Long-lasting brain fog is related with severity clusters of symptoms in COVID-19 patients. Background: COVID-19 patients may experience lon-lasting symptoms from weeks to even months. Aim: to evaluate long-term cognitive impairment based on the severity

Background: COVID-19 patients may experience lon-lasting symptoms from weeks to even months. Aim: To evaluate long-term cognitive impairment based on the severity of symptoms of COVID-19 infection in a primary health system setting. Material and methods: From a database of 363 patients, 83 cases aged 47 +or- 15 years, (58% females) were selected from June to August 2020. In patients who survived the virus, 24 infection-related symptoms were collected to create three severity clusters (mild, moderate, and severe). The follow-up time was at least seven months. Comparing the first two clusters with the severe cluster, the existence of brain fog and risk factors (obesity, hypertension, diabetes, chronic lung disease, and hypothyroidism) were analyzed. Results: Thirty-one patients (37%) had persistent symptoms lasting up to 240 days. Fifty-one patients (61%) experienced brain fog. Concentration was affected by symptom severity (odds ratio [OR] 3.63, 95% confidence interval [CI] 1.26-10.46, p = 0.02). Short- or long-term memory loss was not affected. Moreover, symptom severity was related to brain fog (OR 3.16, 95% CI 1.05-9.51, p = 0.04). Patients with persistent symptoms had a concentration impairment associated with severity patterns (OR 24.3, 95% CI 1.73-340.11, p = 0.03). Conclusions: Brain fog is associated with symptom severity in COVID-19 survivors and lasts for more than eight months.

IMMIGRANT FLOWS AND SARS-COV-2 INFECTIONS IN THE UNITED STATES

BACKGROUND: The relationship between immigrant inflow and SARSCOV- 2 spread in the United States has driven much political discussion and policy, including the implementation of Title 42 by the Centers for Disease Control, effectively banning asylum claims at the US Southwestern Border. The implemenation of Title 42 has led to significant outcry from public health researchers and policymakers alike. To examine the relationship between SARS- COV-2 spread and immigrant inflow, we compared 2020-2021 immigrant flows (from US Border Patrol estimates of Southwest US border crossings and a US seasonal guest worker program) to county-level SARSCOV- 2 rates. METHODS: We drew immigraiton data from US Border Patrol (USBP) 2020-2021 estimates of successful Southwest US Border crossings and from Department of Labor data on H2-A visa allotments for agricultural guest workers. The primary outcome is the one-month lagged natural logarithm of new cases per 100,000 persons at the county level. After arithmetic manipulation, the primary outcome can be interpreted as the percentage change in one-month lagged county- level SARS-COV-2 cases per 100,000 persons as a function of each additional immigrant entrant in the same county (i.e., semielasticity). We controlled for the vaccination rate within a county as well as the interaction between the presence of state-mandated facemask mandates, restaurant closures and gym closures. We analyzed the primary outcome as a linear regression with county- and month-level fixed effects. Multiple robustness checks tested various assumptions undertaken in this analysis. RESULTS:We drew data from 3,144 counties and geographic units, 2,077 of which received immigrants over the course of the study. Among immigrant receiving counties, themedian immigrant inflow was 41 (IQR 13, 139) persons over the period studied. The RioGrandeValley border counties of southeastern Texas received the most immigrants during this period, with an average monthly immigrant inflow of 19,526, peaking in 2021. Under our primary model there was a statistically insignificant 0.0000189% decrease in SARSCOV- 2 cases per 100,000 persons for each additional immigrant (p=0.231, 95% CI -0.0000499%, 0.0000120%). When restricted to H-2A guest workers only, there is a statistically insignificant 0.000197% decrease in SARS-COV-2 cases per 100,000 persons for each additional immigrant (p=0.09, 95% CI -0.00043%, 0.0000298). When restricted to Southwest border crossings alone, there was a statistically significant 0.0000254% increase in SARS-COV-2 cases per 100,000 persons for each additional immigrant (p=0.005, 95% CI 0.0000107%, 0.0000401%). However, the result became insignificant after excluding 2021 Rio Grande Valley sector crossings (0.0000368, p=0.116, 95 CI% -0.0000116, 0.0000852). CONCLUSIONS: The contriibution of immigant inflows to the SARS-COV- 2 pandemic in the United States is small, largely nonstatistically significant, and when statistically significant, is not robust to alternative specifications.

