scholarly journals Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases

PLoS Medicine ◽  
2008 ◽  
Vol 5 (3) ◽  
pp. e74 ◽  
Author(s):  
Joël Mossong ◽  
Niel Hens ◽  
Mark Jit ◽  
Philippe Beutels ◽  
Kari Auranen ◽  
...  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
O. le Polain de Waroux ◽  
S. Cohuet ◽  
D. Ndazima ◽  
A. J. Kucharski ◽  
A. Juan-Giner ◽  
...  

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0148718 ◽  
Author(s):  
Yimer Wasihun Kifle ◽  
Nele Goeyvaerts ◽  
Kim Van Kerckhove ◽  
Lander Willem ◽  
Adam Kucharski ◽  
...  

2020 ◽  
Vol 13 (1) ◽  
pp. 1-12
Author(s):  
Audrey M. Dorélien ◽  
Alisha Simon ◽  
Sarah Hagge ◽  
Kathleen Thiede Call ◽  
Eva Enns ◽  
...  

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0133461 ◽  
Author(s):  
Yimer Wasihun Kifle ◽  
Nele Goeyvaerts ◽  
Kim Van Kerckhove ◽  
Lander Willem ◽  
Christel Faes ◽  
...  

2014 ◽  
Vol 281 (1789) ◽  
pp. 20140709 ◽  
Author(s):  
Kin O. Kwok ◽  
Benjamin J. Cowling ◽  
Vivian W. I. Wei ◽  
Kendra M. Wu ◽  
Jonathan M. Read ◽  
...  

The interaction of human social behaviour and transmission is an intriguing aspect of the life cycle of respiratory viral infections. Although age-specific mixing patterns are often assumed to be the key drivers of the age-specific heterogeneity in transmission, the association between social contacts and biologically confirmed infection has not previously been tested at the individual level. We administered a questionnaire to participants in a longitudinal cohort survey of influenza in which infection was defined by longitudinal paired serology. Using a variety of statistical approaches, we found overwhelming support for the inclusion of individual age in addition to contact variables when explaining odds of infection: the best model not including age explained only 15.7% of the deviance, whereas the best model with age explained 23.6%. However, within age groups, we did observe an association between contacts, locations and infection: median numbers of contacts (or locations) reported by those infected were higher than those from the uninfected group in every age group other than the youngest. Further, we found some support for the retention of location and contact variables in addition to age in our regression models, with excess odds of infection of approximately 10% per additional 10 contacts or one location. These results suggest that, although the relationship between age and incidence of respiratory infection at the level of the individual is not driven by self-reported social contacts, risk within an age group may be.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dina Mistry ◽  
Maria Litvinova ◽  
Ana Pastore y Piontti ◽  
Matteo Chinazzi ◽  
Laura Fumanelli ◽  
...  

AbstractMathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for realism in addressing complex public health questions is, however, calling for accurate models of the human contact patterns that govern the disease transmission processes. Here we present a data-driven approach to generate effective population-level contact matrices by using highly detailed macro (census) and micro (survey) data on key socio-demographic features. We produce age-stratified contact matrices for 35 countries, including 277 sub-national administratvie regions of 8 of those countries, covering approximately 3.5 billion people and reflecting the high degree of cultural and societal diversity of the focus countries. We use the derived contact matrices to model the spread of airborne infectious diseases and show that sub-national heterogeneities in human mixing patterns have a marked impact on epidemic indicators such as the reproduction number and overall attack rate of epidemics of the same etiology. The contact patterns derived here are made publicly available as a modeling tool to study the impact of socio-economic differences and demographic heterogeneities across populations on the epidemiology of infectious diseases.


PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e76180 ◽  
Author(s):  
Albert Jan van Hoek ◽  
Nick Andrews ◽  
Helen Campbell ◽  
Gayatri Amirthalingam ◽  
W. John Edmunds ◽  
...  

2006 ◽  
Vol 3 (1) ◽  
Author(s):  
WJ Edmunds ◽  
G Kafatos ◽  
J Wallinga ◽  
JR Mossong

2021 ◽  
Author(s):  
Deus Thindwa ◽  
Kondwani C Jambo ◽  
John Ojal ◽  
Peter MacPherson ◽  
Mphatso D Phiri ◽  
...  

Introduction: Understanding human mixing patterns relevant to infectious diseases spread through close contact is vital for modelling transmission dynamics and optimisation of disease control strategies. Mixing patterns in low-income countries like Malawi are not well understood. Methodology: We conducted a social mixing survey in urban Blantyre, Malawi between April and July 2021 (between the 2nd and 3rd wave of COVID-19 infections). Participants living in densely-populated neighbourhoods were randomly sampled and, if they consented, reported their physical and non-physical contacts within and outside homes lasting at least 5 minutes during the previous day. Age-specific mixing rates were calculated, and a negative binomial mixed effects model was used to estimate determinants of contact behaviour. Results: Of 1,201 individuals enrolled, 702 (58.5%) were female, the median age was 15 years (interquartile range [IQR] 5-32) and 127 (10.6%) were HIV-positive. On average, participants reported 10.3 contacts per day (range: 1-25). Mixing patterns were highly age-assortative, particularly those within the community and with skin-to-skin contact. Adults aged 20-49y reported the most contacts (median:11, IQR: 8-15) of all age groups; 38% (95%CI: 16-63) more than infants (median: 8, IQR: 5-10), who had the least contacts. Household contact frequency increased by 3% (95%CI 2-5) per additional household member. Unemployed participants had 15% (95%CI: 9-21) fewer contacts than other adults. Among long range (>30 meters away from home) contacts, secondary school children had the largest median contact distance from home (257m, IQR 78-761). HIV-positive status in adults >18 years-old was not associated with increased contact patterns (1%, 95%CI -9-12). During this period of relatively low COVID-19 incidence in Malawi, 301 (25.1%) individuals stated that they had limited their contact with others due to COVID-19 precautions; however, their reported contacts were not fewer (8%, 95%CI 1-13). Conclusion: In urban Malawi, contact rates, are high and age-assortative, with little behavioural change due to either HIV-status or COVID-19 circulation. This highlights the limits of contact-restriction-based mitigation strategies in such settings and the need for pandemic preparedness to better understand how contact reductions can be enabled and motivated. Keywords: Social contacts, Transmission, Mixing data, Infectious disease, Malawi, Africa


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