Mapping the COVID-19 pandemic's secondary health impacts

Exploring contributing factors across British Columbia’s neighbourhoods

All British Columbians have been affected by the COVID-19 pandemic in some way, including with regard to their health. Some people’s health has been directly affected as a result of developing COVID-19. In other cases, people’s health has been, or will be, negatively affected by impacts of the pandemic at-large such as job loss, isolation from friends and family, or other shifts and disruptions. These secondary health impacts can include:  stress leading to anxiety or depression ,  psychological distress contributing to the exacerbation of symptoms of existing chronic illnesses ,  onset of post-traumatic stress disorder , and  malnutrition brought on by food insecurity . The magnitude of these secondary health impacts varies between places based on the nature of who lives there and the kinds of activities they undertake. We also know that people who already experience social disadvantage (e.g., those experiencing poverty, those who are homeless or precariously housed, people identifying as disabled or racialized) are likely to experience the greatest secondary  impacts to their health . Overall, social, economic, and policy changes undertaken throughout the COVID-19 pandemic will have profound impacts on the health of British Columbians for well into the foreseeable future.

By exploring the map below, you will see how our research team has sought to explore where certain factors brought on by the policy, social and economic measures put in place in British Columbia to manage the pandemic are likely to be experienced. We focus on factors that are closely connected to these measures for which data are available. Experiencing these factors can bring about health changes in people's health. And these changes will be the greatest for people experiencing social disadvantage. This map can help us to understand where policy and public health efforts should be focused as we continue through the later stages of the COVID-19 pandemic. This map is the result of a model we created that identifies potential risk variables through reviewing the state of evidence that surrounds each variable and identifying appropriate data sources. Here you can see examples of some of the sources we consulted in this process to identify factors that can contribute to secondary health impacts:  job insecurity;   housing insecurity ;  occupational burnout;   loneliness and isolation;  and  educational disruption .

There are many points to keep in mind when interpreting what you see in this map. First, this map was created using a model built specifically for this study. While we have drawn on the best information and science available to us to create this model, we acknowledge that all models have limitations and can never fully capture all the complexity that surrounds an issue. This is why this map must be considered in relation to other types of evidence, maps, and tools, such as this  dashboard  created by the BCCDC. Second, we recognize that many of the variables included in this model, and their potential for contributing to negative health impacts, intersect with other aspects of people’s lives that also have health risks. We cannot look to these variables alone to fully explain the health patterns that emerge as a result of managing the COVID-19 pandemic. Third, much of the information we have used to create this map comes from the Canadian Census. This means that the variables we have included here are limited to the neighbourhood-level data available through Statistics Canada. Related to this, we use ‘dissemination areas’ to depict neighbourhoods in our maps, which are the smallest standard geographic unit for which census data is disseminated by Statistics Canada. Finally, our maps are based upon the current evidence, which will likely shift as time passes and policies and programs provide, or do not provide, needed supports.

The map that appears to the right combines each of the contributing factors listed in the boxes below. Search for a place or address, zoom in and out, and pan around. You can isolate a single contributing factor to look at by clicking on the box. To return to the full model, click on the box again. Note that white areas on the map indicate areas outside of the population  ecumene  (inhabited area).

Includes: percent of tenants in subsidized housing, and; percent of households spending 30% or more of their income on housing.

Includes: unemployment rate; percent of working population in the agriculture, forestry, fishing, hunting, mining, quarrying, oil and gas extraction, retail trade, arts, entertainment, recreation, accommodation and food services industries.

Includes: percent of lone-parent households; percent of working population in the health care, social assistance, and educational services industries.

Includes: percent of population aged 65+ years, and; percent of private single dwelling households. 

Includes: percent of population aged 5-19 years.

Acknowledgements

This research has been supported by a COVID-19 Rapid Response Grant awarded by the Michael Smith Foundation for Health Research and some additional funding from the BC SUPPORT Unit. Our team members are Dr. Valorie Crooks (Principal Investigator), Dr. Nadine Schuurman (Co-Investigator), Dr. Melissa Giesbrecht (Research Coordinator), Leah Rosenkrantz (PhD trainee), Jessica Tate (Master’s trainee), Kristie Nicol (Patient Partner), and Paul Burgener (Patient Partner). Our team is based out of the Department of Geography at Simon Fraser University.

Questions? Comments? Want technical details about this project? We welcome hearing from you. Connect with Dr. Crooks at  crooks@sfu.ca .