Geo-mapping COVID-19 Cases to Identify Community Clusters in North Central Health District
Abstract
Background: Middle Georgia continues to experience moderate to high COVID-19 activity, and the burden of reported disease follow up belongs to local public health. Priority-based case definitions have been utilized to guide the staff conducting interviews within North Central Health District (NCHD) since 2020. This presentation describes the current process for prioritizing case follow up within NCHD that was developed to improve community exposure and cluster identification.
Methods: An internal workflow involving collecting data reported into the state notifiable disease system, Microsoft Excel, and the Census Geocoder tool are utilized to organize cases in a Tableau workbook by census tract. The Tableau ® workbook was set to detect clusters, which are defined as a census tract with three or more cases in any given MMWR week. This information was then distributed and assigned to the district's COVID-19 Case Investigators which were downloaded from Tableau® and for case follow up. Information collected is then analyzed by Epidemiology staff to facilitate cluster identification.
Results: Geographical mapping or “geo-mapping” of district-wide COVID-19 cases by census tract created data visualizations that helped maintain situational awareness among internal Epidemiology staff. Though some case interviews alluded to possible work or school exposures, additional follow up did not lead to the identification of shared community exposures or clusters outside of household clusters.
Conclusion: Despite limited success in detecting community COVID-19 clusters in North Central Health District, geo-mapping may improve communicable disease outbreak detection and should be considered in epidemiological investigations of other illnesses and outbreaks.
Keywords
Geographical mapping, geo-mapping, COVID-19, outbreak detection
Geo-mapping COVID-19 Cases to Identify Community Clusters in North Central Health District
Background: Middle Georgia continues to experience moderate to high COVID-19 activity, and the burden of reported disease follow up belongs to local public health. Priority-based case definitions have been utilized to guide the staff conducting interviews within North Central Health District (NCHD) since 2020. This presentation describes the current process for prioritizing case follow up within NCHD that was developed to improve community exposure and cluster identification.
Methods: An internal workflow involving collecting data reported into the state notifiable disease system, Microsoft Excel, and the Census Geocoder tool are utilized to organize cases in a Tableau workbook by census tract. The Tableau ® workbook was set to detect clusters, which are defined as a census tract with three or more cases in any given MMWR week. This information was then distributed and assigned to the district's COVID-19 Case Investigators which were downloaded from Tableau® and for case follow up. Information collected is then analyzed by Epidemiology staff to facilitate cluster identification.
Results: Geographical mapping or “geo-mapping” of district-wide COVID-19 cases by census tract created data visualizations that helped maintain situational awareness among internal Epidemiology staff. Though some case interviews alluded to possible work or school exposures, additional follow up did not lead to the identification of shared community exposures or clusters outside of household clusters.
Conclusion: Despite limited success in detecting community COVID-19 clusters in North Central Health District, geo-mapping may improve communicable disease outbreak detection and should be considered in epidemiological investigations of other illnesses and outbreaks.
