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

SOT: Sliced-Optimal-Transport-Sampling

Source code of the sampler proposed in Sliced Optimal Transport Sampling, Loïs Paulin, Nicolas Bonneel, David Coeurjolly, Jean-Claude Iehl, Antoine Webanck, Mathieu Desbrun, Victor Ostromoukhov, ACM Trans. on Graphics, SIGGRAPH 2020

Sliced optimal transport sampling

In this paper, we introduce a numerical technique to generate sample distributions in arbitrary dimension for improved accuracy of Monte Carlo integration. We point out that optimal transport offers theoretical bounds on Monte Carlo integration error, and that the recently-introduced numerical framework of sliced optimal transport (SOT) allows us to formulate a novel and efficient approach to generating well-distributed high-dimensional pointsets. The resulting sliced optimal transport sampling, solely involving repeated 1D solves, is particularly simple and efficient for the common case of a uniform density over a d-dimensional ball. We also construct a volume-preserving map from a d-ball to a d-cube (generalizing the Shirley-Chiu mapping to arbitrary dimensions) to offer fast SOT sampling over d-cubes. We provide ample numerical evidence of the improvement in Monte Carlo integration accuracy that SOT sampling brings compared to existing QMC techniques, and derive a projective variant for rendering which rivals, and at times outperforms, current sampling strategies using low-discrepancy sequences or optimized samples

SOT: Sliced-Optimal-Transport-Sampling

Source code of the sampler proposed in Sliced Optimal Transport Sampling, Loïs Paulin, Nicolas Bonneel, David Coeurjolly, Jean-Claude Iehl, Antoine Webanck, Mathieu Desbrun, Victor Ostromoukhov, ACM Trans. on Graphics, SIGGRAPH 2020

SOT: Sliced-Optimal-Transport-Sampling

Source code of the sampler proposed in Sliced Optimal Transport Sampling, Loïs Paulin, Nicolas Bonneel, David Coeurjolly, Jean-Claude Iehl, Antoine Webanck, Mathieu Desbrun, Victor Ostromoukhov, ACM Trans. on Graphics, SIGGRAPH 2020

Sliced Optimal Transport Sampling

International audienceError Whitenoise DartThrowing Sobol Ours White noise Dart throwing Sobol Ours Fig. 1. Sliced Optimal Transport Sampling. Global illumination of a scene (top left, San Miguel) requires integrating radiance over a high-dimensional space of light paths. The projective variant of our sliced optimal transport (SOT) sampling technique, leveraging the particular nature of integral evaluation in rendering and further combined with a micro-Cranley-Patterson rotation per pixel, outperforms standard Monte Carlo and Quasi-Monte Carlo techniques, exhibiting less noise and no structured artifact (top right, 32spp) while offering a better spatial distribution of error (bottom right, errors from blue (small) to red (large)). Moreover, our projective SOT sampling produces better convergence of the mean absolute error for the central 7×7 zone of the highlighted reference window as a function of the number of samples per pixel (from 4spp to 4096spp, bottom-left graph) in the case of indirect lighting with one bounce. In this paper, we introduce a numerical technique to generate sample distributions in arbitrary dimension for improved accuracy of Monte Carlo integration. We point out that optimal transport offers theoretical bounds on Monte Carlo integration error, and that the recently-introduced numerical framework of sliced optimal transport (SOT) allows us to formulate a novel and efficient approach to generating well-distributed high-dimensional pointsets. The resulting sliced optimal transport sampling, solely involving repeated 1D solves, is particularly simple and efficient for the common case of a uniform density over a d-dimensional ball. We also construct a volume-preserving map from a d-ball to a d-cube (generalizing the Shirley-Chiu mapping to arbitrary dimensions) to offer fast SOT sampling over d-cubes. We provide ample numerical evidence of the improvement in Monte Carlo integration accuracy that SOT sampling brings compared to existing QMC techniques, and derive a projective variant for rendering which rivals, and at times outperforms, current sampling strategies using low-discrepancy sequences or optimized samples

Clinical, laboratory and ultrasonographic findings differentiating low-grade intestinal T-cell lymphoma from lymphoplasmacytic enteritis in cats

