Two outbreaks are unfolding in real time. A hantavirus case linked to a cruise ship appears to be winding down. Ebola cases continue climbing in Africa. Yet despite access to dashboards, trackers, maps, and live risk estimates, the public is asking the same questions it asked during Covid: what can I actually trust? How serious is this? What should I do?
The problem is not a shortage of data. It is that data no longer speaks for itself.
A decade ago, during the 2014 Ebola crisis, most Americans encountered that outbreak through journalists and public health officials who translated complex information into meaning. Experts provided crucial details, acknowledged what they did not know, and connected risk to action. By the time Covid arrived, those interpretive supports had already begun to weaken. Millions of people became direct consumers of Johns Hopkins dashboards receiving billions of daily requests. Social media became a machine for stripping numbers of context and rebroadcasting them as fact. The infrastructure for making sense of data has fractured further since.
The current outbreaks will pass. But researchers estimate a greater than one in five chance of another pandemic killing at least 25 million people within the next decade. Meanwhile, measles continues circulating across the US and globally, a disease so contagious that nine out of 10 unvaccinated exposed people will catch it. We have an effective vaccine. The real bottleneck is communication.
Containing the next outbreak will require managing the information environment alongside the virus itself. The United States has learned enough from recent failures to rebuild.
What fell apart
Deep cuts at the CDC, HHS, and NIH, plus the dismantling of USAID and withdrawal from the WHO, have weakened disease tracking and response systems. Less visible but equally damaging: the parallel collapse of communication capacity within federal health agencies and the hemorrhaging of local and national newsrooms. The newspaper industry has shed more than three quarters of its workforce over two decades.
As those channels eroded, people turned to social media feeds and AI-generated summaries for health information. Social media rewards certainty and simplicity, not the distinction between absolute and relative risk or the transmission dynamics of a novel pathogen. AI summaries often omit the caveats that separate meaningful statistics from misleading ones. The gap does more than enable conspiracy theories. It creates vacuum space where misinformation spreads.
During the early hantavirus outbreak, commonly cited death rates of 30 to 40 percent may have overstated the true risk because milder infections likely went undiagnosed. A radio station in the Democratic Republic of Congo, at the center of the Ebola outbreak, has begun dedicating daily programming to answering questions and combating rumors, betting that explanation beats authority.
How messaging gets twisted
Even accurate numbers can mislead depending on how they are framed. Some figures stripped context entirely. Early in the pandemic, some messengers cited data showing higher death rates among vaccinated versus unvaccinated people. What disappeared was the fact that older adults were both more likely to be vaccinated and more likely to die from Covid. Once broken down by age, the relationship reversed.
The WHO tweeted in January 2020 that Chinese authorities had found "no clear evidence of human-to-human transmission." Beneath that summary lay fuller statements acknowledging transmission was possible. The caveats evaporated once the tweet spread. When a CDC official described a cruise passenger as testing "mildly" positive for hantavirus, the phrasing muddled whether the test was inconclusive or whether the disease was mild. One social media commenter asked: "Is mildly positive like saying kinda pregnant?"
Technical language can trigger wrong associations. The WHO's designation of the current Ebola outbreak as a "public health emergency of international concern" generated headlines implying global danger. In reality, the label is a resource-mobilization tool. A sharp drop in official Ebola case counts in early June appeared to signal improvement but actually reflected a shift from suspected to confirmed cases. The outbreak had not become safer. Confirmed counts have since continued rising.
Geography vanishes from the narrative too. A region may hit vaccination thresholds for herd immunity on paper while unprotected pockets within it function as kindling, allowing viruses to spread between vulnerable clusters. Scientists believe this local variability is driving measles resurgence. That nuance rarely reaches the public, leaving people with false confidence.
Good risk communication helps people understand what response is proportionate to their actual danger: vaccination, symptom monitoring, distancing, or nothing at all. Covid showed what happens when officials translate uncertainty into rules without explaining the reasoning. In February 2020, the surgeon general tweeted "STOP BUYING MASKS" claiming they were ineffective. Two months later, the CDC recommended face coverings. People had already lost trust in the message and messenger.
The hantavirus response sent mixed signals. Officials insisted the virus required prolonged close contact to spread, yet placed some cruise ship passengers in quarantine while telling others to self-isolate at home. The inconsistency reflected genuine scientific uncertainty about whether the Andes strain could cross a room or whether people were contagious before symptoms appeared. But that uncertainty went largely unexplained. Instead, people saw arbitrary rules and drew their own conclusions.
Inconsistency appears incompetent. Research from Covid and earlier outbreaks linked greater trust in institutions, experts, and media with better adherence to public health guidance and lower anxiety.
What needs rebuilding
Restoring the capacity to guide people through outbreaks starts with investing in original reporting. AI systems rely on journalism to synthesize. Without strong reporting, they eventually have nothing of value to work with. Federal communication teams need rebuilding. The US withdrawal from the WHO cost more than position or pride. It reduced the world's primary effort to coordinate health messaging and its capacity to reach platforms like TikTok with public health content.
Scientists, doctors, and trusted voices can communicate directly with the public more aggressively. During Covid, researchers used social media to explain logarithmic scales and curve flattening. One study found that short videos by doctors and nurses ahead of winter holidays reduced travel and subsequent infections.
The best Covid dashboards specified confirmed cases and confirmed deaths, provided both absolute and relative counts, explained methods, and flagged anomalies. But even those could not control what happened when a figure hit a social feed. Framing determined what people understood and misunderstood. Acknowledging uncertainty up front and explaining technical terms before making revisions makes later changes look less like reversals.
As the US approaches 2026 with the World Cup coming and persistent measles circulating globally, the stakes are clear. We have the vaccine and the knowledge. We do not yet have the communication systems that turn knowledge into action.
Author James Rodriguez: "We learned in 2020 that raw information without context breeds confusion and distrust, yet we're repeating the same mistakes with fresh outbreaks."
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