Health

Hacking disease and death – Noushin Nabavi

To address urgent global challenges over the next fifteen years, the United Nations began implementing a transformative plan of action by releasing its 2030 Agenda for Sustainable Development. This plan is based on 17 specific sustainable development goals with good health and well being as one of these goals. To support this endeavour, Statistics Canada has released an invaluable dataset on deaths and causes of death across Canadian provinces for males and females of different ages. This dataset is very rich and can support the reporting on global goals for sustainable development. However, the data comes in long and un-tidied excel sheets that look unappealing for exploration.

To rise up to this challenge, we set up a hackathon team called “anatomy of morbidity” at the University of British Columbia to work on this dataset and make it ‘human’ friendly at the three-day Hackseq event. Our team consisted of a team of undergraduate and graduate students from local universities with a passion for data visualization and design. Our goal was to tidy up the data and make informative visualizations on the status of death and dying across Canada.

With the rise of the aging population and chronic diseases, Canada continues to suffer from the high costs of disease management [1–3]. Additionally, studies on prevalence and patterns of causes of morbidity or co-morbidity and associated determinants in Canada remain scarce and outdated [4]. The open and free life expectancy, death and causes of death datasets are examples of how Statistics Canada (Vital Statistics) supports the reporting on the global goals for sustainable development. These datasets contain comprehensive and well-annotated reports on causes of death and mortality of all Canadians from 2012 until 2016. We hypothesize that understanding the major causes of mortality (i.e. various diseases) among males and females in different age categories across all provinces can inform health care and governmental policies.

Some of the snapshots from our interactive visualizations are shown below.

Relative proportions of different causes of death across genders — filter by age
Average life expectancy at birth across provinces — filter by year
Average life expectancy at birth across provinces — filter by year or sex
Relative proportions of different diseases of death — filter by sex, age, or year

The full analytics workflow developed at the hackseq event can be found on our github page and the dashboard of visualizations can be found on our shiny server. For exploring the data, you can formulate hypotheses about what we most die of as a nation and test them visually on your screen. The overall goal of our project is to elicit the interests of health care professionals and government agencies and enable evidence-informed policymaking.

Accessible, free, and open research technologies hand-in-hand with the power of community is the driving force behind this project. We hope to see more data science for good projects. If interested, please join us for 2019’s hackseq event coming up in October.

Hackseq18 team — Anatomy of Morbidity project (Team members: Eva Yap, Katarina Priecelova, Shannon Lo, Rachel Miller, Mariam Arab, chuhan zhang, Emily Gong, Sophia Chan, Adil Imtiaz, Uyen Nguyen, Lisa Cao, Marion Shadbolt, Raissa Phillibert, Noushin Nabavi)

References:

[1]. Canada’s aging population will strain the health-care system
[2]. Caring for aging parents costs Canadians $33 billion a year — and it’s just going to get worse
[3]. Canada ‘woefully unprepared’ to deal with senior population surge, Senate committee hears
[4]. Roberts, K. C. et al. “Prevalence and Patterns of Chronic Disease Multimorbidity and Associated Determinants in Canada.” Health Promotion and Chronic Disease Prevention in Canada : Research, Policy and Practice 35.6 (2015): 87–94.


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