By Caitlin Rivers, PhD, MPH
I’m excited to announce that with support from the Open Philanthropy Project, my colleagues and I at the Johns Hopkins Center for Health Security will be working over the next eighteen months to develop a plan to develop an Outbreak Science Initiative to support the US government in responding to infectious disease outbreaks. The program would formally integrate the nation’s top disease outbreak scientists into federal response operations, where they could produce the forecasts, models, and analyses that decision makers need to allocate resources, compare interventions, and assess progress on outbreak containment. This capability would improve our ability to respond to outbreaks quickly and effectively.
We coin the term “outbreak science” to mean a subfield of epidemiology that uses infectious disease modeling, data science and visualization, and modern data practices for outbreak response. The goal of outbreak science is to connect public health decision makers with the most current data and analytics necessary to determine how best to contain outbreaks. Although this type of expertise has been influential in several major epidemics, it is often tapped by response officials in sporadic, ad hoc, and pro bono partnerships. There is currently no formal mechanism for public health officials to reliably and quickly access experts who can produce the models and analyses necessary to inform decision making.
The use of outbreak science during the 2014-2015 Ebola response is illustrative of the value of outbreak science. One influential model published by the Centers for Disease Control and Prevention forecast a worst-case scenario of more than one million cases if the epidemic continued unabated. It’s widely acknowledged that the CDC model galvanized the international response that ultimately contributed to control of the epidemic. However, CDC is one of just two groups in government with embedded outbreak science expertise. Most of the other models used during the outbreak, including those used to forecast case counts and monitor containment, were produced by academics with no formal connection to the response. They worked without guidance about the public health questions that needed answering, without official data sets, and without compensation. They also had to put their results in academic journals instead of in the hands of decision makers.
Conversely, decision makers without outbreak science support had no choice but to act without full analysis of the current and future state of the outbreak. This lack of adequate situational awareness potentially contributed to the late identification of funerals as superspreading events, and to the overdue surge of hospital beds. The disconnect between public health decision makers and modeling expertise limited the timeliness and applicability of most of the models produced during the Ebola outbreak, and reduced the effectiveness of the response. An outbreak science program would aim to close this critical gap in future public health events by formally integrating the best outbreak scientists into outbreak response operations to enable faster control of epidemics.