Dataset Information

The interplay between individual social behavior and clinical symptoms in small clustered groups.

ABSTRACT:

Background

Mixing patterns of human populations play a crucial role in shaping the spreading paths of infectious diseases. The diffusion of mobile and wearable devices able to record close proximity interactions represents a great opportunity for gathering detailed data on social interactions and mixing patterns in human populations. The aim of this study is to investigate how social interactions are affected by the onset of symptomatic conditions and to what extent the heterogeneity in human behavior can reflect a different risk of infection.

Methods

We study the relation between individuals' social behavior and the onset of different symptoms, by making use of data collected in 2009 among students sharing a dormitory in a North America university campus. The dataset combines Bluetooth proximity records between study participants with self-reported daily records on their health state. Specifically, we investigate whether individuals' social activity significantly changes during different symptomatic conditions, including those defining Influenza-like illness, and highlight to what extent possible heterogeneities in social behaviors among individuals with similar age and daily routines may be responsible for a different risk of infection for influenza.

Results

Our results suggest that symptoms associated with Influenza-like illness can be responsible of a reduction of about 40% in the average duration of contacts and of 30% in the daily time spent in social interactions, possibly driven by the onset of fever. However, differences in the number of daily contacts were found to be not statistically significant. In addition, we found that individuals who experienced clinical influenza during the study period were characterized by a significantly higher social activity. In particular, both the number of person-to-person contacts and the time spent in social interactions emerged as significant risk factors for influenza infection.

Conclusions

Our findings highlight that Influenza-like illness can remarkably reduce the social activity of individuals and strengthen the idea that the heterogeneity in social habits among individuals can significantly contribute in shaping differences among the individuals' risk of infection.

SUBMITTER: Poletti P

PROVIDER: S-EPMC5530511 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Publications

The interplay between individual social behavior and clinical symptoms in small clustered groups.

Poletti Piero P Visintainer Roberto R Lepri Bruno B Merler Stefano S

BMC infectious diseases 20170726 1

<h4>Background</h4>Mixing patterns of human populations play a crucial role in shaping the spreading paths of infectious diseases. The diffusion of mobile and wearable devices able to record close proximity interactions represents a great opportunity for gathering detailed data on social interactions and mixing patterns in human populations. The aim of this study is to investigate how social interactions are affected by the onset of symptomatic conditions and to what extent the heterogeneity in ...[more]

PMID: 28747154

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Dataset Information

The interplay between individual social behavior and clinical symptoms in small clustered groups.

Background

Methods

Results

Conclusions

Publications

The interplay between individual social behavior and clinical symptoms in small clustered groups.

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