Candice Welhausen

Candice Welhausen, English.

Candice Welhausen, English.

E-mail: candicew@udel.edu
Twitter: candicewe
Web: http://candicewelhausen.com/

Description of Work:

Her research focuses on data visualization in the field of public health and epidemiology. She is currently working on a book project [working title “The Picture of (Public) Health: The Past, Present, and Future of Data Visualizations of Epidemic Disease,”] which investigates quantitative representations of epidemic disease in Western cultures and the ways in which these visuals have constructed knowledge about health and disease historically as well as in modern practice. Her symposium manuscript entitled, “Visualizing a Non-Pandemic: Considerations for Communicating Public Health Risks in Intercultural Contexts,” analyzes four data visualizations of the Ebola outbreak that began in West Africa in 2014 created by the New York Times through several dimensions of intercultural communication.

Symposium Submission:

Visualizing a Non-Pandemic: Considerations for Communicating Public Health Risks in Intercultural Contexts

Risk assessment is central to modern-day public health practice (Samet et al., 1998) with its focus on health promotion and disease prevention in populations. Communicating public health risks involves an “information exchange… about environmental, industrial, or agricultural, processes, policies, or products among individuals, groups, and institutions” (Glik, 2007) that usually involves experts adapting information about risk both for other experts as well as non-expert audiences.

Data visualizations often play a key role in risk communication. For instance, Lipkus and Hollands (1999) argue that graphical forms can increase the effectiveness in communicating certain types of risks, while Ancker et al. (2006) found that some graphical forms are better suited for achieving particular communication objectives. However, experts interpret and perceive risks differently from non-experts (see Slovic, 1986; Fischoff, 1995). Non-experts, for example, perceive public health risks in relationship to their perceived level of control over the risk, and will, in fact, take on more risk if they believe they can control their exposure (Foege, 1991). Further, risk is often understood primarily in terms of numeric values (Short, 1984)—that is, as a measurable and quantifiable construct. This perspective is effective from an epidemiological standpoint because it facilitates managing disease and health at the population-level. But this focus can also downplay the social influences that frame how risk is perceived by public audiences (Grabil & Simmons, 1998). The differences in risk perception between expert and non-expert audiences is further complicated when risk communication is created within intercultural contexts.

In this article, I argue that data visualizations of epidemic disease outbreaks communicate public health risks both to expert and non-expert readers by constructing comparative, temporal, and spatial relationships among quantitative information. The design of these representations tends to privilege expert readers as well as Western cultural ideologies while simultaneously often inadvertently exaggerating perceived risk among non-experts viewers. Further statistical graphics often do not visually account for the cultural considerations that influence how non-experts perceive risk, which would serve to downplay this perception. To make these points, I draw on several intercultural visual communication dimensions discussed in a recent review by Brumberger (2014): high/low context and level of textual information, use of color, and individualist/collectivism. More specifically, I argue that data visualizations are created by experts in a high context cultural environment, and thus usually incorporate scant textual explanations that might clarify the nature of the risk for non-experts. A higher perception of risk is also communicated to non-experts through color schemes that create strong contrast through warm and cool colors. Finally, statistical graphics are inherently collectivistic because they are the visual representations of aggregated data. Yet non-experts from individualistic cultures can interpret any data visualization as constituting some risk even if the purpose of the graphic is to show minimal risk.

I illustrate these ideas by analyzing statistical graphics documenting the Ebola outbreak in West Africa that began in 2014. As the outbreak spread to several countries and reports of infected healthcare workers became increasingly common, data visualizations disseminated through mainstream Western news media visually transformed the spread of the disease into a global pandemic, resulting in widespread panic. In reality the disease was confined to the African continent, and a number of factors—poor healthcare infrastructure and inadequate access to protective gear, for instance—minimized the risk of a full-blown epidemic spreading to developed countries. Yet because non-expert readers perceive risk differently, they perceived this risk inaccurately and with a higher probability. Further rather than clarifying the nature of the risk, data visualizations documenting the spread of the epidemic heightened non-expert audiences’ perception of the risk, contributing to the overall misunderstanding.

In the twenty-first century public health efforts, particularly those to control the spread of epidemic diseases, are frequently enacted on a global level. Thus the visualization strategies used to communicate these risks to both expert and non-expert readers have wide-reaching implications in terms of how current and future risks of epidemic diseases are perceived and subsequently managed.

References
Ancker, J.S., Senathiraja, Y., Kukafka, R., & Starren, J.B. (2006). “Design Features of Graphics in Health Risk Communication: A Systematic Review.” Journal of the Medical Informatics Association, 13(6): 608-618. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1656964/
Brumberger, E. (2014). “Toward a Framework for Intercultural Visual Communication.” Connections: International Professional Communication Journal, 2(1): 91-116.
Fischoff, B. (1995). “Risk Perception and Communication Unplugged: Twenty Years of Process.” Risk Analysis, 15: 137-145.
Foege, W. H. (1991).“Plagues: Perceptions of Risk and Social Responses.” In Time of Plague: The History and Social Consequences of Lethal Epidemic Disease. Ed. Arien Mack. New York, NY: New York University Press. 9–20.
Glik, R. (2007). “Risk Communication for Public Health Emergencies.” The Annual Review of Public Health. 28: 33-54.
Grabill, J. T., & Simmons, W. M. (1998). “Toward a Critical Rhetoric of Risk Communication: Producing Citizens and the Role of Technical Communicators.” Technical Communication Quarterly 7,4: 415–41.
Lipkus, I.M., & Hollands, J.G. (1999). “The Visual Communication of Risk.” Journal of the National Cancer Institutes Monographs, 25: 149-163.
Samet, J. M., Schnatter, R., & Gibb, H. (1998). “Invited Commentary: Epidemiology and Risk Assessment.” American Journal of Epidemiology 148.10: 929–36.
Short, James F. (1984). “The Social Fabric of Risk: Toward the Social Transformation of Risk Analysis.” American Sociological Review 49,6: 711–25.
Slovic, P. (1986). “Informing and Educating the Public about Risk.” Risk Analysis, 6(4): 403-415.