BACKGROUND: Low‐grade intestinal T‐cell lymphoma (LGITL) is the most common intestinal neoplasm in cats. Differentiating LGITL from lymphoplasmacytic enteritis (LPE) is challenging because clinical signs, laboratory results, diagnostic imaging findings, histology, immunohistochemistry, and clonality features may overlap. OBJECTIVES: To evaluate possible discriminatory clinical, laboratory and ultrasonographic features to differentiate LGITL from LPE. ANIMALS: Twenty‐two cats diagnosed with LGITL and 22 cats with LPE based upon histology, immunohistochemistry, and lymphoid clonality. METHODS: Prospective, cohort study. Cats presented with clinical signs consistent with LGITL or LPE were enrolled prospectively. All data contributing to the diagnostic evaluation was recorded. RESULTS: A 3‐variable model (P < .001) consisting of male sex (P = .01), duration of clinical signs (P = .01), and polyphagia (P = .03) and a 2‐variable model (P < .001) including a rounded jejunal lymph node (P < .001) and ultrasonographic abdominal effusion (P = .04) were both helpful to differentiate LGITL from LPE. CONCLUSIONS AND CLINICAL IMPORTANCE: Most clinical signs and laboratory results are similar between cats diagnosed with LGITL and LPE. However, male sex, a longer duration of clinical signs and polyphagia might help clinicians distinguish LGITL from LPE. On ultrasonography, a rounded jejunal lymph node, and the presence of (albeit small volume) abdominal effusion tended to be more prevalent in cats with LGITL. However, a definitive diagnosis requires comprehensive histopathologic and phenotypic assessment

Lymphome intestinal de bas grade félin : validation d’un modèle spontané et émergent illustrant les lymphoproliférations digestives indolentes à cellules T de l’homme

Indolent T-cell lymphoproliferative disorder of the GI tract (GI-TLPD) is a rare human gastrointestinal T cell lymphoma, with no therapeutic consensus. Meanwhile, an emerging indolent GI lymphoma affecting the ageing cat (T-cell low grade intestinal lymphoma ; T-LGIL) has been reported by the veterinary community. T-LGIL entity was prospectively defined at the clinical, paraclinical, histopathological and molecular levels in order to validate a potential model for the human disease. New histopathologic and immunohistochemical criteria were defined. Clonality analysis showed mainly monoclonal TCR rearrangement. The second part of the study led us to describe discriminating criteria to differentiate T-LGIL from lymphoplasmacytic enteritis. A new lymphomagenesis model was therefore suggested, evoking a continuity between an intestinal chronic antigenic stimulation and a clonal emergence of small T-cell lymphocytes within the intestinal mucosa. In conclusion, we assume that feline T-LGIL is a relevant model to better characterize human GI-TLPD.Les lymphoproliférations à cellules T du tractus gastro-intestinal (GI-TLPD) sont des lymphomes T rares chez l’Homme pour lesquels aucun consensus thérapeutique n’est établi. Par ailleurs, une lymphoprolifération digestive indolente à cellules T (T-LGIL) émergente est décrite dans l’espèce féline. La physiopathologie de ces entités est mal définie. Dans un premier temps, nous avons prospectivement analysé des prélèvements lésionnels chez 22 chats présentant un T-LGIL sur les plans clinique, paraclinique, histopathologique et moléculaire. Nos résultats valident que ce modèle animal est pertinent pour l’étude de la maladie humaine. Dans l’autre partie du travail, notre objectif a été l’identification de critères discriminant les lymphoproliférations indolentes félines des entérites lymphoplasmocytaires, ce diagnostic différentiel étant un défi chez le chat. Nous avons établi de nouveaux critères histologiques et immunohistochimiques. Un modèle de lymphomagenèse a été proposé : il repose sur un continuum entre une entéropathie inflammatoire chronique et l’émergence de clones néoplasiques T au sein de la muqueuse intestinale.Freiche Valérie, Cordonnier-Lefort Nathalie, Paulin Mathieu-Victor, Huet Hélène, Turba Maria-Elena, Macintyre Elizabeth, Malamut Georgia, Cerf-Bensussan Nadine, Molina Thierry Jo, Hermine Olivier, Bruneau Julie, Couronné Lucile. Lymphome intestinal de bas grade félin : validation d’un modèle spontané et émergent illustrant les lymphoproliférations digestives indolentes à cellules T de l’homme. In: Bulletin de l'Académie Vétérinaire de France tome 173, 2020. pp. 9-19

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