| Summary: | The Vida Decision Support System (Vida) is an application of the Environment-Vulnerability-
Decision-Technology (EVDT) integrated modeling framework specifically aimed at COVID-19 impact
and response analysis. The development of Vida has been an international collaboration involving
multidisciplinary teams of academics, government officials (including public health, economics,
environmental, and demographic data collection officials), and others from six states: Angola, Brazil,
Chile, Indonesia, Mexico, and the United States. These collaborators have been involved with
the identification of decision support needs, the surfacing and creation of relevant data products,
and the evaluation of prototypes, with the vision of creating an openly available online platform
that integrates earth observation instruments (Landsat, VIIRs, Planet Lab’s PlanetScope, NASA’s
Socioeconomic Data and Applications Center, etc.) with in-situ data sources (COVID-19 case data,
local demographic data, policy histories, mobile device-based mobility indices, etc.). Vida both
visualizes historical data of relevance to decision-makers and simulates possible future scenarios.
The modeling techniques used include system dynamics for public health, EO-based change detection
and machine learning for environmental analysis, and discrete-event simulation of policy changes and
impacts. In addition to the direct object of this collaboration (the development of Vida), collaborators
have also benefited from sharing individual COVID-19-related insights with the network and from
considering COVID-19 response in a more integrated fashion. This work outlines the Vida Decision
Support System concept and the EVDT framework on which it is based. The international team is
using Vida to evaluate the outcomes in several large cities regarding COVID cases, environmental
changes, economic changes and policy decisions. It provides an overview of the overlapping and
diverging needs and data sources of each of the collaborating teams, as well as how each of those
teams have contributed to the development of Vida. The current state of the Vida prototypes and plans
for future development will be presented. Additionally, this work will discuss the lessons learned
from this development process and their relevance to other integrated applications.
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