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                <text>Anqi Wang, Anshu Zhang, Edwin H.W. Chan, Wenzhong Shi, Xiaolin Zhou, Zhewei Liu</text>
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                <text>Along with the increase of big data and the advancement of technologies, comprehensive data-driven knowledge of urban systems is becoming more attainable, yet the connection between big-data research and its application e.g., in smart city development, is not clearly articulated. Focusing on Human Mobility, one of the most frequently investigated applications of big data analytics, a framework for linking international academic research and city-level management policy was established and applied to the case of Hong Kong. Literature regarding human mobility research using big data are reviewed. These studies contribute to (1) discovering the spatial-temporal phenomenon, (2) identifying the difference in human behaviour or spatial attributes, (3) explaining the dynamic of mobility, and (4) applying to city management. Then, the application of the research to smart city development are scrutinised based on email queries to various governmental departments in Hong Kong. The identified challenges include data isolation, data unavailability, gaming between costs and quality of data, limited knowledge derived from rich data, as well as estrangement between public and private sectors. With further improvement in the practical value of data analytics and the utilization of data sourced from multiple sectors, paths to achieve smarter cities from policymaking perspectives are highlighted.</text>
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                <text>SARS-CoV-2 Seroprevalence among Healthcare, First Response, and Public Safety Personnel, Detroit Metropolitan Area, Michigan, USA, May–June 2020</text>
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                <text>Lara J. Akinbami, Nga Vuong, Lyle R. Petersen, Samira Sami, Anita Patel, Susan L. Lukacs, Lisa Mackey, Lisa A. Grohskopf, Amy Shehu, Jenny Atas</text>
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                <text>To estimate seroprevalence of severe acute respiratory syndrome 2 (SARS-CoV-2) among healthcare, first response, and public safety personnel, antibody testing was conducted in emergency medical service agencies and 27 hospitals in the Detroit, Michigan, USA, metropolitan area during May–June 2020. Of 16,403 participants, 6.9% had SARS-CoV-2 antibodies. In adjusted analyses, seropositivity was associated with exposure to SARS-CoV-2–positive household members (adjusted odds ratio [aOR] 6.18, 95% CI 4.81–7.93) and working within 15 km of Detroit (aOR 5.60, 95% CI 3.98–7.89). Nurse assistants (aOR 1.88, 95% CI 1.24–2.83) and nurses (aOR 1.52, 95% CI 1.18–1.95) had higher likelihood of seropositivity than physicians. Working in a hospital emergency department increased the likelihood of seropositivity (aOR 1.16, 95% CI 1.002–1.35). Consistently using N95 respirators (aOR 0.83, 95% CI 0.72–0.95) and surgical facemasks (aOR 0.86, 95% CI 0.75–0.98) decreased the likelihood of seropositivity.</text>
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                <text>Personal protective equipment, SARS-CoV-2, hospitals, Seroepidemiologic Studies, Detroit, Emergency responders</text>
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                <text>10.3201/eid2612.203764</text>
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                <text>Emerging Infectious Diseases</text>
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                <text>Medicine, Infectious and parasitic diseases</text>
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                <text>Osama Abou-Arab, Guillaume Haye, Christophe Beyls, Pierre Huette, Pierre-Alexandre Roger, Mathieu Guilbart, Michaël Bernasinski, Patricia Besserve, Faouzi Trojette, Hervé Dupont, Vincent Jounieaux, Yazine Mahjoub</text>
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                <text>10.1007/s12630-020-01844-9</text>
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                <text>Canadian journal of anaesthesia = Journal canadien d'anesthesie</text>
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                <text>Regarding Telemedicine for the Spine Surgeon in the Age of COVID-19: Multicenter Experiences of Feasibility and Implementation Strategies" by Franco et al."</text>
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                <text>Vikaesh Moorthy</text>
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                <text>10.1177/2192568220956607</text>
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                <text>Global spine journal</text>
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