“To invoke a visual image, it’s as if there are circles of inequalities, powerlessness, and multiple forms of deprivation. All of them are growing wider and deeper, due to COVID-19.”

 Michelle Bachlet, UN High Commissioner for Human Rights



INTRODUCTION

The Socioecological Model (SEM) has been widely adopted in public health and considers how health is determined by complex, interrelated factors at individual, community, and environmental levels. This model can provide insight into the disproportional impact of COVID-19 on specific populations. In this episode of the Public Health Insight Podcast series, the team explores the COVID-19 pandemic as a case study in applying the principles of the SEM. 

In this blog post, we will review COVID-19 measures by exploring each layer of the SEM:

  • Individual Layer
  • Interpersonal Layer
  • Organizational Layer
  • Community Layer
  • Public Policy Layer

The SEM has been revised and adapted for multiple purposes in public health and other arenas. In this blog, we will utilize this model adapted from McLeroy et al (1988). 

The Individual Layer

At the core of the socioecological model is the individual layer, or the specific characteristics of a person. This level includes biological and behavioural factors that place an individual at greater or reduced risk of disease. Gender, socioeconomic status, ethnicity, attitudes, beliefs, and knowledge are all individual factors (CDC, 2022; Cowan, Khan, Shastry, & Edelman, 2021; Levin-Zamir et al., 2021).

Many COVID-19 prevention strategies have focused on individual level decisions stressing people should:

  • wear a mask 
  • choose to stay home
  • maintain social distancing
  • practice good hand and respiratory hygiene, and
  • get vaccinated

to limit the transmission of COVID-19

An individual’s decision to follow these prevention measures may be influenced by a person’s:

  • health literacy
  • perceived risk from COVID-19
  • knowledge of local languages,
  • trust in government, and
  • barriers to accessing information such as vision and hearing impairments.

At an individual level, a person’s likelihood of getting or experiencing severe symptoms COVID-19 can be influenced by age, pre-existing medical conditions, and occupation. A disproportionate number of frontline workers are women, people of colour, and/or recent immigrants which increases COVID risk within these groups (Rho, Brown, & Fremstad, 2020).

The Interpersonal Layer

The interpersonal level of the SEM includes the networks around an individual such as family, friends, colleagues, and other formal or informal contacts (LeRouge, Deckard, Fruhling, & Lyon, 2021; Levin-Zamir et al., 2021).

The groups around an individual can influence whether a person adopts prevention measures against COVID-19. For example, a person may decide to wear a mask in order to conform to their peer group or at the request of a high-risk family member. Contacts can also bridge communication gaps, allowing those with health literacy or language barriers to access knowledge and interventions. However, they may also provide a biased view and influence what type of COVID information an individual obtains (ie. sharing high-quality scientific literature vs. memes on social media).

Contacts within the interpersonal level can influence the risk of contracting COVID. A supportive social network may allow a person at a higher risk from COVID-19 to stay safe at home while neighbours or friends help with groceries and other errands (LeRouge et al., 2021).  On the other hand, people living in large, multigenerational households are at a potentially higher risk if individuals within the group are essential workers.

The Organizational Layer

The organizational level of the SEM includes the rules and regulations of organizations or institutions, such as workplaces, schools, facilities, places of worship, and local health services, that the individual attends (COVID-19 Curriculum, 2021; LeRouge et al., 2021).

Organizational level factors that impact COVID-19 measures can include:

  • facilities installing hand sanitizer or hand washing stations,
  • implementation of remote work/schooling/worship services,
  • work/school/facility mask enforcement,
  • safe distancing incorporated into work/school setups,
  • cancellation of work/school travel or conferences,
  • provision of paid sick leave,
  • provision of time off for vaccination, and
  • promotion and provision of PPE (Ingram et al., 2021; LeRouge et al., 2021).

Unsafe organizational regulations can leave workers vulnerable to disease. Meat-packing workers, for example, often are required to adhere to punitive sick leave policies which require them to work even when exhibiting COVID symptoms or risk job loss, thereby endangering their own health and the health of their colleagues. This industry employs a disproportionate number of minority workers, people with limited local language skills, and previously incarcerated individuals, increasing COVID risk among these vulnerable groups (Ingram et al., 2021; Rho et al., 2020). 

The Community Layer

The community level of the SEM includes the collective networks around the individual, such as the built environment, available services, local culture, transportation network, and advocacy groups (COVID-19 Curriculum, 2021; LeRouge et al., 2021).

Community level factors that impact COVID-19 measures can include:

  • social norms and attitudes towards COVID-19 control measures,
  • scheduling/cancellation of events that draw crowds,
  • availability of safe, spacious places for exercise,
  • crowding on transportation,
  • housing density,
  • law enforcement involvement in COVID measures,
  • COVID information dissemination by local media,
  • redirection of production towards needed supplies (such as breweries producing hand sanitizer), and
  • influence of local leaders (LeRouge et al., 2021; Levin-Zamir et al., 2021).

