Attention to Ebola is important. The virus’s ability to easily cross regional and national borders makes it a significant threat to global health and national security. The swift and aggressive international response to the 2014 outbreak of the Ebola virus, which has killed at least 10,000 people in Liberia, Sierra Leone, and Guinea, has been laudable and has resulted in positive outcomes, such as reduced disease transmission and strengthened global health and coordination systems.
For example, staff from the Centers for Disease Control and Prevention in the United States, including those from various divisions at the National Center for Chronic Disease Prevention and Health Promotion, have put in more than 40,000 work days on the 2014 Ebola response in many parts of West Africa — a truly successful and important horizontal approach to global health.
But what about other silent pandemics that kill slowly, but surely — pandemics like non-communicable diseases that also spread through networks, and which in 2010 caused two-thirds of deaths and 54 percent of disability-adjusted life years worldwide?
We first posed this question in 2009, in the context of the H1N1 (or “swine flu”) pandemic. In light of its presentation as a public health emergency of uncertain scope, duration, and effect, the H1N1 pandemic generated a similarly rapid international response and media attention as Ebola is doing now. Curious about how the global spread and response to H1N1 compared to diabetes, a relatively neglected non-communicable disease, we calculated the numbers of cases and fatalities (spread) and media attention and resource allocation (response) for each.
We used publicly available data from the World Health Organization’s (WHO) Global Alert and Response system and the International Diabetes Federation to tabulate cases of, and deaths from, H1N1, and diabetes, respectively. We focused specifically on cases and deaths occurring between April 24 and July 6, 2009 (the first 73 days of the H1N1 pandemic) in countries reporting the most H1N1 deaths at the time: United States, Mexico, Canada, and Argentina.
Next, we used Google Trends to compare media attention for the search terms “swine flu” and “diabetes” since January 2009, three months before the start of the H1N1 pandemic. To do this, we examined search volume (how often information is publicly searched online relative to all search traffic) and news reference volume (number of times the topic has appeared in Google News stories). Where data were available, we compared national budgets for H1N1 and diabetes.
H1N1 Garnered More Attention And More Money
Our main findings are shown in Figures 1 and 2. During the 73-day comparison period, diabetes outweighed H1N1 in numbers of cases and deaths. In the four countries analyzed, nearly twice as many diabetes cases as H1N1 cases emerged, and H1N1 killed 374 individuals, while diabetes killed over 49,000. Globally, H1N1 killed 429 individuals while diabetes killed an estimated 600,000-800,000.
Figure 2 shows relatively stable media attention (represented by news reference volume) and public attention (represented by search volume index) to diabetes, contrasting with variable levels of media and public attention to H1N1 during the pandemic. Initially, public attention to H1N1 spiked to 25 times that of diabetes.
While diabetes outweighed H1N1 in absolute numbers of cases and deaths, the immediate threat of H1N1—similar to the Ebola virus—mobilized resources rapidly, with one-time budgets much larger than those for multiple years of ongoing diabetes control. Congress allocated $7.65 billion to address H1N1 over the course of the pandemic, while according to Department of Health and Human Services budgets, Congress allocates $61-66 million annually for diabetes surveillance, education, and control.
From 2006-2009, Canada invested $1 billion in pandemic preparedness, and in June 2009 the government announced an additional $10.8 million to fight H1N1. In 2005, the Canadian federal government committed $18 million annually for five years to a diabetes control strategy. (Data were not available for Mexico and Argentina.)
How Does A Global Health Issue Become A Priority?
We believe the following factors influence, and ultimately determine, which global health issues become priorities.
Immediacy
The speed of a disease’s spread appears to trump disease burden. The Ebola and H1N1 viruses spread quickly and extensively over the course of a few months, and efforts to control them were thus rapid. In contrast, the diabetes pandemic has progressed less quickly over the course of three decades, and effective efforts to curb it are largely lacking in many countries.
People often make “time-inconsistent” decisions, giving more weight to issues that are potentially less serious, because their impact will be felt in the immediate future; people don’t excel at planning and making decisions for the longer term — ongoing issues often do not register as “news,” either in the media or as one of an individual’s own priorities. Similarly, governments are more likely to prioritize immediate health threats—partly because of the short-term nature of the political cycle—and politicians may fear contracting the virus themselves and how this might impact the functioning of their cabinets.
