Media Framing of the Ebola Crisis

Theresa Vellek

Undergraduate Honors Thesis, Sanford School of Public Policy

Duke University

Durham, North Carolina

2016

Advisors: Prof. Misha Angrist and Prof. Kenneth Rogerson

Acknowledgements

I would like to offer a sincere thanks to the following people, without whom this

thesis would not have been possible:

Prof. Misha Angrist, my thesis advisor, for his encouragement, guidance, and

feedback was instrumental to the final product.

Prof. Kenneth Rogerson, my honors thesis seminar director, for his constant

support and for challenging me to think and write to the best of my ability.

Prof. Eric Green, my global health professor, for his comments and assistance in

conducting statistical analysis of my results.

Katherine Chernova, Erin Locey, and Surya Veerabagu, my friends, for being

my sounding board for ideas and always brightening my day.

Ann and Mark Vellek, my parents, for being a never-ending source of support

and encouragement.

Table of Contents

ABSTRACT ...................................................................................... 1

INTRODUCTION ........................................................................... 2

THEORETICAL FRAMEWORK .................................................. 3

Implications of Media Framing ....................................................................................... 3 Framing as Perception: True versus Manipulated ........................................................ 5 Risk Reporting: Media Coverage of International Crises .............................................. 7 Media Framing of International Health Crises ............................................................. 8 Media Frames Analysis of the Mid-1990s Ebola Outbreaks ....................................... 11

ANCILLARY RESEARCH QUESTIONS .................................. 12

METHODOLOGY ......................................................................... 13

Cases: 2000-2001 Ebola Outbreak and 2014-2015 Ebola Outbreak ........................... 13 Content Analysis & Coding ........................................................................................... 15 Mutation-Contagion Frame ........................................................................................... 17 “Othering” and Containment Frame ............................................................................ 18 Globalization Frame ...................................................................................................... 18 Human Interest Frame .................................................................................................. 19 Economic Consequences Frame .................................................................................... 19 Attribution of Responsibility Frame ............................................................................. 20 Phrase-to-Frame Coding and Analysis ......................................................................... 20

RESULTS ....................................................................................... 22

Sample ............................................................................................................................ 22 Mutation-Contagion Frame ........................................................................................... 24 “Othering” and Containment Frame ............................................................................ 29 Globalization Frame ...................................................................................................... 31 Human Interest Frame .................................................................................................. 33 Economic Consequences Frame .................................................................................... 35 Attribution of Responsibility Frame ............................................................................. 37

CONCLUSION .............................................................................. 39

Application of Frames from the Literature to Recent Ebola Coverage ....................... 39 Differences in Frames from 2000 to 2014 ..................................................................... 43 Differences in Frames Across Media Outlets ............................................................... 46 Consequences of Framing on Public Opinion of Ebola ................................................ 48 Limitations ..................................................................................................................... 49 Future Research ............................................................................................................. 50

REFERENCES .............................................................................. 51

APPENDICES ............................................................................... 57

Appendix 1. Sampling of the Media Coverage ............................................................ 57 Appendix 2. Number of Articles in which Frames Appeared ...................................... 58 Appendix 3. Total Number of Frame Occurrences ....................................................... 59 Appendix 4. Phrase-to-Frame Coding Inputs ............................................................... 60

Abstract

This study examines the role of international media framing in coverage of Ebola. A

quantitative content analysis compared framing techniques in Ebola coverage across BBC

Monitoring, The New York Times, The Daily Telegraph (UK), and The Straits Times (Singapore)

in the 2000-2001 and 2014-2015 outbreaks. Results show that mutation contagion was by far the

most frequently appearing frame in the media. Recent media coverage also mimicked the

tendency to represent Ebola as distinctively “African,” as found in research on the 1990s Ebola

outbreak. Additionally, the portrayal of Ebola as a globalized threat was especially important in

coverage of the 2014 outbreak. Overall, media coverage of the Ebola crisis appeared highly

politicized and event-based. Particularly because the media serve as the primary source of

information about infectious disease epidemics for much of the public, their framing has

implications for how the world views Ebola.

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Introduction “The level of outbreak is beyond anything we’ve seen—or even imagined.”

— Dr. Tom Frieden, the director of the Centers for Disease Control and Prevention

September 2, 2014

“This is the biggest health problem facing our world in a generation.”

— British Prime Minister David Cameron October 17, 2014

Ebola has become a global issue. The newest outbreak far exceeds any previous one. The

biggest historic outbreak, in 1976, killed 280 people (CDC, 2015). Since 2014, Ebola has

infected almost 30,000 people, killed more than 11,000, and it continues to be a threat because of

sexual transmission from male survivors (WHO, 2015; McNeil, 2015). This is not the first global

epidemic this century. The world endured SARS, the avian bird flu, and Creutzfeldt-Jakob

disease. Sixteen percent of all deaths are from infectious diseases (Center for Strategic and

International Studies, 2015). But absent any effective treatment or vaccine, public health officials

are still unprepared to deal with contagions like Ebola.

Infectious diseases pose a security threat that the public and the media have previously

overlooked. The media serve as a reflection of the public’s concern and contribute to the general

population’s understanding of health epidemics (Shih, Wijaya, & Brossard, 2008). The social

and political contexts of infectious disease epidemics are captured in the frames mass media

employ to tell stories about emerging diseases. Framing theory suggests that how the media

present an issue affects how audiences feel about that issue (Ungar, 1998; Shih, Wijaya, &

Brossard, 2008). Thus analyzing news coverage of disease crises offers a window for

understanding public opinion and knowledge.

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This paper endeavored to understand the role of media framing in coverage of two

international health crises involving a single infectious pathogen. A content and frame analysis

of news articles compared coverage of the 2014 Ebola outbreak with the more extensively

researched 2000-2001 outbreak (425 infections; 224 deaths) (CDC, 2015). This analysis

identified trends in media coverage of the Ebola crisis by applying frames recognized in past

studies of infectious disease outbreaks.

Theoretical Framework

Implications of Media Framing

Individuals use media coverage as a cognitive shortcut, or heuristic, to make sense of

complex risks, including infectious disease pandemics (Ungar, 1998). The public “co-constructs”

what they see, read, and hear from the media with information from personal experience to

understand an issue (Dearing & Rogers, 1996). Thus studying how the media interpret specific

issues is a prerequisite to understanding the dynamics surrounding public perception (Shih,

Wijaya, & Brossard, 2008; Ungar, 1998). Goffman (1986) first introduced the concept of

framing as an interpretation or schema that aims to structure the meaning of a message. Entman

and others suggest that analyses of frames in the media reveal how reading a story influences

readers’ attitudes about an issue (Entman, 1993).

Two types of media framing exist: journalistic and reader (Burton, 2010; Scheufele &

Tewksbury, 2007). Journalistic framing describes familiar features and conventions in text that

make it easy for the reader to take away the intended message of the producer (in this case the

media outlet). Reader framing leaves the meaning and message up to the audience’s

interpretation, including how a reader formulates their own meaning based on their own personal

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experiences and values (Burton 2010; Scheufele & Tewksbury, 2007; Philo, Miller, & Happer,

2014).

Instead of studying the general population’s attitudes toward international health crises

more broadly, which would be required to study reader framing, this study focused on the role of

media outlets and journalistic framing as one influence on people’s understanding and policy

preferences. In journalistic framing, the media draw attention to certain features of an issue while

minimizing attention to others (Shih, Wijaya, & Brossard, 2008). A frame highlights a particular

interpretive package, which is a cluster of metaphors, exemplars, stories, visual images, moral

appeals, and symbolic devices (Ungar, 1998). Framing theory suggests that the way in which the

media talk about a certain issue affects how audiences feel about that issue (Ungar, 1998; Shih,

Wijaya, & Brossard, 2008).

By studying audience effects of the media, some scholars have developed models to

predict the amount of impact coverage will have on the public’s viewpoint. Kim (2014) presents

the concept of need for orientation, which “refers to the tendency of individuals to seek

information about public issues from the media,” as a way to explain how the media agenda

influences the public. He argues that individuals will be more susceptible to media messages and

agenda-setting if the information is relevant to them and if they have a high degree of uncertainty

(Kim, 2014). Berry, Wharf-Higgins, & Naylor (2007) take the ideas underlying this theory one

step further, as they reason that when a person lacks direct experience with a particular risk, their

knowledge originates from news media. Furthermore, they say dramatization, volume, and

symbolic connotations in the media dictate personal responses (Berry, Wharf-Higgins, & Naylor,

2007). Thus the need for orientation theory sets the expectation that media representations of

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Ebola will result in a greater audience effect, as media frames influence audience knowledge and

attitudes toward the public health epidemic (Kim, 2014; Berry, Wharf-Higgins, & Naylor, 2007).

Framing as Perception: True versus Manipulated

Framing in the media is a social construction of news (Johnson-Cartee, 2004). Thus it

represents the media’s perception of an event, which is not necessarily an accurate reflection of

reality. Whether that perception is truthful or manipulated requires a discussion separate from

merely analyzing the media’s frames. The issue attention cycle—the ups and downs of attention

an issue receives either from the public or from mass media—can dictate the public importance

of an issue and explain the volume of associated media coverage (Shih, Wijaya, & Brossard,

2008). The sources media outlets rely upon can also manipulate, or spin, the messages in

coverage (Johnson-Cartee, 2004). Therefore, it is important to recognize the types of sources in

news reports in order to understand the effects of the media on how a story is received.

Depending on the reliability of the sources, coverage may depart from reality to a greater or

lesser extent.

Popular media and novels have fueled myths and hysteria surrounding Ebola. Weldon

(2001) illustrates how non-fiction accounts of Ebola have created an “urban legend” of the

“predatorial virus stalking the human race.” This type of horrific depiction coupled with

misinformation have driven dramatization, which then downplays the extent of human

involvement in the disease (Weldon, 2001).

Several scholars have looked to Richard Preston’s book The Hot Zone as the

quintessential example of how a single work can dramatically affect the public’s perception.

Haynes (2002) contends that Preston’s illustration of Ebola as an emerging virus in the

developing world follows a narrative common in colonist perceptions of Africa as the “heart of

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darkness.” This creates a social construction of Africa as “other,” and in turn avoids casting

blame on the Western world (Haynes, 2002). Preston’s dramatic framing of the 1990s Ebola

outbreak exaggerated symptoms, created a myth of Ebola being airborne, and downplayed the

empirical absence of extreme contagion (Smith, 2014). He used language like “liquefy,”

“bleeding out,” and “dissolving” to describe Ebola, although workers from Médicins Sans

Frontières said patients mostly looked sick and weak, while blood excretion was minimal and

rare. Preston himself has conceded that The Hot Zone could have been more “clear and accurate”

and contains at least one scene that “almost certainly didn’t happen” (Alter, 2014).

