Biology subjects

Cattuto, C.

Publications and source records attributed to Cattuto, C..

6 recordsLinked to original sources

bioRxiv2024

Association Between Oral Microbiota and Close-Range Proximity in a Primary School

The microbiota is the ensemble of microorganisms inhabiting the human body and it deeply influences human health and well-being. Recent studies showed its interplay with social behavior, suggesting that part of the microbiota might be socially transmissible. In this work, we investigate the association between close-range proximity and the oral microbiota composition in a group of children attending primary school. Unlike most related studies, our cohort comprises non-cohabiting individuals, and we use high-resolution proximity sensors to objectively quantify close-range proximity. Our analysis shows that longer time spent in proximity between pairs of children correlates with a higher similarity between their oral microbiota composition. Building on previous studies on cohabiting individuals, our findings suggest that social contacts beyond the closest social circle may also shape oral microbiota composition, although longitudinal studies are needed to test this hypothesis.

microbiology↗

bioRxiv2024

Density-dependent network structuring within and across wild animal systems

High population density should drive individuals to more frequently share space and interact, producing better-connected spatial and social networks [1-4]. Although this theory is fundamental to our understanding of disease dynamics [2,5-8], it remains unconfirmed how local density generally drives individuals positions within their networks, which reduces our ability to understand and predict density-dependent processes [4,9,10]. Here we provide the first general evidence that density drives greater network connectedness at fine spatiotemporal scales, at the scale of individuals within wild animal populations. We analysed 36 datasets of simultaneous spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals, and insects. 80% of systems exhibited strong positive relationships between local density and network centrality. However, >80% of relationships were nonlinear and 75% became shallower at higher values, signifying that demographic and behavioural processes counteract densitys effects, thereby producing saturating trends [11-15]. Densitys effect was much stronger and less saturating for spatial than social networks, such that individuals become disproportionately spatially connected rather than socially at higher densities. Consequently, ecological processes that depend on spatial connections (e.g. indirect pathogen transmission, resource competition, and territory formation) are likely more density-dependent than those involving social interactions (e.g. direct pathogen transmission, aggression, and social learning). These findings reveal fundamental ecological rules governing societal structuring, with widespread implications. Identifying scaling rules based on processes that generalise across systems, such as these patterns of density dependence, might provide the ability to predict network structures in novel systems.

ecology↗

bioRxiv2024

Spatial-temporal dynamics of contact among free-ranging domestic dogs Canis familiaris in rural Africa

1. Transmission of infection is affected by the spatial-temporal dynamics of host contacts. Domestic dogs Canis familiaris share pathogens with humans and wildlife, and managing dog-mediated diseases is a priority for public health and conservation interests. 2. We combined proximity sensors and GPS tracking to analyse spatial-temporal variation in contact among free-ranging dogs in six villages in rural Chad, during both the wet and dry seasons. We investigated dyadic interactions between dogs from different villages, the same village but different households and the same household. We assessed variation in (i) the probability of individuals having had contact, (ii) the hourly frequency of contact and (iii) contact durations. 3. Our results highlight clear seasonal and hourly patterns in contact behaviour. Contacts between dogs from different villages were rare, short in duration, primarily between male-female dyads and predominantly occurred within villages and during the dry season. Contact between dogs in the same village peaked at dawn and dusk. Sex differences were most pronounced in the wet season, where males from different households had the highest hourly contact probabilities, followed by male-female dyads. For all dogs, contact durations were longer in the dry season, but showed little hourly variation. 4. Contact patterns were not equal in space, and the probability of individuals having had contact was less than 5% when dwellings were more than 500m apart. Spatially, the probability of contact was lowest outside the village, but this increased in the dry season and peaked in the morning hours. Contact durations were notably longer outside the village, where they increased in duration for between-household dyads in the dry season. 5. At a coarse temporal scale, variation in dog contacts within and among households, and rarely between villages, may underpin seasonal variation in the incidence of dog-mediated diseases. Variation at finer temporal (hourly) and spatial scales (around households, within and outside villages) highlights the importance of routine behaviours and space use in determining patterns of contact between dogs. Practitioners should consider behavioural heterogeneities, such as those reported here, when using strategic models to support disease management decisions.

