What if the fight against malaria could shift from guesswork to hard evidence? Across Africa, a new wave of statisticians is using advanced data methods to uncover what truly drives people to adopt life-saving malaria prevention practices. And this is where things start to get really interesting—with evidence that could reshape how we think about public health campaigns.
At the University of the Witwatersrand, researcher Edson Mwebesa—Fellow at the Sub-Saharan Africa Advanced Consortium for Biostatistics (SSACAB)—has seen firsthand the devastating toll of malaria. He’s met children who lost their lives due to late diagnoses and discovered through his work that malaria disproportionately affects pregnant women in Uganda. Malaria remains endemic across Africa, affecting health, livelihoods, and economic growth.
Driven by the question of why people choose certain malaria prevention strategies, Mwebesa turned his focus toward the subtle yet powerful role of social and behavioral change messaging. These are the health communication efforts encouraging the use of insecticide-treated nets (ITNs). But here’s the challenge: while countless campaigns promote ITNs through schools, hospitals, and media outlets, no one really knew whether these messages changed behavior—or simply raised awareness.
That’s where Mwebesa’s innovative use of biostatistics comes in. Applying a quasi-experimental causal inference technique known as Propensity Score Matching (PSM), he sought to separate mere correlation from true cause-and-effect. Unlike traditional approaches that just compare how many people heard messages and used nets, PSM controls for factors like income, education, and location. This allows researchers to ask a more meaningful question: Did the message itself drive action, or were these people already more likely to use nets?
This issue is more than academic—it’s practical and political. Policymakers invest heavily in communication campaigns, but if the data only show correlations, how can they know what’s working? As Mwebesa explains, those who hear malaria messages are often wealthier or better educated, and those characteristics alone can boost ITN use. Without controlling for these differences, leaders risk misallocating resources.
Using nationally representative data from Uganda’s 2018–2019 Malaria Indicator Survey, Mwebesa explored the real impact of malaria messaging. Among Ugandan women aged 15–49, about 37.6% had been exposed to malaria prevention messages in the six months before the survey. Similarly, 37.9% of caregivers for children under five had heard or seen such messages. Net use was high but far from universal: around 69.3% of women and 71.8% of children slept under an ITN the night before the survey.
Mwebesa’s statistical approach compared women who had received malaria messages with others who had similar characteristics but had not received them. The results were telling: exposure to malaria communication increased the likelihood of ITN use among women by 5.1% and among children by 4.3%. That might sound small, but on a national scale, it represents tens of thousands of families protected from infection.
So, what’s actually working? Radio remains the most powerful communication channel, reaching about two-thirds of women and caregivers. Interpersonal conversations and community health worker visits also proved influential. However, digital communication remains vastly underused—an eye-opener in an era of growing internet access across Africa. Could social media or mobile apps soon become the next frontier for malaria communication?
To understand the significance of this breakthrough, consider the past. In 2001, economists John Luke Gallup and Jeffrey Sachs, in their influential work The Intolerable Burden of Malaria, lamented that reliable malaria data were missing in many affected nations. They had to rely on indirect estimates based on population and risk maps—insightful but highly constrained. They couldn’t measure how behaviors or prevention messages shaped outcomes.
Mwebesa’s generation faces a very different reality. Today’s researchers have access to repeated Malaria Indicator Surveys, geocoded data, expanded health records, and nation-wide surveillance systems. More importantly, Africa now has scientists trained to wield these tools confidently. As Mwebesa notes, “We’re finally able to analyze local data using modern causal methods, allowing us to measure impact instead of just describing problems.”
Professor Tobias Chirwa, Head of the Wits School of Public Health and Principal Investigator for SSACAB, believes this milestone represents a turning point for the continent. By strengthening Africa’s statistical capacity, he argues, researchers are achieving data independence—producing locally grounded, high-quality evidence that can guide national policies with precision and trust.
This transformation also ties into the 2025 theme for African Statistics Day: leveraging data innovation to build a just, prosperous, and inclusive society. In malaria prevention, that message hits home. Through studies like Mwebesa’s, Africa isn’t just receiving health guidance—it’s generating it.
So here’s the thought-provoking question: As Africa gains the power to produce its own causal evidence, will global health agencies finally begin deferring to African-led data instead of imposing external frameworks? The answers—and the debates—will shape not just malaria control, but the future of evidence-based public health across the continent.
