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IMPORTANCE Little is known about the risk factors for, and the risk of, developing post-COVID-19 conditions (PCCs) among children. OBJECTIVES To estimate the proportion of SARS-CoV-2-positive children with PCCs 90 days after a positive test result, to compare this proportion with SARS-CoV-2-negative children, and to assess factors associated with PCCs. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study, conducted in 36 emergency departments (EDs) in 8 countries between March 7, 2020, and January 20, 2021, included 1884 SARS-CoV-2-positive children who completed 90-day follow-up; 1686 of these children were frequency matched by hospitalization status, country, and recruitment date with 1701 SARS-CoV-2-negative controls. EXPOSURE SARS-CoV-2 detected via nucleic acid testing. MAIN OUTCOMES AND MEASURES Post-COVID-19 conditions, defined as any persistent, new, or recurrent health problems reported in the 90-day follow-up survey. RESULTS Of 8642 enrolled children, 2368 (27.4%) were SARS-CoV-2 positive, among whom 2365 (99.9%) had index ED visit disposition data available; among the 1884 children (79.7%) who completed follow-up, the median age was 3 years (IQR, 0-10 years) and 994 (52.8%) were boys. A total of 110 SARS-CoV-2-positive children (5.8%; 95% CI, 4.8%-7.0%) reported PCCs, including 44 of 447 children (9.8%; 95% CI, 7.4%-13.0%) hospitalized during the acute illness and 66 of 1437 children (4.6%; 95% CI, 3.6%-5.8%) not hospitalized during the acute illness (difference. 5.3%; 95% CI, 2.5%-8.5%). Among SARS-CoV-2-positive children, the most common symptom was fatigue or weakness (21 [1.1%]). Characteristics associated with reporting at least 1 PCC at 90 days included being hospitalized 48 hours or more compared with no hospitalization (adjusted odds ratio [aOR], 2.67 [95% CI, 1.63-4.38]); having 4 or more symptoms reported at the index ED visit compared with 1 to 3 symptoms (4-6 symptoms: aOR, 2.35 [95% CI, 1.28-4.31]; >= 7 symptoms: aOR, 4.59 [95% CI, 2.50 8.44]); and being 14 years of age or older compared with younger than 1 year (aOR, 2.67 [95% CI, 1.43-4.99]). SARS-CoV-2-positive children were more likely to report PCCs at 90 days compared with those who tested negative, both among those who were not hospitalized (55 of 1295 [4.2%; 95% CI, 3.2%-5.5%] vs 35 of 1321[2.7%; 95% CI, 1.9%-3.7%]; difference, 1.6% [95% CI, 0.2%-3.0%]) and those who were hospitalized (40 of 391[10.2%; 95% CI, 7.4%-13.7%] vs 19 of 380 [5.0%; 95% CI, 3.0%-7.7%]; difference, 5.2% [95% CI, 1.5%-9.1%]). In addition, SARS-CoV-2 positivity was associated with reporting PCCs 90 days after the index ED visit (aOR, 1.63 [95% CI, 1.14-2.35]), specifically systemic health problems (eg, fatigue, weakness, fever; aOR, 2.44 [95% CI, 1.19-5.00]). CONCLUSIONS AND RELEVANCE In this cohort study, SARS-CoV-2 infection was associated with reporting PCCs at 90 days in children. Guidance and follow-up are particularly necessary for hospitalized children who have numerous acute symptoms and are older. This studywas supported by grants from the Canadian Institutes of Health Research (operating grant: COVID-19-clinical management); the Alberta Health Services-University of Calgary-Clinical Research Fund; the Alberta Children's Hospital Research Institute; the COVID-19 Research Accelerator Funding Track (CRAFT) Program at the University of California, Davis; and the Cincinnati Children's Hospital Medical Center Division of Emergency Medicine Small Grants Program. Dr Funk is supported by the University of Calgary Eyes-High PostDoctoral Research Fund. Dr Freedman is supported by the Alberta Children's Hospital Foundation Professorship in Child Health andWellness.

