Surveillance Tool in Liberia

Two analysts from the Johns Hopkins Applied Physics Laboratory’s (APL) traveled to Liberia last year to deploy APL-developed disease surveillance tools to help the country deal with future disease outbreaks.

During their first visit, Shraddha Patel, Public Health Specialist and Rich Wojcik, both computer programmers, visited the medical clinic at Camp EBK military training facility and met with stakeholders from the Armed Forces of Liberia (AFL) to take stock of their current public health and disease surveillance capabilities.

They were joined by representatives from the Naval Medical Research Unit-3 (NAMRU-3), the sponsor of the project. NAMRU-3 is the largest Department of Defense (DOD) overseas biomedical research facility and conducts research on a range of diseases. They also perform infectious disease surveillance to support military personnel in Africa, Middle East, and Southwest Asia.

At Camp EBK, the analysts found that there was no internet service, electricity was provided by a generator, patient records were kept in paper logbooks, and the data was not standardized. However, they were able to install the “Suite for Automated Global Electronic BioSurveillance (SAGES) tool kit developed by APL and the Department of Defense.

The SAGES software suite collects, analyzes, visualizes, and shares information within a national disease surveillance system. Individual tools may be used to complement existing disease surveillance systems or used together to create an end-to-end capability.

The AFL personnel from four military medical clinics in the country were provided training to use the SAGES tool kit. Prior to the training, Patel and Wojcik took four new laptops donated by the Henry Jackson Foundation and configured them with SAGES tools.

“We are in the process of building out dashboards for the Ministry of Health’s headquarters to allow aggregate data from various hospitals and clinics to be visualized using graphs and maps,” Patel said. “These dashboards will allow epidemiologists to analyze health data both temporally and spatially.”


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