Other accounts were more measured. Laurie Garrett’s The Coming Plague offered a

sharp contrast to Preston’s sensationalism. Her thoroughness was a likely product of her

background in public health and epidemiology; she acquired an “obsession with details” as she

researched and wrote the book over a 10-year period (Hall, 1994). Preston’s and Garrett’s

radically different framing of Ebola show how personal background and the sources journalists

consult can have a major impact on the end result.

A study of the construction of news reports on health topics revealed that public health

authorities (e.g., the World Health Organization, the Centers for Disease Control and Prevention,

and doctors from treating hospitals) are commonly the most used and quoted sources (Berry,

Wharf-Higgins, and Naylor, 2007). Similarly, a content analysis of European media coverage of

the opening days of the H1N1 influenza pandemic revealed that 74 percent of articles used

national and international public health authorities as the leading sources of information (Duncan,

2009). An analysis of Creutzfeldt-Jakob disease, West Nile virus, and avian flu also found the

media commonly cited official sources in their stories (Shih, Wijaya, & Brossard, 2008). These

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studies set the expectation that official sources in media coverage of the 2000-2001 and 2014

Ebola outbreaks will play a significant role in framing stories.

Risk Reporting: Media Coverage of International Crises

To fully understand international health crises, including Ebola, it is necessary to evaluate

their impact in terms of their risk to global health. Sociological models of risk, which view risk

as socially, culturally, societally, and/or data contingent, create a framework to analyze how the

media portray the risk associated with disease. Thus studying sociological models of risk is

helpful. Previous research on health media coverage revealed that health topics were most often

discussed in terms of risk (Berry, Wharf-Higgins, & Naylor, 2007).

There are several models of risk in the social sciences. The realist or techno-scientific

view sees risk as a quantity to be calculated from hard data, which reflect unbiased, objective

reality (Anderson, 2006; Washer, 2004). This perspective would see media coverage of health

crises from a factual and statistical perspective, such as the number of individuals infected by a

disease or the dollar amount a disease cost a country’s health system. Another model, the social

constructivist or anthropologist view, perceives risk as subjectively mediated through social and

cultural processes (Anderson, 2006; Washer, 2004). This emphasis on social contexts of risk

would explain why, for example, HIV/AIDS was not frequently reported on initially because of

its taboo social characteristics. A third model, the risk society, deems post-modern society as

obsessed with risk due to the unique challenges that globalization poses (Beck, 1992). Following

this logic, the media magnify risks to create alarm, and with international health crises they

might focus on, for example, the added risk of spreading disease through air travel since it

creates a problem the previously less globalized world did not face. Critics of the risk society

model argue that people defend themselves against increased anxiety by creating representations

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of risk (Joffe, 1999). For example, in the media coverage of the 1990s Ebola outbreak, the media

emphasized the ways in which Western biomedicine could help rid foreign countries of this

disease. These representations in the media, according to critics, transform risk into a rational,

calculable, and solvable phenomenon (Joffe, 1999).

Social and political contexts dictate the prominence of particular types of risks in the

public and media’s consciousness (Bennett, 2010). Consequently, the social and political

contexts brought the Ebola outbreaks to the forefront of media coverage. Fright factors—such as

risks being involuntary, inequitably distributed, inescapable, dreadful, and poorly understood by

science—increase the likelihood that public attention will focus on a particular risk (Bennett,

2010). The Social Amplification of Risk Framework (SARF) seeks to explain why certain events

attract more socio-political attention, although they do not always reflect relative objective risk

(Anderson, 2006). It asserts that when a person lacks direct experience with a particular risk,

their knowledge originates from news media (Berry, Wharf-Higgins, & Naylor, 2007).

Dramatization, volume, and symbolic connotations in the media dictate personal responses

(Berry, Wharf-Higgins, & Naylor, 2007). Thus SARF sets the expectation that media

representations of Ebola will result in a greater audience effect, as media frames influence

audience knowledge and attitudes toward the public health epidemic.

Media Framing of International Health Crises

Following the pattern of past research, this paper will concentrate on infectious disease

epidemics as a form of an international health crisis. The issue attention cycle explains why the

media sometimes drive public consciousness toward disease epidemics, while seemingly

ignoring them at other times (Shih, Wijaya, & Brossard, 2008). Studying public health epidemics,

such as CJD, West Nile virus, and avian flu, researchers discovered that coverage of epidemic

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diseases was highly event-based and did not always mirror the total number of people infected.

Instead, media coverage varied along lines of government actions and major surges in numbers

of infected cases (Shih, Wijaya, & Brossard, 2008). Disease has become politicized because

costs of healthcare and resource allocation to public health and medical research are highly

contingent on governmental action (Hong, 2014). Using this logic, one would anticipate seeing

media coverage of Ebola highly contingent on political events and politicized outbreaks.

Social representations theory (SRT) argues that when faced with a newly encountered

illness, people collectively create a shared narrative based on “common sense” knowledge to

cope with the novelty and impose order (Washer, 2004; Joffe & Haarhoff, 2002). These social

representations construct the world through past events, images, terms, descriptions, examples,

models, and metaphors to anchor a new phenomenon and make it seem more familiar and

therefore less threatening (Moscovici, 2001). The mass media both cultivate and reflect these

representations (Washer, 2004).

With the threat of a new infectious disease, media reporting reveals broader anxieties

about the inability of technology and biomedicine to contain epidemics and about the ecological

and economic threats of globalization (Washer, 2004). These recurrent worries resurface with

each subsequent epidemic, allowing researchers to draw broader conclusions about media

coverage of international health crises.

Various studies of infectious disease epidemics demonstrated a shift from alarming to

reassuring coverage (Washer, 2004; Ungar, 1998; Joffe & Haarhoff, 2002). In an analysis of

SARS in British newspapers, Washer showed that coverage began with a mutation-contagion

frame by representing SARS as a threatening killer, but then contained the threat (a containment

frame) by illustrating how “different” or “other” the Chinese were to “us” as British (2004).

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Early coverage of HIV/AIDS, however, skipped the mutation-contagion frame and instead

focused on the containment frame because of the stigma and “otherness” associated with the

homosexual population (Washer, 2004). Media editors initially avoided all news about AIDS

because they failed to see how a story about homosexuals and drug users would interest their

reader population (Washer, 2004). This dichotomy between “us” versus “them” created a

separation from the threat of an emerging infectious disease (Allan, 2002).

However, the containment representation of epidemics—and the coping mechanism the

media use to alleviate fears by focusing on how the disease affects “others” rather than the

immediate audience—does not translate to all infectious diseases. For example, British news

coverage of Creutzfeldt-Jakob disease (CJD) could not blame “others” for the emergence and

spread of the disease, since the English were at fault (Washer, 2006). The frames used in media

coverage of CJD instead lowered public anxiety about the disease by using the process of

anchoring in SRT: Media representations of CJD integrated the understanding of this new

disease by configuring it, i.e., anchoring it, in terms of past epidemics (like the flu and

salmonella), which made it more familiar and less frightening (Washer, 2006).

Media coverage of international health crises uses metaphors to describe emerging

infectious diseases to an uneducated public. Reports depict diseases as killers, plagues, or hostile

combatants in war (Wallis & Nerlich, 2005). The mass media have framed cancer, drug-resistant

tuberculosis, and HIV/AIDS in terms of militerized wars, mimicking the language of politicians,

such as President Richard Nixon’s “war on cancer,” which launched in the early 1970s. Yet

militarizing health crises can promote shame and guilt among sufferers, make it easier to

sacrifice rights, and encourage massive resource expenditure (Wallis & Nerlich, 2005). Initial

HIV/AIDS media coverage compared the disease to a plague (Wallis & Nerlich, 2005; Sontag,

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1989). Rather than the historically prevalent military or plague metaphors, media coverage of

SARS in the early 2000s treated SARS as a “killer” (Wallis & Nerlich, 2005). Stories

incorporated language typically associated with a killer, using words such as “rampant,” ravages,”

“hunting,” and “victim.” Attention to metaphors in mass media representations of the Ebola

outbreaks will help illuminate the framing of the disease epidemic.

Content analyses of media coverage of the SARS epidemic in the early 2000s provide a

good framework for an analysis that can be applied to the Ebola outbreaks. The SARS studies

compared Chinese versus U.S. media coverage on the basis of several frames: responsibility,

conflict, severity, leadership, human interest, and economic consequences (Beaudoin, 2007;

Luther & Zhou, 2005). The present analysis of media reports about the 2000-2001 and 2014

Ebola outbreaks mirrored this content analysis and analyzed which of the frames were most

prevalent. Drawing from literature about SARS and Ebola media coverage, a model of

previously formulated frames analyzed the media’s portrayal of recent Ebola crises.

Media Frames Analysis of the Mid-1990s Ebola Outbreaks

Ungar analyzed media frames of the 1990s Ebola epidemic and found that the initial

mutation-contagion package (a frightful account of the emerging disease) transformed into a

containment package (a classification of victims as “others” to allay fear) (1998). He argued that

the earliest coverage contained the most terrifying aspects of the mutation-contagion package:

the Ebola virus was seen as being on a rampage, as cleverer than biomedicine, and as knowing

no boundaries. But after merely a few days, he noted that coverage began to contain the threats

of Ebola to Africa, emphasizing the “other” and “foreign” aspects, presumably to alleviate

anxiety. Drawing upon the sociology of moral panic, Ungar termed this switch from alarming to

reassuring coverage “the moderation effect.” This leads one to wonder whether this transition

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from mutation-contagion to containment frames occurred in the media coverage of the 2000-

2001 and 2014 Ebola outbreaks.

Another content analysis of the mid-1990s Ebola outbreak examined how British

broadsheets, tabloids, and their readers interpreted Ebola as a far-flung illness (Joffe & Haarhoff,

2002). Joffe and Haarhoff’s research revealed that the mass media represented Ebola as African,

and as posing little threat to Britain (Joffe & Haarhoff, 2002). During this outbreak, tabloids used

a more sensationalized vision of Ebola, whereas broadsheets concentrated on the structural

features that led to Ebola’s escalation. This division in the British media illustrates how different

types of press may differ in their coverage of one event. The press made Ebola appear real by

focusing on its potential to globalize and how it could be contained. But readers drew an analogy

between Ebola and science fiction to share their view that Ebola, which plagued a distant land,

seemed unrealistically horrific (Joffe & Haarhoff, 2002). Although this study did not evaluate

readers’ interpretations of the 2000-2001 and 2014 Ebola outbreaks, it did test whether media

outlets characterized Ebola as African and not a threat to other parts of the world.

