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Held on March 5th<\/sup>, 2026, the panel discussion <\/a>brought together Dr. Osman Ahmed Dar<\/strong>, Senior Advisor at the Africa Centres for Disease Control and Prevention (Africa CDC) and member of the One Health High Level Expert Panel (OHHLEP), Prof. Wanda Markotter<\/strong>, Director of the Centre for Viral Zoonoses at the University of Pretoria and Co-Chair of the OHHLEP, Dr. Marc Leandri<\/strong>, Associate Professor of Economics at Universit\u00e9 Paris Saclay and researcher at UMI SOURCE-IRD, and Yoeri Booijink<\/strong>, One Health Economist at CIRAD. Dr. <\/strong>Christina Pettan-Brewer<\/strong>,<\/a> Global One Health leader at the University of Washington School of Medicine and member of the Steering Committee, moderated the panel. You can watch the replay<\/strong> of the panel discussion here<\/strong><\/a>.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n At the centre of the conversation was the need to move away from reactive models of disease control toward a more proactive approach. Primary prevention focuses on reducing the likelihood that pathogens ever spill over from animals to humans, rather than on detecting outbreaks early. This demands a One Health perspective, recognizing the deep interconnections between ecological systems, animal health, and human behaviour. As Wanda Markotter<\/a><\/strong> framed it, prevention is fundamentally about \u201cshifting disease control from reactive to proactive<\/em>\u201d, requiring attention to the environmental and social conditions that create opportunities for pathogens’ emergence in the first place. Early signals need to be connected to wildlife data, risk assessments, and sentinel surveillance sites. Deforestation, wildlife trade, agricultural intensification, and even consumer demand all shape these risks, often in ways that remain invisible to traditional health metrics.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n This raises a critical challenge: what should we measure? Conventional indicators \u2014 cases, hospitalizations, mortality \u2014 capture the consequences of failure, not the success of prevention. On the question of what indicator could make prevention both financially and politically sustainable, speakers offered complementary \u2014 if sometimes contrasting \u2014 answers. Wanda Markotter<\/strong> emphasized the foundational role of governance<\/strong>, pointing to “a strong and functional multisectoral One Health coordination system<\/em>” with high-level political backing as a prerequisite for any meaningful progress. Yoeri Booijink<\/strong><\/a> <\/strong>cautioned that \u201cprevention is too complex to be reduced to a single metric<\/em>\u201d. Marc Leandri<\/strong> <\/a>took a different angle, proposing to use monetary measures to combine ecological, epidemiological and economic dimensions into a single indicator, simple in principle, yet reflective of the broader ambition of One Health: To connect signals across systems and translate them into timely action. In order to be robust, such a cost-benefit analysis requires including also the specific costs of One Health coordination, to correctly assess the added value of an integrated prevention strategy.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n The question is not only how to design better indicators<\/strong>, but how to make them usable<\/strong>. The panellists cautioned against creating yet another layer of frameworks in an already crowded landscape. They advocated building on existing systems, such as international health regulations,<\/strong> including UN frameworks to report on climate indicators that can also feed into the space, and maybe do some kind of collective indicator while expanding them to better capture environmental and socioeconomic dimensions. At the same time, indicators must remain sensitive to context<\/strong>. As Osman<\/strong> Dar<\/strong><\/a> emphasized, \u201cWhat you need is a global core indicator set for comparability combined with context-specific indicators tailored to local ecosystems and local ecological drivers<\/em>\u201d.