Rethinking Dengue Surveillance in Bangladesh
Published in Social Sciences, Microbiology, and Public Health
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Evaluating surveillance systems to understand dengue burden in Bangladesh: a narrative review
Dengue has long been a familiar public health threat in Bangladesh, but the scale and severity of recent outbreaks have been unprecedented. When Bangladesh experienced its deadliest dengue outbreak in 2023, with over 320,000 reported cases and more than 1,700 deaths, it became clear that traditional ways of understanding and responding to dengue transmission were no longer sufficient. This moment prompted us to step back and ask a fundamental question: how well do existing dengue surveillance systems in Bangladesh actually capture the evolving burden of disease—and where are the gaps?
This narrative review emerged from that question. Rather than focusing on a single dataset or method, we set out to synthesize what is already known about dengue surveillance in Bangladesh across multiple approaches, including passive and active surveillance, community-based systems, early warning tools, forecasting, and predictive modeling. Our goal was not only to catalog these systems, but also to understand how they function together—or, in many cases, fail to do so.
As we reviewed the literature, one of the most striking findings was the fragmentation of dengue surveillance efforts. Hospital-based passive surveillance provides nationwide coverage and remains the backbone of reporting, yet it is vulnerable to underreporting and delays. Community-based and active surveillance approaches often offer earlier signals of transmission but are rarely integrated into national systems. Forecasting and predictive models show promise for anticipatory outbreak detection, but they depend heavily on the quality and consistency of routine surveillance data and are seldom linked to real-time public health decision-making.
Another unexpected observation was the lack of standardized definitions. Across the studies we reviewed, very few clearly defined what constitutes a dengue outbreak, and only one explicitly referenced a dengue case definition. This absence complicates comparisons across studies and surveillance systems and underscores the need for greater standardization to improve interpretability and response.
Conducting this review also highlighted the importance of thinking about surveillance not as a single tool, but as a system—one that depends on governance, data integration, service delivery, and coordination across sectors. Drawing on the WHO Health System Building Blocks framework helped us situate surveillance within a broader health system context and identify where integration could be strengthened.
We hope this review contributes to ongoing conversations about how dengue surveillance can evolve in Bangladesh and similar high-burden, resource-constrained settings. More cohesive, mixed surveillance approaches—combining routine reporting, community-level data, and predictive analytics—have the potential to support earlier detection, better preparedness, and more timely response. Ultimately, strengthening surveillance is not just about better data; it is about enabling public health action that can save lives.
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