Case Study

Dengue Chat

What problem were they solving?

As climate change lengthens the mosquito season, the geographical range of the mosquito is expanding to new regions and re-emerging in areas where mosquito numbers had subsided for decades. To control dengue and other arboviruses, elimination of potential breeding grounds where the transmitting mosquito reproduces is needed. This is a task generally assigned to the local government. But the water hatcheries which are potential breeding grounds are mostly in the homes of residents, and are clean water storage containers, or small containers that escape government chemical control. The challenge is to motivate residents in affected locations to take action.

What did they do?

DengueChat is an interactive web and mobile platform that combines mobile technology, data collection, reporting, analysis, pedagogic information and game concepts to motivate communities to participate in dengue vector control. DengueChat (a) crowdsources the identification and mapping of vector breeding sites; (b) motivates communities to act; (c) embodies a user-centered and collaborative model of software design; (d) promotes civic engagement; and (e) involves residents in public health education. DengueChat was developed through participatory technology design involving young user-residents in Brazil, Mexico and Nicaragua. DengueChat crowdsources the identification of breeding sites through photographic evidence, generating data that appear on the website. The web interface is interactive, allowing residents to create their own profiles and blogs and to exchange information regarding dengue and chikungunya in their neighborhoods. Also teams of volunteer youth brigades deploy DengueChat under the supervision of a project facilitator. Through the brigades, young people earn badges and points for their efforts in identifying and eliminating breeding sites.

What was the benefit of using collective intelligence for this issue?

During an 18-month pilot study in Managua, Nicaragua, DengueChat was found to reduce the mosquito transmission for dengue, chikungunya, and Zika by 90 percent in five intervention neighborhoods, while it increased by over 400 percent in five control neighborhoods (where DengueChat was not used). DengueChat’s innovative approach to community-based vector control has scaled to other countries since its initial pilot.

What does this experience tell us about collective intelligence for climate action?

Combining community-led data collection, preventative actions by local residents and government programs is an effective way to stem the tide of disease transmission without the use of toxic chemicals. DengueChat engages community members who are affected by the disease, as they are often the best sources of information about active and potential mosquito breeding sites. This helps to build trust between residents and institutions when public officials commit to interventions based on data collected through the project. Residents are also empowered to mitigate against the spread of disease themselves as data about transmissions are shared with them directly.

CLIMATE ACTION GAPS ADDRESSEDData Gap, Doing Gap
COLLECTIVE INTELLIGENCE USE CASEAnticipatory Monitoring And Adapting To Systemic Risk
IPCC CATEGORYAdaptation, Cross Sectoral, Health And Health Systems Adaptation
COUNTRIESBrazil, Mexico, Nicaragua
COLLECTIVE INTELLIGENCE METHODSCrowdsourcing, GIS, Gamification
PEOPLELocal Community, Young People
DATACrowdsourced Observations, Citizen-Generated Data
TECHNOLOGYApp, Platform