A Novel Olfactory Self-Test Effectively Screens for COVID-19

Key to curtailing the COVID-19 pandemic are wide-scale testing strategies 1,2 . An ideal test is one that would not rely on transporting, distributing, and collecting physical specimens. Given the olfactory impairment associated with COVID-19 3-7 , we developed a novel measure of olfactory perception that relies on smelling household odorants and rating them online. We tested the performance of this real-time tool in 12,020 participants from 134 countries who provided 171,500 perceptual ratings of 60 different household odorants. We observed that olfactory ratings were indicative of COVID-19 status in a country, significantly correlating with national infection rates over time. More importantly, we observed remarkable indicative power at the individual level (90% sensitivity and 80% specificity). Critically, olfactory testing remained highly effective in participants with COVID-19 but without symptoms, and in participants with symptoms but without COVID-19. In this, the current odorant-based olfactory test stands apart from symptom-checkers (including olfactory symptom-checkers) 3 , and even from antigen tests 8 , to potentially provide a first line of screening that can help halt disease progression at the population level.

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Harnessing testing strategies and public health measures to avert COVID-19 outbreaks during ocean cruises

Scientific Reports ◽

10.1038/s41598-021-95032-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Gerardo Chowell ◽

Sushma Dahal ◽

Raquel Bono ◽

Kenji Mizumoto

Keyword(s):

Public Health ◽

Cost Effective ◽

Contact Network ◽

Social Distancing ◽

Individual Level ◽

Health Measures ◽

Testing Strategies ◽

Novel Coronavirus ◽

The Individual ◽

The Impact

AbstractTo ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the test’s sensitivity profile, and testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.

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Migration, acculturation, and the maintenance of between-group cultural variation

10.1101/234807 ◽

2017 ◽

Cited By ~ 1

Author(s):

Alex Mesoudi

Keyword(s):

Social Learning ◽

Cultural Values ◽

Cultural Evolution ◽

Population Level ◽

Empirical Literature ◽

Cultural Variation ◽

Individual Level ◽

And Migration ◽

The Individual ◽

Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

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General intelligence disentangled via a generality metric for natural and artificial intelligence

Scientific Reports ◽

10.1038/s41598-021-01997-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

José Hernández-Orallo ◽

Bao Sheng Loe ◽

Lucy Cheke ◽

Fernando Martínez-Plumed ◽

Seán Ó hÉigeartaigh

Keyword(s):

Task Difficulty ◽

Population Level ◽

Limited Resources ◽

General Intelligence ◽

Individual Level ◽

Cognitive Efficiency ◽

Comprehensive Performance ◽

Individual Measure ◽

Level Of Difficulty ◽

The Individual

AbstractSuccess in all sorts of situations is the most classical interpretation of general intelligence. Under limited resources, however, the capability of an agent must necessarily be limited too, and generality needs to be understood as comprehensive performance up to a level of difficulty. The degree of generality then refers to the way an agent’s capability is distributed as a function of task difficulty. This dissects the notion of general intelligence into two non-populational measures, generality and capability, which we apply to individuals and groups of humans, other animals and AI systems, on several cognitive and perceptual tests. Our results indicate that generality and capability can decouple at the individual level: very specialised agents can show high capability and vice versa. The metrics also decouple at the population level, and we rarely see diminishing returns in generality for those groups of high capability. We relate the individual measure of generality to traditional notions of general intelligence and cognitive efficiency in humans, collectives, non-human animals and machines. The choice of the difficulty function now plays a prominent role in this new conception of generality, which brings a quantitative tool for shedding light on long-standing questions about the evolution of general intelligence and the evaluation of progress in Artificial General Intelligence.

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Ecology and Prediction of Compensatory Growth: From Theory to Application in Forestry

Frontiers in Plant Science ◽

10.3389/fpls.2021.655417 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chao Li ◽

Hugh Barclay ◽

Bernard Roitberg ◽

Robert Lalonde

Keyword(s):

Compensatory Growth ◽

Population Level ◽

Human Society ◽

Common Phenomenon ◽

Partial Mortality ◽

Individual Level ◽

State Dependent ◽

Dependent Model ◽

Accelerated Growth ◽

The Individual

Compensatory growth has been observed in forests, and it also appears as a common phenomenon in biology. Though it sometimes takes different names, the essential meanings are the same, describing the accelerated growth of organisms when recovering from a period of unfavorable conditions such as tissue damage at the individual level and partial mortality at the population level. Diverse patterns of compensatory growth have been reported in the literature, ranging from under-, to compensation-induced-equality, and to over-compensation. In this review and synthesis, we provide examples of analogous compensatory growth from different fields, clarify different meanings of it, summarize its current understanding and modeling efforts, and argue that it is possible to develop a state-dependent model under the conceptual framework of compensatory growth, aimed at explaining and predicting diverse observations according to different disturbances and environmental conditions. When properly applied, compensatory growth can benefit different industries and human society in various forms.

