Integrating and scaling seasonal climate-driven dengue forecasting
Lead Research Organisation:
HR Wallingford
Department Name: Water Management
Abstract
Outbreaks of climate sensitive diseases present a major growing threat to human health, but they are predictable and maybe even preventable. The mosquito transmitted disease dengue is one of the fastest growing global infectious diseases and now causes over 400 million annual cases globally. Dengue is becoming the primary acute infectious disease threat in countries such as Vietnam and Malaysia. Between 2017 and 2019, Vietnam averaged over 200,000 cases every year and in Malaysia dengue fever has the highest incidence rate among any other communicable disease (398 cases per 100,000).
Dengue outbreaks are preventable with existing interventions, but only if they are used in the right places at the right times. The ability to forecast disease outbreaks months in advance can reduce the burden on health services. This is important in resource-constrained Low and Middle Income Countries (LMICs) where they can make the difference between an effective and efficient proactive response compared to a costly and often unsuccessful reactive response. We aim to demonstrate the value of disease forecasting via a local level dengue forecasting system in Vietnam and Malaysia, which will pave the way for scale up of dengue forecasting and other digital health solutions for climate sensitive diseases.
We have developed the necessary disease forecasting techniques as part of the Dengue forecasting MOdel Satellite-based System (D-MOSS) project. Although this system has been operational since July 2019 in Vietnam and July 2020 in Malaysia, more work is needed to bridge the implementation gap to ensure forecasts have direct actionable and measurable impacts on preventing outbreaks at a local level.
Further research is required to establish if the forecasting techniques already in operation are capable of producing accurate forecasts at the required spatial and temporal resolutions, tailored to the practices applied by specific sectors of the health system. We will test this by co-developing new forecasts that provide advance predictions in Vietnam and Malaysia. Through a series of longitudinal workshops we will develop risk assessment protocols that link forecasts to outbreak prevention activities at different sectors of the Vietnamese and Malaysian health systems.
These knowledge gaps will be addressed by a multidisciplinary team of dengue experts, modellers, public health experts, software engineers and early warning systems experts from multiple institutes in Vietnam, Malaysia and the UK. Training and co-design of the research is central to all aspects of our proposal and we intend to leverage the equitable partnerships established as part of the D-MOSS project to meet our aims. Cross-cutting activities will compare and contrast the operational context in these countries and enable collaboration between them with the goal of deriving generalisable principles and specific guidelines for expansion to other countries.
This research will demonstrate clear health value against dengue and other Aedes mosquito-borne diseases (e.g. chikungunya, Zika) in Vietnam and Malaysia, and a plan for how the intervention will be scaled up to other LMICs currently struggling to address the growing threat of dengue and other climate-sensitive diseases. In the longer term, this project will provide evidence on the value of forecasting to health systems for a wide range of health conditions.
Dengue outbreaks are preventable with existing interventions, but only if they are used in the right places at the right times. The ability to forecast disease outbreaks months in advance can reduce the burden on health services. This is important in resource-constrained Low and Middle Income Countries (LMICs) where they can make the difference between an effective and efficient proactive response compared to a costly and often unsuccessful reactive response. We aim to demonstrate the value of disease forecasting via a local level dengue forecasting system in Vietnam and Malaysia, which will pave the way for scale up of dengue forecasting and other digital health solutions for climate sensitive diseases.
We have developed the necessary disease forecasting techniques as part of the Dengue forecasting MOdel Satellite-based System (D-MOSS) project. Although this system has been operational since July 2019 in Vietnam and July 2020 in Malaysia, more work is needed to bridge the implementation gap to ensure forecasts have direct actionable and measurable impacts on preventing outbreaks at a local level.
Further research is required to establish if the forecasting techniques already in operation are capable of producing accurate forecasts at the required spatial and temporal resolutions, tailored to the practices applied by specific sectors of the health system. We will test this by co-developing new forecasts that provide advance predictions in Vietnam and Malaysia. Through a series of longitudinal workshops we will develop risk assessment protocols that link forecasts to outbreak prevention activities at different sectors of the Vietnamese and Malaysian health systems.
These knowledge gaps will be addressed by a multidisciplinary team of dengue experts, modellers, public health experts, software engineers and early warning systems experts from multiple institutes in Vietnam, Malaysia and the UK. Training and co-design of the research is central to all aspects of our proposal and we intend to leverage the equitable partnerships established as part of the D-MOSS project to meet our aims. Cross-cutting activities will compare and contrast the operational context in these countries and enable collaboration between them with the goal of deriving generalisable principles and specific guidelines for expansion to other countries.
This research will demonstrate clear health value against dengue and other Aedes mosquito-borne diseases (e.g. chikungunya, Zika) in Vietnam and Malaysia, and a plan for how the intervention will be scaled up to other LMICs currently struggling to address the growing threat of dengue and other climate-sensitive diseases. In the longer term, this project will provide evidence on the value of forecasting to health systems for a wide range of health conditions.
Technical Summary
Dengue fever is the fastest spreading mosquito-borne viral disease in the world today causing an estimated 400 million infections a year. Vietnam has suffered major outbreaks in recent years that are increasing in frequency and intensity. Dengue is hyper-endemic in Malaysia and has the highest incidence rate among communicable diseases in the country.
The Dengue MOdel forecasting Satellite-based System (D-MOSS) project developed a dengue fever forecasting system and proved that dengue outbreaks can be consistently predicted, creating the opportunity for practitioners to use interventions proactively. This system has been operational since July 2019 in Vietnam and July 2020 in Malaysia and more work is needed to ensure forecasts have direct, actionable and measurable impacts.
The project team will advance the D-MOSS forecasting framework to produce dengue forecasts that align with disease control decision making, in particular relating to frequency of issue, temporal resolution, different outbreak thresholds, and probabilistic information provided. Risk assessment protocols for dengue control, resource management, and mosquito control will be developed, relating directly to the forecasts provided.
The Dengue MOdel forecasting Satellite-based System (D-MOSS) project developed a dengue fever forecasting system and proved that dengue outbreaks can be consistently predicted, creating the opportunity for practitioners to use interventions proactively. This system has been operational since July 2019 in Vietnam and July 2020 in Malaysia and more work is needed to ensure forecasts have direct, actionable and measurable impacts.
The project team will advance the D-MOSS forecasting framework to produce dengue forecasts that align with disease control decision making, in particular relating to frequency of issue, temporal resolution, different outbreak thresholds, and probabilistic information provided. Risk assessment protocols for dengue control, resource management, and mosquito control will be developed, relating directly to the forecasts provided.