Key Points Question What proportion of SARS-CoV-2–positive youths tested in emergency departments (ED) experience severe outcomes (ie, intensive interventions, severe organ impairment, or death) within 14 days? Findings Among 3221 SARS-CoV-2–positive youths enrolled in a global prospective cohort study with outcome data, 3.3% had severe outcomes within 14 days. Across a subgroup of 2510 SARS-CoV-2–positive youths discharged home after testing, 0.5% had severe outcomes during the 2-week follow-up period. Meaning The findings of this study suggest that risk factors such as age, underlying chronic illness, and symptom duration may be useful for clinicians to consider when evaluating pediatric patients with SARS-CoV-2 infection., This cohort study investigates the prevalence of severe outcomes among youths aged 17 years or younger within 14 days of testing positive for SARS-CoV-2 in emergency departments in 8 countries., Importance Severe outcomes among youths with SARS-CoV-2 infections are poorly characterized. Objective To estimate the proportion of children with severe outcomes within 14 days of testing positive for SARS-CoV-2 in an emergency department (ED). Design, Setting, and Participants This prospective cohort study with 14-day follow-up enrolled participants between March 2020 and June 2021. Participants were youths aged younger than 18 years who were tested for SARS-CoV-2 infection at one of 41 EDs across 10 countries including Argentina, Australia, Canada, Costa Rica, Italy, New Zealand, Paraguay, Singapore, Spain, and the United States. Statistical analysis was performed from September to October 2021. Exposures Acute SARS-CoV-2 infection was determined by nucleic acid (eg, polymerase chain reaction) testing. Main Outcomes and Measures Severe outcomes, a composite measure defined as intensive interventions during hospitalization (eg, inotropic support, positive pressure ventilation), diagnoses indicating severe organ impairment, or death. Results Among 3222 enrolled youths who tested positive for SARS-CoV-2 infection, 3221 (>99.9%) had index visit outcome data available, 2007 (62.3%) were from the United States, 1694 (52.6%) were male, and 484 (15.0%) had a self-reported chronic illness; the median (IQR) age was 3 (0-10) years. After 14 days of follow-up, 735 children (22.8% [95% CI, 21.4%-24.3%]) were hospitalized, 107 (3.3% [95% CI, 2.7%-4.0%]) had severe outcomes, and 4 children (0.12% [95% CI, 0.03%-0.32%]) died. Characteristics associated with severe outcomes included being aged 5 to 18 years (age 5 to

There is ample evidence of regions diversifying in new occupations that are related to pre-existing activities in the region. However, it is still poorly understood through which mechanisms related diversification operates. To unpack relatedness, we distinguish between three mechanisms: complementarity (interdependent tasks), similarity (sharing similar skills) and local synergy (based on pure co-location). We propose a measure for each of these relatedness dimensions and assess their impact on the evolution of the occupational structure of 389 US Metropolitan Statistical Areas (MSA) for the period 2005–2016. Our findings show that new jobs appearing in MSA’s are related to existing ones, while those more likely to disappear are more unrelated to a city’s jobs’ portfolio. We found that all three relatedness dimensions matter, but local synergy shows the largest impact on entry and exit of jobs in US cities, thus being the strongest force of diversification.

How do regions enter new and distant technological fields? Who is triggering this process? This work addresses these compelling research questions by investigating the role of migrant inventors in the process of technological diversification. Immigrant inventors can indeed act as carriers of knowledge across borders and influence the direction of technological change. We test these latter propositions by using an original dataset of immigrant inventors in the context of European regions during the period 2003-2011. Our findings show that: immigrant inventors generate positive local knowledge spillovers; they help their host regions to develop new technological specialisations; they trigger a process of unrelated diversification. Their contribution comes via two main mechanisms: immigrant inventors use their own personal knowledge (knowledge creation); they import knowledge from their home country to the host region (knowledge transfer). Their impact is maximised when their knowledge is not recombined with the local one (in mixed teams of inventors), but it is reused (in teams made by only migrant inventors). Our work contributes to the existing literature of regional diversification by providing fresh evidence of unrelated diversification for European regions and by identifying important agents of structural change. It also contributes to the literature of migration and innovation by adding fresh evidence on European regions and by unveiling some of the mechanisms of immigrants’ knowledge transmission.

A possible unintended but damaging consequence of anti-immigrant rhetoric, and the policies it inspires, is that they may put high-skilled immigrants off more than low-skilled ones at times when countries and businesses intensify their competition for global talent. We investigate this argument following the location choices of thousands of immigrant inventors across US counties during the Age of Mass Migration. To do so we combine a unique USPTO historical patent dataset with Census data and exploit exogenous variation in both immigration flows and diversity induced by former settlements, WWI and the 1920s Immigration Acts. We find that co-ethnic networks play an important role in attracting immigrant inventors. However, we also find that immigrant diversity acts as an additional significant pull factor. This is mainly due to externalities that foster immigrant inventors' innovativeness. These findings are relevant for today's advanced economies that have become major receivers of migrant flows and, in a long-term perspective, have started thinking about immigration in terms of not only level but also composition.

