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Estimating contact patterns relevant to the spread of infectious diseases in Russia.pdf

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Estimating contact patterns relevant to the spread of infectious diseases in Russia.pdf

Journal of Theoretical Biology 419 (2017) 1–7 Contents lists available at ScienceDirect Journal of Theoretical Biology journal homepage: /locate/yjtbi Estimating contact patterns relevant to the spread of infectious diseases in Russia Marco Ajellia,?, Maria Litvinovab,c a Bruno Kessler Foundation, Trento, Italy b School of Social Sciences, University of Trento, Trento, Italy c Tomsk Polytechnic University, Tomsk, Russia MARK ARTICLE INFO Keywords: Contact pattern Human behavior Airborne infectious diseases Age Mathematical modeling ABSTRACT Understanding human mixing patterns is the key to provide public health decision makers with model-based evaluation of strategies for the control of infectious diseases. Here we conducted a population-based survey in Tomsk, Russia, asking participants to record all their contacts in physical person during the day. We estimated 9.8 contacts per person per day on average, 15.2 when including additional estimated professional contacts. We found that contacts were highly assortative by age, especially for school-age individuals, and the number of contacts negatively correlated with the age of the participant. The network of contacts was quite clustered, with the majority of contacts (about 72%) occurring between family members, students of the same school/ university, and work colleagues. School represents the location where the largest number of contacts was recorded – students contacted about 7 individuals per day at school. Our modeling analysis based on the recorded contact patterns supports the importance of modeling age-mixing patterns – we show that, in the case of an epidemic caused by a novel in?uenza virus, school-age individuals would be the most a?ected age group, followed by adults aged 35–44 years. In conclusion, this study reveals an age-mixing pattern in general agreement with that estimated for European countries, although with several quantitative di?erences. The observed di?erences can be attributable to sociodemog