It's time to use data technology to help tackle epidemics and pandemic preparedness.
How will we tackle the next epidemic? In the face of measles re-emerging in the United States, Ebola spreading from the Democratic Republic of the Congo into Uganda, and the rampant rise of antimicrobial resistance, using all the tools in our arsenal is critical. Epidemics challenge us in new ways; through identification, isolation, and communication, we have a better chance to mitigate the spread. Pandemics are both our history and our future and, as many have noted, we must prepare for them. This was one of the many discussions held this week during the 5th Annual Biodefense World Summit.
One of the hardest aspects of biodefense, though, is integrating new technology to truly make a difference. Every day, there are advancements in tech; yet, it can be challenging to truly discern how these new tools can help global health security and prevent the next pandemic. In a Biodefense presentation that called on the use of data technology and forecasting to help tackle the next epidemic, Dylan George, PhD, BS, vice president of technical staff at In-Q-Tel and associate director of BNext, discussed integrating novel and available data technologies into public health processes to not only help guide interventions, but also to establish more efficient response practices and improve situational awareness.
According to George, to be effective, we need to initiate interventions as early as possible within the ecosystem and human cases, prior to large outbreaks, epidemics, and even pandemics. Simply put, George noted that “outbreaks are inevitable, epidemics are options.” You might be wondering, “what’s the holdup to build a more robust biodefense in the United States?” From a lack of markets to translate science to limited manufacturing and access to start-up innovation for the government, the truth is that US biodefense is in a panic-neglect cycle.
This is where data analytics come in, according to George. Although their needs change across epidemics (risk assessment tools, disease risk mapping, etc.), the use of disease forecasting is truly critical for epidemic management. Realistically, if we use it for forecasting hurricanes, why wouldn’t we use it for infectious diseases? Forecasting capabilities can help build policy, but also response within even the private sector. Consider influenza forecasting—we use this within hospitals to help determine how much PPE, vaccine, and even staffing we should prepare for.
George said, though, that the forecasting we’re using currently still needs a lot of work. To make it a more suitable tool for outbreak decision-making, there needs to be more resources for data cleaning, visualization of results, and advanced analytics… all of which take time. Here’s the tricky part, though: There’s currently a shortage of analytical talent in the United States. That’s right—it’s estimated that we have a shortage of 140,000-190,000 people with deep analytical skills to help break through the barriers of big data. Consider even the visualization and risk communication efforts that are needed to help improve communication of epidemics and disease threats. Although the US Centers for Disease Control and Prevention prototypes like Viziflu help to improve communication of flu forecasts, there is a desperate need to spread the knowledge of forecasting in a manner that can be beneficial.
As George emphasized, forecasting results will become increasingly common in outbreak preparedness and response, but we also need to invest in data cleaning, advanced analytics, and visualizations to truly help mitigate the next epidemic or even pandemic. It is critical that public health, biodefense, health care, and data analytics work together to help strengthen the application of forecasting and data technology in preventing the next pandemic…or at least giving us enough time to prepare.