Ancillary Research Questions

The newest outbreak of Ebola has killed over 40 times the number of people than any

previous outbreak (WHO, 2015; CDC, 2015). Because of the uniqueness of the 2014-2015

epidemic and the fact that this was the first study to analyze its media coverage, it was difficult

to predict what frames the media used. Therefore, an inductive study to answer key research

questions was appropriate, rather than a deductive study to test previously formulated

hypotheses. Overall, the content analysis worked to answer the question of the role of media

framing in coverage of the recent Ebola outbreaks.

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This analysis of media reports from the British Broadcasting Corporation World Service

Group’s BBC Monitoring, The New York Times, The Daily Telegraph (UK), and The Straits

Times (Singapore) for a year-long period following the initial confirmation of Ebola in 2000

(October 15) and the 2014 World Health Organization announcement of the outbreak (March 25)

also addressed several ancillary questions. These were derived from past research on

international health crises in the media:

• Do the frames from existing literature of international health crises apply to Ebola

coverage in 2000-2001 and 2014-2015?

• How does framing differ between the 2000-2001 outbreak and the 2014-2015 outbreak?

• How does framing differ among media outlets (BBC Monitoring, The New York Times,

The Daily Telegraph, and The Straits Times)?

Methodology

The method to assess the role of media framing in coverage of Ebola was a quantitative

content analysis of articles published by BBC Monitoring, The New York Times, The Daily

Telegraph (UK), and The Straits Times (Singapore). The two outbreaks analyzed were during

2000-2001 and 2014-2015, the two largest Ebola epidemics, to allow for a comparison in

coverage. The sample of media reports included one year of coverage from the LexisNexis

database, starting from the date the WHO confirmed the first cases of Ebola.

Cases: 2000-2001 Ebola Outbreak and 2014 Ebola Outbreak

Ebola is spread through direct contact via broken skin or unprotected mucus

membranes—such as those found in the eyes, nose, or mouth—with blood or bodily fluids,

needles and syringes contaminated with the virus, and infected fruit bats or primates (CDC,

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2015). For every individual infected with Ebola, 1.5 to 2.5 other people will develop the disease

(Chowell & Nishiura, 2014). A person infected with the Ebola virus is not contagious until

symptoms appear. Symptoms appear on average 8 to 10 days after exposure, but may take up to

21 days to materialize. Symptoms of Ebola include fever, severe headache, fatigue, muscle pain,

weakness, diarrhea, vomiting, abdominal pain, and unexplained hemorrhage (CDC, 2015). There

is no cure or vaccine for Ebola. Ebola is more deadly than measles, plague, and smallpox (CDC

“Measles”, 2015; WHO “Plague”, 2014; “WHO Fact Sheet on Smallpox”, 2001). On average, 50

percent of people who contracted Ebola have died from it (WHO, 2015).

The 2014 Ebola outbreak was the most recent example of an emerging infectious disease

generating an international health crisis. The 2000-2001 outbreak acted as a model for

comparison because of previous research analyzing media frames in stories covering this event

(Joffe & Haaarhoff, 2002). The 2014 outbreak, the largest in history, affected 28,637 individuals

and caused 11,314 deaths as of November 22, 2015 (CDC, 2015). Ebola, previously known as

Ebola hemorrhagic fever, is a virus named after the Ebola River in what is now the Democratic

Republic of the Congo, where the first known outbreak of this disease occurred in 1976 (CDC,

2015). Aggregated, these early outbreaks in the DRC and Sudan killed more than 400 people.

Since then, Ebola outbreaks have sporadically appeared in Africa. The DRC saw the next big

outbreak of Ebola in 1995, when it killed 250 people. In 2000-2001, there was another upsurge

in Ebola deaths, killing 224 people in Uganda. There was also a flareup in 2007-2008 in DRC

and Uganda, which killed 187 people (CDC, 2015).

The impact and timeliness of the 2014 and 2000-2001 Ebola outbreaks made them

essential to answering the larger question of the role of the media in international health crises.

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Table 1 below illustrated the justification for each case study selection and the sampling timeline

for media articles.

Table 1. Case Studies

Case Study Time Period and Prevalence

2000-2001 Ebola outbreak

15 October 2000

No. of infected individuals: 425

Sampling Duration: 10/15/00 – 02/15/01

2014 Ebola outbreak

25 March 2014

No. of infected individuals: 28,637

Sampling Duration: 03/25/14 – 07/25/14

* Sources: CDC, 2015; CDC, 2001

Content Analysis & Coding

A content analysis assessed media frames from stories about the 2000-2001 and 2014-

2015 Ebola outbreaks. This identified framing trends in five media sources from three countries

– the BBC Monitoring, The New York Times, The Daily Telegraph (UK), and The Straits Times

(Singapore) – over a year-long period following the initial confirmation of Ebola in 2000

(October 15) and the 2014 World Health Organization announcement of the outbreak (March 25)

(CDC, 2001). The LexisNexis database helped create a sample of 4,251 articles from worldwide

media coverage of Ebola (full sample information in Appendix 1). BBC Monitoring, The New

York Times, The Daily Telegraph, and The Straits Times were chosen because of their large

readership and wide geographic distribution. Table 2 below outlines the reasoning behind the

selection of each media outlet.

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Table 2. Media outlet selection

Media outlet Justification for selection

BBC Monitoring News, information, and comment gathered from mass media

worldwide

Reach: 3,000 radio, television, press, and internet news agency

sources in over 150 countries

The New York Times Won more Pulitzer prizes than any other news organization and is

No. 1 in overall reach of U.S. opinion leaders

Audience: 1.87 million daily circulation

The Daily Telegraph,

United Kingdom

Widest circulated broadsheet newspaper in the United Kingdom

and won Newspaper of the Year in 2010 at the British Press

Awards

Audience: 489,739 daily paper circulation

The Straits Times,

Singapore

English-language broadsheet newspaper and is the widest

circulated daily publication in Singapore

Audience: 322,056 daily paper circulation, 113,477 daily digital

circulation

* Sources: BBC Monitoring, n.d.; The New York Times, 2014; Haughney, 2013; Audit Bureau of Circulations (UK), 2015; The Telegraph, 2010; Turville, 2014; Audit Bureau of

Circulations (Singapore), 2015

NVivo software, a qualitative research tool, aided in coding and analyzing media frames.

It helped count the number of references to each frame in all of the articles as well as the number

of articles that employed each frame. Using this platform, I studied changes in frame usage over

time, compared the 2000-2001 outbreak to the 2014-2015 outbreak, and compared coverage

among media outlets.

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Content analysis of news articles from the 2000-2001 and 2014 outbreaks identified

recurring themes and frames as well as assessed their prevalence and differences between

outbreaks and media outlets. I used deductive content analysis: I analyzed articles and coded

them for pre-designated themes found in past literature of media coverage of international health

crises. Even articles with a brief mention of Ebola in business, world briefs, and book review

sections were included for analysis. This allowed for a comprehensive viewing of readers’ total

exposure to the topic of Ebola and avoided the possibility of cherry-picking articles with the

most vivid descriptions. Each article was coded based on six frames: mutation-contagion,

“othering” / containment, globalization human interest, economics, and attribution of

responsibility. The subsequent sections discuss these frames in detail and provide examples from

previous literature.

Mutation-Contagion Frame

The mutation-contagion frame, used by Ungar in his study of 1995 Ebola media

coverage, coded language and information used to render frightful accounts of Ebola (Ungar,

1998). Articles depicting the Ebola virus as being on a rampage, as cleverer than biomedicine,

and as knowing no boundaries were coded as mutation-contagion. The mutation-contagion frame

was coded using three metaphorical sub-frames: war, plague, and killer, which were previously

employed in the media content analysis of SARS (Wallis & Nerlich, 2005). An example of a

militarized mutation-contagion frame came from a New York Times article from July 31, 2014:

“First recognized in March in Guinea, the Ebola outbreak has surged through porous borders to

invade neighboring countries, quickly outstripping fragile health systems and forcing health

officials to fight the battle on many fronts” (Nossiter & Grady, 2014). The imagery employed in

this excerpt painted Ebola as a growing, unmanageable war-like threat. An example of the plague

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metaphor came from the Daily Mirror on SARS: there was no certain “freedom from this latest

modern plague” (Wallis & Nerlich, 2005). The metaphor of Ebola as a killer was similar to

media coverage of SARS, which labeled SARS as the “killer virus” or “deadly bug,” described it

as “rampant,” and used “victim” to refer to those infected.

“Othering” and Containment Frame

The “othering” and containment frame, used in previous research on the 1995 Ebola

outbreak, 2000 Ebola outbreak, SARS outbreak, and HIV/AIDS, classified victims as “others” or

foreign to allay fear (Ungar, 1998; Joffe & Haarhoff, 2002; Washer, 2004; Allan, 2002). This

frame contained the virus in the African continent by describing it as a phenomenon that only

affects others. The media emphasized how Westerners practicing isolation, quarantine, and

surveillance could control Ebola, while Africans were depicted as passive and voiceless (Washer,

2004). Using this frame, the media created a dichotomy between “us” and “them” (Allan, 2002).

Globalization frame

The globalization frame, used in media coverage research of past Ebola outbreaks,

concentrated on the spreading and globalized effects of Ebola (Joffe & Haarhoff, 2002). Press in

the past referred to globalization relating to Ebola in terms of the spread of the virus from Africa

to the outside world (Joffe & Haarhoff, 2002). This frame looked at Ebola as a worldwide

problem, rather than a localized one, and emphasized how the disease could have wide-reaching

consequences in the current age of connectedness. An example of globalization in The Daily

Telegraph from May 17, 1995 was: “An Ebola outbreak in a Stone Age family would die out

with the demise of their isolated settlement. But with tourism, air travel and trucking, it is now

possible for a putative doomsday mutant of Ebola to ripple rapidly outwards from the dead”

19

(Joffe & Haarhoff, 2002). This excerpt depicted Ebola as a global threat due to increased long-

distance travel in the modern world.

