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During the COVID-19 pandemic, individuals depended on risk information to make decisions about everyday behaviors and public policy. Here, we assessed whether an interactive website influenced individuals’ risk tolerance to support public health goals. We collected data from 11,169 unique users who engaged with the online COVID-19 Event Risk Tool ( https://covid19risk.biosci.gatech.edu/ ) between 9/22/21 and 1/22/22. The website featured interactive elements, including a dynamic risk map, survey questions, and a risk quiz with accuracy feedback. After learning about the risk of COVID-19 exposure, participants reported being less willing to participate in events that could spread COVID-19, especially for high-risk large events. We also uncovered a bias in risk estimation: Participants tended to overestimate the risk of small events but underestimate the risk of large events. Importantly, even participants who voluntarily sought information about COVID risks tended to misestimate exposure risk, demonstrating the need for intervention. Participants from liberal-leaning counties were more likely to use the website tools and more responsive to feedback about risk misestimation, indicating that political partisanship influences how individuals seek and engage with COVID-19 information. Lastly, we explored temporal dynamics and found that user engagement and risk estimation fluctuated over the course of the Omicron variant outbreak. Overall, we report an effective large-scale method for communicating viral exposure risk; our findings are relevant to broader research on risk communication, epidemiological modeling, and risky decision-making.

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics. This study shows that a multitrophic community model jointly recapitulates diel rhythms in abundances of Prochlorococcus picocyanobacteria, as well as viral infection, viral abundances and grazer abundances. Model-data integration implies that grazing predominantly controls Prochlorococcus abundances in surface waters of the North Pacific Subtropical Gyre, despite high viral densities.

The dilution method is the principal tool used to infer in situ microzooplankton grazing rates. However, grazing is the only mortality process considered in the theoretical model underlying the interpretation of dilution method experiments. Here we evaluate the robustness of mortality estimates inferred from dilution experiments when there is concurrent niche competition amongst phytoplankton. Using a combination of mathematical analysis and numerical simulations, we find that grazing rates may be overestimated-the degree of overestimation is related to the importance of niche competition relative to microzooplankton grazing. In response, we propose a conceptual method to disentangle the effects of niche competition and grazing by diluting out microzooplankton, but not phytoplankton. Our theoretical results suggest this revised \"Z-dilution\" method can robustly infer grazing mortality, regardless of the dominant phytoplankton mortality driver in our system. Further, we show it is possible to independently estimate both grazing mortality and niche competition if the classical and Z-dilution methods can be used in tandem. We discuss the significance of these results for quantifying phytoplankton mortality rates; and the feasibility of implementing the Z-dilution method in practice, whether in model systems or in complex communities with overlap in the size distributions of phytoplankton and microzooplankton.

The encounter and capture of bacteria and phytoplankton by microbial predators and parasites is fundamental to marine ecosystem organization and activity. Here, we combined biophysical models with published laboratory measurements to infer functional traits, including encounter kernel and capture efficiency, for a wide range of marine viruses and microzooplankton grazers. Despite virus particles being orders of magnitude smaller than microzooplankton grazers, virus encounter kernels and adsorption rates were in many cases comparable in magnitude to grazer encounter kernel and clearance, pointing to Brownian motion as a highly effective method of transport for viruses. Inferred virus adsorption efficiency covered many orders of magnitude, but the median virus adsorption efficiency was between 5 to 25% depending on the assumed host swimming speed. Uncertainty on predator detection area and swimming speed prevented robust inference of grazer capture efficiency, but sensitivity analysis was used to identify bounds on unconstrained processes. These results provide a common functional trait framework for understanding marine host-virus and predator-prey interactions, and highlight the value of theory for interpreting measured life-history traits.

Long-term stability of picocyanobacteria in the open oceans is maintained by a balance between synchronous division and death on daily timescales. Viruses are considered a major source of microbial mortality, however, current methods to measure infection have significant methodological limitations. Here we describe a method that pairs flow-cytometric sorting with a PCR-based polony technique to simultaneously screen thousands of taxonomically resolved individual cells for intracellular virus DNA, enabling sensitive, high-throughput, and direct quantification of infection by different virus lineages. Under controlled conditions with picocyanobacteria-cyanophage models, the method detected infection throughout the lytic cycle and discriminated between varying infection levels. In North Pacific subtropical surface waters, the method revealed that only a small percentage of Prochlorococcus (0.35–1.6%) were infected, predominantly by T4-like cyanophages, and that infection oscillated 2-fold in phase with the diel cycle. This corresponds to 0.35–4.8% of Prochlorococcus mortality daily. Cyanophages were 2–4-fold more abundant than Prochlorococcus , indicating that most encounters did not result in infection and suggesting infection is mitigated via host resistance, reduced phage infectivity and inefficient adsorption. This method will enable quantification of infection for key microbial taxa across oceanic regimes and will help determine the extent that viruses shape microbial communities and ecosystem level processes.

