What are special considerations needed to address infodemic-related needs of at-risk, vulnerable, and unnetworked or partially hidden communities?

This is one of eleven primers that the organizing team of the WHO infodemiology conference (June/July 2020) prepared to feed into multidisciplinary discussions in working groups that were discussing a public health research agenda. The primer is not intended to be exhaustive review of literature, but more a rapid review and a starting point for discussion. I will be publishing the primers over the course of next weeks. Hope you find them useful as well. Thank you to colleagues from Demand for Immunization Team at US CDC for participation in primer preparation.

Definitions and Key Concepts

• Vulnerable populations: “The vulnerable populations refers to but not limited to children, minors, pregnant women, fetuses, human in vitro fertilization, prisoners, employees, military persons and students in hierarchical organizations, terminally ill, comatose, physically and intellectually challenged individuals, institutionalized, elderly individuals, visual or hearing impaired, ethnic minorities, refugees, international research, economically and educationally disabled and healthy volunteers[1].”
• Marginalized populations: “Those excluded from mainstream social, economic, cultural, or political life. Examples of marginalized populations include, but are by no means limited to, groups excluded due to race, religion, political or cultural group, age, gender, or financial status. To what extent such populations are marginalized, however, is context specific and reliant on the cultural organization of the social site in question[2].”
• Health equity: Idea that everyone should have a fair opportunity to attain their full health potential and that no one should be disadvantaged from achieving this potential[3].
• Health inequality: Differences in health across population sub-groups, and is an important part of addressing health inequities (differences in health that are deemed unfair or ethically problematic).
• Social determinants of health: Conditions in the places where people live, learn, work, and play affect a wide range of health risks and outcomes[4].
• Social stigma: “Social stigma in the context of health is the negative association between a person or group of people who share certain characteristics and a specific disease[5].”

 Considering the Needs of Marginalized Populations

Vulnerable and marginalized populations often lack basic health services and resources. These populations often face challenges to seeking healthcare which include but are not limited to access, socio-economic, geographic and cultural barriers. Common barriers to seeking healthcare include access to healthcare and socio-cultural factors[6].

Vulnerability of population differs by context, examples of vulnerable populations in health care in the US include chronically ill and disabled, low-income and homeless individuals, certain geographical communities, LGBTQ+ populations, and the very young and very old[7]. In comparison, another study from southeastern Europe considered three different groups as vulnerable, the “Roma,” Internally displaced populations (IDPs) or refugees, and majority residing in close proximity to Roma groups based on poverty rates among these groups[8].

Levesque et. al. conceptualized a framework (Figure 1. Attached below) exploring supply and demand side determinants of access. The dimensions of accessibility of services include;

• Approachability (transparency, outreach, information, screening)
• Acceptability (professional values, norms, culture, gender)
• Availability and Accommodation (Geographic location, accommodation, hours of opening, appointments mechanisms)
• Affordability (direct costs, indirect costs, opportunity costs), and
• Appropriateness (technical and interpersonal quality, adequacy, coordination and continuity).

These correspond with a person’s ability to interact with the dimensions and include ability to:

• Perceive (Health literacy, health beliefs, trust and expectations)
• Seek (personal and social values, culture, gender, autonomy)
• Reach (living environments, transport, mobility, social support)
• Pay (income, assets, social capital, health insurance), and
• Engage (empowerment, information, adherence, caregiver support).

These determinants serve as either facilitators or barrier to access to care based on individual[9]. The barriers that vulnerable individuals must overcome to seek health services tend to be higher than other groups and therefore deserve special attention.

Innovative solutions addressing components of this framework were examined to determine the special needs of marginalized population1. The majority of existing innovations are aimed to address supply side access issues and most catered to few determinants from the framework. Focus on multisectoral determinants and emphasis on demand side factors is needed to achieve health equity as these vulnerable populations often bear significant amount of disease burden and related social and economic disparities. However, social norms also play a role in accessing health care.

Stigma undermines social cohesion and causes social isolation of affected groups, and it may be further amplified in already vulnerable or marginalized groups. The impact of social stigma may cause individuals to hide illness, prevent them for seeking care and discourage adoption of healthy behaviors8. Stigma may be instigated due to misinformation, inadequate health literacy or lack of access to credible information from trusted sources. There have been several studies looking at the effects of stigma during disease outbreaks. 

