TY - GEN
T1 - Planning Epidemic Interventions with EpiPolicy
AU - Tariq, Zain
AU - Mannino, Miro
AU - Le Xuan Anh, Mai
AU - Bagge, Whitney
AU - Abouzied, Azza
AU - Shasha, Dennis
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/10/10
Y1 - 2021/10/10
N2 - Model-driven policymaking for epidemic control is a challenging collaborative process. It begins when a team of public-health officials, epidemiologists, and economists construct a reasonably predictive disease model representative of the team's region of interest as a function of its unique socio-economic and demographic characteristics. As the team considers possible interventions such as school closures, social distancing, vaccination drives, etc., they need to simultaneously model each intervention's effect on disease spread and economic cost. The team then engages in an extensive what-if analysis process to determine a cost-effective policy: a schedule of when, where and how extensively each intervention should be applied. This policymaking process is often an iterative and laborious programming-intensive effort where parameters are introduced and refined, model and intervention behaviors are modified, and schedules changed. We have designed and developed EpiPolicy to support this effort. EpiPolicy is a policy aid and epidemic simulation tool that supports the mathematical specification and simulation of disease and population models, the programmatic specification of interventions and the declarative construction of schedules. EpiPolicy's design supports a separation of concerns in the modeling process and enables capabilities such as the iterative and automatic exploration of intervention plans with Monte Carlo simulations to find a cost-effective one. We report expert feedback on EpiPolicy. In general, experts found EpiPolicy's capabilities powerful and transformative, when compared with their current practice.
AB - Model-driven policymaking for epidemic control is a challenging collaborative process. It begins when a team of public-health officials, epidemiologists, and economists construct a reasonably predictive disease model representative of the team's region of interest as a function of its unique socio-economic and demographic characteristics. As the team considers possible interventions such as school closures, social distancing, vaccination drives, etc., they need to simultaneously model each intervention's effect on disease spread and economic cost. The team then engages in an extensive what-if analysis process to determine a cost-effective policy: a schedule of when, where and how extensively each intervention should be applied. This policymaking process is often an iterative and laborious programming-intensive effort where parameters are introduced and refined, model and intervention behaviors are modified, and schedules changed. We have designed and developed EpiPolicy to support this effort. EpiPolicy is a policy aid and epidemic simulation tool that supports the mathematical specification and simulation of disease and population models, the programmatic specification of interventions and the declarative construction of schedules. EpiPolicy's design supports a separation of concerns in the modeling process and enables capabilities such as the iterative and automatic exploration of intervention plans with Monte Carlo simulations to find a cost-effective one. We report expert feedback on EpiPolicy. In general, experts found EpiPolicy's capabilities powerful and transformative, when compared with their current practice.
KW - Epidemic Simulation
KW - Interactive Modeling
KW - Policy Exploration
UR - http://www.scopus.com/inward/record.url?scp=85118208288&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118208288&partnerID=8YFLogxK
U2 - 10.1145/3472749.3474794
DO - 10.1145/3472749.3474794
M3 - Conference contribution
AN - SCOPUS:85118208288
T3 - UIST 2021 - Proceedings of the 34th Annual ACM Symposium on User Interface Software and Technology
SP - 894
EP - 909
BT - UIST 2021 - Proceedings of the 34th Annual ACM Symposium on User Interface Software and Technology
PB - Association for Computing Machinery, Inc
T2 - 34th Annual ACM Symposium on User Interface Software and Technology, UIST 2021
Y2 - 10 October 2021 through 14 October 2021
ER -