Nestedness is a statistical measure used to interpret bipartite interaction data in several ecological and evolutionary contexts, e.g. biogeography (species-site relationships) and species interactions (plant-pollinator and host-parasite networks). Multiple methods have been used to evaluate nestedness, which differ in how the metrics for nestedness are determined. Furthermore, several different null models have been used to calculate statistical significance of nestedness scores. The profusion of measures and null models, many of which give conflicting results, is problematic for comparison of nestedness across different studies. We developed the FALCON software package to allow easy and efficient comparison of nestedness scores and statistical significances for a given input network, using a selection of the more popular measures and null models from the current literature. FALCON currently includes six measures and five null models for nestedness in binary networks, and two measures and four null models for nestedness in weighted networks. The FALCON software is designed to be efficient and easy to use. FALCON code is offered in three languages (R, MATLAB, Octave) and is designed to be modular and extensible, enabling users to easily expand its functionality by adding further measures and null models. FALCON provides a robust methodology for comparing the strength and significance of nestedness in a given bipartite network using multiple measures and null models. It includes an \"adaptive ensemble\" method to reduce undersampling of the null distribution when calculating statistical significance. It can work with binary or weighted input networks. FALCON is a response to the proliferation of different nestedness measures and associated null models in the literature. It allows easy and efficient calculation of nestedness scores and statistical significances using different methods, enabling comparison of results from different studies and thereby supporting theoretical study of the causes and implications of nestedness in different biological contexts.

Abstract Bacteriophages (viruses that exclusively infect bacteria) exhibit a continuum of infection mechanisms, including lysis and lysogeny in interactions with bacterial hosts. Recent work has demonstrated the short-term advantages of lysogeny over lysis in conditions of low host availability. Hence, temperate phage which can switch between lytic and lysogenic strategies—both stochastically and responsively—are hypothesized to have an evolutionary advantage in a broad range of conditions. However, the long-term advantages of lysogeny are not well understood, particularly when environmental conditions vary over time. To examine generalized drivers of viral strategies over the short- and long-term, we explore the eco-evolutionary dynamics of temperate viruses in periodic environments with varying levels of host availability and viral mortality. We use a nonlinear system of ordinary differential equations to simulate periodically-forced dynamics that separate a ‘within-growth’ phase and a ‘between-growth’ phase, in which a (potentially unequal) fraction of virus particles and lysogens survive. Using this ecological model and invasion analysis, we show and quantify how conflicts can arise between strategies in the short term that may favour lysis and strategies in the long term that may favour lysogeny. In doing so, we identify a wide range of conditions in which temperate strategies can outperform obligately lytic or lysogenic strategies. Finally, we demonstrate that temperate strategies can mitigate against the potential local extinction of viruses in stochastically fluctuating environments, providing further evidence of the eco-evolutionary benefits of being temperate.

Large events and gatherings, particularly those taking place indoors, have been linked to multitransmission events that have accelerated the pandemic spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To provide real-time, geolocalized risk information, we developed an interactive online dashboard that estimates the risk that at least one individual with SARS-CoV-2 is present in gatherings of different sizes in the United States. The website combines documented case reports at the county level with ascertainment bias information obtained via population-wide serological surveys to estimate real-time circulating, per-capita infection rates. These rates are updated daily as a means to visualize the risk associated with gatherings, including county maps and state-level plots. The website provides data-driven information to help individuals and policy makers make prudent decisions (for example, increasing mask-wearing compliance and avoiding larger gatherings) that could help control the spread of SARS-CoV-2, particularly in hard-hit regions. The COVID-19 Real-Time Event Risk Assessment Planning Tool allows individuals to assess risk associated with attending events of different sizes via a real-time, interactive website and helps individuals assess whether this risk is worth taking.

The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 2020 1 – 4 . Mitigation and suppression of new infections have emerged as the two predominant public health control strategies 5 . Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests 6 , 7 to identify and deploy recovered individuals 8 as focal points for sustaining safer interactions via interaction substitution, developing what we term ‘shield immunity’ at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services 9 while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence 10 , 11 and in the potential development of plasma-based therapies 12 – 15 . A new study models the potential effects of preferentially deploying recovered individuals, who are seropositive for anti-SARS-CoV-2 antibodies, into the community to reduce the number of interactions between susceptible and infected people, thereby limiting transmission of the virus.