Spatial Analysis of Determinants of COVID-19 Vaccine Hesitancy in Portugal.

Vaccine hesitancy tends to exhibit geographical patterns and is often associated with social deprivation and migrant status. We aimed to estimate COVID-19 vaccination hesitancy in a high-vaccination-acceptance country, Portugal, and determine its association with sociodemographic risk factors. We used the Registry of National Health System Users to determine the eligible population and the Vaccination Registry to determine individuals without COVID-19 vaccine doses. Individuals older than five with no COVID-19 vaccine dose administered by 31 March 2022 were considered hesitant. We calculated hesitancy rates by municipality, gender, and age group for all municipalities in mainland Portugal. We used the spatial statistical scan method to identify spatial clusters and the Besag, Yorke, and Mollié (BYM) model to estimate the effect of age, gender, social deprivation, and migrant proportion across all mainland municipalities. The eligible population was 9,852,283, with 1,212,565 (12%) COVID-19 vaccine-hesitant individuals. We found high-hesitancy spatial clusters in the Lisbon metropolitan area and the country's southwest. Our model showed that municipalities with higher proportions of migrants are associated with an increased relative risk (RR) of vaccine hesitancy (RR = 8.0; CI 95% 4.6; 14.0). Social deprivation and gender were not associated with vaccine hesitancy rates. We found COVID-19 vaccine hesitancy has a heterogeneous distribution across Portugal and has a strong association with the proportion of migrants per municipality.

The effects of weather and mobility on respiratory viruses dynamics before and during the COVID-19 pandemic in the USA and Canada.

The flu season is caused by a combination of different pathogens, including influenza viruses (IVS), that cause the flu, and non-influenza respiratory viruses (NIRVs), that cause common colds or influenza-like illness. These viruses exhibit similar dynamics and meteorological conditions have historically been regarded as a principal modulator of their epidemiology, with outbreaks in the winter and almost no circulation during the summer, in temperate regions. However, after the emergence of SARS-CoV2, in late 2019, the dynamics of these respiratory viruses were strongly perturbed worldwide: some infections displayed near-eradication, while others experienced temporal shifts or occurred "off-season". This disruption raised questions regarding the dominant role of weather while also providing an unique opportunity to investigate the roles of different determinants on the epidemiological dynamics of IVs and NIRVs. Here, we employ statistical analysis and modelling to test the effects of weather and mobility in viral dynamics, before and during the COVID-19 pandemic. Leveraging epidemiological surveillance data on several respiratory viruses, from Canada and the USA, from 2016 to 2023, we found that whereas in the pre-COVID-19 pandemic period, weather had a strong effect, in the pandemic period the effect of weather was strongly reduced and mobility played a more relevant role. These results, together with previous studies, indicate that behavioral changes resulting from the non-pharmacological interventions implemented to control SARS-CoV2, interfered with the dynamics of other respiratory viruses, and that the past dynamical equilibrium was disturbed, and perhaps permanently altered, by the COVID-19 pandemic.

Intermediate levels of scientific knowledge are associated with overconfidence and negative attitudes towards science.

Overconfidence is a prevalent problem and it is particularly consequential in its relation with scientific knowledge: being unaware of one's own ignorance can affect behaviours and threaten public policies and health. However, it is not clear how confidence varies with knowledge. Here, we examine four large surveys, spanning 30 years in Europe and the United States and propose a new confidence metric. This metric does not rely on self-reporting or peer comparison, operationalizing (over)confidence as the tendency to give incorrect answers rather than 'don't know' responses to questions on scientific facts. We find a nonlinear relationship between knowledge and confidence, with overconfidence (the confidence gap) peaking at intermediate levels of actual scientific knowledge. These high-confidence/intermediate-knowledge groups also display the least positive attitudes towards science. These results differ from current models and, by identifying specific audiences, can help inform science communication strategies.

Author Correction: Human Sexual Cycles are Driven by Culture and Match Collective Moods.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Human Sexual Cycles are Driven by Culture and Match Collective Moods.

Human reproduction does not happen uniformly throughout the year and what drives human sexual cycles is a long-standing question. The literature is mixed with respect to whether biological or cultural factors best explain these cycles. The biological hypothesis proposes that human reproductive cycles are an adaptation to the seasonal (hemisphere-dependent) cycles, while the cultural hypothesis proposes that conception dates vary mostly due to cultural factors, such as holidays. However, for many countries, common records used to investigate these hypotheses are incomplete or unavailable, biasing existing analysis towards Northern Hemisphere Christian countries. Here we show that interest in sex peaks sharply online during major cultural and religious celebrations, regardless of hemisphere location. This online interest, when shifted by nine months, corresponds to documented human births, even after adjusting for numerous factors such as language and amount of free time due to holidays. We further show that mood, measured independently on Twitter, contains distinct collective emotions associated with those cultural celebrations. Our results provide converging evidence that the cyclic sexual and reproductive behavior of human populations is mostly driven by culture and that this interest in sex is associated with specific emotions, characteristic of major cultural and religious celebrations.

Early and Real-Time Detection of Seasonal Influenza Onset.

Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.

A Predictive Model for Yeast Cell Polarization in Pheromone Gradients.

Budding yeast cells exist in two mating types, a and α, which use peptide pheromones to communicate with each other during mating. Mating depends on the ability of cells to polarize up pheromone gradients, but cells also respond to spatially uniform fields of pheromone by polarizing along a single axis. We used quantitative measurements of the response of a cells to α-factor to produce a predictive model of yeast polarization towards a pheromone gradient. We found that cells make a sharp transition between budding cycles and mating induced polarization and that they detect pheromone gradients accurately only over a narrow range of pheromone concentrations corresponding to this transition. We fit all the parameters of the mathematical model by using quantitative data on spontaneous polarization in uniform pheromone concentration. Once these parameters have been computed, and without any further fit, our model quantitatively predicts the yeast cell response to pheromone gradient providing an important step toward understanding how cells communicate with each other.

Asymmetry in sexual pheromones is not required for ascomycete mating.

BACKGROUND: We investigated the determinants of sexual identity in the budding yeast Saccharomyces cerevisiae. The higher fungi are divided into the ascomycetes and the basidiomycetes. Most ascomycetes have two mating types: one (called α in yeasts and MAT1-1 in filamentous fungi) produces a small, unmodified, peptide pheromone, and the other (a in yeasts and MAT1-2 in filamentous fungi) produces a peptide pheromone conjugated to a C-terminal farnesyl group that makes it very hydrophobic. In the basidiomycetes, all pheromones are lipid-modified, and this difference is a distinguishing feature between the phyla. We asked whether the asymmetry in pheromone modification is required for successful mating in ascomycetes. RESULTS: We cloned receptor and pheromone genes from a filamentous ascomycete and a basidiomycete and expressed these in the budding yeast, Saccharomyces cerevisiae, to generate novel, alternative mating pairs. We find that two yeast cells can mate even when both cells secrete a-like or α-like peptides. Importantly, this is true regardless of whether the cells express the a- or α-mating-type loci, which control the expression of other, sex-specific genes, in addition to the pheromones and pheromone receptors. CONCLUSIONS: We demonstrate that the asymmetric pheromone modification is not required for successful mating of ascomycete fungi and confirm that, in budding yeast, the primary determinants of mating are the specificity of the receptors and their corresponding pheromones.