Since the onset of the SARS‐CoV‐2 pandemic, the direct causative role of the virus in COVID‐19‐associated chilblains (CAC) has remained under question due to the low rate of positivity to SARS‐CoV‐2 ...nasopharyngeal polymerase chain reaction (PCR) and blood serology.1 Likewise, the suspected pivotal pathogenic role of upregulation of interferon type I (IFN‐I) is mainly indirectly supported by assessment of in situ immune response.2From April 2020 to January 2022, we prospectively assessed children and adults with new‐onset CAC seen in the dermatology, infectious diseases, and adult and paediatric emergency departments, as well as the intensive care unit of the University Hospital of Montpellier. The study was approved by the local institutional review board (ID: 202000442).
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Estimating the date at which an epidemic started in a country and the date at which it can end depending on interventions intensity are important to guide public health responses. Both are ...potentially shaped by similar factors including stochasticity (due to small population sizes), superspreading events, and memory effects. Focusing on COVID-19 epidemics, we develop and analyse mathematical models to explore how these three factors may affect early and final epidemic dynamics. Regarding the date of origin, we find limited effects on the mean estimates, but strong effects on their variances. Regarding the date of extinction following lock-down onset, mean values decrease with stochasticity or with the presence of superspreading events. These results underline the importance of accounting for heterogeneity in infection history and transmission patterns to make accurate predictions regarding epidemic temporal estimates.
BackgroundThe COVID-19 pandemic has led to an unprecedented daily use of RT-PCR tests. These tests are interpreted qualitatively for diagnosis, and the relevance of the test result intensity, i.e. ...the number of quantification cycles (Cq), is debated because of strong potential biases.AimWe explored the possibility to use Cq values from SARS-CoV-2 screening tests to better understand the spread of an epidemic and to better understand the biology of the infection.MethodsWe used linear regression models to analyse a large database of 793,479 Cq values from tests performed on more than 2 million samples between 21 January and 30 November 2020, i.e. the first two pandemic waves. We performed time series analysis using autoregressive integrated moving average (ARIMA) models to estimate whether Cq data information improves short-term predictions of epidemiological dynamics.ResultsAlthough we found that the Cq values varied depending on the testing laboratory or the assay used, we detected strong significant trends associated with patient age, number of days after symptoms onset or the state of the epidemic (the temporal reproduction number) at the time of the test. Furthermore, knowing the quartiles of the Cq distribution greatly reduced the error in predicting the temporal reproduction number of the COVID-19 epidemic.ConclusionOur results suggest that Cq values of screening tests performed in the general population generate testable hypotheses and help improve short-term predictions for epidemic surveillance.
Abstract
Multipartite viruses have segmented genomes and package each of their genome segments individually into distinct virus particles. Multipartitism is common among plant viruses, but why this ...apparently costly genome organization and packaging has evolved remains unclear. Recently Zhang and colleagues developed network epidemiology models to study the epidemic spread of multipartite viruses and their distribution over plant and animal hosts (Phys. Rev. Lett. 2019, 123, 138101). In this short commentary, we call into question the relevance of these results because of key model assumptions. First, the model of plant hosts assumes virus transmission only occurs between adjacent plants. This assumption overlooks the basic but imperative fact that most multipartite viruses are transmitted over variable distances by mobile animal vectors, rendering the model results irrelevant to differences between plant and animal hosts. Second, when not all genome segments of a multipartite virus are transmitted to a host, the model assumes an incessant latent infection occurs. This is a bold assumption for which there is no evidence to date, making the relevance of these results to understanding multipartitism questionable.
A two-species Lotka-Volterra model extended with an arbitrary number of indirect interactions through diffusible and renewable compounds is presented according to its relevance in microbial community ...modelling. After the determination of the system's fixed points and a short discussion over their local asymptotic stability, Lyapunov's second method is applied to derive a sufficient condition of global asymptotic stability. Biologically, this condition indicates the necessity for one microbial type to show strong self-inhibition and the compounds to be fastly replaced.
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Many hosts are infected by several parasite genotypes at a time. In these co-infected hosts, parasites can interact in various ways thus creating diverse within-host dynamics, making it difficult to ...predict the expression and the evolution of virulence. Moreover, multiple infections generate a combinatorial diversity of cotransmission routes at the host population level, which complicates the epidemiology and may lead to non-trivial outcomes. We introduce a new model for multiple infections, which allows any number of parasite genotypes to infect hosts and potentially coexist in the population. In our model, parasites affect one another's within-host growth through density-dependent interactions and by means of public goods and spite. These within-host interactions determine virulence, recovery and transmission rates, which are then integrated in a transmission network. We use analytical solutions and numerical simulations to investigate epidemiological feedbacks in host populations infected by several parasite genotypes. Finally, we discuss general perspectives on multiple infections.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
During the COVID-19 pandemic, the field of mathematical epidemiology experienced an exceptional production and media coverage of its work. Even though data and knowledge on the emerging disease were ...patchy, a wide variety of models were developed and applied in unprecedented timeframes, with the aim of estimating the reproduction number, the starting date of the epidemic or the cumulative incidence, but also to explore different scenarios of non-pharmaceutical interventions. Their results have made a major contribution to epidemiological surveillance and informed public health policy decisions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Le champ de l’épidémiologie mathématique a connu, au cours de la pandémie de Covid-19, une production doublée d’une médiatisation exceptionnelle de ses travaux. Alors même que les données et les ...connaissances sur la maladie émergente étaient parcellaires, une grande diversité de modèles a été développée et appliquée dans des délais inédits, dans l’objectif d’estimer le nombre de reproduction, la date de début de l’épidémie ou l’incidence cumulée, mais aussi afin d’explorer différents scénarios d’interventions non pharmaceutiques. Leurs résultats ont largement contribué à l’épidémiosurveillance et éclairé la prise de décisions relatives aux politiques de santé publique.
During the COVID-19 pandemic, the field of mathematical epidemiology experienced an exceptional production and media coverage of its work. Even though data and knowledge on the emerging disease were patchy, a wide variety of models were developed and applied in unprecedented timeframes, with the aim of estimating the reproduction number, the starting date of the epidemic or the cumulative incidence, but also to explore different scenarios of non-pharmaceutical interventions. Their results have made a major contribution to epidemiological surveillance and informed public health policy decisions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Understanding Ebola virus (EBOV) virulence evolution not only is timely but also raises specific questions because it causes one of the most virulent human infections and it is capable of ...transmission after the death of its host. Using a compartmental epidemiological model that captures three transmission routes (by regular contact, via dead bodies and by sexual contact), we infer the evolutionary dynamics of case fatality ratio on the scale of an outbreak and in the long term. Our major finding is that the virus's specific life cycle imposes selection for high levels of virulence and that this pattern is robust to parameter variations in biological ranges. In addition to shedding a new light on the ultimate causes of EBOV's high virulence, these results generate testable predictions and contribute to informing public health policies. In particular, burial management stands out as the most appropriate intervention since it decreases the R0 of the epidemics, while imposing selection for less virulent strains.
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