tetano
Editor, Senior Moderator
Math Biosci. 2012 Aug 2. [Epub ahead of print]
Social contact patterns and control strategies for influenza in the elderly.
Towers S, Feng Z.
Source
Department of Mathematics, Purdue University, West Lafayette, IN 47907, United States.
Abstract
Despite dramatic increases in influenza vaccination coverage in the elderly population over the past 30years, influenza mortality rates have remained static in this age group. Children are believed to be the primary spreaders of diseases such as influenza due to their high degree of inter-contact in school settings, and several studies have examined control of influenza in the entire population, including the elderly, via targeted vaccination of school children. However, such vaccination programs are expensive, and fraught with difficulties of public perception of what may be seen as an unnecessary vaccination against a disease that is normally mild in the children themselves. In the study presented here, we examine the control of influenza in the elderly using simple social distancing measures during an influenza epidemic. The recent work of Glasser et al. characterizes daily contact interactions within the population in terms of preferential mixing between age group peers, co-workers, and parents and children. We expand upon this to include interactions between grandparents and grandchildren, and fit the parameters of this formulation to the recently published social contact survey data of Mossong et al. Using this formulation, we then model an influenza epidemic with an age-structured deterministic disease model and examine how reduction in contacts between grandchildren and grandparents affects the spread of influenza to the elderly. We find that over 50% of all influenza infections in the elderly are caused by direct contact with an infected child, and we determine that social distancing between grandparents and grandchildren is remarkably effective, and is capable of reducing influenza attack rates in the elderly by up to 60%.
Copyright ? 2012. Published by Elsevier Inc.
PMID:
22877728
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/22877728
Social contact patterns and control strategies for influenza in the elderly.
Towers S, Feng Z.
Source
Department of Mathematics, Purdue University, West Lafayette, IN 47907, United States.
Abstract
Despite dramatic increases in influenza vaccination coverage in the elderly population over the past 30years, influenza mortality rates have remained static in this age group. Children are believed to be the primary spreaders of diseases such as influenza due to their high degree of inter-contact in school settings, and several studies have examined control of influenza in the entire population, including the elderly, via targeted vaccination of school children. However, such vaccination programs are expensive, and fraught with difficulties of public perception of what may be seen as an unnecessary vaccination against a disease that is normally mild in the children themselves. In the study presented here, we examine the control of influenza in the elderly using simple social distancing measures during an influenza epidemic. The recent work of Glasser et al. characterizes daily contact interactions within the population in terms of preferential mixing between age group peers, co-workers, and parents and children. We expand upon this to include interactions between grandparents and grandchildren, and fit the parameters of this formulation to the recently published social contact survey data of Mossong et al. Using this formulation, we then model an influenza epidemic with an age-structured deterministic disease model and examine how reduction in contacts between grandchildren and grandparents affects the spread of influenza to the elderly. We find that over 50% of all influenza infections in the elderly are caused by direct contact with an infected child, and we determine that social distancing between grandparents and grandchildren is remarkably effective, and is capable of reducing influenza attack rates in the elderly by up to 60%.
Copyright ? 2012. Published by Elsevier Inc.
PMID:
22877728
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/22877728