Three ways Ginkgo is closing biosecurity’s first mile gap

By Nita Madhav, MSPH
Head of Epidemiology and Risk, Ginkgo Biosecurity

Traditional pathogen surveillance – testing samples for dangerous strains of viruses and bacteria – usually relies on identifying symptomatic cases at hospitals or clinical laboratories, which wastes valuable time in outbreak detection. By the time a case reaches that detection threshold, the pathogen has already likely been circulating in the community for some time. Why wait for a disease to insidiously circulate within our communities before taking action? 

We need to revamp the detection model to focus on earlier identification. We should be solving biosecurity’s “first mile problem.” 

Practitioners have discussed the “last mile problem” in the context of delivering life-saving medicines and vaccines into remote rural areas or connecting different modes of transportation to the final endpoint. The “first mile problem” is the converse problem. With this way of thinking, we are trying to identify infectious threats earlier. We should aim to detect threats as early as possible, so that vaccines can be developed within the first 100 days, as the Coalition for Epidemic Preparedness Innovations (CEPI) framed the challenge. The ultimate goal is to anticipate threats before the first case infects the second, third, and so on. In other words, in order to prevent the spread of the next pandemic, we must focus on anticipating the most likely risks—before they become infections. 

For travelers, the first mile is the journey from their doorsteps to the trains, buses, or whatever means make up their local transit network. A lack of first mile solutions leaves even the best-designed system underutilized, the way a missing bus can derail a commute. It’s similar for biosecurity. 

There is a robust network of solutions and experts committed to the goal of detecting the risks and mitigating them—the early makings of a global detection system. However, what we need to build is more infrastructure that identifies pathogens circulating around us as early as possible. 

Monitoring airports and ports of entry

When it comes to travel, if a disease does not originate domestically, the first case would enter through disease importation. And so the “first mile” is the port of entry. Pre-flight screening, for example, cannot guarantee all cases, especially asymptomatic carriers, will not spread. Monitoring ports of entry to understand what pathogens are entering is a valuable tool for early warning and disease identification. 

The CDC’s Traveler-based Genomic Surveillance (TGS) program, managed in partnership with Ginkgo and XpresCheck, identified the first instances of COVID-19 strains Omicron BA.2 and BA.3 in the U.S. weeks earlier than other systems. The extra lead time to characterize a lineage is worth investing in, because it can provide crucial information to public health officials and national security experts to inform next steps, such as whether or not the strain will respond to existing vaccines and antiviral drugs.

Performing persistent digital biothreat monitoring

To provide actionable intelligence, insights on pathogen risks can’t live in silos. Our digital biothreat monitoring platform taps into open source data to get the big picture around infectious disease baseline activity and flagging potential outbreaks of concern. We scour thousands of media reports and official reporting sources to construct a global view of biological threats on a daily basis.

The picture that emerges from this monitoring layer can be triangulated with data coming from other sources, such as data from monitoring airports and ports of entry, to provide a more complete and comprehensive view of risk than we could get by looking at any single dataset on its own.

Enabling data-driven epidemic mitigation strategies

Data provides only part of the story. Modeling tools, including those using machine learning and artificial intelligence, amplify the insights and can estimate the percent of disease cases that are going undetected and unreported. We have also built risk modeling tools to get a picture of the wide range of possible scenarios that could occur in the future.

Our disease spread model, for example, factors in the probability of zoonotic spillover and emergence, migration through global travel networks, and epidemic preparedness. The ability to simulate hundreds of thousands of epidemic trajectories for thousands of locations around the world provides actionable insights around the impacts, allowing decision makers to plan for and identify areas to shore up preparedness and response capacities, and reveal the key drivers of risk that could be reduced through mitigation activities.

The end of the line for harmful outbreaks

Knowing how an epidemic might unfold can help us anticipate worst case scenarios. Many of the ripple effects we experienced from COVID-19, such as supply chain disruptions, medical supply shortages, healthcare capacity issues, and closed schools and businesses, arose because the pandemic caught us off guard. It doesn’t have to be this way. 

Removing the first mile gap and looking to mitigate risks before they become pandemics will help ensure communities are better prepared and solutions will arrive sooner, increasing biosecurity for everyone.