Kearney Pathfinders| Light the Path

Light the Path

The COVID-19 pandemic initiated changes in human population movements and activities around the world. Your challenge is to use Earth observations to explore how human activity and regional land-based human movement patterns may have shifted in response to COVID-19.

A Model for Data-Informed Policies

Summary

Our Project involved the analysis and modeling of data from 10 countries showing the effect of movement restriction policies on the COVID-19 transmission and GDP. The choice of countries to sample was based on those with a population of over 4M, five with the highest and lowest cases limiting to a minimum of 5,000 cases. Joining data such as the number of molecules of Nitrogen Dioxide (NO2) in the tropospheric atmospheric column, COVID-19 transmission, and GDP Data, we utilized Data Analytics and Visualization tools to show that an overall proactive approach to policies could reduce the negative impact of a pandemic on a country’s GDP and increase the quality of life.

How We Addressed This Challenge

The Light the Path challenge is to use Earth observations to explore how human activity and regional land-based human movement patterns may have shifted in response to COVID-19.  Our project analyzed 10 countries, using the criteria mentioned in the summary. We researched how strict their movement restriction policies were and when they were implemented.  We combined this data to the reported COVID-19 cases and projected drop in GDP. We found that the restrictions of land-based movement had an effect on the reduction of reported COVID-19 cases in the long term. Additionally, countries that applied restrictions earlier had an overall lower percentage of COVID-19 cases and less of a negative impact on their GDP in the long run.  These observations may help governments realize the long-term benefits and influence in their future decisions to restrict human movement preemptively in pandemic situations to not only save human lives, but to also prevent long-lasting unstable or negative economic outcomes.

How We Developed This Project

Inspiration: 

A team member had a child that was diagnosed with cancer.  She was part of one of the first studies that incorporated a risk-based treatment plan to improve quality of life.  Based on 50 years of research, the hospital had learned that although extreme treatment may increase survivability, quality of life mattered.  Using a more balanced and risk-based approach, the hospital was able to achieve a 95 percent cure rate and improved quality of life.  This demonstrates that using lessons learned and a measured approach can achieve the same results or improved results while incorporating the quality of life.  This inspired us to develop a model to determine whether balanced policies could achieve similar results as more stringent policies when responding to pandemics to provide a more sustainable approach focused on sustainability, quality of life, and minimizing the impact to the economy.

Approach:

  • We researched the countries with the highest and lowest amount of COVID-19 cases.
    We explored how the countries did with their movement restriction policies.
  • We identified global and country specific policies related to COVID-19 that restricted movement and when those policies were put into place looking at the country’s government’s news and policy releases.
    (Data: publicly available policy data). By representing policy responses for the countries selected as 5 response metrics, we were able to develop a composite measure called the Policy Index Score.  
    The index of any given day is calculated as the mean score of the five metrics, each taking a value between 0 and 100:

            I = 1/5 * I(1) + I(2) + I(3) + I(4) + I(5)
          We applied additional factors as to whether the policy was applied locally or nationwide.

  • Using the NASA satellite imagery of NO2, we were able to observe the impact the policies had on population movement over time.
    Policy Data: Travel restrictions and Re-open plans per country selected.
    Population Movement Data:  NASA satellite imagery Nighttime Imagery Data
    Population Movement Data: NO2. We used a delta between 2 years of NO2 data.
  • We gathered GPD and economic data (unemployment, GDP, supply chain) to identify what happens to the economy as population movement declines.
    Economy (Unemployment) Data:  NO2 data and GDP data
    Economy (GDP) Data:  IMF and CIA World Factbook
    Economy (Supply Chain) Data:  NO2
  • We used COVID-19 transmission rate of the 10 countries that were selected to understand the impact the policies and reduced (or not reduced) human movement had on the spread of COVID-19.
    Data:  John Hopkins University CSSE

Tools:

Using Tableau, Python and ArcGIS, we were able to align the population movement, policies enacted per countries selected, COVID transmission rate, and economic data.

Project Demo
Project Code
Data & Resources

Population Movement Data    - NASA

Population Data - NASA

COVID Cases

GDP Data

Policy Data

Tags
#LightthePath #DataYourWayThrough #PolicyRestrictions #TravelRestrictions #CountryPolicy #TravelPolicy #DataInformedPolicy #ProtectOurVulnerableCommunities #ImproveCommunication #ImproveEconomicPerformance #EnsureResponseTimeliness #ImprovePandemicResponse #ImproveLeadershipDecisions #QualityOfLife #BalancedApproach #PeopleAreTheFuture #GDPRisk #RiskBasedSolutions #ChangeTodayInfluenceTomorrow #GabbysSolution #ImproveTomorrowToday #StayHome #EverythingInModeration
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.