Using Geographic Monitoring for Early COVID-19 Cluster Detection

GeoMEDD enhances investigation in near real-time and in the context of health system operations to a dynamic situation.

In a recent paper published in Nature Scientific Reports, investigators from Case Western Reserve University (CWRU) School of Medicine, University Hospitals (UH) Cleveland Medical Center, and Texas A & M University discuss the development of a spatial assessment of the coronavirus disease 2019 (COVID-19) which can help guide local medical responses to clusters of outbreak at the local level in near real-time.

During the early stages of the COVID-19 pandemic, the investigators were developing a tracking system when they realized that they needed to refocus to a more granular detection methodology, instead of the more traditional spatial mapping. The goal was to employ a health systems access to data streams from numerous sources that give location and time to be able to surveil early indicators of emerging disease.

"Without such integration, there are missed opportunities for hospitals, health departments, and community leaders to mobilize early intervention activities and save lives," Andrew Curtis, Co-Director of the GIS Health & Hazards Lab said. "This information provides insights to targeted community testing opportunities, post-acute care intervention, and targeted community education in areas with community spread."

Positive COVID-19 test results could be analyzed in real time as they are gathered into health care systems, which can give all of the particular data of individual cases. For example, information like medical histories, associated symptoms and background neighborhood risk could be assessed to give a deeper understanding of where and why the disease is likely to occur and spread next. Identifying these patterns could potentially be used to reduce further transmission.

"Syndromic surveillance interest lies in the first case in a post-acute care home, or the timing pattern of emerging positives in an apartment complex, or along a rural street, or how houses on city streets 'emerge' suggesting a local transmission mechanism," Maulik Purohit, Associate Chief Medical Information Officer at UH said. "With this information, teams can mobilize to minimize the spread. This methodology will be relevant for many infectious diseases and operational responses, not just COVID."

Contract tracing will remain an important aspect of understanding disease spread, but the clusters can reveal geographic patterns in almost real time, much quicker than other monitoring systems. The data has also aided local health departments and has gained the interest of states and community leaders.