Human Interest Frame

The human interest frame, used in previously published research on SARS media

coverage, incorporated emotional or personal stories to humanize or dramatize a story

(Beaudoin, 2007; Luther & Zhou, 2005). In terms of Ebola coverage, this meant identifying

examples containing language and anecdotes that conveyed emotion, gave Ebola a “human

face,” or emphasized the effects of Ebola on everyday people (Beaudoin, 2007). An article from

The New York Times on December 14, 2014 exemplified this human interest frame. It spoke of

how Ebola has created a new generation of orphans in West Africa. “None of the other children

in the group home looked especially healthy -- twice a day their temperatures are taken to make

sure they are not coming down with Ebola. One infant was sucking on an empty box of milk,

clearly hungry. Another little boy kept shielding his eyes, even though he was sitting in the

shade. He had survived Ebola but his eyes still hurt.” The emphasis on an individual’s

experience with Ebola characterizes the human interest frame.

Economic Consequences Frame

The economic consequences frame, used in past SARS media coverage studies, focused

on articles that concentrated on the financial and economic implications of Ebola (Beaudoin,

2007; Luther & Zhou, 2005). This frame helps to demonstrate how the media transformed the

Ebola issue from one of just a medical condition inflicted by a virus to one that affected various

parts of society, including financial and economic conditions. An example came from the BBC

20

from August 20, 2014: “‘The economy has been deflated by 30% because of Ebola,’ Sierra

Leone's Agriculture Minister Joseph Sam Sesay told the BBC” (Hamilton, 2014).

Attribution of Responsibility Frame

The attribution of responsibility frame, used in SARS media coverage research, related to

how the media tie blame and responsibility to the spread of Ebola (Beaudoin, 2007; Luther &

Zhou, 2005). It is important to analyze this theme because it illustrates whether the media

portrayed Ebola as something in people’s control, and thus able to single out a person, policy, or

group to blame, or out of any person or institution’s control. An example of attribution of

responsibility in The New York Times from December 30, 2014 was: “Some in the W.H.O. along

with Guinean officials played down the threat, leading to overconfidence and inattention” (Sack,

Fink, Belluck, & Nossiter, 2014). This quotation showed how the inaccurate threat assessment

by public health experts harmed the institutional reaction to Ebola, and thus laid blame on these

experts.

Phrase-to-Frame Coding and Analysis

To use NVivo to code for the six media frames, it was necessary to first determine which

words and phrases designated a particular frame. I read numerous randomly selected articles to

assign particular words and phrases to each media frame. These articles included a quarterly

sample from each news outlet for both the 2000-2001 and 2014 outbreaks; for example, there

were articles from BBC Monitoring, The New York Times, The Daily Telegraph and The Straits

Times for the first quarter following the initial confirmation of Ebola in 2000 (from October 15,

2000 to January 15, 2000), and for every quarter thereafter. Appendix 4 contains a full listing of

21

the words and phrases used in assigning each frame. These selected words and phrases were

mutually exclusive to each frame.

After this phrase-to-frame assignment, I used an automatic search function in NVivo to

find occurrences of keywords and assign them to their related frame. A manual reading of all

coded articles to check for computer errors was also necessary. Any automatic coding that

selected words used outside the context of the intended frame was “uncoded”. The criteria used

to warrant “uncoding” of automatically selected phrases were the following: words directly

related to another topic discussed in the article; words used as part of a proper noun or title (e.g..

“Centers for Disease Control and Prevention”); words used in the descriptor of an individual’s

title (e.g., “investment strategist”); or words appearing in graphic captions, news desk section

titles (e.g., “foreign desk”), or byline descriptors. Additionally, duplicate articles and those where

Ebola only appeared in the byline descriptor or graphic caption were discarded.

Once all articles were coded and checked in NVivo, the software supplied the raw data in

terms of the number of appearances of each frame, the number of articles containing each frame,

and the percentage of each article dedicated to each frame. These data allowed a comparison of

media frames, the 2000-2001 and 2014 outbreaks, and media outlets as well as identified trends

over time. R Studio, a statistical software package, and Microsoft Excel aided in cleaning up the

data and conducting this analysis.

To understand the relationships between media coverage of the two outbreaks, media

outlets, frames, and search terms, Excel helped to calculate the prevalence of frames and percent

of articles including various frames. Using R studio enabled me to calculate the internal

reliability of the phrase-to-frame constructs by testing the average correlation of all phrases

pertaining to their parent frame. Cronbach’s alpha was used for this calculation. R studio also

22

helped me determine whether differences in media frame usage between the 2000 and 2014

outbreaks were significant by calculating p-values with chi-square analysis.

Results

The content analysis of media coverage of Ebola outbreaks revealed differences in how

journalists framed the disease in 2000-2001 versus 2014-2015, as well as differences between

media outlets. This section will discuss the findings from this analysis, as well as provide the

basis for further discussion. It will begin by analyzing the sample of news coverage, and then

move through how keywords used by the media shaped the framing of articles.

Sample

This study coded 4,251 articles from BBC Monitoring, The New York Times, The Daily

Telegraph (UK), and The Straits Times (Singapore). Table 3 below outlines the sampling

distribution of articles by outbreak and media outlet.

Table 3. Sample Distribution

2000-2001

2014-2015

Total

BBC Monitoring

152 2,081 2,233

The New York Times 56 1,265 1,321

The Daily Telegraph, UK 12 465 477

The Straits-Times, Singapore 6 214 220

Total 226 4,025 4,251

23

Ninety-five percent of coverage came from the 2014-2015 Ebola outbreak versus five

percent from the 2000-2001 outbreak. This was unsurprising considering this outbreak

experienced 67 times more cases and infected people outside the confines of Africa (CDC,

2015). These more extreme direct consequences of the outbreak prompted an explosion of media

coverage in 2014-2015 across the globe. Figure 1 below shows the distribution of media

coverage broken year by outbreak.

Figure 1. Sample Distribution by Year

Additionally, national newspapers – The New York Times, The Daily Telegraph, and The

Straits Times – were underrepresented in the 2000-2001 coverage. Two-thirds of all articles

during this earlier timeframe were from BBC Monitoring, which included local newspapers from

Western and Central Africa. In 2014-2015, just over half of all articles came from BBC

Monitoring. Overall, the source with the most coverage of Ebola in both outbreaks was The New

York Times, with 56 articles in 2000-2001 and 1,265 articles in 2014-2015. This was followed by

The Daily Telegraph (477 articles total) and The Straits Times (220 articles total). Figure 2 below

shows the distribution of articles published by media outlet and the percentage of stories from

each outlet.

226

4025

0500

10001500200025003000350040004500

2000 2014

5%

95%

2000

2014

24

Figure 2. Sample Distribution by Media Outlet

Mutation Contagion Frame

The mutation contagion frame was the most widely used perspective in media coverage

of the Ebola outbreaks, as it was present in 71.1 percent of all articles. There was a difference

between 2000 and 2014, with 81.0 percent of reports in 2000-2001 containing the frame,

compared to only 70.5 percent in 2014-2015. Usage between media outlets varied only slightly.

Overall, there were 3,021 instances of the mutation contagion frame in all of the coverage. On

average, of those articles that included this frame, there were 9.0 keywords per piece. In 2000-

2001, there were on average 6.7 keywords per article, compared to 9.1 in 2014-2015.

Analyzing the metaphors commonly used by the media, the mutation contagion frame

was divided into three themes – plague, killer, and war. The plague metaphor was the most

prevalent, with 62.3 percent of all articles using this approach. In comparison, the killer and war

metaphors appeared in about half the number of articles, 32.5 percent and 30.8 percent of

articles, respectively. Figure 3 below demonstrates the distribution of metaphors in media

coverage.

2233

1321

477220

0

500

1000

1500

2000

2500

53%31%

11%

5%BBC Monitoring

The New York Times

The Daily Telegraph

The Straits Times

25

Figure 3. Distribution of Metaphor Usage in Terms of Number of Articles in which Metaphors Appeared

The plague metaphor also appeared approximately three more times per article on

average (6.2 appearances per article). Perhaps the reason for this difference is because two of the

keywords used to identify the plague frame were “disease” and “virus,” which appeared 1,620

and 1,956 times, respectively. The media also frequently used the words “infection” and

“epidemic” within the plague metaphor to describe the Ebola outbreaks, as 27.5 percent and 20.8

percent of all articles included these terms, respectively. Figure 4 below shows the distribution of

plague metaphor keywords in media coverage.

50%

26%

24%Plague

Killer

War

26

Figure 4. Percent of Articles with Mutation Contagion: Plague Frame Keywords

The killer metaphor appeared more frequently in 2000-2001 coverage of Ebola versus

2014-2015. Over 40 percent of articles in 2000-2001 used this metaphor, compared to just over

30 percent in 2014-2015. The killer metaphor also varied across media outlets, from 29.85

percent of articles in BBC Monitoring to 38.6 percent of articles in The Daily Telegraph

employing this technique. Using the killer metaphor, media outlets often described the virus as

“deadly”; 16.7 percent of articles used this term. Stories also frequently referred to Ebola as

“killing” infected individuals (11.5% of articles) and as creating “victims” (9.5% of articles).

Figure 5 below demonstrates the percent of articles using each keyword included in the killer

metaphor.

0.00%5.00%

10.00%15.00%20.00%25.00%30.00%35.00%40.00%45.00%50.00%

Asym

ptom

atic

Cure

Dis

ease

Epid

emic

Infe

ctio

n

Infe

ctio

us

Mor

bidi

ty

Mor

talit

y

Mut

ate

Patie

nt ze

ro

Plag

ue

Sick

Sym

ptom

Sym

ptom

atic

Tran

smis

sion

Tran

smit

Vira

l

Viru

lenc

e

Viru

s

2000 2014

27

Figure 5. Percent of Articles with Mutation Contagion: Killer Frame Keywords

By contrast, the war metaphor was more prevalent in coverage of the 2014 Ebola

outbreak. In 2014-2015, 31.6 percent of articles included this metaphor, compared to just 17.7

percent in 2000-2001. Within the war metaphor, “fight” was the most commonly used keyword,

as journalists or their sources frequently described efforts against the disease as “fighting” Ebola;

17.7 percent of all articles used this phrase. There was a disparity between years of coverage in

using this phrase, as the 8.4 percent of articles that used “fight” in 2000-2001 increased to 18.2

percent in 2014-2015. Figure 6 below shows how the media used a war metaphor in coverage of

Ebola by distribution of search terms.

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

Dea

dly

Hun

t

Hur

t

Kill

Kill

er

Leth

al

Mys

tery

Ragi

ng

Ram

page

Stal

k

Stri

ke

Trac

k

Vict

im

2000 2014

28

Figure 6. Percent of Articles with Mutation Contagion: War Frame Keywords

The mutation contagion frame also included certain keywords outside of the categories of

the three metaphors. The search terms “death” and “die” were the most prevalent in this general

category, with 15.2 percent and 19.4 percent of articles including these words, respectively.

