods to identify poor quality medicine. He is also working with the Georgia Institute of Technology to test drug samples.

CDC’s Mike Green has designed a counterfeit drug identifier to detect falsified, degraded, and expired drugs. The project has focused on testing antimalarial tablets. CDC photo, Mike Green.

CGH- Thinking outside the container: Unlocking the full potential of solar sanitation

The photo depicts solid waste collected from households that’s treated, converted to charcoal briquettes, and sold.

Working in collaboration with NCEZID and CDC Kenya, Mintz’s project is testing the sustainability and scalability of solar waste treatment among households and municipalities without sewage access in Kenya. Solid waste is collected from households, treated, converted to charcoal briquettes, and sold. The FY2013 iFund demonstration pilot focused on pathogen inactivation with solar sanitation in Kenya’s Kakuma refugee camp as well as the development of robust health and safety protocols for processing non-sewered waste. The current project is focused on scalability to support the Ministry of Health’s goals and ensure more waste is safely managed. The project has received additional funding from USAID, the Bill and Melinda Gates Foundation, and others.

Solid waste is collected from households, treated, converted to charcoal briquettes, and sold. Photo credit, Sanivation CEO, Andrew Foote.

  • Page last reviewed: October 11, 2017
  • Page last updated: April 13, 2017
  • Content source:
    • Office of the Associate Director for Science
TOP