Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong

Scientific Reports

Volumn 7, Issue , 2017, Pages

  Leung, Kathy ^a   Jit, Mark ^a,b,c   Lau, Eric H Y ^a   Wu, Joseph T ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

^c PUBLIC HEALTH ENGLAND   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADOLESCENT; ADULT; AGED; CHILD; CONTACT EXAMINATION; DISEASE TRANSMISSION; FEMALE; HONG KONG; HUMAN; HUMAN RELATION; INFANT; MALE; MIDDLE AGED; PRESCHOOL CHILD; RESPIRATORY TRACT INFECTION; STATISTICS AND NUMERICAL DATA; TRANSMISSION;

ADOLESCENT; ADULT; AGED; CHILD; CHILD, PRESCHOOL; CONTACT TRACING; DISEASE TRANSMISSION, INFECTIOUS; FEMALE; HONG KONG; HUMANS; INFANT; INTERPERSONAL RELATIONS; MALE; MIDDLE AGED; RESPIRATORY TRACT INFECTIONS;

EID: 85031108972     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-017-08241-1     Document Type: Article

References (39)

1. Beutels, P., Shkedy, Z., Aerts, M. & Van Damme, P. Social mixing patterns for transmission models of close contact infections: exploring self-evaluation and diary-based data collection through a web-based interface. Epidemiology and Infection 134, 1158-1166, doi:10.1017/S0950268806006418 (2006).
2. McCaw, J. M. et al. Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks. BMC Infectious Diseases 10, 166, doi:10.1186/1471-2334-10-166 (2010).
3. Read, J. M., Edmunds, W. J., Riley, S., Lessler, J. & Cummings, D. A. T. Close encounters of the infectious kind: methods to measure social mixing behaviour. Epidemiology and Infection 140, 2117-2130, doi:10.1017/S0950268812000842 (2012).
4. Mossong, J. et al. Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases. PLOS Medicine 5, e74, doi:10.1371/journal.pmed.0050074 (2008).
5. Danon, L., House, T. A., Read, J. M. & Keeling, M. J. Social encounter networks: collective properties and disease transmission. Journal of The Royal Society Interface 9, 2826-2833, doi:10.1098/rsif.2012.0357 (2012).
6. Danon, L., Read, J. M., House, T. A., Vernon, M. C. & Keeling, M. J. Social encounter networks: characterizing Great Britain. Proceedings of the Royal Society B: Biological Sciences 280, doi:10.1098/rspb.2013.1037 (2013).
7. Béraud, G. et al. The French Connection: The First Large Population-Based Contact Survey in France Relevant for the Spread of Infectious Diseases. PLOS ONE 10, e0133203, doi:10.1371/journal.pone.0133203 (2015).
8. Kifle, Y. W. et al. Animal Ownership and Touching Enrich the Context of Social Contacts Relevant to the Spread of Human Infectious Diseases. PLOS ONE 10, e0133461, doi:10.1371/journal.pone.0133461 (2015).
9. Ibuka, Y. et al. Social contacts, vaccination decisions and influenza in Japan. Journal of Epidemiology and Community Health 70, 162-167, doi:10.1136/jech-2015-205777 (2016).
10. Ajelli, M. & Litvinova, M. Estimating contact patterns relevant to the spread of infectious diseases in Russia. Journal of Theoretical Biology 419, 1-7, doi:10.1016/j.jtbi.2017.01.041 (2017).
11. Read, J. M. et al. Social mixing patterns in rural and urban areas of southern China. Proceedings of the Royal Society B: Biological Sciences 281, doi:10.1098/rspb.2014.0268 (2014).
12. Kucharski, A. J. et al. The Contribution of Social Behaviour to the Transmission of Influenza A in a Human Population. PLOS Pathogens 10, e1004206, doi:10.1371/journal.ppat.1004206 (2014).
13. Kwok, K. O. et al. Social contacts and the locations in which they occur as risk factors for influenza infection. Proceedings of the Royal Society B: Biological Sciences 281, doi:10.1098/rspb.2014.0709 (2014).
14. Fu, Y.-C., Wang, D.-W. & Chuang, J.-H. Representative Contact Diaries for Modeling the Spread of Infectious Diseases in Taiwan. PLOS ONE 7, e45113, doi:10.1371/journal.pone.0045113 (2012).
15. Horby, P. et al. Social Contact Patterns in Vietnam and Implications for the Control of Infectious Diseases. PLOS ONE 6, e16965, doi:10.1371/journal.pone.0016965 (2011).
16. Johnstone-Robertson, S. P. et al. Social Mixing Patterns Within a South African Township Community: Implications for Respiratory Disease Transmission and Control. American Journal of Epidemiology 174, 1246-1255, doi:10.1093/aje/kwr251 (2011).
17. Stein, M. L. et al. Online Respondent-Driven Sampling for Studying Contact Patterns Relevant for the Spread of Close-Contact Pathogens: A Pilot Study in Thailand. PLOS ONE 9, e85256, doi:10.1371/journal.pone.0085256 (2014).