Interestingly, articles published about the 2000 outbreak were twice as likely to include the word

“death” (29.2% of articles) as those published about the 2014 outbreak (14.5% of articles).

Media also commonly used the word “fear” in describing Ebola, as 14.4 percent of articles

included this term. Stories published in 2014-2015 much more frequently used the word “crisis”;

13.0 percent of articles during this year used “crisis,” compared to just 0.4 percent in 2000-2001.

Figure 7 breaks down the keywords not included in any of the metaphors used in the mutation

contagion frame by illustrating the percent of articles with each term.

0.00%2.00%4.00%6.00%8.00%

10.00%12.00%14.00%16.00%18.00%20.00%

Batt

le

Casu

alty

Com

bat

Conf

lict

Conq

uer

Def

eat

Def

end

Det

ain

Enem

y

Figh

t

Figh

ter

Har

bor

Rava

ge

Sacr

ifice

Secu

rity

Tack

le

Terr

oris

m

Terr

oris

t

Triu

mph

Vanq

uish

Vict

ory

War

2000 2014

29

Figure 7. Percent of Articles with Mutation Contagion: General Frame Keywords

To test the reliability of the set of keywords used to predict the latent construct of a

mutation contagion frame, an analysis of the average correlation of all keywords pertaining to

mutation contagion was useful. Cronbach’s alpha revealed a value of 0.753, which is above the

0.7 acceptable mark for internal consistency. However, none of the individual metaphor

categories passed this test. The Cronbach’s alpha value for the plague metaphor came closest,

with 0.699, but there is a possibility that this is an inflated value because of the high prevalence

of the words “disease” and “virus.” In comparison, the alpha value for the killer metaphor was

0.407 and for the war metaphor was 0.362. Part of the reason for these low values was perhaps

the relatively few number of terms assigned to identify these metaphors.

“Othering” and Containment Frame

Nearly one-third (30.1%) of all articles about the Ebola outbreaks utilized the “othering”

or containment frame. These statistics differed between the two outbreaks, with 23.0 percent of

articles in 2000-2001 and 30.5 percent of articles in 2014-2015 including words associated with

this perspective. The coverage among media outlets differed similarly, with the lowest

0.00%5.00%

10.00%15.00%20.00%25.00%30.00%35.00%

Cont

agio

us

Cris

is

Dan

ger

Dea

th

Dev

asta

ting

Die

Dis

aste

r

Exte

nsiv

e

Fata

l

Fear

Hor

rific

Hor

rify

Pani

c

Suffe

r

Terr

ifyin

g

Thre

at

Unt

reat

able

2000 2014

30

percentage of articles coming from The Daily Telegraph (24.7%) and the highest percent from

The New York Times (33.3%). Altogether, this frame was used 4,261 times throughout the media

coverage. On average, those articles portraying this interpretation used 3.2 keywords associated

with “othering” or containment. Notably, The New York Times had 3.9 keywords per article on

average, while all of the others had around 2.8 keywords.

As anticipated, the media employed this “othering” frame to describe the disease, and the

problems it caused, as inherently contained to Africa. Interfax News Agency in Russia,

distributed by BBC Monitoring, epitomized this notion of terming Ebola as “African” in a report

published October 9, 2014: “’The spread and establishment of this infection in Russia is not

possible. The spread of the Ebola virus is not possible anywhere except in tropical Africa. That's

obvious.” This showed how the Russian Health Ministry attempted to downplay the epidemic

and portray it as under control.

However, media outlets also used the “othering” frame to distance Ebola patients from

the greater population. Frequently media spoke about quarantine policies and controlling the

virus. For example, on October 23, 2014 The New York Times published an article about North

Korea’s attempt to separate itself from the rest of the Ebola-stricken world and disallow

foreigners from entering the country: “Fearful that Ebola could find a foothold in North Korea,

officials in the reclusive country have abruptly shut down its small and tightly-controlled tourism

industry… There was no word on how long Pyongyang intends to quarantine itself from the

world.” The North Korean response highlighted in Western media represented how the issue of

quarantine and disease control became global.

“Othering” and containment keywords varied from a prevalence of 0.2 percent of articles

for “alien” to 12.9 percent of articles for “control.” Media coverage of the 2014 outbreak had

31

nearly twice as many articles with “control”, as well as more “African,” “contain,” “foreign,”

“isolate,” and “quarantine.” The disparity between the media coverage of the two outbreaks and

usage of “quarantine” was especially notable, as it only appeared in 1.8 percent of reports in

2000-2001 compared to 8.7 percent of reports in 2014-2015. Interestingly, the opposite was true

of the word “surveillance.” Articles in 2000-2001 were nearly twice as likely to use the word

“surveillance” as compared to 2014-2015. Figure 8 below shows the percent of articles using the

“othering”/containment frame by associated keywords.

Figure 8. Percent of Articles with “Othering” Frame Keywords

Although the “othering” frame did not pass the internal reliability test with a Cronbach’s

alpha value of 0.500, this is not surprising given the relatively few search terms that fit in this

category.

Globalization Frame

The globalization frame was widely used by media outlets in their media coverage of

Ebola. Almost 43 percent of articles included search terms used to identify globalization.

However, there was a large discrepancy between 2000-2001 coverage and 2014-2015 coverage.

0.00%2.00%4.00%6.00%8.00%

10.00%12.00%14.00%

Afri

can

Alie

n

Cont

ain

Cont

rol

Dis

tant

Exot

ic

Fore

ign

Isol

ate

Qua

rant

ine

Surv

eilla

nce

2000 2014

32

Articles reporting on the latter outbreak were nearly twice as likely to utilize a globalized

perspective in their writing. In 2014-2015, 44.0 percent of articles included a globalization

keyword, but in 2000-2001, only 23.0 percent of articles included such words. Media outlets

were split in terms of the amount of coverage, with The Straits Times and The Daily Telegraph

having 47 percent of articles with a globalization frame, and BBC Monitoring and The New York

Times having 42 percent of articles with the frame. Overall, there were 9,782 instances of

globalization search terms. Out of those reports that included this worldwide spreading theme, on

average each article had 5.0 key words.

The media often portrayed Ebola as a growing global threat, and frequently spoke of

increased efforts to screen travelers at border checkpoints for the disease. For example, even

BBC Monitoring’s October 12, 2014 report from Russian National Television addressed the

possibility of the transmission of Ebola to foreign countries: “The Ebola outbreak has presented

the world with an ‘unusual situation’ in which ‘globalization has opened the door’ to the spread

of a virus. Whether we want it or not Ebola will reach Russia, scientists in Boston have said, but

Rospotrebnadzor head Anna Popova casts doubt on the prediction.” Thus the impending

worldwide threat of Ebola made it into newspapers across the globe.

The search terms used to identify the globalization frame differed in their prevalence

from “tourist” in 0.3 percent of articles to “spread” in 24.7 percent. As the word in the most

reports, “spread” was found in 29 articles in 2000-2001 and 1,022 in 2014-2015. This pointed to

a substantive difference in coverage between the two outbreaks. Journalists in 2014-2015 were

twice as likely to include “spread” in their work. Additionally, seven times more articles

included “global,” five times more articles included “flight,” three times more articles included

“travel” and “airport.” Apart from spread, the most commonly used keywords were “world”

33

(13.9% of articles) and “travel” (13.6% of articles). Figure 9 below illustrates the fraction of

articles that include keywords connected to the globalization frame.

Figure 9. Percent of Articles with Globalization Frame Keywords

The globalization frame’s search terms passed the internal reliability test, and thus were

sufficiently correlated to point towards the same “globalization” construct. The Cronbach’s alpha

value was 0.706, which is above the widely used 0.7 cutoff.

Human Interest Frame

Of all articles, 42.3 percent included a keyword from the human interest frame. This high

prevalence was not surprising considering the words included “doctor,” “family,” and “patient.”

A slightly higher percentage of stories (42.4%) from 2014-2015 included this perspective

compared to stories from 2000-2001 (38.9%). Media outlets varied in their use of the human

interest from 35.9 percent of articles in The Straits Times to 51.7 percent in The New York Times.

Overall, keywords appeared in media coverage of both outbreaks 9,042 times. On average, each

article that used the frame included 5.0 search terms.

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

Airp

lane

Airp

ort

Bord

er

Bus

Entr

y

Flig

ht

Glo

bal

Glo

be

Pass

enge

r

Port

Scre

en

Ship

Spre

ad

Tour

ism

Tour

ist

Tour

ists

Trad

e

Trav

el

Visa

Visi

tor

Wor

ld

2000 2014

34

The media coverage of Ebola included hundreds of touching stories of Ebola victims and

doctors’ struggles to fight the disease. Frequently stories began with an anecdote about a

personal narrative of one individual, but other times entire articles were dedicated to these

human interest topics. One example was published by The Daily Telegraph on January 10, 2015

and told the story of Ebola survivors in Liberia: “Saah Blackie, 39, a father-of-two who lives in

Monrovia's rowdy Bushrod Island slum, says he too is a victim of stigmatisation. ‘If I didn't own

my house,’ he says, ‘I would have been thrown out.’ … When he contracted the disease, most of

his possessions were burnt. Among the few items he has left are a certificate from the MSF clinic

declaring him Ebola-free, and a handful of photographs taken when he was sick.” This quotation

showed how the media focused on a personal story to tell the broader narrative of Ebola.

Other human interest stories brought to life the weakened health care infrastructure. BBC

Monitoring’s September 18, 2014 piece from a Nairobi online news service spoke of how

already-full health clinics were forced to turn patients away: “’The first person I had to turn away

was a father who had brought in his sick daughter in the trunk of his car. He was an educated

man, and he pleaded [with] me to take her, saying while he knew we couldn't save her life, we

could save the rest of his family from her. At that point I had to go behind one of the tents to

cry.’” The personal stories humanized the crisis and emphasized that it was more than just

statistics.

The human interest frame’s associated keywords varied in terms of the numbers of

articles in which they appeared. Over one-quarter of the articles published included the word

“patient” with little difference between outbreak years (23.5% in 2000-2001 and 27.4% in 2014-

2015). “Nurse/nurses” and “doctor” were also relatively frequently occurring, appearing 17.5 and

16.9 percent of articles, respectively. Notably, stories in 2014-2015 were 10.6% more likely to

35

include “nurse/nurses” than in 2000-2001. Perhaps this higher prevalence of “nurse/nurses”

could be attributed to the nurses in Dallas, New Jersey, and Glasgow who contracted Ebola and

brought it back to the United States and United Kingdom. Figure 10 exhibits the prevalence of

human interest keywords in media coverage of the 2000 and 2014 Ebola outbreaks.

