Evaluating the Effectiveness of Messaging and Modeling during Pandemics (PandEval)

Evaluating the Effectiveness of Pandemic Messaging (PandEval)

An effective response to fight the spread of a pandemic requires a clear understanding of the complex interactions between biological, environmental and human networks. The COVID19 pandemic revealed both human and systemic failures along this chain. A key takeaway was the need for timely, relevant and actionable information to support effective public messaging and policy making that can impact in-real-life  (IRL) outcomes. The COVID19 pandemic also revealed the need for  messaging and policy making at a local scale, when national- or state-level approaches might not appropriately address the needs at community scale. Frontline public health officials often had little insight into the individuals that they wished to serve. Decision makers who managed cities or school systems often relied on epidemiological models that did not account for the impact of human beliefs and in-real-life behaviors -  e.g., the willingness to wear a mask - on disease transmission. The PandEval project will address these challenges, so as to ultimately increase the trust and confidence in our public health infrastructure. If successful, public health officials will gain insight into the success of (past) messaging campaigns so that they can deliver the right message at the right time. In addition, decision makers will be able to use  the outcomes  of the epidemiological models, customized to population segments, while planning vaccine rollouts, or admitting visitors to congregate living.

The innovation of the PandEval project is to rely on curating rich complex multimodal datasets. Social media-based models of community beliefs and attitudes around science skepticism, moral foundations, or the willingness to contribute to the public good, will be developed. Baseline profiles of in-real-life (IRL) behavior tracked by human mobility traces will be computed. Compartmental epidemiological models that account for population characteristics will be customized to account for a diversity of micro-targeted population segments and regions across the US. The PandEval platform will be engineered to measure the effectiveness of community targeted messaging around pandemic mitigation, including recommendations and mandates, and to measure the prediction accuracy of the customized epidemiological models. As we face the potential of endemic COVID19, the PandEval project will create and curate Pand-Index, an index of online social beliefs and in-real-life (IRL) profiles at a national scale. Pand-Index profiles will help individuals to make personalized decisions about social distancing or masking versus working from home.

This research is supported by the National Science Foundation award CCF2200256.