Our health depends on timely data about the pathogens around us
Disease epidemics have impacted every society and economy in human history. The key to reducing future epidemics is the early detection of potential pathogens—before they cause large disease outbreaks. This gives researchers time to develop new treatments, public health organizations time to prepare responses, and individuals time to minimize their exposure to sources of disease risk.
However, detecting pathogens before they cause outbreaks is no easy task. Pathogens move through the environment in complex ways that are difficult to monitor by traditional methods. It is estimated that 60 – 75% of emerging infectious diseases are caused by pathogens that jump from animals to people. Viruses like Zika, dengue and West Nile move between humans, animals, and mosquitoes in complex cycles. Yet, today we have limited technologies and capacity to monitor potential pathogens as they move through the environment.
What if we could predict epidemics like we predict the weather?
Through a network of robotic sensing platforms, Premonition aims to continuously monitor our environment to detect potential pathogens and disease-carrying animals before they cause outbreaks.
Scroll to learn how it all starts with a mosquito…
Mapping the biome
Mosquitoes cause over 600 million cases of human disease per year, and it’s essential to monitor and control them. They also feed on many species of animals and encounter other pathogens that they don’t transmit. By monitoring mosquitoes, we can detect other pathogens and disease carriers in the environment.
The image below shows some of the important signals that can be detected from mosquito samples.
Meet our robot detectives
Premonition uses a network of robotic smart traps that continuously lure, identify and collect arthropod species like mosquitoes.
To provide real-time data about important mosquito species, these smart traps must autonomously identify arthropods within a few milliseconds as they fly past sensors.
The Proving Ground
A whole biome in the lab
To make our smart traps work in the real world, we created a simulated world in the lab.
No place like home
The goal is to replicate the wild to test and evaluate our systems with mosquitoes in their natural habitats.
All about the climate
Our environmental condition system precisely controls humidity, temperature, wind, and CO2 levels, while monitoring other parameters like oxygen and nitrogen.
The laboratory biome can be set to any place and date, and it will replicate the solar cycle that would have been experienced there.
Scalable monitoring of the biome
After many years of developing these core technologies, we have a new goal: to deploy these sensor networks into the world at scale. We believe this will empower better detection of potential pathogens before they cause outbreaks, more efficient control of threats like disease-carrying mosquitoes, and improved prediction of when and where known pathogens will emerge next. Scalable monitoring of the biome will get us much closer to predicting outbreaks like we predict the weather today.
To make this possible, a variety of disciplines and partners are integral, including experts in robotics, artificial intelligence, cloud computing, genomics, vector biology, virology, and epidemiology.
For example, with our partners we have analyzed over 80 trillion base pairs of genomic material from environmental samples. This helps battle test our cloud-scale genomics services to ensure they can quickly and accurately find potential threats.
Better detection and prediction of biological threats can’t be done with technology alone. It will require industry, government, and academia to work together on new paradigms and approaches.
Check back for more information about our early access program.
With the help of our partners, Microsoft Premonition aims to monitor our biome and help make our world safer and healthier to live in.
Working with partners in real environments
Developing scalable monitoring solutions for real-world is an interdisciplinary effort requiring a diverse set of partners. Microsoft Premonition embraces academic, governmental, and industrial partners to help deploy and evaluate our technologies in complex ecosystems. We have focused our field deployments on answering several related scientific questions: (1) How many types of arthropods will visit a robot, and how hard is it to autonomously classify them? (2) Can autonomously collected data be used to build better forecasts of disease risks, and can those forecasts be used to better inform human health programs? (3) How reliably can microbes, viruses, and other environmental DNA be recovered from robotically collected specimens in urban and rural environments?
For example, in a collaboration with Harris County Public Health, we trialed our technologies in Houston, TX during the peak of Zika transmission risk in 2016. We saw that robot field biologists could be trained to identify and selectively capture medically relevant mosquitoes with high accuracy (> 90%). Our robots were also able to digitize mosquito behaviors at high resolution, allowing us to better understand how they moved through the environment. Our genomics analyses were able to detect microorganisms and viruses in mosquito specimens, and identify the types of animals on which they fed. Since then, we have explored diverse habitats ranging from the southern tip of Florida to the remote forests of Tanzania. Along the way, we have continued to learn how these technologies and data sets can assist our partners with their essential human health missions.
Tech Minutes – Premonition
Ethan Jackson and Nicolas Villar describe the Proving Ground facility that detects disease threats using robotics and genomics.
Premonition technical deep dive
Discover the technical layers of Microsoft Premonition in this exploration of the different technologies that make this system reality.
Premonition wins Fast Company award
Fast Company’s World Changing Ideas focuses on social good, seeking to elevate finished products and brave concepts that make the world better.