Figure 10. Percent of Articles with Human Interest Frame Keywords

In testing the reliability of the set of search terms to predict a uniform human interest

frame, Cronbach’s alpha calculation revealed a value of 0.734, which exceeds the 0.7 acceptable

mark for internal consistency. This indicates that the keywords each signify a consistent human

interest frame.

Economic Consequences Frame

The media framed Ebola around its economic consequences and related costs in 21.35

percent of all articles published following the 2000 and 2014 outbreaks. Articles in 2014-2015

were twice as likely (21.9 percent) to adopt this economic perspective as those in 2000-2001

(11.0 percent). The Daily Telegraph had the greatest percentage of articles that included an

economics theme, with over one-quarter of all articles including an associated search term. BBC

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

Boy

Brot

her

Child

Child

ren

Doc

tor

Emot

ion

Fam

ily

Fath

er

Gir

l

Indi

vidu

al

Indi

vidu

als

Man

Mot

her

Nur

se

Nur

ses

Patie

nt

Phys

icia

n

Sist

er

Wom

an

2000 2014

36

Monitoring had the lowest percentage of articles with 19.3 percent. Overall, economics

keywords appeared almost 4,000 times in the media. In those articles that included information

about the financial status or costs related to Ebola, an economics-category keyword appeared 3.3

times on average.

The economic consequences frame often appeared in the form of assessing hospital costs

of treatment, noting international health agency and NGO donations to infected countries, and

explaining the economic consequences of Ebola for countries’ GDP and industry. A particularly

telling example of this appeared in BBC Monitoring’s September 8, 2014 article from Alwihda in

Chad, which explained how the closure of the Chad-Nigeria border affected the country’s trade

and economic situation: “Every day, prices of products are skyrocketing and vulnerable

Chadians can neither eat to their fill nor support their families. Entry of products is difficult and

life is becoming expensive to Chadians.”

The incidence of keywords related to economics varied from appearing in only 0.2

percent of articles to appearing in 5.3 percent of articles. Unsurprisingly, the word in the most

number of articles was “dollar,” which was coded in 241 articles. “Fund,” the second-most-

occurring word was found in 218 articles (5.0 percent). Notably, this word was over four times

more likely to appear in coverage of the 2014 outbreak than it was in 2000-2001. Likewise, on a

percentage basis, the term “economic” appeared in four times as many articles in 2014-2015

articles as it did in 2000-2001 articles. “Financial” made it in 93 articles and “price” in 57

articles in 2014-2015 but were not included in any coverage following the outbreak in 2000.

Although not always as drastic, nearly all of the economics keywords were in a greater

percentage of 2014-2015 articles than 2000-2001 articles. The two exceptions to this rule were

“monetary” (0.4% in 2000-2001 versus 0.2% in 2014-2015) and “payment” (0.4% in 2000-2001

37

versus 0.2% in 2014-2015). Figure 11 below presents the coverage data associated with

economics consequences keywords.

Figure 11. Percent of Articles with Economic Consequences Frame Keywords

To test the consistency of the set of search terms used to predict the construct of an

economic consequences frame, Cronbach’s alpha calculation revealed a value of 0.697, which is

just barely under the 0.7 acceptable mark for internal consistency. This suggests that the search

terms each point to a consistent economics frame.

Attribution of Responsibility Frame

The attribution of responsibility frame was notably the least occurring frame in media

coverage of Ebola. Only 9.6 percent of articles included keywords associated with responsibility

or blame. This percentage was even smaller among articles in 2000-2001 – only 5.3 percent of

articles employed this frame. There was also some variance among media outlets in terms of

articles’ likelihood of speaking to who or what was responsible for causing and treating Ebola.

Whereas 15.8 percent of stories in the The New York Times included the responsibility frame,

only 6.2 percent of stories in BBC Monitoring included the frame. In total, there were 615

0.00%1.00%2.00%3.00%4.00%5.00%6.00%7.00%

Boug

htBu

dget

Busi

ness

Busi

ness

esBu

yCo

mm

erce

Com

mer

cial

Cost

Dol

lar

Don

atio

nEc

onom

icEc

onom

yEm

ploy

men

tEu

roFi

nanc

eFi

nanc

ial

Fisc

alFu

ndIn

dust

ryIn

vest

men

tM

arke

tM

onet

ary

Mon

ey Pay

Paym

ent

Pric

eRe

tail

2000 2014

38

instances of responsibility-related keywords. Of those articles including a keyword, the average

number of times a keyword appeared per piece was 1.5, which is the lowest average among any

of the frames. No noteworthy variation existed in this average number of appearances between

outbreaks or media outlets.

When media employed the attribution of responsibility frame, they typically used these

keywords to explain a failure in healthcare infrastructure or policy interventions. Additionally,

coverage used this perspective to attribute blame as well as to suggest who was accountable for

fixing the Ebola problem. A problem when coding for this frame was the articles’ diverse

number of phrasings used to speak about responsibility. For example, while the following

excerpt from The New York Times on January 31, 2015 was clearly about the idea of blame and

responsibility, no keyword existed: “The fear that was spread by the dramatic reports that

accentuated the negative, undermined confidence, made it harder to encourage people to seek

care, and misdirected attention away from Sierra Leone's urban areas, where data suggest the

economic effects of Ebola have been concentrated… Why were projections so bad? Partly

because it is hard to collect good data in a crisis. But also, we believe, because dramatic

headlines make for a better story.” This quotation showed how the phrase-to-frame model may

not have worked as well for this attribution of responsibility frame as it did for the other frames.

None of the search terms within the attribution of responsibility frame appeared in even 2

percent of the articles published. “Blame” was the most prevalent keyword, with occurrences in

only 80 reports – 1.9 percent of all coverage. Most of the keywords appeared in fewer than 10

articles. Figure 12 below shows the percent of articles using keywords associated with attribution

of responsibility. It is important to note the scale in this chart, as the vertical axis only reaches

2.5 percent.

39

Figure 12. Percent of Articles with Attribution of Responsibility Frame Keywords

The keywords used to predict the attribution of responsibility frame did not meet the

standards for sufficient internal consistency, with a Cronbach’s alpha value of 0.300. However,

because of the such low prevalence of this frame in the literature, this was to be expected. It did

call into question whether this frame was actually used in much of the media coverage, and

casted doubt on its relevance for these two more recent Ebola outbreaks.

Conclusion

Application of Frames from the Literature to Recent Ebola Coverage

The media coverage of the 2000-2001 and 2014-2015 Ebola outbreaks used a

combination of frames similar to previous literature about infectious disease reporting. The

mutation contagion frame was particularly important, as 3,021 out of 4,251 articles used

keywords from this perspective at least once. This may show how the media were likely to

sensationalize coverage and create a sense of panic to gain the public’s attention. By using words

commonly associated with plagues, killers, and war, the media painted a vivid picture of the

0.00%0.50%1.00%1.50%2.00%2.50%

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2000 2014

40

dangers of Ebola. The next most frequently occurring frame was the globalization frame,

followed by human interest, othering, and economic consequences. Stories were least likely to

include aspects of attribution of responsibility. The general lack of articles that included the

attribution of responsibility frame may have had implications for how the rest of the world

viewed the Ebola crisis. Because the media only rarely spoke of blame, the public and

policymakers may have been less likely to view Ebola as a result of a failure of health

infrastructure or a specific group of people. Figure 13 shows the distribution of frame usage by

the media.

Figure 13. Distribution of Frame Usage in Terms of Number of Articles in which Frames Appeared

Of those articles containing the frame, the average number of times it appeared in the text

revealed that the mutation contagion frame was also the most used frame in this respect. Articles

using the mutation contagion frame on average included almost six related keywords. Articles

using the plague metaphor included three times as many related keywords (6.0) as those

following the killer (1.9) or war (2.2) metaphors. The average number of keywords associated

with attribution of responsibility was the lowest of any frame. Figure 14 below exhibits the

average number of frame appearances per article containing frame terminology.

10%

20%

19%33%

14%4%

Economics

Globalization

Human Interest

Mutation Contagion

Othering

Responsibility

41

Figure 14. Average Number of Frame Appearances Per Article Containing Frame Terminology

Trends identified in previous literature prevailed in media coverage of the most recent

Ebola crisis. Ungar’s conclusion that media coverage shifted from a theme of mutation contagion

to a containment package in reports on the 1990s Ebola outbreak could not be tested due to a

lack of temporal analysis, although these themes appeared in the mutation contagion and

othering frames, respectively, in recent outbreaks (Ungar, 1998). Recent media coverage also

mimicked the tendency to represent Ebola as distinctively “African,” as found in Joffe and

Haarhoff’s research on the 1990s Ebola outbreak (Joffe & Haarhoff, 2002). The media appeared

to use the “othering” or containment representation as a coping mechanism to alleviate fears by

focusing on how the disease affects “others” rather than the immediate audience. However, the

current data suggest that the media more frequently portrayed Ebola as a global security threat,

and focused on the political issues of travel bans and quarantines rather than simply writing off

the disease as a purely African problem. Although the media did not seem to interpret the virus

using science fiction imagery as the public did in the 1990s, it is difficult to conclude audience

effects of media coverage with the given data (Joffe & Haarhoff, 2002).

0123456789

10

42

The trend of media reporting revealing anxieties about the inability of technology and

biomedicine to contain epidemics and about the ecological and economic threats of globalization

appeared to continue with recent Ebola crises (Washer, 2004). The portrayal of Ebola as a

globalized threat was especially important in coverage of the 2014 outbreak. In the year

following the initial WHO announcement of Ebola, 44 percent of articles included a keyword

associated with globalization. Fewer articles in 2000-2001, only 23 percent, included this frame.

The frames identified in past research of SARS coverage seemed to translate to articles

about Ebola. Just as Wallis & Nerlich (2005) found that reports depicted diseases as killers,

plagues, or hostile combatants in war, keywords related to these metaphors were prevalent in

media coverage of the 2000 and 2014 Ebola outbreaks. Furthermore, media about these recent

outbreaks used frames of responsibility, human interest, and economic consequences, similar to

previous research on SARS media coverage (Beaudoin, 2007; Luther & Zhou, 2005). Therefore,

the data confirmed the hypothesis that media reports of the recent Ebola crises would mirror the

results found in previous content analyses of media coverage of infectious disease epidemics.

