Analytical observational study evaluating global pandemic preparedness and the effectiveness of early COVID-19 responses in Ethiopia, Nigeria, Singapore, South Korea, Sweden, Taiwan, UK and USA.

OBJECTIVES: An analysis of early country-specific COVID-19 strategies and the impact of policies, healthcare resources and cultural influences on their effectiveness. DESIGN: Analytical observational study. SETTING: USA, UK, Sweden, South Korea, Singapore, Taiwan, Ethiopia and Nigeria. MAIN OUTCOME MEASURES: OxCGRT indices were used to quantify variations in governments' responses, and effectiveness was measured by the number of deaths as a proportion of the population. Hofstede's cultural dimensions, and the availability of healthcare resources, were analysed for their potential impact on effectiveness. RESULTS: Effective strategies reflect factors such as speed of governmental intervention, cultural norms, population demographics and available resources. While biases, confounders and lack of data at the beginning of the pandemic make inferences challenging, publicly available data suggest that South Korea, Singapore and Taiwan were most successful through rapid identification and isolation of cases, and effective contact tracing systems. CONCLUSION: The rapid spread of the highly transmissible SARS-CoV-2 virus took many countries by surprise and the delayed global response contributed to the severity of the COVID-19 pandemic. The speed at which strategies were implemented is highly correlated to the number of deaths. Factors such as cultural norms and healthcare resources impact effectiveness significantly, implying that implementation of a global 'one size fits all' approach is challenging. Global preparedness should focus on effective surveillance and preparedness strategies to enable timely identification and containment of future threats

Identifying and prioritizing uncertainties: patient and clinician engagement in the identification of research questions

Background To arrive at an agreed, prioritized ranking of treatment uncertainties in asthma that need further research, by developing a collaboration of patients, carers and clinicians, facilitated by the James Lind AllianceWorking Partnership between Asthma UK and the British Thoracic Society. Methods A four-step procedure: (1) establish a collaborative Working Partnership; (2) identify and collect treatment uncertainties by using a patient survey and analysing existing systematic reviews, clinical guidelines and query-answering services; (3) categorize uncertainties; and (4) convene a workshop using a nominal group process to establish a ranked prioritization of treatment uncertainties in asthma. Findings Agreement and rankings were reached for 10 treatment uncertainties. The highest was given to the uncertainty surrounding the adverse effects of inhaled and oral steroids. The top three priorities dealt with clinical management issues, where uncertainties still exist, namely concerns about the side effects of inhaled and oral steroids, how to manage asthma when other illnesses exist or how to rely on personal decisions in an ever-changing illness (self-management). Interpretation The key outcome is the generation of a prioritized list of treatment uncertainties in asthma, agreed by a collaboration of patients and health professionals, to inform the commissioning of new research. Such a large number of patient-identified treatment uncertainties had not previously been identified in the literature, an indication perhaps that asthma self-management is a neglected research area. Whether the results have an influence of research funding decisions is not yet known

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways