Does exposure to different menstrual products affect the vaginal environment?

The vaginal ecosystem is a key component of women's health. It also represents an ideal system for ecologists to investigate the consequence of perturbations on species diversity and emerging properties between organizational levels. Here, we study how exposure to different types of menstrual products is linked to microbial, immunological, demographic, and behavioural measurements in a cohort of young adult women who reported using more often tampons (n = 107) or menstrual cups (n = 31). We first found that cup users were older and smoked less than tampon users. When analysing health indicators, we detected potential associations between cups use reporting and fungal genital infection. A multivariate analysis confirmed that in our cohort, reporting using cups over tampons was associated with the higher odds ratio to report a fungal genital infection diagnosis by a medical doctor within the last 3 months. We did not detect significant differences between groups in terms of their bacterial vaginal microbiota composition and found marginal differences in the level of expression of 20 cytokines. However, a multivariate analysis of these biological data identified some level of clustering based on the menstrual product type preferred (cups or tampons). These results suggest that exposure to different types of menstrual products could influence menstrual health. Larger studies and studies with a more powered setting are needed to assess the robustness of these associations and identify causal mechanisms.

Analysing different exposures identifies that wearing masks and establishing COVID-19 areas reduce secondary-attack risk in aged-care facilities.

BACKGROUND: The COVID-19 epidemic has spread rapidly within aged-care facilities (ACFs), where the infection-fatality ratio is high. It is therefore urgent to evaluate the efficiency of infection prevention and control (IPC) measures in reducing SARS-CoV-2 transmission. METHODS: We analysed the COVID-19 outbreaks that took place between March and May 2020 in 12 ACFs using reverse transcription-polymerase chain reaction (RT-PCR) and serological tests for SARS-CoV-2 infection. Using maximum-likelihood approaches and generalized linear mixed models, we analysed the proportion of infected residents in ACFs and identified covariates associated with the proportion of infected residents. RESULTS: The secondary-attack risk was estimated at 4.1%, suggesting a high efficiency of the IPC measures implemented in the region. Mask wearing and the establishment of COVID-19 zones for infected residents were the two main covariates associated with lower secondary-attack risks. CONCLUSIONS: Wearing masks and isolating potentially infected residents appear to be associated with a more limited spread of SARS-CoV-2 in ACFs.

Memory is key in capturing COVID-19 epidemiological dynamics.

SARS-CoV-2 virus has spread over the world rapidly creating one of the largest pandemics ever. The absence of immunity, presymptomatic transmission, and the relatively high level of virulence of the COVID-19 infection led to a massive flow of patients in intensive care units (ICU). This unprecedented situation calls for rapid and accurate mathematical models to best inform public health policies. We develop an original parsimonious discrete-time model that accounts for the effect of the age of infection on the natural history of the disease. Analysing the ongoing COVID-19 in France as a test case, through the publicly available time series of nationwide hospital mortality and ICU activity, we estimate the value of the key epidemiological parameters and the impact of lock-down implementation delay. This work shows that including memory-effects in the modelling of COVID-19 spreading greatly improves the accuracy of the fit to the epidemiological data. We estimate that the epidemic wave in France started on Jan 20 [Jan 12, Jan 28] (95% likelihood interval) with a reproduction number initially equal to 2.99 [2.59, 3.39], which was reduced by the national lock-down started on Mar 17 to 24 [21, 27] of its value. We also estimate that the implementation of the latter a week earlier or later would have lead to a difference of about respectively -13k and +50k hospital deaths by the end of lock-down. The present parsimonious discrete-time framework constitutes a useful tool for now- and forecasting simultaneously community incidence and ICU capacity strain.

HPV cervical infections and serological status in vaccinated and unvaccinated women.

Understanding genital infections by Human papillomaviruses (HPVs) remains a major public health issue, especially in countries where vaccine uptake is low. We investigate HPV prevalence and antibody status in 150 women (ages 18 to 25) in Montpellier, France. At inclusion and one month later, cervical swabs, blood samples and questionnaires (for demographics and behavioural variables) were collected. Oncogenic, non-vaccine genotypes HPV51, HPV66, HPV53, and HPV52 were the most frequently detected viral genotypes overall. Vaccination status, which was well-balanced in the cohort, showed the strongest (protective) effect against HPV infections, with an associated odds ratio for alphapapillomavirus detection of 0.45 (95% confidence interval: [0.22;0.58]). We also identified significant effects of age, number of partners, body mass index, and contraception status on HPV detection and on coinfections. Type-specific IgG serological status was also largely explained by the vaccination status. IgM seropositivity was best explained by HPV detection at inclusion only. Finally, we identify a strong significant effect of vaccination on genotype prevalence, with a striking under-representation of HPV51 in vaccinated women. Variations in HPV prevalence correlate with key demographic and behavioural variables. The cross-protective effect of the vaccine against HPV51 merits further investigation.