The ‘life cycle’ approach has become popular in studies on industrial clusters. However, some concerns have been raised over the inherent determinism of this approach and its tendencies to focus exclusively on cluster internal dynamics while neglecting the role of external factors and socio-economic contingencies. This paper addresses these criticisms by investigating the long-term development of Castel Goffredo, a traditional textile cluster in Italy. In our analysis, we identify and characterize the main stages of the life cycle and its antecedents. We single out the main triggering factors behind each of these stages and show that a variety of factors, both external and internal to the cluster, contributed to its development. Our findings confirm that an ‘adaptive’ cycle approach, which focuses also on contingencies and external factors, appear to be appropriate for investigating the long-term evolution of clusters.

Despite being the main thriving force behind economic growth and industrial development, technological innovation remains highly concentrated on a handful of countries. It is therefore of a great interest to know how countries accumulate and develop their innovative capabilities, what kind of obstacles they need to overcome, and whether it is possible to identify opportunities to develop new areas of technological specialization. In this paper we analyze countries’ patterns of technological diversification and specialization along the development process. We provide evidence regarding the importance of existing technological capabilities and the relationship among technologies in shaping possible paths of technological development. We show that the likelihood of diversification is higher for those technologies that are related to countries’ existing profile of competences. Moreover, we show this effect to be stronger at earlier stages of development. Additionally, we show that countries tend to follow clear patterns of specialization along the development path, by moving towards more complex and valuable technologies.

The idea that skills, technology, and knowledge, are spatially concentrated, has a long academic tradition. Yet, only recently this hypothesis has been empirically formalized and corroborated at multiple spatial scales, for different economic activities, and for a diversity of institutional regimes. The new synthesis is an empirical principle describing the probability that a region enters---or exits---an economic activity as a function of the number of related activities present in that location. In this paper we summarize some of the recent empirical evidence that has generalized the principle of relatedness to a fact describing the entry and exit of products, industries, occupations, and technologies, at the national, regional, and metropolitan scales. We conclude by describing some of the policy implications and future avenues of research implied by this robust empirical principle.

The development of clusters has become a widespread tool used by many governments to increase the competitiveness and economic growth, since clusters have positive effect on the performance of affiliated firms, as well as on regional and industrial development (Ketels et al., 2006). In particular, clusters are the key building block in the development and implementation of smart specialisation strategies (European Commission, 2013), which represent the new orientation of regional innovation policies in Europe (Querejeta and Wilson, 2013). In the context of smart specialisation, cluster initiatives might be useful in the identification of priority domains, in engaging and mobilising actors to formulate the strategy, and in pushing the activities forward in the implementation. Many countries are combining specialisation strategies with clusters policies to bring industry and researchers together to establish strategic research and development directions and to fund projects that provide industry with the innovation and productivity tools needed to compete in global markets (OECD, 2012 ; European Commission, 2013 ; Querejeta and Wilson, 2013). However, there are many risks for smart specialisation strategies to be implemented effectively through the development of clusters, which is related to the choice of the right priorities and objectives, and to the implementation of adequate activities, modes of governance and collaboration among existing members (Querejeta and Wilson, 2013 ; Boschma, 2016). This paper investigates the development of Competitiveness Clusters in Croatia, which were created in 2013 as a part of a country’s Smart Specialization strategy in order to increase the country competitiveness and reduce its gaps with more advanced EU countries (MINGO, 2016). In doing so, this work relies upon an original dataset deriving from a survey on 250 cluster members. We contribute to the literature on cluster initiatives (e.g. Sölvell et al., 2003 ; Lindqvist et al., 2013 ; Maffioli et al., 2016), by distinguishing groups of competitiveness clusters along different sets of objectives, and by investigating how these differences are reflected in the process of management and governance, as well as in the perception of the most important dimensions of performance. The findings of this paper are expected to have important implications for policy-makers in Croatia and for competitiveness clusters themselves. In particular, results provide policy makers with useful insights on the perception of cluster members on what are the relevant objectives for the creation of clusters, and how the setting of different objectives might be translated into different modes of governance and different performance outcomes. This is especially important for the future revision of the framework of competitiveness clusters in terms of objectives, as well as for the evolution in the organisation and management processes of such initiatives.