To tame the COVID‐19 pandemic, staggering pullback in economic and social activities has been imposed globally. Yet, the containment measures can rapidly succumb to human mobility not accompanied by adequate precaution. Absent treatment or vaccine for mass inoculation in the near future, it is indispensable to adopt target-oriented intervention to avert the infection resurgence and eschew mounting economic fallout before the return to normalcy. This entails an accurate spatiotemporal predictive model that accounts for the spatial heterogeneity and human motion. Notably, research in human mobility and contagion dynamics cannot be done in isolation, and innovative solutions are increasingly emanating from cross-border intellectual interactions. However, with lockdown and travel restrictions in play, the traditional academic activities have ground to a screeching halt, and the academia is embracing virtual mobility and connectivity. This has also triggered concerns over the quality and engagement of participants, and sustainable international collaboration over the long run. This EAGER project will investigate how spatiotemporal human mobility will affect the contagion dynamics of COVID-19, which is conducive for optimal design of nonpharmaceutical intervention. It also brings research scholars from the U.S., Japan and Australia to study the impact of COVID-19 prevalence on international collaboration, and design innovative mechanism to render such cross-border cooperation resilient and sustainable against future disturbances.

Part 2. This interdisciplinary collaborative research integrates epidemic dynamics, computational social science, statistical learning and systems engineering at an unprecedented scale. The PI’s team will pursue the following research thrusts: (1) Spatiotemporal modeling for human mobility and contagion dynamics and the connection to intervention policy: A spatiotemporal compartmental model considering human motion and asymptomatic infection will be developed to delineate dynamical geographical prevalence of the contagion and the inherent uncertainty. (2) Dynamic graph modeling for collaboration network: International publication co-authorship will be represented as dynamic networks, which along with disease prevalence will uncover the contagion impact on cross-border cooperation, reveal weak coordination in existing partnerships and identify future trend of international collaboration. (3) Innovative mechanism design for sustainable international collaboration: Leveraging the emerging novel digital infrastructure, the team will collectively explore open-science initiatives for research interaction, documentation, protocol formulation and assessment for resilient and sustainable collaboration. This project is anticipated to decipher the impact of COVID-19 on international collaboration and design strategic mechanism to foster future resilient and sustainable cross-border cooperation.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
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Maija Kukla
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Suny at Binghamton
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