Machine Learning Sustainable Competitiveness for Global Recovery

The unexpected appearance and expansion of the pandemic caused by COVID-19 have shown that both developed and less developed countries need strategic, scientific-technological capacities and an innovation ecosystem to respond quickly to these challenges. The objective of this research is to analyze the potential correlation between competitiveness and sustainable development for a global recovery. To carry out the study, five global indexes were considered: competitiveness, sustainability, innovation, impunity, and human development which were analyzed with a mixed-method approach, quantitative and qualitative analysis. Organizational and government leaders are facing significant collateral effects of the health pandemic including economic recession and social development regression;therefore, the road to recovery requires they work toward sustainable development to reach desired competitiveness. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Business Model Innovation and Decision-Making for the Productive Sector in Times of Crisis

The pandemic caused by COVID-19 has affected all companies and their business models. For this reason, firms have needed to redesign these models, focusing on customer value proposition. The purpose of this research is to analyze Business Model Innovation (BMI) for decision-making. The methodological strategy is carried out through Bayesian networks. A model is made in which the main elements that make up a BMI are identified and quantified, which impact better decision-making to properly manage the proposal value for customers, technology, and achieve innovation. Evidence shows that the construction of BMI requires a model that mainly considers the relationships between variables such as knowledge architecture, implementation operation, change and evolution, and agile response. BMI will apply to organizations to the extent that it contemplates variables related to customer service and attention, as well as those related to innovation in organizations, attention, and those related to innovation in organizations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Finally Back to Campus? Motivations for Facemask Adoption in the Higher Education Sector

The COVID-19 pandemic caused an unprecedented crisis in the higher education sector through campuses closing worldwide. To contain the disease, authorities required their citizens to wear facemasks in public spaces. As universities return to in-person instruction, they will probably require all students to wear facemasks while on-campus. This study examined antecedents of voluntary adoption of facemasks through a survey of students enrolled in Mexico City universities in the Fall of 2020. It was hypothesized that Social Value Orientation (SVO) and Trust would be positively related to facemask adoption. Findings revealed that among students, wearing a facemask reflects distinct conducts depending on the social context. Regression results show that SVO and Trust significantly predict facemask use but only in some contexts, giving partial support to hypotheses. A key implication is that public health communications should avoid general messages recommending facemasks, and craft more nuanced appeals targeting specific social contexts. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Impact of COVID-19 infection on the outcome of patients with ischemic stroke

Background and Aims: We evaluated whether stroke severity, functional outcome and mortality are different in patients with ischemic stroke with or without COVID-19 infection. Methods: A prospective, observational, multicentre cohort study in Catalonia, Spain. Recruitment was consecutive from mid-March to mid-May 2020. Patients had had an acute ischemic stroke within 48 hours and a previous modified Rankin scale (mRS) score of 0 to 3. We collected demographic data, vascular risk factors, prior mRS score, NIHSS score, rate of reperfusion therapies, logistics and metrics. Primary end-point was functional outcome at 3 months. Favourable outcome was defined depending on the previous mRS score. Secondary outcome was mortality at 3 months. We performed mRS shift and multivariate analyses. Results: We evaluated 701 patients (mean age 72.3±13.3 years, 60.5% men), and 91 (13%) had COVID-19 infection. Median baseline NIHSS score was higher in COVID-19 patients compared to patients without COVID-19 [8 (3-18) vs 6 (2-14), p=0.049)]. Proportion of patients with a favourable functional outcome was 33.7% in the COVID-19 and 47% in the non-COVID-19 group. However, after a multivariate logistic regression analysis, COVID-19 infection did not increase the probability of unfavourable functional outcome. Mortality rate was 39.3% among COVID-19 patients and 16.1% in the non-COVID-19 group. In the multivariate logistic regression analysis, COVID-19 infection was a risk factor for mortality (HR 3.14 (95% CI, 2.10-4.71;p<0.001). Conclusions: Patients with ischemic stroke and COVID-19 infection have more severe strokes and higher mortality than stroke patients without COVID-19 infection. However, functional outcome is comparable in both groups.

