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App: ReCOVer: COVID-19 Vulnerability Tracker

Hosted on GitHub:

Hosted in ArcGIS Online:


Mission statement

The 2019 novel coronavirus disease (COVID-19) was declared a pandemic by the World Health Organization (WHO) on March 11th, 20201, and now surpasses 500,000 cases across 200 countries2. While the events of this outbreak are still unfolding, this unprecedented event has already devastated many communities, resulting in loss of life, depletion of healthcare resources, and economic instability.

The ability of a community to prevent and minimize harm and financial loss in the face of disaster is typically linked to its social conditions. Vulnerable communities with poorer social indicators are often less prepared for disaster, and less likely to fully recover3. Effectively identifying and addressing these disparities is crucial to address health inequities and ensure community resilience to new health risks.

Vulnerability indices summarize social and spatially relevant information, and are often used by public health officials, planners, and policymakers to respond to emergency events, such as natural disasters, anthropogenic events, or disease outbreak. The Centers for Disease Control’s Social Vulnerability Index (SVI) compiles dimensions such as socioeconomic status and household composition to help identify vulnerable communities that need support before, during, and after a hazardous event3. Locally, Public Health Ontario’s Ontario Marginalization Index (ON-Marg) also measures multiple indicators of deprivation, based on dimensions of residential instability, dependency, and ethnic concentration4.

While these indices provide substantial value towards identifying vulnerable populations, in the context of the COVID-19 crisis, social vulnerability indicators alone may not paint the whole picture. We are observing early on that COVID-19 disproportionately affects the senior population5, and as a communicable disease, is more likely to affect densely populated areas. As such, our goal was to develop a COVID-19-specific index, to identify susceptible populations and evaluate the vulnerability of Toronto neighbourhoods in response to the COVID-19 outbreak.

References

  1. WHO Director-General’s opening remarks at the media briefing on COVID-19. (2020, March 11). World Health Organization. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19—11-march-2020
  2. World Health Organization. (2020). COVID-19 Situation Report (No. 67). World Health Organization. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200327-sitrep-67-covid-19.pdf?sfvrsn=b65f68eb_4
  3. Agency for Toxic Substances and Disease Registry (ATSDR), (2018, September 10). The Social Vulnerability Index (SVI): Fact Sheet. Centers for Disease Control and Prevention.
  4. Ontario Marginalization Index (ON-Marg). (n.d.). Public Health Ontario. Retrieved March 28, 2020, from https://www.publichealthontario.ca/en/Data and Analysis/Health Equity/Ontario Marginalization Index
  5. Wu, C., Chen, X., Cai, Y., Xia, J., Zhou, X., Xu, S., Huang, H., Zhang, L., Zhou, X., Du, C., Zhang, Y., Song, J., Wang, S., Chao, Y., Yang, Z., Xu, J., Zhou, X., Chen, D., Xiong, W., et al. (2020). Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2020.0994

Video Presentation

Documentation

Team Members

Cathy Yang: Cathy is a 3rd year undergraduate student at U of T studying Physiology, Human Geography and GIS. She was the lead researcher and data curator for this project. Her interests lie in public health and assessing psychosocial barriers to healthcare access. Throughout this experience, she thoroughly enjoyed being able to merge her background and knowledge in healthcare and clinical research with the tools she has learned from her GIS courses. She hopes in the future to be able to continue using geospatial technologies to help communicate and solve health problems. In her free time, she enjoys listening to podcasts, playing piano, and watching her favourite sports teams.

Tia Datta: Tia is a 3rd year undergraduate student at U of T studying Computer Science and Statistics. She helped with coding this app and enjoyed exploring the functionalities of ArcGIS Online and learning about spatial analysis techniques. She hopes to utilize these skills in future projects. Her hobbies include cooking, video games, and spending time with her cat.

Chloe Nguyen: Chloe is a 1st year undergraduate student at U of T studying Computer Science. She was a developer for this project. She has an interest in data science and her hobbies include dance, martial arts, chess and piano.