COVID-19: A Vaccine Priority Index Mapping Tool for Rapidly Assessing Priority Populations in North Carolina.
Online J Public Health Inform
; 13(3): E13, 2021.
Article
en En
| MEDLINE
| ID: mdl-35082975
ABSTRACT
BACKGROUND:
The initial limited supply of COVID-19 vaccine in the U.S. presented significant allocation, distribution, and delivery challenges. Information that can assist health officials, hospital administrators and other decision makers with readily identifying who and where to target vaccine resources and efforts can improve public health response.OBJECTIVE:
The objective of this project was to develop a publicly available geographical information system (GIS) web mapping tool that would assist North Carolina health officials readily identify high-risk, high priority population groups and facilities in the immunization decision making process.METHODS:
Publicly available data were used to identify 14 key health and socio-demographic variables and 5 differing themes (social and economic status; minority status and language; housing situation; at risk population; and health status). Vaccine priority population index (VPI) scores were created by calculating a percentile rank for each variable over each N.C. Census tract. All Census tracts (N = 2,195) values were ranked from lowest to highest (0.0 to 1.0) with a non-zero population and mapped using ArcGIS.RESULTS:
The VPI tool was made publicly available (https//enchealth.org/) during the pandemic to readily assist with identifying high risk population priority areas in N.C. for the planning, distribution, and delivery of COVID-19 vaccine.DISCUSSION:
While health officials may have benefitted by using the VPI tool during the pandemic, a more formal evaluation process is needed to fully assess its usefulness, functionality, and limitations.CONCLUSION:
When considering COVID-19 immunization efforts, the VPI tool can serve as an added component in the decision-making process.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
1_ASSA2030
Problema de salud:
1_sistemas_informacao_saude
Tipo de estudio:
Prognostic_studies
Aspecto:
Patient_preference
Idioma:
En
Revista:
Online J Public Health Inform
Año:
2021
Tipo del documento:
Article