As hypothesized based on previous research on international health crises, media

coverage of the Ebola outbreak appeared highly politicized and event-based. Although the data

did not allow for a timeline analysis of how frames changed over time in relation to political

events, the topics of stories frequently reflected politicized events and policy decisions. For

example, the North Korean decision to close its borders to all outsiders instigated a wave of

media reports and analyses evaluating the political decision and its consequences. Media

coverage did not appear to follow a trend based on the number of people infected at any given

time, although the volume of articles in 2014-2015 greatly outnumbered those in 2000-2001

because of the greater magnitude of the epidemic.

43

Differences in Frames from 2000 to 2014

In comparing the 2000 to 2014 outbreaks, it is important to remember the differences in

the sheer quantity of coverage and differences in media environment. There were 226 stories in

2000-2001 compared to 4,025 in 2014-2015. Thus framing techniques may have appeared to

vary simply because of the differences in the volume of coverage. Additionally, radical changes

in the media landscape and increased global connectivity through the internet may have

influenced coverage (Couldry, 2012). For example, news outlets now may face increased

pressure to use dramatic and inflammatory words and frames to increase the number of clicks on

their websites and increase ad revenue. Social media may also have propagated increased media

coverage of Ebola as more people participated in the storytelling of this shocking topic.

In 2000-2001, the media were more likely to include references to the mutation contagion

frame. According to table 4 using chi-square analysis, a significantly higher percentage of

articles from 2000-2001 included this mutation contagion frame compared to articles from 2014-

2015. However, the average number of keywords associated with the mutation contagion frame

was higher in 2014-2015 than 2000-2001. This could possibly be attributed to the fact that the

2014-2015 coverage included a number of lengthy articles that made use of many keywords, thus

pushing up the average keyword appearances for this year of coverage. The stories following the

2000 outbreak were specifically more likely to use the metaphors of killer and plague. Perhaps

this demonstrated that the media saw this smaller outbreak as simply a medical rather than a

global security threat. According to chi-square analysis, the war metaphor was significantly more

prevalent in stories following the 2014 outbreak. It may be that the media included references to

fighting Ebola more frequently in 2014-2015 to justify outside-country intervention and create a

common enemy to unite against.

44

Figure 15. Percent of Articles with Frames by Year

Figure 15 and table 4 demonstrated that the articles from media coverage in 2014-2015

were also significantly more likely to include keywords associated with the economic

consequences, globalization, othering, and attribution of responsibility frames. Differences in

usage of the human interest frame were not significant. The frames that experienced the most

significant differences in usage between outbreaks were globalization and economics, which

could speak to a kind of global financial anxiety in 2014-2015 coverage. The increase in the

prevalence of the globalization frame is likely to be attributed to the more global influence of

Ebola, as there were so many more cases in 2014-2015 and the outbreak was less localized. This

also would affect the usage of the economics frame, as Ebola could increasingly be viewed as a

threat to the stability of the global economy. It is surprising that articles in 2000-2001were less

likely to use an “othering” frame and illustrate Ebola as distinctively “African,” since this

outbreak could in fact be characterized as isolated to the African continent. However, there was a

more immediate pressure to work to contain the virus during the 2014 outbreak because of the

need to stop the spread to other continents. This “othering” frame could have also been used to

mitigate panic and divert attention from the global threat.

0.00%10.00%20.00%30.00%40.00%50.00%60.00%70.00%80.00%90.00%

2000 2014

45

Table 4. Differences in Percentage of Articles with Frames by Year

2000-2001

2014-2015

Chi-Square

Mutation Contagion

81.0% 70.5% 9.494*

General 56.6% 49.1% 4.84*

Killer 41.2% 31.9% 8.48**

Plague 64.6% 62.2% 0.46

War 17.7% 31.6% 19.57***

“Othering” 23.0% 30.5% 5.63*

Globalization 23.0% 44.0% 39.57***

Human Interest 38.9% 42.4% 0.97

Economic Consequences 11.0% 21.9% 14.89***

Attribution of Responsibility 5.3% 9.8% 4.66*

Chi-square tests were conducted with df = 3. H0 = 2014-2015 % value; H1 = 2000-2001 % value. *p<.05. **p<.01. ***p<.001.

In terms of the average number of times a frame appeared in an article, those published in

2014-2015 included more frame keywords in each of the frame categories, except for killer and

responsibility. Perhaps this can be attributed to the fact that several of these articles in this time

period were long-form, giving the authors more opportunities to use a frame keyword. Figure 16

displays the differences in frame inclusion in media coverage of the 2000 and 2014 outbreaks.

46

Figure 16. Average Number of Frame Appearances Per Article Containing Frame Terminology by Year

Differences in Frames Across Media Outlets

The trends of frame usage across media outlets were very similar. The New York Times

was slightly more likely to have articles with a human interest angle. BBC Monitoring published

a slightly higher percentage of articles using the plague metaphor, but a lower percentage of

articles using the killer metaphor, compared to the other news outlets. The publication with the

highest percentage of articles using the globalization frame was The Straits Times. This was not

surprising considering the location of its publication. Singapore was relatively removed from the

Ebola outbreak, and so speaking of Ebola using a global framework would make the topic more

relevant to its readers. Figure 17 below illustrates the prevalence of frames according to media

outlet.

02468

10

2000 2014

47

Figure 17. Percent of Articles with Frames by Media Outlet

The difference in typical article length published by each media outlet may have

contributed to the variance in average frame appearances per article containing frame

terminology across outlets. The New York Times included a higher average number of frame

appearances per article containing frame terminology for all frames, with the exception of

attribution of responsibility. This could be due to the several long-form stories published by The

Times that included many phrases associated with frames. Figure 18 shows the average number

of frame appearances per article based on media outlet.

0.00%10.00%20.00%30.00%40.00%50.00%60.00%70.00%80.00%

BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times

48

Figure 18. Average Number of Frame Appearances Per Article Containing Frame Terminology by Media Outlet

Consequences of Framing on Public Opinion of Ebola

Particularly because the media serve as the primary source of information about

infectious disease epidemics for much of the public, its framing has implications for how the

world views Ebola. Although the intent of this study was not to assess audience effects, it is

important to understand the public perception of Ebola to draw conclusions about media impacts.

A U.S. Gallup Poll in October 2014 revealed that almost one-fourth of Americans said they

worried about getting the Ebola virus, whereas a fewer percentage said they worried about

getting H1N1 (swine flu virus) during most of its outbreak (Gallup News Service, 2014).

Furthermore, almost two-thirds of respondents in this poll said they thought there would be a

minor outbreak of Ebola in the United States (Gallup News Service, 2014). A Harvard study

conducted in October 2014 revealed similar results: over half of respondents said they were

concerned that there will be an Ebola outbreak in the United States within the next 12 months

(Harvard School of Public Health, 2014). These results suggest that the media’s intensive

coverage of Ebola in 2014 may have distorted the public’s perception of its risk. Only four

people in the United States ever contracted the Ebola virus, yet perhaps the sensationalized

02468

101214

BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times

49

media coverage led the public to believe that it was a greater threat than it was in reality (WHO,

2015). If the media affected these respondents’ attitudes toward Ebola, they blatantly failed to

accurately represent risk.

Limitations

The present analysis had several limitations. First, a level of subjectivity was associated

with phrase-to-frame coding both in selecting relevant keywords and in determining whether

keywords used in the context of an article related to their linked frame. This subjectivity was

exacerbated by the fact that only one researcher coded all of the articles, which presented internal

reliability and validity problems. Multiple coders are preferred in qualitative data analysis

because high degrees of inter-coder agreement indicate that they are applying the codes similarly,

thus acting as “reliable” measurement instruments (Ryan, 1999). Because this study only used

one coder, it was not possible to calculate inter-coder reliability, or “the amount of agreement

between two or more coders for the codes applied to qualitative text” (MacPhail et al., 2015).

Contrastingly, a study with a single coder depends on the coder’s ability to not miss examples.

The current study attempted to minimize these problems by using an automatic search function

in NVivo, yet determining whether selected keywords were used in the context of their linked

frame was still subjective. Furthermore, when multiple independent coders mark the same text as

the same theme, it provides evidence that this theme has external validity and is not a figment of

the researcher’s imagination (Ryan, 1999).

With the limited sample of media outlets, it was also difficult to make broad

categorizations of worldwide media coverage of the Ebola crisis. Although the selected five

media outlets gave a depth to the data because of their differing geographic locations, nuances

such as political ideology of media organizations were lost. Liberal and conservative media may

50

have reacted differently to reporting on Ebola, but this analysis was constrained to the sample

from the four media outlets selected. These four outlets did not provide an adequate political-

position comparison because of their different countries of origin. Furthermore, the LexisNexis

database frequently included duplicates of stories, and although these were sorted through to

eliminate duplicates, human error could have missed some. Moreover, the current study would

have benefited from analyzing articles along a timeline from the first WHO announcement of

Ebola to one year later and by length of article. However, it proved prohibitively difficult to link

articles to their publication date and word count in analysis. Notably, the data excluded any

reference to media’s effects on audiences or public policy. Thus although the present analysis

suggested important trends in media coverage of the Ebola outbreaks, this topic requires further

research.

Future Research

Investigating media coverage of infectious disease epidemics should be a high priority for

media research and risk analysis. Scholars should look to the media to understand society’s

perception of these unique health threats. The recent Ebola crisis has opened a window for

potential research into not only the epidemiology of the mutated virus, but also the public’s

reaction and attitudes towards the disease. Using media coverage in combination with policy

actions of governments and international public health organizations is vital to understanding the

relationship between politics and media in a health crisis. Further research must be conducted on

the effects media have on public opinion during infectious disease epidemics, since the news

media serve as many people’s primary source of information. These analyses may help

government and public health officials better communicate the risk of the disease to

policymakers and the public. Assessment of risk perception of Ebola is crucial to prepare for

51

future epidemics and understand the relationship between the media and the public during health

crises.