Housing, unemployment, and crisis centre networks are also part of the community level. COVID-19 has disrupted many of these services, leaving many vulnerable populations with limited support (Cowan et al., 2021; Levin-Zamir et al., 2021).

The Policy Layer

Public policy is the outer layer of the SEM. This layer pertains to laws, policies, and regulatory decisions at local, national, and international levels. It is at this level of the SEM that laws regarding COVID-19 containment measures are set, resources are allocated, and emergency taskforces are activated (COVID-19 Curriculum, 2021; LeRouge et al., 2021). For example:

  • laws regarding masks, social distancing, and business closures,
  • vaccine mandates,
  • movement control orders (stay-at-home/shelter-in-place),
  • distance-learning directives,
  • public health campaigns,
  • establishment of laboratory networks for increased testing capacity, and
  • funding for COVID research

are public policy level COVID-19 measures (LeRouge et al., 2021; Levin-Zamir et al., 2021).

This ring of the SEM can influence all other layers, highlighting the importance of ensuring interventions at this level are equitable and consider the needs of vulnerable populations (LeRouge et al., 2021; Levin-Zamir et al., 2021). For example, movement control orders have inadvertently increased COVID-19 cases amongst migrant working populations, particularly in areas where many workers live in the same, crowded facilities (Levin-Zamir et al., 2021).

Around the world, public policies have called for distance learning through much of the COVID crisis.  Students without access to technology or high-speed internet are left distinctly disadvantaged. Vulnerable children and adolescents can also miss out on important school services such as affordable or free lunches, counseling, and social protections provided through face-to-face learning. Policies that neglect to factor in these important populations will result in ongoing negative effects of COVID-19 (Levin-Zamir et al., 2021; Pinheiro & Bauer, 2020).

Conclusion/Key Takeaways

The COVID-19 pandemic provides a topical SEM case study. Exploring factors at each layer of the SEM can help public health decision makers understand how the complex interplay between individuals, their networks, and surrounding environments may make specific groups more or less susceptible to the effects of COVID-19. Using this model can help target interventions at each level, ultimately influencing an individual’s health.

Written by: Malissa Underwood, BSN, MPH

Public Health Insight

The Public Health Insight (PHI) is a public health communication and knowledge translation organization that disseminates information on a variety of public health issues focusing on the social determinants of health and the Sustainable Development Goals. 

CDC. (2022). The Social-Ecological Model: A Framework for Prevention |Violence Prevention|Injury Center. Retrieved February 23, 2022, from Centers for Disease Control and Prevention website here.

COVID-19 Curriculum. (2021). Social-Ecological Model for Understanding Differential Impact of COVID-19. Retrieved February 23, 2022, from Medical Student COVID-19 Curriculum website here.

Cowan, E., Khan, M. R., Shastry, S., & Edelman, E. J. (2021). Conceptualizing the effects of the COVID-19 pandemic on people with opioid use disorder: an application of the social ecological model. Addiction Science and Clinical Practice, 16(1), 1–6. Available here.

Haischer, M. H., Beilfuss, R., Hart, M. R., Opielinski, L., Wrucke, D., Zirgaitis, G., … Hunter, S. K. (2020). Who is wearing a mask? Gender-, age-, and location-related differences during the COVID-19 pandemic. PLOS ONE, 15(10), e0240785. Available here.

Ingram, M., Wolf, A. M. A., López-Gálvez, N. I., Griffin, S. C., & Beamer, P. I. (2021). Proposing a social ecological approach to address disparities in occupational exposures and health for low-wage and minority workers employed in small businesses. Journal of Exposure Science and Environmental Epidemiology, 31(3), 404–411. Available here.

LeRouge, C., Deckard, G., Fruhling, A., & Lyon, V. (2021). An Exercise Using a Social Ecological Lens To Understand the Vast Network of Stakeholders Required To Manage a Pandemic. Journal of Health Administration Education, 38(1), 399–425. Available here.

Levin-Zamir, D., Sorensen, K., Su, T. T., Sentell, T., Rowlands, G., Messer, M., … Okan, O. (2021). Health promotion preparedness for health crises – a ‘must’ or ‘nice to have’? Case studies and global lessons learned from the COVID-19 pandemic. Global Health Promotion, 28(2), 27–37. Available here.

McLeroy, K., Bibeau, D., Steckler, A., & Glanz, K. (1988). An Ecological Perspective on Health Promotion Programs. Health Education Quarterly, 15(4), 351–377. 

Pinheiro, P., & Bauer, U. (2020). From at risk to as risk and back again: children and adolescents during COVID-19. Retrieved February 23, 2022, from the Transforming Society website here.

Rho, H. J., Brown, H., & Fremstad, S. (2020). A basic demographic profile of workers in frontline industries. Available here.