NLT Partners with UC San Diego to Develop a Dynamic Infectious Disease Risk Platform

Dengue fever is one of the most common and rapidly spreading vector-borne viral diseases, with major public health and economic consequences, particularly in tropical and subtropical regions. According to the World Health Organization (WHO), the global burden of Dengue increased eightfold over the last two decades, due in part to climate change and anthropogenic activities. With almost half of the world’s population living in areas with a risk of Dengue fever and with its increasing spread, there is an overwhelming need for near real-time prediction and effective monitoring of Dengue transmission rates and the ability to estimate the public health resources required for disease prevention and treatment.

UC San Diego School of Global Policy and Strategy faculty member Gordon McCord is partnering with NLT to develop an online data analytics platform to support decision makers with spatial and temporal patterns of existing and forecasted Dengue fever outbreaks. The project is funded for five years by the Wellcome Trust. This online, publicly accessible platform, will offer a geospatial display, tabular data and summary statistics of predicted, current and historical Dengue fever cases generated first in Latin America and potentially expanded to other regions and countries. The platform will be designed to influence climate-focused policy change and to generate data that can provide health services preemptive warning of a likely imminent spike in disease incidence rate and critical information necessary for proactive resource allocation towards prevention or monitoring/testing and treatment. With the development of the platform, the team will work hand in hand with public health officials and provide training and assistance to ensure its successful implementation and use for decision-making based on dynamic risk mapping.

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According to NLT`s Chief Scientist, Dr. Ran Goldblatt, who will co-lead this study, the platform will advance the state-of-the-art of climate services for the public health sector, not only by highlighting the key climate factors responsible for triggering disease transmission, but also by providing near-real-time predictions of potential hotspots of outbreaks of Dengue fever incidents. “Our hope is that this platform will influence positive climate-focused policy change by the governing administrative body of the affected areas,” said Goldblatt.

The envisaged platform will rely on a novel climatological-socio-economic ensemble AI model developed by UNICEF and the European Space Agency (ESA) which utilizes climate factors accessed via satellite data from Google Earth Engine and The Copernicus Climate Change Service. According to Prof. Gordon McCord, Associate Dean at the UC, San Diego School of Global Policy and Strategy, the ability to leverage scalable AI models to predict outbreaks of infectious diseases such as Dengue, their distribution across space and time and their potential impacts particularly upon vulnerable populations and children, would give governing bodies of at-risk geographic regions access to critical information to preemptively distribute resources for transmission reduction and for patient care.

According to UC San Diego doctoral student Gabriel Carrasco-Escobar, the platform will also provide key insights for preventive decision making. “It is critical that in addition to predicting and tracking Dengue outbreaks, we also provide health program needs (commodities, personnel) and projected costs based on disease risk projections in order to assist decision-making of prevention and control interventions,” said Carrasco.

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