Simplicity
Diseases that can be addressed through seemingly simple, short-term solutions (such as vaccines) are prioritized over those that involve complex long-term interventions. On April 25, a month after the first H1N1 cases were identified, WHO classified H1N1’s spread as a public health emergency of international concern. In May, Director-General Chan held a high-level consultation in Geneva at the Sixty-Second World Health Assembly, where Member States discussed the outbreak, shared experiences, and highlighted challenges.
The World Health Organization published near-daily updates on the spread of the virus and held multiple International Health Regulations Emergency Committee meetings and high-level consultations. Effective communication between stakeholders has helped to sustain a cohesive global response. The response was worthwhile; countries reported declines in transmission, and a vaccine was available seven months after the start of the pandemic.
In contrast, although 60 percent of type 2 diabetes could be prevented by eating a healthy diet and increasing physical activity, addressing these risk factors requires complex behavioral and societal action, and these interventions are not yet effectively translated to populations, more than three decades into the epidemic.
Headlines
So that they will be seen as addressing the immediate concerns of their constituents, policymakers tend to focus on what is most prominently featured in media coverage. The media, on the other hand, exploit the “scare factor,” focusing on dramatic issues such as natural disasters, bio-terrorism threats, emerging virulent pandemics, and other shock-inducing crises, to increase their market share.
The availability bias, which states that an issue’s perceived importance may increase simply because it’s discussed more frequently, plays a large role in prioritization of issues, and the public’s increased attention to issues may be sustained long after media blitzes fade, as Figure 2 illustrates.
Next Steps
A recent New York Times editorial reminds us that diseases like Ebola may not actually be that different from diabetes: in 1982, an article by European researchers in Annals of Virology noted that, “The results seem to indicate that Liberia has to be included in the Ebola virus endemic zone…..[and in the future] medical personnel in Liberian health centers should be aware of the possibility that they may come across active cases and thus be prepared to avoid nosocomial epidemics,” referring to hospital-acquired infection.
But, according to the authors of The New York Times editorial, no senior officials in Liberia—nor in the international agencies now helping the Ebola response—had heard of the studies’ findings, and the ill-prepared hospitals and clinics may have helped to contribute to, rather than control, the 2014 outbreak. No action was taken until Ebola became a major threat.
The global policy lens remains biased towards short-term, dramatic priorities. However, there is a crucial need to take steps to make global health resources and attention more proportionate to current and future disease burdens. The extraordinary response to H1N1 in 2009, and to Ebola in 2014, show what governments and global collaboration can do when faced with a serious health threat.
In addition to the necessary short-term view of threat, policymakers, public health decision makers, and researchers should be encouraged to think more about potential for greater long-term harm to societies down the road and to enhance research to better quantify proportionate risks, as well as to invest in translational research to get important research findings into the hands of global health practitioners.
An increasingly horizontal, health systems-wide approach may have wide-reaching effects for global health improvement. For example, H1N1 and Ebola disproportionately and more severely affect individuals with chronic, underlying medical conditions; addressing the risk factors for chronic diseases may also help to mitigate the effects of infectious diseases. Increased investment, planning, and translating research findings into action for reducing diabetes and other chronic diseases should begin without delay.
Figure 1
Source: Reported new H1N1 cases and deaths are from the World Health Organisation Pandemic (H1N1) 2009 Situation updates. Estimated new diabetes cases are based on prevalence data and estimated diabetes deaths are based on mortality data from the International Diabetes Federation Diabetes e-atlas 3rd edition 2009.
Figure 2
Source: Google Trends results obtained on August 18, 2009. All results are normalised. Data for Search Volume index is scaled to the average search traffic for the “diabetes” term (represented as 1.0) during the time period represented. Numbers on the y-axis do not reflect actual search traffic numbers; all numbers are relative to total traffic. Data for news reference volume is not scaled and simply shows the number of times the topic has appeared in Google News stories.