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Civil infrastructure systems transform over the long-term due to complex interactions among socio-environmental stressors, degradation of physical networks, and decision-making processes of infrastructure agencies. To incorporate such complex transformation mechanisms into infrastructure cost management, this study integrates simulation modeling and life-cycle cost analysis (LCCA) to create a framework for dynamic network-level LCCA in infrastructure systems. The proposed framework was implemented using a multi-agent simulation model in a numerical case study related to a road network affected by sea-level rise, population growth, and uncertain maintenance funding. The results include identification of several state transition, and tipping point behaviors at which small changes in service demand, maintenance budget, and adaptation investment may result in significant improvement in network cost and performance conditions. The results show the capability of the proposed framework in modeling the long-term trajectories of life-cycle costs at the network level under different stressors and decision scenarios. [ABSTRACT FROM AUTHOR]

The Covid-19 has presented an unprecedented challenge to public health worldwide. However, residents in different countries showed diverse levels of Covid-19 awareness during the outbreak and suffered from uneven health impacts. This study analyzed the global Twitter data from January 1st to June 30th, 2020, to answer two research questions. What are the linguistic and geographical disparities of public awareness in the Covid-19 outbreak period reflected on social media? Does significant association exist between the changing Covid-19 awareness and the pandemic outbreak? We established a Twitter data mining framework calculating the Ratio index to quantify and track awareness. The lag correlations between awareness and health impacts were examined at global and country levels. Results show that users presenting the highest Covid-19 awareness were mainly those tweeting in the official languages of India and Bangladesh. Asian countries showed more disparities in awareness than European countries, and awareness in Eastern Europe was higher than in central Europe. Finally, the Ratio index had high correlations with global mortality rate, global case fatality ratio, and country-level mortality rate, with 21-31, 35-42, and 13–18 leading days, respectively. This study yields timely insights into social media use in understanding human behaviors for public health research. [ABSTRACT FROM AUTHOR]