animal behavior and cognition↗

bioRxiv2018

The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic

In recent years, many studies have drawn attention to the important role of collective awareness and human behaviour during epidemic outbreaks. A number of modelling efforts have investigated the interaction between the disease transmission dynamics and human behaviour change mediated by news coverage and by information spreading in the population. Yet, given the scarcity of data on public awareness during an epidemic, few studies have relied on empirical data. Here, we use fine-grained, geo-referenced data from three online sources - Wikipedia, the GDELT Project and the Internet Archive - to quantify population-scale information seeking about the 2016 Zika virus epidemic in the U.S., explicitly linking such behavioural signal to epidemiological data. Geolocalized Wikipedia pageview data reveal that visiting patterns of Zika-related pages in Wikipedia were highly synchronized across the United States and largely explained by exposure to national television broadcast. Contrary to the assumption of some theoretical models, news volume and Wikipedia visiting patterns were not significantly correlated with the magnitude or the extent of the epidemic. Attention to Zika, in terms of Zika-related Wikipedia pageviews, was high at the beginning of the outbreak, when public health agencies raised an international alert and triggered media coverage, but subsequently exhibited an activity profile that suggests nonlinear dependencies and memory effects in the relation between information seeking, media pressure, and disease dynamics. This calls for a new and more general modelling framework to describe the interaction between media exposure, public awareness and disease dynamics during epidemic outbreaks.

epidemiology↗

bioRxiv2018

Unsupervised Extraction of Epidemic Syndromes from Participatory Influenza Surveillance Self-reported Symptoms

Seasonal influenza surveillance is usually carried out by sentinel general practitioners who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This practice for surveillance is generally affected by two main issues: i) reports are usually released with a lag of about one week or more, ii) the definition of a case of influenza-like illness based on patients symptoms varies from one surveillance system to the other, i.e. from one country to the other. The availability of novel data streams for disease surveillance can alleviate these issues; in this paper, we employed data from Influenzanet, a participatory web-based surveillance project which collects symptoms directly from the general population in real time. We developed an unsupervised probabilistic framework that combines time series analysis of symptoms counts and performs an algorithmic detection of groups of symptoms, hereafter called syndromes. Symptoms counts were collected through the participatory web-based surveillance platforms of a consortium called Influenzanet which is found to correlate with Influenza-like illness incidence as detected by sentinel doctors. Our aim is to suggest how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness temporal trends without relying on a specific case definition. We evaluated the performance of our framework by showing that the temporal trends of the detected syndromes closely follow the ILI incidence as reported by the traditional surveillance, and consist of combinations of symptoms that are compatible with the ILI definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.\n\nAuthor summaryThis study suggests how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness temporal trends without relying on a specific case definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.

epidemiology↗

bioRxiv2017

Close encounters between infants and household members measured through wearable proximity sensors

Describing and understanding close proximity interactions between infant and family members can provide key information on transmission opportunities of respiratory infections within households. Among respiratory infections, pertussis represents a public health priority. Pertussis infection can be particularly harmful to young, unvaccinated infants and for these patients, family members represent the main sources of transmission. Here, we report on the use of wearable proximity sensors based on RFID technology to measure face-to-face proximity between family members within 16 households with infants younger than 6 months for 2-5 consecutive days of data collection. The sensors were deployed over the course of approximately 1 year, in the context of a national research project aimed at the improvement of infant pertussis prevention strategies. We recorded 5,958 contact events between 55 individuals: 16 infants, 4 siblings, 31 parents and 4 grandparents. The contact networks showed a heterogeneous distribution of the cumulative time spent in proximity with the infant by family members. Most of the contacts occurred between the infant and other family members (70%), and many contacts were observed between infants and adults, in particular between infant and mother, followed by father, siblings and grandparents. A larger number of contacts and longer contact durations between infant and other family members were observed in families adopting exclusive breastfeeding, compared to families in which the infant receives artificial or mixed feeding.\n\nOur results demonstrate how a high-resolution measurement of contact matrices within infants households is feasible using wearable proximity sensing devices. Moreover, our findings suggest the mother is responsible for the large majority of the infants contact pattern, thus being the main potential source of infection for a transmissible disease. As the contribution to the infants contact pattern by other family members is very variable, vaccination against pertussis during pregnancy is probably the best strategy to protect young, unvaccinated infants.

epidemiology↗