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n Yet, even with better indicators, the \u201cprevention paradox\u201d remains. When prevention works, there is no crisis to point to, no immediate evidence of impact. As Osman Dar<\/strong> noted, the solution lies in reframing what counts as success<\/strong>: \u201cRather than measuring outcomes, we need to measure changes in risk trajectory and system resilience<\/em>\u201d. This shift allows prevention to be understood not as the absence of disease, but as the active reduction of risk over time<\/strong>. Economic arguments play a powerful role in making this case. Estimates discussed during the webinar suggest that limited investments<\/strong> in primary prevention – on the order of tens of billions of dollars – could avert pandemic losses <\/strong>measured in the tens of trillions. Such figures point to 10,000 times returns on investment. As Marc Leandri<\/strong> observed, \u201cwhen you speak in dollars, people tend to listen<\/em>\u201d. \u201cThere is a need to give value to health in monetary terms<\/em>\u201d, added Yoeri Booijink<\/strong>. Still, translating these insights into policy is far from straightforward. Competing priorities and political realities often dominate decision-making. Against this backdrop, we need to get much better at measuring co-benefits \u2014 the gains for productivity, biodiversity, and climate that come alongside prevention. Doing so gives a fuller sense of the true value of preventing spillover, as Osman Dar<\/strong> underlined: “Co-benefits are interesting as a way to work around the prevention paradox, if not overcome it<\/em>“. Within a One Health philosophy, this calls for coherent governmental action: “We need to convince the Minister of Finance<\/em>\u201d observed Marc Leandri<\/strong>, to demonstrate that there is a plan to reduce what can be seen as a systemic risk<\/em>.”<\/p>\n\n\n\n We need to get much better at measuring co-benefits \u2014 the gains for productivity, biodiversity, and climate that come alongside prevention.<\/p>\n<\/blockquote>\n\n\n\n <\/p>\n\n\n\n Evidence alone is rarely sufficient. Prevention suffers from structural disadvantages: its benefits are long-term and diffuse, while its costs are immediate and borne by specific sectors. Political cycles favour visible infrastructure over crisis avoidance. Funding decisions are shaped not only by need but also by power dynamics and donor priorities. In some cases, countries may prioritize diseases not because they are most urgent locally, but because they align with external funding streams. As Osman Dar<\/strong> phrased it, \u201cthis may sound cynical, but funders and decision-makers tend to focus on threats within their own jurisdiction rather than those emerging elsewhere in the world<\/em>\u201d.<\/p>\n\n\n\n Public health is a matter of continuous education: historical outbreaks must remain alive in the memory of society, but also of policymakers and funders, so that the importance of prevention is not lost.<\/p>\n<\/blockquote>\n\n\n\n The immediate aftermath of a pandemic is still fresh in everyone’s mind, but after a few months or a couple of years, it is forgotten. Public health is a matter of continuous education: historical outbreaks must remain alive in the memory of society, but also of policymakers and funders, so that the importance of prevention is not lost. Drawing on the example of military preparation, Osman Dar<\/strong> explained that a strong military, seen as a deterrent to war, is itself a form of prevention of armed conflict. It is an accepted reality that the stronger it is, the less likely we are to end up in a war. The same concept must apply to pandemic and zoonosis prevention. This links to the cost of inaction. “We have the option to do nothing, but we need to understand the consequences,<\/em>” noted Yoeri<\/strong> Booijink<\/strong>.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n Together, these contributions point to a shared conclusion: prevention is a systemic endeavour that requires integrating quantitative data with qualitative understanding, and scientific evidence with political strategy. A broader set of operational indicators that track changes in risk drivers, system resilience, and human behaviour \u2014 including ecological signals, such as habitat loss; animal health indicators, such as pathogen circulation in wildlife; and governance measures, such as the strength of cross-sectoral coordination.<\/p>\n\n\n\n In the end, making prevention visible is not just a technical challenge, but a societal one. It requires rethinking what we value, how we measure progress, and how we communicate success. Or, as one speaker implied, learning to see \u201cnothing happening\u201d not as a failure of evidence, but as the clearest sign that prevention is working.<\/p>\n","protected":false},"excerpt":{"rendered":"Shifting from reaction to prevention<\/strong><\/h3>\n\n\n\n
Measuring what matters<\/strong><\/h3>\n\n\n\n
Field realities<\/strong><\/h3>\n\n\n\n
Overcome the prevention paradox<\/strong><\/h3>\n\n\n\n
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Make prevention a cultural norm<\/strong><\/h3>\n\n\n\n
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Valuing the absence of crisis<\/strong><\/h3>\n\n\n\n