52

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Appendices

Appendix 1. Sampling of Media Coverage Figure 1.1. Sample Distribution in 2000-2001

Figure 1.2. Sample Distribution in 2014-2015

67%

25%

5%

3%

BBC

NY Times

Telegraph

Straits

52%31%

12%5%

BBC

NY Times

Telegraph

Straits

59

Appendix 2. Number of Articles in which Frames Appeared Figure 2.1. Number of Articles with Frames by Year

Figure 2.2. Number of Articles with Frames by Media Outlet

0500

100015002000250030003500

2000 2014

0

500

1000

1500

2000

2500

3000

3500

BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times

60

Appendix 3. Total Number of Frame Occurrences Figure 3.1. Total Number of Frame Occurrences by Year

Figure 3.2. Total Number of Frame Occurrences by Media Outlet

05000

100001500020000250003000035000

2000-2001 2014-2015

0

5000

10000

15000

20000

25000

30000

35000

BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times

61

Appendix 4. Phrase-to-Frame Coding Inputs

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Mutation Contagion 3,021 80.97% 70.51% 6.72 9.10

General 2,106 56.64% 49.14% 3.06 3.06

Contagious 171 3.54 4.05 1.13 1.18

Crisis 525 0.44 13.02 1.00 1.58

Danger 264 3.54 6.56 1.50 1.26

Death 272 29.20 14.46 1.76 1.70

Devastating 78 0.88 1.89 1.00 1.05

Die 823 26.11 18.98 2.47 1.98

Disaster 83 0.44 2.04 1.00 1.20

Extensive 39 0.44 0.94 1.00 1.11

Fatal 160 1.77 3.88 1.25 1.21

Fear 611 13.72 14.41 1.48 1.57

Horrific 23 0.44 0.55 1.00 1.05

Horrify 7 - 0.17 - 1.29

Panic 245 3.98 5.86 1.33 1.32

Suffer 234 8.41 5.34 1.21 1.16

Terrifying 35 - 0.87 - 1.11

Threat 423 4.87 10.24 1.55 1.36

Untreatable 10 - 0.25 - 1.30

Killer 1,376 41.15% 31.88% 1.91 1.89

Deadly 709 20.80 16.45 1.13 1.23

ç

% of Articles

Mean

62

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Hunt 20 - 0.50 - 1.35

Hurt 30 - 0.75 - 1.23

Kill 490 14.60 11.35 1.45 1.26

Killer 28 0.88 0.65 2.00 1.04

Lethal 55 3.98 1.14 1.22 1.15

Mystery 30 2.21 0.62 1.20 1.20

Raging 64 0.44 1.57 1.00 1.08

Rampage 14 - 0.35 - 1.00

Stalk 1 - 0.02 - 1.00

Strike 57 0.44 1.39 1.00 1.11

Track 121 0.88 2.96 2.00 1.28

Victim 404 16.37 9.12 1.59 1.52

Plague 2,649 64.60% 62.19% 4.12 6.16

Asymptomatic 25 - 0.62 - 1.12

Cure 190 2.21 4.60 1.40 1.45

Disease 1,620 39.82 38.01 2.57 2.52

Epidemic 882 19.03 20.84 1.53 1.80

Infection 1,170 16.37 28.15 2.46 2.38

Infectious 310 5.31 7.40 2.08 1.43

Morbidity 5 0.44 0.10 2.00 1.00

Mortality 63 1.77 1.47 1.00 1.08

Mutate 34 - 0.84 - 2.18

ç

% of Articles

Mean

63

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Patient Zero 8 - 0.20 - 1.13

Plague 56 1.77 1.29 1.75 1.31

Sick 335 4.42 8.07 2.60 1.61

Symptom 610 10.18 14.58 1.52 1.90

Symptomatic 48 - 1.19 - 1.42

Transmission 211 3.10 5.07 1.29 1.52

Transmit 182 2.56 4.37 1.17 1.24

Viral 150 3.54 3.53 1.38 1.28

Virulence 37 0.88 0.87 1.00 1.11

Virus 1,956 29.65 46.93 1.84 2.58

War 1,311 17.70% 31.58% 1.93 2.18

Battle 188 3.54 4.47 1.00 1.17

Casualty 25 - 0.62 - 1.08

Combat 208 1.77 5.07 1.25 1.21

Conflict 43 - 1.07 - 1.09

Conquer 3 - 0.07 - 1.00

Defeat 53 0.44 1.29 2.00 1.19

Defend 46 0.44 1.12 1.00 1.22

Detain 21 - 0.52 - 1.57

Enemy 24 - 0.60 - 1.13

Fight 751 8.41 18.19 1.42 1.77

Fighter 7 - 0.17 - 1.00

ç

% of Articles

Mean

64

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Harbor 10 0.44 0.22 1.00 1.22

Ravage 95 0.44 2.34 1.00 1.04

Sacrifice 17 - 0.42 - 1.06

Security 267 3.10 6.46 1.43 1.31

Tackle 108 - 2.68 - 1.14

Terrorism 14 0.88 0.30 3.50 1.08

Terrorist 20 2.21 0.37 1.80 1.27

Triumph 6 0.44 0.12 1.00 1.00

Vanquish 4 - 0.10 - 1.25

Victory 9 - 0.22 - 1.00

War 97 1.77 2.31 1.25 1.47

“Othering” 1,279 23.01% 30.48% 2.35 3.27

African 397 3.10 9.69 1.57 1.55

Alien 7 - 0.17 - 1.43

Contain 366 5.31 8.80 1.58 1.59

Control 549 7.52 12.22 1.59 1.42

Distant 11 - 0.27 - 1.00

Exotic 8 0.44 0.17 2.00 1.00

Foreign 215 3.54 5.14 2.00 1.40

Isolate 461 5.75 11.13 2.31 1.76

Quarantine 355 1.77 8.72 1.00 2.39

Surveillance 129 5.31 2.91 1.08 1.83

ç

% of Articles

Mean

65

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Globalization 1,823 23.01% 44.00% 4.77 5.06

Airplane 22 0.88 0.50 1.00 1.15

Airport 471 3.98 11.48 1.89 2.09

Border 353 9.73 8.22 2.50 2.02

Bus 25 0.88 0.57 3.00 1.43

Entry 189 2.21 4.57 1.40 1.56

Flight 263 1.33 6.46 1.67 2.15

Global 394 1.33 9.71 1.33 1.48

Globe 33 0.44 0.80 1.00 1.03

Passenger 299 2.65 7.28 2.83 2.03

Port 135 1.77 3.25 1.25 1.79

Screen 296 5.75 7.03 2.62 2.37

Ship 63 - 1.57 - 1.87

Spread 1,051 12.83 25.39 1.90 1.82

Tourism 36 - 0.89 - 1.47

Tourist 12 0.44 0.27 1.00 1.18

Tourists 32 - 0.80 - 1.94

Trade 74 2.65 1.69 1.33 1.31

Travel 578 4.42 14.11 2.70 2.46

Visa 53 0.44 1.29 1.00 1.63

Visitor 79 0.88 1.91 1.50 1.60

World 590 6.64 14.29 1.80 1.57

ç

% of Articles

Mean

66

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Human Interest 1,796 38.94% 42.43% 4.33 5.07

Boy 64 0.88 1.54 1.00 2.00

Brother 49 0.44 1.19 1.00 1.65

Child 71 1.33 1.69 1.00 1.49

Children 186 3.98 4.40 3.33 1.81

Doctor 720 11.50 17.24 2.42 2.02

Emotion 26 - 0.65 - 1.35

Family 391 7.08 9.32 1.75 2.13

Father 69 0.44 1.69 3.00 1.59

Girl 70 - 1.74 - 2.01

Individual 89 - 2.21 - 1.19

Individuals 91 0.88 2.21 1.00 1.25

Man 325 3.10 7.90 1.71 1.66

Mother 102 1.33 2.46 2.00 2.11

Nurse 375 3.10 9.14 4.71 2.15

Nurses 370 4.42 8.94 3.60 1.69

Patient 1,156 23.45 27.40 2.77 2.76

Physician 119 1.33 2.88 1.33 1.34

Sister 71 0.44 1.74 3.00 1.53

Woman 158 5.31 3.63 1.42 1.92

Economic Consequences 908 11.06% 21.94% 2.08 3.32

Bought 12 - 0.30 - 1.17

ç

% of Articles

Mean

67

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Budget 59 0.44 1.44 1.00 1.48

Business 77 0.44 1.89 1.00 1.37

Businesses 18 - 0.45 - 1.11

Buy 40 0.88 0.94 1.00 1.26

Commerce 10 - 0.25 - 1.00

Commercial 38 - 0.94 - 1.24

Cost 168 0.88 4.12 1.00 1.42

Dollar 241 4.42 5.74 1.10 1.61

Donation 139 1.77 3.35 2.50 1.83

Economic 147 0.88 3.60 1.00 1.76

Economy 127 1.33 3.08 1.00 1.56

Employment 24 - 0.60 - 1.21

Euro 16 - 0.40 - 1.44

Finance 62 0.40 1.52 1.00 1.38

Financial 93 - 2.31 - 1.24

Fiscal 8 - 0.20 - 1.38

Fund 218 1.33 5.34 1.00 1.57

Industry 55 0.88 1.32 1.00 1.25

Investment 55 - 1.37 - 1.42

Market 115 0.88 2.81 1.00 1.73

Monetary 7 0.44 0.15 1.00 1.67

Money 165 1.77 4.00 1.25 1.39

ç

% of Articles

Mean

68

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Pay 99 1.33 2.39 1.67 1.24

Payment 10 0.44 0.22 1.00 1.22

Price 57 - 1.42 - 1.44

Retail 9 - 0.22 - 1.44

Attribution of Responsibility

406 5.31% 9.79% 1.50 1.49

Accountability 5 - 0.12 - 1.00

Accountable 4 - 0.10 - 1.00

Blame 80 0.44 1.96 1.00 1.15

Chaos 23 - 0.57 - 1.17

Chaotic 18 - 0.45 - 1.17

Complacency 27 0.44 0.65 1.00 1.15

Corruption 17 0.44 0.40 1.00 2.31

Delay 77 0.88 1.86 1.50 1.21

Fault 15 - 0.37 - 1.07

Guilt 4 - 0.10 - 1.50

Guilty 4 - 0.10 - 1.00

Inaction - - - - -

Inattention 1 - 0.02 - 1.00

Incompetent 20 - 0.50 - 1.15

Inept - - - - -

Ineptitude 2 - 0.05 - 1.00

Liable - - - - -

ç

% of Articles

Mean

69

Coding Frames

Total No. of Articles

2000

2014

2000

2014

Overconfidence 1 - 0.02 - 1.00

Passive 4 0.44 0.07 1.00 1.33

Procrastination - - - - -

Responsibilities 19 0.44 0.45 1.00 1.17

Responsibility 66 0.88 1.59 1.50 1.20

Responsible 77 1.77 1.81 1.00 1.07

Scepticism 2 - 0.05 - 1.50

Secrecy 2 - 0.05 - 1.00

Secret 17 0.44 0.40 1.00 1.25

Secretive 1 - 0.05 - 1.00

Secretly 4 0.88 0.05 1.00 1.50

Shortcoming 10 - 0.25 1.00 1.10

Skepticism 16 - 0.40 - 1.06

ç

% of Articles

Mean