Dynamic pathogen detection and social feedback shape collective hygiene in ants.

Cooperative disease defense emerges as group-level collective behavior, yet how group members make the underlying individual decisions is poorly understood. Using garden ants and fungal pathogens as an experimental model, we derive the rules governing individual ant grooming choices and show how they produce colony-level hygiene. Time-resolved behavioral analysis, pathogen quantification, and probabilistic modeling reveal that ants increase grooming and preferentially target highly-infectious individuals when perceiving high pathogen load, but transiently suppress grooming after having been groomed by nestmates. Ants thus react to both, the infectivity of others and the social feedback they receive on their own contagiousness. While inferred solely from momentary ant decisions, these behavioral rules quantitatively predict hour-long experimental dynamics, and synergistically combine into efficient colony-wide pathogen removal. Our analyses show that noisy individual decisions based on only local, incomplete, yet dynamically-updated information on pathogen threat and social feedback can lead to potent collective disease defense.

Seroprevalence of SARS-CoV-2 IgG antibodies in the staff of the Slovak Academy of Sciences in response to COVID-19 and/or vaccination: situation in August 2021.

Cross-sectional seroprevalence study of SARS-CoV-2 IgG antibodies was accomplished in the Slovak Academy of Sciences to inform authorities of research institutions about the situation at their workplaces, to assess the risk of next exposure to SARS-CoV-2, and to guide decisions on institutional measures sustaining essential research in evolving epidemic situation. Study participants provided informed consent, anamnestic information, and self-collected dry blood spot samples that were analyzed by ELISA for SARS-CoV-2 S protein-specific IgG antibodies. Relative antibody levels detected in 1928 subjects showed seroprevalence of 84.13% and led to the following main findings consistent with the current knowledge: (1) mRNA-based vaccines induce better humoral response compared to adenovirus vaccines, (2) antibody levels reflect severity of COVID-19 symptoms, (3) post-COVID vaccination results in marked elevation of IgG levels particularly in asymptomatic and mild cases, (4) antibody levels decrease with increasing time elapsed from vaccination or COVID-19. In addition, data sorting to distinct research institutes and their clustering to three principal scientific sections of the Slovak Academy of Sciences revealed marked differences in seroprevalence, and allowed to identify workplaces with relatively high seropositivity and response rate that can potentially provide a safer working environment than those, where seroprevalence was low or unknown due to low participation. Thus, findings of this study can have direct implications on management decisions during the next pandemic development, with the necessity to keep in mind the phenomenon of time-dependent immunity waning and current spread of more contagious Delta variant of SARS-CoV-2. Keywords: SARS-CoV-2 coronavirus; COVID-19; spike protein; seroprevalence; antibodies; vaccination.

Spatial scales, patterns, and positivity trends of SARS-CoV-2 pandemics in mass rapid antigen testing in Slovakia.

We study geographical epidemic scales and patterns and positivity trends of SARS-CoV-2 pandemics in mass antigen testing in Slovakia in 2020. The observed test positivity was exponentially distributed with a long scale exponential spatial trend, and its characteristic correlation length was approximately 10 km. Spatial scales also play an important role in test positivity reduction between two consecutive testing rounds. While test positivity decreased in all counties, it increased in individual municipalities with low test positivity in the earlier testing round in a way statistically different from a mean-reversion process. Also, non-residents testing influences the mass testing results as test positivity of non-residents was higher than of residents when testing was offered only in municipalities with the highest positivity in previous rounds. Our results provide direct guidance for pandemic geographical data surveillance and epidemic response management.

Characterizing spiking in noisy type II neurons.

Understanding the dynamics of noisy neurons remains an important challenge in neuroscience. Here, we describe a simple probabilistic model that accurately describes the firing behavior in a large class (type II) of neurons. To demonstrate the usefulness of this model, we show how it accurately predicts the interspike interval (ISI) distributions, bursting patterns and mean firing rates found by: (1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental data from squid giant axon with a noisy input current and (3) experimental data on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple model has 6 parameters, however, in some cases, two of these parameters are coupled and only 5 parameters account for much of the known behavior. From these parameters, many properties of spiking can be found through simple calculation. Thus, we show how the complex effects of noise can be understood through a simple and general probabilistic model.