As a science journalist working in Africa, one of my greatest preoccupations for more than two decades has been the unglamorous task of turning dreary scientific findings into simple vignettes accessible to ordinary mortals.
The nature of that task has changed dramatically over the years, as science becomes more interconnected and development challenges demand more vigorous responses.
The story that broke this past week of Kenyan scientist Dr Samuel Oyola winning a Sh187 million grant to help predict disease outbreaks is a powerful signpost of the kind of future the continent can build if seemingly complex scientific knowledge is allowed to travel beyond laboratories, journals and conference rooms into the places where public decisions are made.
The grant is aimed at using data and artificial intelligence to anticipate disease outbreaks before they overwhelm communities. This is because every epidemiologist knows that outbreaks rarely begin as national emergencies, but as scattered signals, and by the time the public sees and feels the crisis, scientists may have long been seeing the writing on the wall, with varying degrees of clarity.
In reality, Dr Oyola, who is a senior scientist and head of genomic science at the International Livestock Research Institute (ILRI), is grappling with one of the most uncomfortable truths about evidence that informs public policy; the need to act before absolute certainty is established. That has always been one of science’s greatest paradoxes: by the time every doubt has been eliminated, the opportunity to prevent harm may already have passed.
Public health interventions
That dilemma is often best illustrated in the story of English physician John Snow, who in 1854 made one of the most consequential public health interventions in modern history when he traced the source of a cholera outbreak in London to a particular public water pump on the city’s Broad Street. In those days, the dominant belief was that cholera spread through what was vaguely termed as “bad air”. Furthermore, the phenomenon that scientists now refer to as the germ theory of disease had not yet been established.
Snow himself could not explain the biological mechanism by which the disease spread. But by painstakingly mapping cases, interviewing residents and following the emerging pattern, Snow carefully assembled compelling circumstantial evidence that persuaded local authorities to remove the pump handle, effectively halting the outbreak. His achievement was not merely identifying the source of cholera; it was demonstrating that public decisions sometimes have to make do with convincing patterns long before science can offer complete explanations.
Dr Oyola and his team will be embarking on a somewhat similar mission, albeit in a different context. In the design of the study, the team will draw wastewater from 30 sites, run it through AI-enabled genomic sequencing and machine learning, and try to flag outbreaks and drug-resistant pathogens before hospitals can see them. In ordinary parlance it can be called an early warning system.
This is no doubt an exciting new frontier in predictive medicine, and absolutely deserving of the glowing reviews it continues to receive. But for science journalists seeking to explain what is really going on, this is only the beginning of the story. Every scientific breakthrough carries with it a second question that is often less obvious, but ultimately just as important: who will benefit first, and who might be left behind?
First, the selection of the sites to be studied is not random. The sample locations will be in Kisumu and Mombasa, partly because these cities have some of Kenya’s more developed sewer connections, alongside Nairobi, which already had a similar project. That is a practical choice any researcher has to make, but in the bigger scheme of things it also raises the question of whether a small town with no sewerage system could ever benefit from such a novel study.
Scientific knowledge never emerges out of a vacuum, but from systems of observation which inevitably have limits. A surveillance study based on a piped sewerage system will always see the plumbed first, and the unplumbed last, if at all. In that sense, infrastructure does more than transport wastewater; it quietly determines whose risks become visible and whose remain statistically invisible.
This is where journalism’s job extends beyond simply reporting the grant, even when it is tempting to do so. It is to ask who the surveillance sees and who it misses, who wrote the safeguards and who was merely consulted. Our responsibility is to follow scientific knowledge all the way from the laboratory to legislation, asking not only whether a scientific finding or innovation works, but who it works for, who remains invisible to it, and who answers when its warnings go unheeded.
That job also requires us to connect ideas and breakthroughs across generations to draw useful lessons. John Snow’s map changed history because it made an invisible pattern visible. Dr Oyola’s work seeks to do the same, this time, with genomic data. It deserves every accolade it has received so far. To that extent, science has done what it does best, the next challenge now belongs to society; to ensure that the systems we build make every community visible enough to benefit from scientific advances.
In this age of fast-evolving scientific development, Africa will no doubt need to develop more predictive technologies, at scale and in every field. But just as urgently, it will need to ensure that the public infrastructure and institutions surrounding these novel discoveries are just as innovative and inclusive. Otherwise, the communities most vulnerable to tomorrow’s outbreaks may remain the last to appear on tomorrow’s public health map.
Dr Ageyo is the Editor in Chief of the Nation Media Group. He holds a PhD in media studies with a focus on language use in science and environment communication