18. Grijalva, C. G. et al. A Household-Based Study of Contact Networks Relevant for the Spread of Infectious Diseases in the Highlands of Peru. PLOS ONE 10, e0118457, doi:10.1371/journal.pone.0118457 (2015).
19. Kiti, M. C. et al. Quantifying Age-Related Rates of Social Contact Using Diaries in a Rural Coastal Population of Kenya. PLOS ONE 9, e104786, doi:10.1371/journal.pone.0104786 (2014).
20. Dodd, P. J. et al. Age- and Sex-Specific Social Contact Patterns and Incidence of Mycobacterium tuberculosis Infection. American Journal of Epidemiology 183, 156-166, doi:10.1093/aje/kwv160 (2016).
21. Melegaro, A. et al. Social Contact Structures and Time Use Patterns in the Manicaland Province of Zimbabwe. PLOS ONE 12, e0170459, doi:10.1371/journal.pone.0170459 (2017).
22. Eames, K. T. D., Tilston, N. L., Brooks-Pollock, E. & Edmunds, W. J. Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza. PLOS Computational Biology 8, e1002425, doi:10.1371/journal.pcbi.1002425 (2012).
23. Rohani, P., Zhong, X. & King, A. A. Contact Network Structure Explains the Changing Epidemiology of Pertussis. Science 330, 982 (2010).
24. Wu, J. T. et al. Logistical feasibility and potential benefits of a population-wide passive-immunotherapy program during an influenza pandemic. Proceedings of the National Academy of Sciences 107, 3269-3274, doi:10.1073/pnas.0911596107 (2010).
25. Birrell, P. J. et al. Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London. Proceedings of the National Academy of Sciences 108, 18238-18243, doi:10.1073/pnas.1103002108 (2011).
26. Wu, J. T. et al. Inferring Influenza Infection Attack Rate from Seroprevalence Data. PLOS Pathogens 10, e1004054, doi:10.1371/ journal.ppat.1004054 (2014).
27. Bedford, T. et al. Global circulation patterns of seasonal influenza viruses vary with antigenic drift. Nature 523, 217-220, doi:10.1038/nature14460 (2015).
28. Yamin, D. et al. Vaccination strategies against respiratory syncytial virus. Proceedings of the National Academy of Sciences 113, 13239-13244, doi:10.1073/pnas.1522597113 (2016).
29. Ogunjimi, B. et al. Using empirical social contact data to model person to person infectious disease transmission: An illustration for varicella. Mathematical Biosciences 218, 80-87, doi:10.1016/j.mbs.2008.12.009 (2009).
30. Xiao, X., van Hoek, A. J., Kenward, M. G., Melegaro, A. & Jit, M. Clustering of contacts relevant to the spread of infectious disease. Epidemics 17, 1-9, doi:10.1016/j.epidem.2016.08.001 (2016).
31. Melegaro, A., Jit, M., Gay, N., Zagheni, E. & Edmunds, W. J. What types of contacts are important for the spread of infections? Using contact survey data to explore European mixing patterns. Epidemics 3, 143-151, doi:10.1016/j.epidem.2011.04.001 (2011).
32. Horby, P. W., Pfeiffer, D. & Oshitani, H. Prospects for Emerging Infections in East and Southeast Asia 10 Years after Severe Acute Respiratory Syndrome. Emerging Infectious Disease journal 19, 853, doi:10.3201/eid1906.121783 (2013).
33. Riley, S. et al. Epidemiological Characteristics of 2009 (H1N1) Pandemic Influenza Based on Paired Sera from a Longitudinal Community Cohort Study. PLOS Medicine 8, e1000442, doi:10.1371/journal.pmed.1000442 (2011).
34. The Government of the Hong Kong Special Administrative Region Census and Statistics Department. Thematic Household Survey Report - Report No. 56, http://www.censtatd.gov.hk/hkstat/sub/sp453.jsp?productCode=C0000085 (2015).
35. Rübsamen, N., Akmatov, M. K., Castell, S., Karch, A. & Mikolajczyk, R. T. Comparison of response patterns in different survey designs: a longitudinal panel with mixed-mode and online-only design. Emerging Themes in Epidemiology 14, 4, doi:10.1186/ s12982-017-0058-2 (2017).
36. Kenny, D. A. Learn how you can do a mediation analysis and output a text description of your results: Go to mediational analysis using DataToText using SPSS or R, http://davidakenny.net/cm/mediate.htm (2016).
37. Austin, P. C. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate behavioral research 46, 399-424 (2011).
38. Ho, D., Imai, K., King, G. & Stuart, E. MatchIt: Nonparametric Preprocessing for Parametric Causal Inference, https://gking.harvard. edu/matchit (2017).
39. Silverman, B. W. Density estimation for statistics and data analysis. Vol. 26 (CRC press, 1986).