133 research outputs found
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers
Over the last decade, the demand for better segmentation and classification
algorithms in 3D spaces has significantly grown due to the popularity of new 3D
sensor technologies and advancements in the field of robotics. Point-clouds are
one of the most popular representations to store a digital description of 3D
shapes. However, point-clouds are stored in irregular and unordered structures,
which limits the direct use of segmentation algorithms such as Convolutional
Neural Networks. The objective of our work is twofold: First, we aim to provide
a full analysis of the PointNet architecture to illustrate which features are
being extracted from the point-clouds. Second, to propose a new network
architecture called IPC-Net to improve the state-of-the-art point cloud
architectures. We show that IPC-Net extracts a larger set of unique features
allowing the model to produce more accurate segmentations compared to the
PointNet architecture. In general, our approach outperforms PointNet on every
family of 3D geometries on which the models were tested. A high generalisation
improvement was observed on every 3D shape, especially on the rockets dataset.
Our experiments demonstrate that our main contribution, inter-point activation
on the network's layers, is essential to accurately segment 3D point-clouds
A prospect on the use of antiviral drugs to control local outbreaks of COVID-19
Background: Current outbreaks of COVID-19 are threatening the health care systems of several countries around the world. Control measures, based on isolation, contact tracing, and quarantine, can decrease and delay the burden of the ongoing epidemic. With respect to the ongoing COVID-19 epidemic, recent modeling work shows that these interventions may be inadequate to control local outbreaks, even when perfect isolation is assumed. The effect of infectiousness prior to symptom onset combined with asymptomatic infectees further complicates the use of contact tracing. We aim to study whether antivirals, which decrease the viral load and reduce infectiousness, could be integrated into control measures in order to augment the feasibility of controlling the epidemic. Methods: Using a simulation-based model of viral transmission, we tested the efficacy of different intervention measures to control local COVID-19 outbreaks. For individuals that were identified through contact tracing, we evaluate two procedures: monitoring individuals for symptoms onset and testing of individuals. Additionally, we investigate the implementation of an antiviral compound combined with the contact tracing process. Results: For an infectious disease in which asymptomatic and presymptomatic infections are plausible, an intervention measure based on contact tracing performs better when combined with testing instead of monitoring, provided that the test is able to detect infections during the incubation period. Antiviral drugs, in combination with contact tracing, quarantine, and isolation, result in a significant decrease of the final size and the peak incidence, and increase the probability that the outbreak will fade out. Conclusion: In all tested scenarios, the model highlights the benefits of control measures based on the testing of traced individuals. In addition, the administration of an antiviral drug, together with quarantine, isolation, and contact tracing, is shown to decrease the spread of the epidemic. This control measure could be an effective strategy to control local and re-emerging outbreaks of COVID-19.publishersversionpublishe
Time to harmonize dengue nomenclature and classification
Dengue virus (DENV) is estimated to cause 390 million infections per year worldwide. A quarter of these infections manifest clinically and are associated with a morbidity and mortality that put a significant burden on the affected regions. Reports of increased frequency, intensity, and extended geographical range of outbreaks highlight the virus's ongoing global spread. Persistent transmission in endemic areas and the emergence in territories formerly devoid of transmission have shaped DENV's current genetic diversity and divergence. This genetic layout is hierarchically organized in serotypes, genotypes, and sub-genotypic clades. While serotypes are well defined, the genotype nomenclature and classification system lack consistency, which complicates a broader analysis of their clinical and epidemiological characteristics. We identify five key challenges: (1) Currently, there is no formal definition of a DENV genotype; (2) Two different nomenclature systems are used in parallel, which causes significant confusion; (3) A standardized classification procedure is lacking so far; (4) No formal definition of sub-genotypic clades is in place; (5) There is no consensus on how to report antigenic diversity. Therefore, we believe that the time is right to re-evaluate DENV genetic diversity in an essential effort to provide harmonization across DENV studies.publishersversionpublishe
Different forms of superspreading lead to different outcomes:heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2
Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes—with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity
the Portuguese case
BACKGROUND: Portugal has one of the most severe HIV-1 epidemics in Western Europe. Two subtypes circulate in parallel since the beginning of the epidemic. Comparing their transmission patterns and its association with transmitted drug resistance (TDR) is important to pinpoint transmission hotspots and to develop evidence-based treatment guidelines. METHODS: Demographic, clinical and genomic data were collected from 3599 HIV-1 naive patients between 2001 and 2014. Sequences obtained from drug resistance testing were used for subtyping, TDR determination and transmission clusters (TC) analyses. RESULTS: In Portugal, transmission of subtype B was significantly associated with young males, while transmission of subtype G was associated with older heterosexuals. In Portuguese originated people, there was a decreasing trend both for prevalence of subtype G and for number of TCs in this subtype. The active TCs that were identified (i.e. clusters originated after 2008) were associated with subtype B-infected males residing in Lisbon. TDR was significantly different when comparing subtypes B (10.8% [9.5-12.2]) and G (7.6% [6.4-9.0]) (p = 0.001). DISCUSSION: TC analyses shows that, in Portugal, the subtype B epidemic is active and fueled by young male patients residing in Lisbon, while transmission of subtype G is decreasing. Despite similar treatment rates for both subtypes in Portugal, TDR is significantly different between subtypes.publishersversionpublishe
Serological screening in a large-scale municipal survey in Cascais, Portugal, during the first waves of the COVID-19 pandemic: lessons for future pandemic preparedness efforts
BackgroundSerological surveys for SARS-CoV-2 were used early in the COVID-19 pandemic to assess epidemiological scenarios. In the municipality of Cascais (Portugal), serological testing combined with a comprehensive socio-demographic, clinical and behavioral questionnaire was offered to residents between May 2020 and beginning of 2021. In this study, we analyze the factors associated with adherence to this municipal initiative, as well as the sociodemographic profile and chronic diseases clinical correlates associated to seropositivity. We aim to contribute with relevant information for future pandemic preparedness efforts.MethodsThis was a cross-sectional study with non-probabilistic sampling. Citizens residing in Cascais Municipality went voluntarily to blood collection centers to participate in the serological survey. The proportion of participants, stratified by socio-demographic variables, was compared to the census proportions to identify the groups with lower levels of adherence to the survey. Univariate and multivariate logistic regression were used to identify socio-demographic, clinical and behavioral factors associated with seropositivity.ResultsFrom May 2020 to February 2021, 19,608 participants (9.2% of the residents of Cascais) were included in the study. Based on the comparison to census data, groups with lower adherence to this survey were men, the youngest and the oldest age groups, individuals with lower levels of education and unemployed/inactive. Significant predictors of a reactive (positive) serological test were younger age, being employed or a student, and living in larger households. Individuals with chronic diseases generally showed lower seroprevalence.ConclusionThe groups with low adherence to this voluntary study, as well as the socio-economic contexts identified as more at risk of viral transmission, may be targeted in future pandemic situations. We also found that the individuals with chronic diseases, perceiving higher risk of serious illness, adopted protective behaviors that limited infection rates, revealing that health education on preventive measures was effective for these patients
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