The Sentinel Forecasting System for Infectious Disease Risk

An integrated real-time platform to forecast and manage infectious disease risk for public health agencies

Kate Jones, Professor of Ecology and Biodiversity, University College London, UK. 

The majority of high consequence human diseases are animal-borne, either directly from vertebrates (zoonotic) or transmitted by animal vectors. Although the causes of such outbreaks have their roots in how humans interact with the environment, limited understanding of this area severely limits the ability of public health systems to predict and prevent future outbreaks, with severe global economic and health consequences. West Africa is a critical nexus of these issues, as it contains some of the most biodiverse natural habitats on earth, one of the fastest growing human populations, rapidly degrading ecosystems, frequent disease outbreaks and overstretched public health systems with limited response capacities. Examples include the rodent-borne disease Lassa fever, which is estimated to cause over 500,000 cases and 5,000 deaths across the region every year, particularly in Nigeria, and the Ebola outbreak of 2013-2016 which caused 28,616 cases, killing 11,310 people. Such outbreaks have a disproportionate impact on affected societies. For example, the World Bank estimates a cost of the Ebola outbreak at US$2.2 billion to the three most affected countries (Guinea, Sierra Leone, and Liberia) due to widespread infrastructure breakdown, mass migration, crop abandonment and a rise in endemic diseases due to overrun healthcare systems.

Our Sentinel Forecasting System will be developed firstly for Lassa fever in Nigeria before expanding the geographic scope and disease system. We will develop a key national and regional stake-holder group at the beginning of the project to understand requirements and with whom the solution will be co-developed throughout the course of the project. This important focus on stake-holder co-development will ensure the product fits requirements, is embedded into national decision-making processes, and is continued to be used by local health agencies in public health planning during and after the term of the grant.

Target audiences for the Sentinel Forecasting System:

• In-country healthcare policy decision makers;

• Multilateral surveillance networks including the African CDC, ALERRT, and the WHO's EWARS and GOARN; 

• Vaccine development and response (e.g., The Coalition for Epidemic Preparedness Innovations (CEPI) and DIOSynVax);

• Infectious disease academic research community.

The Sentinel Forecasting System will be a powerful freely available information platform that allows national and regional public health decision makers to continuously integrate surveillance data and forecast disease risk in real-time or near real-time. By integrating this solution into the public health systems of Nigeria and other West African countries, officials can manage outbreaks more easily but also, by understanding the present and future spillover risks, intervene to prevent or mitigate outbreaks on the ground. Our solution will:

• Connect frontline healthcare workers, hospitals, laboratories, and public health institutions to ensure efficient coordination, robust data sharing, and real-time analytics for risk forecasting and rapid response.
• Empower the entire public health community – from frontline workers to national authorities – to deploy the Sentinel Forecasting System anywhere in West Africa and ultimately use this system to save lives and reduce economic losses.
• Leverage the Sentinel and OVEL projects to gain the latest information on pathogen genomics.

The proposed Sentinel Forecasting System will provide tangible health benefits for communities across West Africa, including those poor and marginalised communities that often suffer disproportionate impacts of the disease. The impact will be realised through our activities to integrate new and existing data for the generation of risk models within a bespoke stakeholder-led platform. These outputs will allow national and regional public health officials to fine tune their disease management responses to deploy limited resources most effectively, and potentially free up resources for outbreaks of other diseases (see our letters of support from both Africa Centre of Disease Control and Prevention and Nigeria Centre of Disease Control). Our outputs will also transform the ability to predict outbreaks early and radically improve the speed at which public health authorities respond to an outbreak for millions of people across West Africa. All of these advancements will save lives, improve healthcare, help prevent pandemics, and lead to greater economic prosperity. Although the Sentinel Forecasting System's immediate coverage area will lie in West Africa, the benefits will be global as understanding the risk of a known or novel pathogen in one part of the world reduces the chance that it will spread.

From the initial focus on forecasting Lassa fever risk in Nigeria in Year one, we will scale-up impact along two main axes over three years. First, taking advantage of our close links to other countries in West Africa, we will increase the Lassa forecasting geographic scope. Our team have been collecting data, for instance, in Sierra Leone - another Lassa hotspot - for over a decade. By forecasting Lassa Fever across the whole of West Africa we can directly impact the lives of many of the 367 million people who live in agricultural and urban environments alongside the rodent hosts. Second, working with our public health partners and stakeholders, we will increase disease scope of our system to make predictions for other priority diseases, particularly other Viral Haemorrhagic Fevers. Founded on Bayesian statistics, our system is ideally placed to create risk hotspot maps of diseases with very limited data (including novel pathogens) that then will continually update to produce predictions with increased accuracy and resolution as more information becomes available. By incorporating more diseases, we will be able to impact the lives of many millions more people both across Africa and the rest of the world.

Relevant Key Performance Indicators (KPIs) will be developed at the beginning of the project with our public health stakeholder group. Examples of KPIs will (but not only) include the amount of platform uptake with public health officials, the number of people trained to access the data and analytics, the success of the models to forecast cases over time and in new areas, number of peer-reviewed research papers or media coverage. As the time frame is short to accurately assess the impact on reducing case numbers, given highly variable numbers of cases per year, we will also use alternative measurements, for example the time and resources saved by public health agencies using our forecasts to plan interventions. KPIs will be monitored and reported to the Senior Management Team, and the External Advisory Committee to help adaptively manage the project and to assess whether key milestones have been reached. Performance from our pilot: the Nigeria Centre for Disease Control is part our team to create Lassa forecasting models; the Sentinel Project has already provided practitioner training, the current Lassa model currently shows good predictive power to forecast cases in Nigeria; and our approach is founded on peer-reviewed high impact publications. 

We are in an excellent position to deliver a working Lassa forecasting platform as we have a working model, good data and close working relationship with the Nigeria Centre for Disease Control and Africa Centre for Disease Control and Prevention. However, there are other potential barriers. It might be difficult to show people working in public health on the ground that our products are worth their time investment, given many other demands on their time. We will overcome this by co-developing the portal with end-users and providing ongoing, in-depth training. There might be further barriers extending to other diseases and geographic areas, as the models are known to work well for Lassa Fever in Nigeria, but might not be as accurate elsewhere. However, our initial work, not yet published, with other diseases has shown that the risk maps produced using our approach accurately recreate the known endemic areas for many other diseases.

University College London (UCL)

Zoological Society of London (ZSL)

African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University

Nigeria Centre of Disease Control (NCDC)

Africa Centre for Disease Control and Prevention (ACDC)

University of Cambridge (UCAM)

London School of Hygiene and Tropical Medicine (LSHTM)

Microsoft

We are aware that we cannot address a problem of this scale alone and the Trinity Challenge can provide the resources to enable us to integrate and scale-up our solution. Our solution is an incredible fit for the Identify Challenge Area. Indeed, our team's previous work on global risk hotspots of infectious diseases (Jones et al. 2008) was used as inspiration for the scope of the challenge. From the outset, we will build upon our work with many partners, including governments, public health agencies, NGOs, academic groups, and tech companies, to help fight spillover and prevent outbreaks before they start, and save lives.

Institute of Health Metrics and Evaluation http://www.healthdata.org/ Global Burden of Disease Team to understand in more detail the disease case data in West Africa.