The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT

International audienceIntroduction While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (<20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets

Table_1_Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT.xls

IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (Results, Discussion, ConclusionThe examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.</p

DataSheet_1_Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT.docx

IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (Results, Discussion, ConclusionThe examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.</p

COVID-19 outcomes in patients with inflammatory rheumatic and musculoskeletal diseases treated with rituximab: a cohort study

International audienceBackground: Various observations have suggested that the course of COVID-19 might be less favourable in patients with inflammatory rheumatic and musculoskeletal diseases receiving rituximab compared with those not receiving rituximab. We aimed to investigate whether treatment with rituximab is associated with severe COVID-19 outcomes in patients with inflammatory rheumatic and musculoskeletal diseases.Methods: In this cohort study, we analysed data from the French RMD COVID-19 cohort, which included patients aged 18 years or older with inflammatory rheumatic and musculoskeletal diseases and highly suspected or confirmed COVID-19. The primary endpoint was the severity of COVID-19 in patients treated with rituximab (rituximab group) compared with patients who did not receive rituximab (no rituximab group). Severe disease was defined as that requiring admission to an intensive care unit or leading to death. Secondary objectives were to analyse deaths and duration of hospital stay. The inverse probability of treatment weighting propensity score method was used to adjust for potential confounding factors (age, sex, arterial hypertension, diabetes, smoking status, body-mass index, interstitial lung disease, cardiovascular diseases, cancer, corticosteroid use, chronic renal failure, and the underlying disease [rheumatoid arthritis vs others]). Odds ratios and hazard ratios and their 95% CIs were calculated as effect size, by dividing the two population mean differences by their SD. This study is registered with ClinicalTrials.gov, NCT04353609.Findings: Between April 15, 2020, and Nov 20, 2020, data were collected for 1090 patients (mean age 55·2 years [SD 16·4]); 734 (67%) were female and 356 (33%) were male. Of the 1090 patients, 137 (13%) developed severe COVID-19 and 89 (8%) died. After adjusting for potential confounding factors, severe disease was observed more frequently (effect size 3·26, 95% CI 1·66-6·40, p=0·0006) and the duration of hospital stay was markedly longer (0·62, 0·46-0·85, p=0·0024) in the 63 patients in the rituximab group than in the 1027 patients in the no rituximab group. 13 (21%) of 63 patients in the rituximab group died compared with 76 (7%) of 1027 patients in the no rituximab group, but the adjusted risk of death was not significantly increased in the rituximab group (effect size 1·32, 95% CI 0·55-3·19, p=0·53).Interpretation: Rituximab therapy is associated with more severe COVID-19. Rituximab will have to be prescribed with particular caution in patients with inflammatory rheumatic and musculoskeletal diseases

Severity of COVID-19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID-19 cohort of 694 patients

International audienceObjectives: There is little known about the impact of SARS-CoV-2 on patients with inflammatory rheumatic and musculoskeletal diseases (iRMD). We examined epidemiological characteristics associated with severe disease, then with death. We also compared mortality between patients hospitalised for COVID-19 with and without iRMD.Methods: Individuals with suspected iRMD-COVID-19 were included in this French cohort. Logistic regression models adjusted for age and sex were used to estimate adjusted ORs and 95% CIs of severe COVID-19. The most significant clinically relevant factors were analysed by multivariable penalised logistic regression models, using a forward selection method. The death rate of hospitalised patients with iRMD-COVID-19 (moderate-severe) was compared with a subset of patients with non-iRMD-COVID-19 from a French hospital matched for age, sex, and comorbidities.Results: Of 694 adults, 438 (63%) developed mild (not hospitalised), 169 (24%) moderate (hospitalised out of the intensive care unit (ICU) and 87 (13%) severe (patients in ICU/deceased) disease. In multivariable imputed analyses, the variables associated with severe infection were age (OR=1.08, 95% CI: 1.05-1.10), female gender (OR=0.45, 95% CI: 0.25-0.80), body mass index (OR=1.07, 95% CI: 1.02-1.12), hypertension (OR=1.86, 95% CI: 1.01-3.42), and use of corticosteroids (OR=1.97, 95% CI: 1.09-3.54), mycophenolate mofetil (OR=6.6, 95% CI: 1.47-29.62) and rituximab (OR=4.21, 95% CI: 1.61-10.98). Fifty-eight patients died (8% (total) and 23% (hospitalised)). Compared with 175 matched hospitalised patients with non-iRMD-COVID-19, the OR of mortality associated with hospitalised patients with iRMD-COVID-19 was 1.45 (95% CI: 0.87-2.42) (n=175 each group).Conclusions: In the French RMD COVID-19 cohort, as already identified in the general population, older age, male gender, obesity, and hypertension were found to be associated with severe COVID-19. Patients with iRMD on corticosteroids, but not methotrexate, or tumour necrosis factor alpha and interleukin-6 inhibitors, should be considered as more likely to develop severe COVID-19. Unlike common comorbidities such as obesity, and cardiovascular or lung diseases, the risk of death is not significantly increased in patients with iRMD