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Opposite outcomes of coinfection at individual and population scales

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1801095115 ◽

2018 ◽

Vol 115 (29) ◽

pp. 7545-7550 ◽

Cited By ~ 10

Author(s):

Erin E. Gorsich ◽

Rampal S. Etienne ◽

Jan Medlock ◽

Brianna R. Beechler ◽

Johannie M. Spaan ◽

...

Keyword(s):

Reproduction Number ◽

Negative Impact ◽

Scale Up ◽

Population Level ◽

Clear Understanding ◽

African Buffalo ◽

Global Public Health ◽

Individual Level ◽

Secondary Infections ◽

The Individual

Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number (R0) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.

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Smart Sanitation—Biosensors as a Public Health Tool in Sanitation Infrastructure

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17145146 ◽

2020 ◽

Vol 17 (14) ◽

pp. 5146 ◽

Cited By ~ 1

Author(s):

Emma Rary ◽

Sarah M. Anderson ◽

Brandon D. Philbrick ◽

Tanvi Suresh ◽

Jasmine Burton

Keyword(s):

Public Health ◽

Health Monitoring ◽

Disease Surveillance ◽

Population Level ◽

Cost Effective ◽

Small Scale ◽

Individual Level ◽

Emergent Technologies ◽

The Individual ◽

Sanitation Infrastructure

The health of individuals and communities is more interconnected than ever, and emergent technologies have the potential to improve public health monitoring at both the community and individual level. A systematic literature review of peer-reviewed and gray literature from 2000-present was conducted on the use of biosensors in sanitation infrastructure (such as toilets, sewage pipes and septic tanks) to assess individual and population health. 21 relevant papers were identified using PubMed, Embase, Global Health, CDC Stacks and NexisUni databases and a reflexive thematic analysis was conducted. Biosensors are being developed for a range of uses including monitoring illicit drug usage in communities, screening for viruses and diagnosing conditions such as diabetes. Most studies were nonrandomized, small-scale pilot or lab studies. Of the sanitation-related biosensors found in the literature, 11 gathered population-level data, seven provided real-time continuous data and 14 were noted to be more cost-effective than traditional surveillance methods. The most commonly discussed strength of these technologies was their ability to conduct rapid, on-site analysis. The findings demonstrate the potential of this emerging technology and the concept of Smart Sanitation to enhance health monitoring at the individual level (for diagnostics) as well as at the community level (for disease surveillance).

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Individual-Level and Population-Level Lateralization: Two Sides of the Same Coin

Symmetry ◽

10.3390/sym10120739 ◽

2018 ◽

Vol 10 (12) ◽

pp. 739 ◽

Cited By ~ 22

Author(s):

Elisa Frasnelli ◽

Giorgio Vallortigara

Keyword(s):

Evolutionarily Stable Strategy ◽

Population Level ◽

Point Of View ◽

Theoretical Point ◽

Evolutionarily Stable Strategies ◽

Functional Roles ◽

Individual Level ◽

Social Species ◽

The Individual ◽

Evolutionarily Stable

Lateralization, i.e., the different functional roles played by the left and right sides of the brain, is expressed in two main ways: (1) in single individuals, regardless of a common direction (bias) in the population (aka individual-level lateralization); or (2) in single individuals and in the same direction in most of them, so that the population is biased (aka population-level lateralization). Indeed, lateralization often occurs at the population-level, with 60–90% of individuals showing the same direction (right or left) of bias, depending on species and tasks. It is usually maintained that lateralization can increase the brain’s efficiency. However, this may explain individual-level lateralization, but not population-level lateralization, for individual brain efficiency is unrelated to the direction of the asymmetry in other individuals. From a theoretical point of view, a possible explanation for population-level lateralization is that it may reflect an evolutionarily stable strategy (ESS) that can develop when individually asymmetrical organisms are under specific selective pressures to coordinate their behavior with that of other asymmetrical organisms. This prediction has been sometimes misunderstood as it is equated with the idea that population-level lateralization should only be present in social species. However, population-level asymmetries have been observed in aggressive and mating displays in so-called “solitary” insects, suggesting that engagement in specific inter-individual interactions rather than “sociality” per se may promote population-level lateralization. Here, we clarify that the nature of inter-individuals interaction can generate evolutionarily stable strategies of lateralization at the individual- or population-level, depending on ecological contexts, showing that individual-level and population-level lateralization should be considered as two aspects of the same continuum.

