Seek & Find: Supporting Dengue Elimination through Data Analytics

Novel data analytics, consisting of algorithm development and a platform will be developed and scaled for use within communities to support lasting and cost-effective elimination of dengue disease using Wolbachia. 

Dr Kathleen M O'Reilly is a Assistant Professor at the London School of Hygiene and Tropical Medicine, London, UK.

Dengue is a viral disease that is largely endemic in the tropics, where >40% of the world's population are at risk. Each year, ~390 million dengue infections occur, resulting in ~25,000 deaths. Prevention includes reducing the habitat of the mosquito vector, Aedes aegypti, with limited effectiveness. Introduction of Wolbachia-carrying mosquitoes have been shown to naturally prevent mosquito borne diseases such as dengue. 

Our partners, the World Mosquito Program (WMP) have shown Wolbachia to be highly effective. In Yogyakarta (Indonesia), a randomised controlled trial (RCT) illustrated a 77% reduction in dengue incidence over 3 years. Wolbachiais so effective that elimination of dengue is now possible, but the steps towards this being economically manageable is not yet clear. Significant resource was put in place to monitor the RCT, which is not feasible across low and middle income settings.

The problem we seek to solve is what data are required to monitor Wolbachiaintroduction in the short and long term to enable elimination of dengue disease, and how should surveillance be carried out to monitor dengue introductions and Wolbachia coverage? 

The primary audience are health workers in dengue control and elimination, especially where Wolbachia has been introduced. The WMP have projects in 10 countries; Brazil, Colombia, Mexico, Indonesia, Sri Lanka, Vietnam, Australia, Fiji, Kiribati, New Caledonia and Vanuatu, where dengue is endemic. The Indonesian project is most relevant; here detailed data are collected as part of a randomised controlled trial (RCT) meaning that the algorithm and platform can be refined and validated. Wolbachia has been released into the wider community where identifying suitable surveillance to assess elimination is warranted.

More broadly, the algorithm and platform will provide a novel analytics framework that illustrates the power of Wolbachia in preventing dengue, but also illustrates best practice in illustrating elimination of an infectious disease. We envisage that the platform will serve many common requirements (production of elimination targets, inputting data, and visualising data for stakeholders), whilst being adaptable for specific needs. We are confident that the unique partnership between WMP and local communities will act as a springboard to develop this tool. Engagement is at the centre of this Solution, through workshops to understand stakeholder needs and an iterative process for platform development to ensure these needs are met.

Public good is inherent in this Solution. The algorithm and platform provide a unique way for useful data to be targeted and enables health workers to engage better with the data that they collect. Improved data collection and curation has a public good because of the limited resources available in health are prioritised towards collecting evidence of dengue disease and transmission, which informs elimination. By improving efficiency in resource use, free resource can be used in other disease programs, creating further public good.

More broadly, the impact of Wolbachia on preventing and eliminating dengue has yet to be fully utilised. Current WHO Global Strategy for dengue control is outdated (last updated in 2012 but due to be updated this year) and barely mentions innovative controls such as Wolbachia, let alone the potential for elimination. This Solution will support the statistical methodology required to make local assessment of dengue elimination, by identifying suitable data collection, and will make scale-up of Wolbachia more possible in low resourced settings. By providing solid evidence of dengue control and elimination, this Solution will improve adoption of Wolbachia, further improving public health. Our strong relationships with WHO make use well placed to inform strategy.  

Our Solution will create a tangible impact for people working in public health, and for the communities where Wolbachia is in use against dengue. In public health this Solution provides the framework for assessing elimination, and its application to specific settings will illustrate to the scientific community the feasibility of elimination (but additionally the barriers where it has not occurred). By defining targets, we will identify what data is useful for estimating elimination, and conversely what data does not meaningfully impact this assessment, and so no longer requires collection. For communities, especially those in low and middle income settings, the Solution will be part of the Wolbachia programme, and consequently support the prevention of dengue disease. Critically, the Solution will support economic use of resources, potentially freeing up resources to be spent on other health priorities.  

In the first year, the primary focus of the Solution team will be to develop the algorithm, and validate in silico and using data from Indonesia. Platform development will begin, with the aim of having a beta-version for data input and visualisation.

In years 2-3, the algorithm will be applied to data within the platform and outputs generated. At this stage, engagement with end users will be critical to assess the requirements, provide training, and refine the platform to the users needs. We also expect tangible assessments of elimination within specific settings, thus providing a “case use” for a wider audience (stakeholders in public health). It is also anticipated that in this period Wolbachia will have been scaled up to larger communities within and beyond the 10 countries where it is already in use. The algorithm may require refinement to specific settings in this latter stage, and better account for dengue importations. We envisage that as the Solution develops, wider use of the targets and platform will occur across Wolbachia areas, illustrating suitable scaling of this assessment tool.

We will monitor and evaluate our impact by producing products (1: algorithm, 2: platform) that are usable by partners and available in a timely manner. A Gantt chart will be developed and shared with partners detailing when products will be available, and when workshops will be held.

Several algorithms have been developed by the PI related to previous projects, and apps have already been developed by the broader research team (see apps https://cmmid.github.io/visualisations). As an academic, publication of high-quality peer-reviewed papers are a clear indicator of progress, which act as documentation of the approaches developed and how they have been applied to real-world public issues. The research team have considerable portfolio of research papers that illustrate development of algorithms and application to infectious disease problems.

Out impact goals are based on identifying useful data to collect and targets. This can easily be monitored through use of the platform, where data collection can be monitored, and we can assess how data collection evolves during the timeframe.

The major barrier to this Solution being completed is the availability of finances to support employment of staff to carry out the objectives. The Trinity Challenge will provide this resource, removing the largest barrier to our success. Whilst funds have been sought from other agencies (eg. Medical Research Council, UK), research funding in the UK is tightly constrained. Salary support is requested for several team members (Dr O’Reilly, Prof Jewell, Dr Clifford, all on a part-time basis), and new staff will be recruited to work on the algorithm and platform. LSHTM has an international reputation in infectious disease analysis so we expect to recruit a highly qualified and motivated individual.

A potential barrier to a successful Solution includes less experience in web development within LSHTM to develop the platform. We will work with additional partners (Aus Vet) that have more experience in bespoke web applications, but would also welcome support and mentoring from Trinity partners for platform development using appropriate, scalable, and open-source resources.

Solution Partners are World Mosquito Program and AusVet.

The Trinity Challenge will provide secure funding and support to deliver an innovative algorithm and platform that will help eliminate dengue. The Solution has a clear potential to help expedite informative data collection that informs dengue elimination, but requires investment in analysis and development of the platform. This Solution strongly fits the objectives of the Trinity Challenge; investing in this Solution will enable health workers to fully engage with the data they collect to understand how close they are to dengue elimination. As dengue is an acute infectious disease, preventing transmission by ensuring sufficient coverage of Wolbachia will be critical and something that communities have wanted for several decades.

Support from Trinity Members with our Solution will be highly valued; Members have considerable experience in scale-up of data driven interventions, and many have software development expertise that would complement our Solution.   

The BMGF have previously invested in Wolbachia research carried out by the WMP and LSHTM, predominantly in the Wolbachia technology itself (and some modelling funded at LSHTM). Our Solution focusses instead on data analytics and data engagement with stakeholders. We would be delighted to partner with BMGF, and would also welcome input and support from computing partners such as Microsoft and other interested partners.