Africa’s response to the COVID-19 pandemic : A review of the nature of the virus, impacts and implications for preparedness

Background: COVID-19 continues to wreak havoc in different countries across the world, claiming thousands of lives, increasing morbidity and disrupting lifestyles. The global scientific community is in urgent need of relevant evidence, to understand the challenges and knowledge gaps, as well as the opportunities to contain the spread of the virus. Considering the unique socio-economic, demographic, political, ecological and climatic contexts in Africa, the responses which may prove to be successful in other regions may not be appropriate on the continent. This paper aims to provide insight for scientists, policy makers and international agencies to contain the virus and to mitigate its impact at all levels. Methods: The Affiliates of the African Academy of Sciences (AAS), came together to synthesize the current evidence, identify the challenges and opportunities to enhance the understanding of the disease. We assess the potential impact of this pandemic and the unique challenges of the disease on African nations. We examine the state of Africa’s preparedness and make recommendations for steps needed to win the war against this pandemic and combat potential resurgence. Results: We identified gaps and opportunities among cross-cutting issueswhich must be addressed or harnessed in this pandemic. Factors such as the nature of the virus and the opportunities for drug targeting, point of care diagnostics, health surveillance systems, food security, mental health, xenophobia and gender-based violence, shelter for the homeless, water and sanitation, telecommunications challenges, domestic regional coordination and financing. Conclusion: Based on our synthesis of the current evidence, while there are plans for preparedness in several African countries, there are significant limitations. A multi-sectoral efforts from the science, education, medical, technology, communication, business, and industry sectors, as well as local communities, must work collaboratively to assist countries in order to win this fight

DataSHIELD: Taking the analysis to the data, not the data to the analysis

\ua9 The Author 2014; all rights reserved. Background: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK\u27s proposed \u27care.data\u27 initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Methods: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Results: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. Conclusions: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis

Clear correlation of genotype with disease phenotype in very-long-chain acyl-CoA dehydrogenase deficiency.

Very-long-chain acyl-CoA dehydrogenase (VLCAD) catalyzes the initial rate-limiting step in mitochondrial fatty acid beta-oxidation. VLCAD deficiency is clinically heterogenous, with three major phenotypes: a severe childhood form, with early onset, high mortality, and high incidence of cardiomyopathy; a milder childhood form, with later onset, usually with hypoketotic hypoglycemia as the main presenting feature, low mortality, and rare cardiomyopathy; and an adult form, with isolated skeletal muscle involvement, rhabdomyolysis, and myoglobinuria, usually triggered by exercise or fasting. To examine whether these different phenotypes are due to differences in the VLCAD genotype, we investigated 58 different mutations in 55 unrelated patients representing all known clinical phenotypes and correlated the mutation type with the clinical phenotype. Our results show a clear relationship between the nature of the mutation and the severity of disease. Patients with the severe childhood phenotype have mutations that result in no residual enzyme activity, whereas patients with the milder childhood and adult phenotypes have mutations that may result in residual enzyme activity. This clear genotype-phenotype relationship is in sharp contrast to what has been observed in medium-chain acyl-CoA dehydrogenase deficiency, in which no correlation between genotype and phenotype can be established