A study in Ghana examining Ebola-related stigma and its determinants found that individuals endorsing Ebola-related misinformation also endorsed Ebola-related stigma and usually were perceived as having high risk of contracting Ebola[10]. Ebola studies in Sierra Leone found stigma adversely affected infected individuals and persisted long after an individual recovered from the illness. Additionally, certain groups such as widows and orphans were further marginalized as a result. Lack of knowledge and awareness led many to believe survivors could transmit the disease as well[11]. Health campaigns heightened the stigma around individuals affected with Ebola due to quarantine policies and lack of community involvement[12].

A similar situation is emerging with the onset of COVID-19 infodemic on social media, with increase in instances of xenophobia and anti-Asian racism[13]. Misinformation is rampant on social media regarding COVID-19, ranging from fake news including postulation of causes to unproven treatments, causing a widespread anxiety across society. While encrypted platforms, such as WhatsApp, facilitate easier access and facilitation of information, often times information is disseminated without ability to easily verify the content as the messages are only accessible by the sender and recipients[14]. The digital divide also impacts how misinformation spreads throughout communities[15].

Measures to detect and mitigate misinformation are necessary, even more so in vulnerable populations. Community engagement through involvement of trusted leaders or social influencers to disseminate information and debunk misinformation may prove to be an essential tool, as these resources can reduce concerns and unintended consequences resulting from the widespread dissemination of misinformation8. Building the evidence base to understand what misinformation-fighting approaches work for these communities should be a priority for researchers to support a strengthened COVID-19 pandemic response.

Figure 1. A conceptual framework of access to healthcare (Levesque et al., 2013).

[1] Shivayogi, P. (2013). Vulnerable population and methods for their safeguard. Perspectives in clinical research, 4(1), 53-57. doi:10.4103/2229-3485.106389

[2] The SAGE Encyclopedia of Qualitative Research Methods. (2008). doi:10.4135/9781412963909

[3] World Health Organization (2017). Health Equity. Retrieved from https://www.who.int/topics/health_equity/en/

[4] Centers for Disease Control and Prevention. (2017). Social determinants of health: Know what affects health. Retrieved from https://www.cdc.gov/socialdeterminants/index.htm

[5] World Health Organization (2020). A guide to preventing and addressing social stigma. Social Stigma associated with COVID-19. Retrieved from https://www.who.int/docs/default-source/coronaviruse/covid19-stigma-guide.pdf?sfvrsn=226180f4_2

[6] Richard, L., Furler, J., Densley, K., Haggerty, J., Russell, G., Levesque, J.-F., & Gunn, J. (2016). Equity of access to primary healthcare for vulnerable populations: the IMPACT international online survey of innovations. Int J Equity Health, 15(1), 64. doi:10.1186/s12939-016-0351-7

[7] Joszt, L. (2018). 5 Vulnerable Populations in Healthcare. Retrieved from https://www.ajmc.com/newsroom/5-vulnerable-populations-in-healthcare?p=1

[8] Milcher, S. J. C. E. S. (2006). Poverty and the determinants of welfare for Roma and other vulnerable groups in Southeastern Europe. 48(1), 20-35.

[9] Levesque, J. F., Harris, M. F., & Russell, G. (2013). Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health, 12, 18. doi:10.1186/1475-9276-12-18

[10] Tenkorang, E. Y. J. S. S., & Medicine. (2017). Ebola-related stigma in Ghana: Individual and community level determinants. 182, 142-149.

[11] Nuriddin, A., Jalloh, M. F., Meyer, E., Bunnell, R., Bio, F. A., Jalloh, M. B., . . . Morgan, O. (2018). Trust, fear, stigma and disruptions: community perceptions and experiences during periods of low but ongoing transmission of Ebola virus disease in Sierra Leone, 2015. BMJ Global Health, 3(2), e000410. doi:10.1136/bmjgh-2017-000410

[12] Denis-Ramirez, E., S?rensen, K. H., Skovdal, M. J. C., & Review, Y. S. (2017). In the midst of a ‘perfect storm’: Unpacking the causes and consequences of Ebola-related stigma for children orphaned by Ebola in Sierra Leone. 73, 445-453.

[13] Haynes, S. (2020). As coronavirus spreads, so does xenophobia and anti-Asian racism. Time.com.

[14] Romm, T. (2020, March 2, 2020). Fake cures and other coronavirus conspiracy theories are flooding WhatsApp, leaving governments and users with a ‘sense of panic’. The Washington Post. Retrieved from https://www.washingtonpost.com/technology/2020/03/02/whatsapp-coronavirus-misinformation/

[15] Bakibinga-Gaswaga, E., Bakibinga, S., Bakibinga, D. B. M., & Bakibinga, P. (2020). Digital technologies in the COVID-19 responses in sub-Saharan Africa: policies, problems and promises. The Pan African Medical Journal, 35(38).