Quantifying the Shift in Social Contact Patterns in Response to Non-Pharmaceutical Interventions

2020 ◽  
Author(s):  
Zachary McCarthy ◽  
Yanyu Xiao ◽  
Francesca Scarabel ◽  
Biao Tang ◽  
Nicola Luigi Bragazzi ◽  
...  
Keyword(s):  
Social Contact ◽  
Contact Patterns ◽  
Pharmaceutical Interventions

scholarly journals Estimating data-driven COVID-19 mitigation strategies for safe university reopening

2021 ◽  
Author(s):  
Qihui Yang ◽  
Don M. Gruenbacher ◽  
Caterina M. Scoglio
Keyword(s):  
Extreme Events ◽  
Social Contact ◽  
The United States ◽  
Vaccination Rate ◽  
Mitigation Strategies ◽  
Contact Patterns ◽  
University Population ◽  
The University ◽  
University Settings ◽  
Pharmaceutical Interventions

AbstractAfter one pandemic year of remote or hybrid instructional modes, universities in the United States are now planning for an in-person fall semester in 2021. However, it is uncertain what the vaccination rate will look like after students, faculty, and staff return to campus. To help inform university-reopening policies, we collected survey data on social contact patterns and developed an agent-based model to simulate the spread of COVID-19 in university settings. In this paper, we aim to identify the immunity threshold that, if exceeded, would lead to a relatively safe on-campus experience for the university population. With relaxed non-pharmaceutical interventions, we estimated that immunity in at least 60% of the university population is needed for safe university reopening. Still, attention needs to be paid to extreme events that could lead to huge infection size spikes. At an immune level of 60%, continuing non-pharmaceutical interventions, such as wearing masks, could lead to an 89% reduction in the maximum cumulative infection, which reflects the possible non-negligible infection size from extreme events.

scholarly journals Influence of social contact patterns and demographic factors on influenza simulation results

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Ruprecht Schmidt-Ott ◽  
Markus Schwehm ◽  
Martin Eichner
Keyword(s):  
Social Contact ◽  
Demographic Factors ◽  
Contact Patterns ◽  
Simulation Results

scholarly journals Social contact patterns of infants in deciding vaccination strategy: a prospective, cross-sectional, single-centre study

2018 ◽  
Vol 146 (9) ◽  
pp. 1157-1166 ◽  
Author(s):  
M. M. Oguz ◽  
A. D. Camurdan ◽  
F. N. Aksakal ◽  
M. Akcaboy ◽  
E. Altinel Acoglu
Keyword(s):  
Respiratory Tract ◽  
Respiratory Symptoms ◽  
Whooping Cough ◽  
Social Contact ◽  
Vaccination Strategy ◽  
Median Number ◽  
Cross Sectional ◽  
Contact Patterns ◽  
Single Centre Study ◽  
Tract Infections

AbstractSocial contact between individuals is believed to be a fundamental cause in the transmission of many respiratory tract infections. Because they have not yet been fully vaccinated, infants are at high risk for contracting whooping cough, influenza and their serious complications. Therefore, determining infant social contact patterns is an important step in protecting them from respiratory tract infection. This study included 1200 healthy infants (<12 months of age). Social contact diaries were used to estimate the frequency and nature of the infants’ social contacts. This survey also gathered information regarding the infants’ respiratory symptoms and their frequency of attendance at crowded places over a period of 1 week. The diary return rate was 83.8% (N = 1006), and there was a total of 4706 contacts reported for these infants. The median daily contact number per capita was 4 (range 1–18). The median number of contacts with adolescents was 0 (range 0–7). Of the infants, 50.3% had contact with non-household individuals. The mothers had the longest contacts with their babies. Contacts with school children, frequency of attendance at crowded places and age were determined to be significant effective factors for reporting respiratory symptoms. Results suggest that school-age siblings and the mothers should be primarily vaccinated, and parents should keep their babies away from crowded places for protecting their infants.

scholarly journals Quantifying heterogeneous contact patterns in Japan: a social contact survey

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Lankeshwara Munasinghe ◽  
Yusuke Asai ◽  
Hiroshi Nishiura
Keyword(s):  
Social Contact ◽  
Contact Patterns ◽  
Contact Survey

The effect of age, environment and management on social contact patterns in sheep

2020 ◽  
Vol 225 ◽  
pp. 104964
Author(s):  
Laura Ozella ◽  
Joss Langford ◽  
Laetitia Gauvin ◽  
Emily Price ◽  
Ciro Cattuto ◽  
...  
Keyword(s):  
Social Contact ◽  
Contact Patterns ◽  
Effect Of Age

Predicting Temporal Social Contact Patterns for Data Forwarding in Opportunistic Mobile Networks

2017 ◽  
Vol 66 (11) ◽  
pp. 10372-10383 ◽  
Author(s):  
Huan Zhou ◽  
Victor C. M. Leung ◽  
Chunsheng Zhu ◽  
Shouzhi Xu ◽  
Jialu Fan
Keyword(s):  
Mobile Networks ◽  
Social Contact ◽  
Data Forwarding ◽  
Contact Patterns ◽  
Opportunistic Mobile Networks

Age Trends in Daily Social Contact Patterns

2011 ◽  
Vol 33 (5) ◽  
pp. 598-631 ◽  
Author(s):  
Benjamin Cornwell
Keyword(s):  
Social Contact ◽  
Contact Patterns ◽  
Age Trends

scholarly journals Age- and Sex-Specific Social Contact Patterns and Incidence ofMycobacterium tuberculosisInfection

2015 ◽  
pp. kwv160 ◽  
Author(s):  
Peter J. Dodd ◽  
Clare Looker ◽  
Ian D. Plumb ◽  
Virginia Bond ◽  
Ab Schaap ◽  
...  
Keyword(s):  
Social Contact ◽  
Contact Patterns ◽  
Age And Sex

scholarly journals Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors

2019 ◽  
Vol 4 ◽  
pp. 84 ◽  
Author(s):  
Moses Chapa Kiti ◽  
Alessia Melegaro ◽  
Ciro Cattuto ◽  
David James Nokes
Keyword(s):  
Urban Areas ◽  
Respiratory Infections ◽  
Social Contact ◽  
Simulation Models ◽  
Face To Face ◽  
Rural And Urban Areas ◽  
Contact Patterns ◽  
Rural And Urban ◽  
Syncytial Virus ◽  
The Impact

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

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