Seroprevalence and SARS-CoV-2 invasion in general populations: A scoping review over the first year of the pandemic.

Since the beginning of the COVID-19 pandemic, counting infected people has underestimated asymptomatic cases. This literature scoping review assessed the seroprevalence progression in general populations worldwide over the first year of the pandemic. Seroprevalence studies were searched in PubMed, Web of Science and medRxiv databases up to early April 2021. Inclusion criteria were a general population of all ages or blood donors as a proxy. All articles were screened for the title and abstract by two readers, and data were extracted from selected articles. Discrepancies were resolved with a third reader. From 139 articles (including 6 reviews), the seroprevalence estimated in 41 countries ranged from 0 to 69%, with a heterogenous increase over time and continents, unevenly distributed among countries (differences up to 69%) and sometimes among regions within a country (up to 10%). The seroprevalence of asymptomatic cases ranged from 0% to 31.5%. Seropositivity risk factors included low income, low education, low smoking frequency, deprived area residency, high number of children, densely populated centres, and presence of a case in a household. This review of seroprevalence studies over the first year of the pandemic documented the progression of this virus across the world in time and space and the risk factors that influenced its spread.

Seroprevalence of SARS-CoV-2, Symptom Profiles and Sero-Neutralization in a Suburban Area, France.

The World Health Organisation recommends monitoring the circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We investigated anti-SARS-CoV-2 total immunoglobulin (IgT) antibody seroprevalence and in vitro sero-neutralization in Nancy, France, in spring 2020. Individuals were randomly sampled from electoral lists and invited with household members over 5 years old to be tested for anti-SARS-CoV-2 (IgT, i.e., IgA/IgG/IgM) antibodies by ELISA (Bio-rad); the sero-neutralization activity was evaluated on Vero CCL-81 cells. Among 2006 individuals, the raw seroprevalence was 2.1% (95% confidence interval 1.5 to 2.9), was highest for 20- to 34-year-old participants (4.7% (2.3 to 8.4)), within than out of socially deprived area (2.5% vs. 1%, p = 0.02) and with than without intra-family infection (p < 10-6). Moreover, 25% of participants presented at least one COVID-19 symptom associated with SARS-CoV-2 positivity (p < 10-13), with highly discriminant anosmia or ageusia (odds ratio 27.8 [13.9 to 54.5]); 16.3% (6.8 to 30.7) of seropositive individuals were asymptomatic. Positive sero-neutralization was demonstrated in vitro for 31/43 seropositive subjects. Regarding the very low seroprevalence, a preventive effect of the lockdown in March 2020 can be assumed for the summer, but a second COVID-19 wave, as expected, could be subsequently observed in this poorly immunized population.

Background mortality drivers of European tree species: climate change matters.

Increases in tree mortality rates have been highlighted in different biomes over the past decades. However, disentangling the effects of climate change on the temporal increase in tree mortality from those of management and forest dynamics remains a challenge. Using a modelling approach taking tree and stand characteristics into account, we sought to evaluate the impact of climate change on background mortality for the most common European tree species. We focused on background mortality, which is the mortality observed in a stand in the absence of abrupt disturbances, to avoid confusion with mortality events unrelated to long-term changes in temperature and rainfall. We studied 372 974 trees including 7312 dead trees from forest inventory data surveyed across France between 2009 and 2015. Factors related to competition, stand characteristics, management intensity, and site conditions were the expected preponderant drivers of mortality. Taking these main drivers into account, we detected a climate change signal on 45% of the 43 studied species, explaining an average 6% of the total modelled mortality. For 18 out of the 19 species sensitive to climate change, we evidenced greater mortality with increasing temperature or decreasing rainfall. By quantifying the mortality excess linked to the current climate change for European temperate forest tree species, we provide new insights into forest vulnerability that will prove useful for adapting forest management to future conditions.

The individual's signature of telomere length distribution.

Mean telomere length in human leukocyte DNA samples reflects the different lengths of telomeres at the ends of the 23 chromosomes and in an admixture of cells. However, only rudimentary information is available regarding the distribution of telomere lengths in all chromosomes and the different cell types in leukocyte samples. Understanding the configuration of leukocyte telomere length distribution (LTLD) could be helpful in capturing intrinsic elements that are not provided by the mean leukocyte telomere length (mLTL). The objective of this study was to analyse LTLD and its temporal variation in adults. Leukocyte samples were donated on two occasions (8 years apart) by 72 participants in the ADELAHYDE study. Telomere length was measured by Southern blotting of the terminal restriction fragments. Individuals with comparable mLTLs displayed different shapes of LTLDs. Inter-individual variation in LTLD shape was much larger than intra-individual variation in LTLD shape between baseline and follow-up leukocyte samples. These results show an important individual stability of LTLD shape over time indicating that each individual has a characteristic LTLD signature.

The stochastic system approach for estimating dynamic treatments effect.

The problem of assessing the effect of a treatment on a marker in observational studies raises the difficulty that attribution of the treatment may depend on the observed marker values. As an example, we focus on the analysis of the effect of a HAART on CD4 counts, where attribution of the treatment may depend on the observed marker values. This problem has been treated using marginal structural models relying on the counterfactual/potential response formalism. Another approach to causality is based on dynamical models, and causal influence has been formalized in the framework of the Doob-Meyer decomposition of stochastic processes. Causal inference however needs assumptions that we detail in this paper and we call this approach to causality the "stochastic system" approach. First we treat this problem in discrete time, then in continuous time. This approach allows incorporating biological knowledge naturally. When working in continuous time, the mechanistic approach involves distinguishing the model for the system and the model for the observations. Indeed, biological systems live in continuous time, and mechanisms can be expressed in the form of a system of differential equations, while observations are taken at discrete times. Inference in mechanistic models is challenging, particularly from a numerical point of view, but these models can yield much richer and reliable results.

A general definition of influence between stochastic processes.

We extend the study of weak local conditional independence (WCLI) based on a measurability condition made by (Commenges and Gégout-Petit J R Stat Soc B 71:1-18) to a larger class of processes that we call D'. We also give a definition related to the same concept based on certain likelihood processes, using the Girsanov theorem. Under certain conditions, the two definitions coincide on D'. These results may be used in causal models in that we define what may be the largest class of processes in which influences of one component of a stochastic process on another can be described without ambiguity. From WCLI we can construct a concept of strong local conditional independence (SCLI). When WCLI does not hold, there is a direct influence while when SCLI does not hold there is direct or indirect influence. We investigate whether WCLI and SCLI can be defined via conventional independence conditions and find that this is the case for the latter but not for the former. Finally we recall that causal interpretation does not follow from mere mathematical definitions, but requires working with a good system and with the true probability.