Effective Preparedness and Response to Dengue Through Multisectoral Coordination

Cases of dengue fever in Brazil have risen steadily over time, with 2.9 million cases accounting for 60% of global incidence in 2023. At the local level, urban cities such as Rio de Janeiro are disproportionately burdened by dengue due to a combination of infrastructural, geographic, and socioeconomic vulnerability.

Impermeable building materials, for example, cause the runoff and collection of water in stagnant pools. Similarly, the trapping of heat and humidity across urban infrastructure, make cities ideal breeding spots for Aedes aegypti mosquitoes, as carriers of dengue fever. Compounding this, high population densities and poor sanitation networks in favelas have amplified cases amongst Rio’s most vulnerable.

In July and August of 2023, Brazil’s year-round epidemiological monitoring system registered a small, but above-expected change in dengue cases for the season. A myriad of factors including climate change, rapid urbanization, and poor sanitation infrastructure have contributed to this rise, in turn increasing the pressure on local health systems. From December 2023 onwards, a sustained rise in cases triggered the elevation of dengue response, with the initiation of the Dengue Emergency Operations Center (COE Dengue) in January of 2024, to intensify control measures and install care centers. 58 days later, the declared public health emergency was concluded, with the city observing the lowest lethality rate over the past four dengue epidemics. 

While disaster response has been traditionally siloed, the emergence of joint climate-health risks has spotlighted the need for new forms of cross-sectoral partnership. Aware of this issue, Rio’s Health Surveillance Superintendence (SVS) has made a concerted effort to integrate multisectoral collaboration into city-wide dengue management, drawing on the expertise of the Operations and Resilience Center (COR) and other partners.  Through the strategic integration of entomological, meteorological, and geographic data, the team was able to predict a spike in dengue cases two months earlier than forecasted by traditional epidemiological models alone. Feeding this information back into a centralized data unit allowed responders to deploy resources and identify potential hotspots before their emergence. Leveraging the complementary skills of key response partners, the city was able to manage dengue outbreaks in a dynamic and responsive manner.

 

Key learning: Fostering multisectoral coordination through dialogue, standard operating procedures, and cross-team training

The SVS brought together a multidisciplinary team, comprised of experts in entomology, meteorology, geography, and urban planning who, much like pieces of a jigsaw, brought complementary skillsets. SVS provided crucial epidemiological and IT expertise, with a cross-disciplinary team of doctors, nurses, veterinarians, and geographers responsible for entomological modelling and analysis. An IT sub-unit provided programming support and maintains the data management infrastructure, with automated risk modelling further streamlining the process of data collection and visualization. Underwriting this partnership was the transfer of skills and knowledge across teams, with the epidemiological team taking courses in climate risk, and the IT team receiving foundational epidemiological training.

Supplementing this, COR acted as a major intelligence and operations hub for the city. During the epidemic, it drew on its large-scale emergency management capabilities to building georeferencing tools to track the spread of dengue. COR’s geographers work to geocode hotspots and set over 2,000 mosquito egg traps for further entomological research. Through engaging with communities in favelas, teams often managed to geocode 90% of cases within just a few days of their incidence. A risk communication wing further engaged local communities in data collection and health education. Importantly, COR served as a major interface between climate and other sectors, drawing on its powers of integration between agencies.

While practitioners note the challenge of integrating multiple streams of data – demographic, entomological, and climatic - over multiple timeframes, interorganizational dialogue proved invaluable. The convening power of local leadership was similarly critical, with Rio’s mayor facilitating collaboration between teams. Bringing these actors together in a centralized Operations Center facilitated an in-house response coordinated in real-time, thus overcoming key barriers to collaboration including poor interoperability and institutional fragmentation.

Reinforcing this, collective action was streamlined under the 2024-2025 Municipal Contingency Plan for Arboviruses, developed by SVS in agreement with all technical areas of the Municipal Health Secretariat. This Plan acted as a standard operating guide for all involved parties, maximizing effectiveness and minimizing delays in response. Operations are also convened under the specific city Summer Plan, which focused on specific responsibilities for each agency in response to seasonal concerns such as heavy rainfall.

Key learning: Creating robust data collection and management processes

The success of SVS’s multisectoral coordination stemmed, in large part, from a robust, city-wide data collection methodology, critical in the identification and georeferencing of breeding sites. Through a shared platform, SVS was able to access climate data from COR to layer on top of epidemiological modelling. Weather station data from the municipal Alerta Rio network, the Air Force Meteorology Network (REDMET), and the National Institute of Meteorology (INMET) was automatically extracted, and meteorological models were integrated to generate heatwave alerts. This extensive range of data is inserted into the Data Lake of the Epidemiological Intelligence Center of the Health Surveillance Superintendence (CIE/SVS/SMS-Rio).

Further, dengue cases were systematically georeferenced for spatial distribution analysis by the Geographical Information Advisory of the SVS. 2,656 traps across the city collected and evaluated monthly entomological surveillance data. A kernel map, produced based on this data, indicated priority areas for vector control and elimination. All these analyses are integrated into the GeoArbo monitoring tool, accessible to a range of practitioners to inform response actions.

The geolocation of human cases indicated priority areas for the creation of dengue care centers, in addition to strengthening healthcare and laboratory surveillance actions in these areas. It also enabled intersectoral actions in communication, health promotion, and vector control.

The models provided a four-week action opportunity. Statistical modeling for alerts and predictive modeling based on real-time collected healthcare data supported the preparation and response of the emergency and primary healthcare network, enabling timely tracking of trend changes, case increases in certain localities, and adequate resource allocation for effective interventions, ensuring more efficient and targeted health service management.