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Changes in wild red squirrel personality across ontogeny: activity and aggression regress towards the mean

Behaviour ◽

10.1163/1568539x-00003279 ◽

2015 ◽

Vol 152 (10) ◽

pp. 1291-1306 ◽

Cited By ~ 14

Author(s):

A.D. Kelley ◽

M.M. Humphries ◽

A.G. McAdam ◽

Stan Boutin

Keyword(s):

Structural Stability ◽

Environmental Changes ◽

Population Level ◽

Behavioural Syndrome ◽

Red Squirrels ◽

Individual Level ◽

Personality Changes ◽

The Mean ◽

Differential Stability ◽

The Individual

Both juvenile and adult animals display stable behavioural differences (personality), but lifestyles and niches may change as animals mature, raising the question of whether personality changes across ontogeny. Here, we use a wild population of red squirrels to examine changes in activity and aggression from juvenile to yearling life stages. Personality may change at the individual level (individual stability), population level (mean level stability), and relative to other individuals (differential stability). We calculated all three types of stability, as well as the structural stability of the activity–aggression behavioural syndrome. Within individuals, both activity and aggression scores regressed towards the mean. Differential stability was maintained for activity, but not aggression. Structural stability was maintained; however, the activity–aggression correlation increased in squirrels that gained territories later in the season. These results suggest that personality undergoes some changes as animals mature, and that the ontogeny of personality can be linked to environmental changes.

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Analyzing 24-Hour Blood Pressure Measurements with a Novel Cuffless Pulse Transit Time Device in Clinical Practice—Does the Software for Heartbeat Detection Matter?

Diagnostics ◽

10.3390/diagnostics10060361 ◽

2020 ◽

Vol 10 (6) ◽

pp. 361

Author(s):

Leo Kilian ◽

Philipp Krisai ◽

Thenral Socrates ◽

Christian Arranto ◽

Otmar Pfister ◽

...

Keyword(s):

Blood Pressure ◽

Transit Time ◽

Pulse Transit Time ◽

Population Level ◽

Raw Data ◽

Invasive Blood Pressure ◽

Individual Level ◽

Non Invasive ◽

The Individual ◽

The Impact

Background: The Somnotouch-Non-Invasive-Blood-Pressure (NIBP) device delivers raw data consisting of electrocardiography and photoplethysmography for estimating blood pressure (BP) over 24 h using pulse-transit-time. The study’s aim was to analyze the impact on 24-hour BP results when processing raw data by two different software solutions delivered with the device. Methods: We used data from 234 participants. The Somnotouch-NIBP measurements were analyzed using the Domino-light and Schiller software and compared. BP values differing >5 mmHg were regarded as relevant and explored for their impact on BP classification (normotension vs. hypertension). Results: Mean (±standard deviation) absolute systolic/diastolic differences for 24-hour mean BP were 1.5 (±1.7)/1.1 (±1.3) mm Hg. Besides awake systolic BP (p = 0.022), there were no statistically significant differences in systolic/diastolic 24-hour mean, awake, and asleep BP. Twenty four-hour mean BP agreement (number (%)) between the software solutions within 5, 10, and 15 mmHg were 222 (94.8%), 231 (98.7%), 234 (100%) for systolic and 228 (97.4%), 232 (99.1%), 233 (99.5%) for diastolic measurements, respectively. A BP difference of >5 mmHg was present in 24 (10.3%) participants leading to discordant classification in 4–17%. Conclusion: By comparing the two software solutions, differences in BP are negligible at the population level. However, at the individual level there are, in a minority of cases, differences that lead to different BP classifications, which can influence the therapeutic decision.

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Survival dynamical systems: individual-level survival analysis from population-level epidemic models

Interface Focus ◽

10.1098/rsfs.2019.0048 ◽

2019 ◽

Vol 10 (1) ◽

pp. 20190048 ◽

Cited By ~ 5

Author(s):

Wasiur R. KhudaBukhsh ◽

Boseung Choi ◽

Eben Kenah ◽

Grzegorz A. Rempała

Keyword(s):

Influenza A ◽

Large Population ◽

Synthetic Data ◽

Population Level ◽

Epidemic Models ◽

Hazard Functions ◽

Individual Level ◽

Washington State University ◽

Influenza A H1n1 ◽

The Individual

In this paper, we show that solutions to ordinary differential equations describing the large-population limits of Markovian stochastic epidemic models can be interpreted as survival or cumulative hazard functions when analysing data on individuals sampled from the population. We refer to the individual-level survival and hazard functions derived from population-level equations as a survival dynamical system (SDS). To illustrate how population-level dynamics imply probability laws for individual-level infection and recovery times that can be used for statistical inference, we show numerical examples based on synthetic data. In these examples, we show that an SDS analysis compares favourably with a complete-data maximum-likelihood analysis. Finally, we use the SDS approach to analyse data from a 2009 influenza A(H1N1) outbreak at Washington State University.

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