Increased in hospital mortality in stroke during the COVID-19 era and related factors

Background and Aims: The COVID-19 pandemic has had enormous implications for stroke care. We aim to analyze its impact in stroke outcomes and mortality in two comprehensive stroke centers (CSC) from the Catalonian network. Methods:We studied all stroke patients admitted during 2020 and compared them with the admissions of 2019. Clinical and functional outcomes (mRS at discharge, in-hospital complications and mortality) were analyzed. Related factors, including SARS-CoV-2 infection, were determined. Results: A total of 2674 stroke patients were admitted in 2020, and 2652 during 2019. A higher number of unknown-onset strokes (45% vs 40%, p<0.01), ASPECTS<7 (8.3% vs 5.7%, p=0.03) and longer time from symptoms-onset to hospital-admission (median: 337 vs. 272min, p<0.01) were detected during 2020. Conversely, no significant differences appeared in stroke code activation (61.5% vs 62.5%), stroke subtype (ICH 9.1% vs 8.9%), severity (median NIHSS: 4 vs 5), pre-morbid mRS (mRS<3 81.8% vs 80.2%) or other relevant clinical characteristics nor reperfusion treatments (23.8% vs 23.9%). In-hospital complications and discharge-mRS were similar. However, we observed higher inhospital mortality in 2020 (9.6 vs 6.6%, p<0.001). An adjusted regression model pointed pre-morbid mRS, baseline NIHSS, ASPECTS and inhospital complications (OR 1.26, 1.14, 0.87 and 1.38 respectively, p<0.01) as independent predictors of mortality. SARS-CoV-2 infection (3.7% of strokes in 2020) was not predictor of mortality;in fact, these patients showed similar outcomes than the remaining 2020 strokes. Conclusions: The increased in-hospital mortality detected in 2020 in our series may be due to pandemic-related delays in stroke detection and hospital arrival rather than the direct effect of COVID-19.

Stroke etiologies in patients with COVID-19: the svin COVID-19 multinational registry

Background and purpose: Coronavirus disease 2019 (COVID-19) is associated with a small but clinically significant risk of stroke, the cause of which is frequently cryptogenic. In a large multinational cohort of consecutive COVID-19 patients with stroke, we evaluated clinical predictors of cryptogenic stroke, short-term functional outcomes and in-hospital mortality among patients according to stroke etiology. Methods: We explored clinical characteristics and short-term outcomes of consecutively evaluated patients 18 years of age or older with acute ischemic stroke (AIS) and laboratory-confirmed COVID- 19 from 31 hospitals in 4 countries (3/1/20-6/16/20). Results: Of the 14.483 laboratory-confirmed patients with COVID-19, 156 (1.1%) were diagnosed with AIS. Sixty-one (39.4%) were female, 84 (67.2%) white, and 88 (61.5%) were between 60-79 years of age. The most frequently reported etiology of AIS was cryptogenic (55/129, 42.6%), which was associated with significantly higher white blood cell count, c-reactive protein, and D-dimer levels than non-cryptogenic AIS patients (p</=0.05 for all comparisons). In a multivariable backward stepwise regression model estimating the odds of in-hospital mortality, cryptogenic stroke mechanism was associated with a fivefold greater odds in-hospital mortality than strokes due to any other mechanism (adjusted OR 5.16, 95%CI 1.41-18.87, p=0.01). In that model, older age (aOR2.05 per decade, 95%CI 1.35-3.11, p<0.01) and higher baseline NIHSS (aOR 1.12, 95%CI 1.02-1.21, p=0.01) were also independently predictive of mortality. Conclusions: Our findings suggest that cryptogenic stroke among COVID-19 patients may berelated to more severe disease and carries a significant risk of early mortality.

Experience and management of two paediatric patients infected with SARS-CoV-2 with major burn injuries in an intensive care unit

SARS-CoV-2 infection is rapidly disseminating, leading to a world pandemics in which we are also affected. In San Borja Peruvian National Children Health Institute, which is the reference center for surgical pediatric patients, 106 patients infected with SARS-CoV-2 were hospitalized. Of them, 11 presented with burns and two had large burns. The viral infection was diagnosed using molecular testing. We present in detail the case of a pediatric seven-year old patient who had large burns and was taken care of in the intensive care unit. She had asymptomatic SARS-CoV-2 infection, and her outcome was good, with a good prognosis, and she recovered completely and uneventfully. On the other hand, COVID-19 may present as a severe disease leading to a multi- systemic inflammatory syndrome with some uncommon clinical manifestations which affect its prognosis, as it was the case with another seven-month old patient who passed away in spite of having received specialized and timely therapy.