Social contact structures and time use patterns in the Manicaland Province of Zimbabwe.
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
BACKGROUND: Patterns of person-to-person contacts relevant for infectious diseases transmission are still poorly quantified in Sub-Saharan Africa (SSA), where socio-demographic structures and behavioral attitudes are expected to be different from those of more developed countries. METHODS AND FINDINGS: We conducted a diary-based survey on daily contacts and time-use of individuals of different ages in one rural and one peri-urban site of Manicaland, Zimbabwe. A total of 2,490 diaries were collected and used to derive age-structured contact matrices, to analyze time spent by individuals in different settings, and to identify the key determinants of individuals' mixing patterns. Overall 10.8 contacts per person/day were reported, with a significant difference between the peri-urban and the rural site (11.6 versus 10.2). A strong age-assortativeness characterized contacts of school-aged children, whereas the high proportion of extended families and the young population age-structure led to a significant intergenerational mixing at older ages. Individuals spent on average 67% of daytime at home, 2% at work, and 9% at school. Active participation in school and work resulted the key drivers of the number of contacts and, similarly, household size, class size, and time spent at work influenced the number of home, school, and work contacts, respectively. We found that the heterogeneous nature of home contacts is critical for an epidemic transmission chain. In particular, our results suggest that, during the initial phase of an epidemic, about 50% of infections are expected to occur among individuals younger than 12 years and less than 20% among individuals older than 35 years. CONCLUSIONS: With the current work, we have gathered data and information on the ways through which individuals in SSA interact, and on the factors that mostly facilitate this interaction. Monitoring these processes is critical to realistically predict the effects of interventions on infectious diseases dynamics.
Date Issued
2017-01-18
Date Acceptance
2017-01-05
Citation
PLOS One, 2017, 12 (1)
ISSN
1932-6203
Publisher
Public Library of Science
Journal / Book Title
PLOS One
Volume
12
Issue
1
Copyright Statement
©
2017
Melega
ro et al. This is an open
access
article
distributed
under
the terms
of the
Creative
Commons
Attribution
License (https://creativecommons.org/licenses/by/4.0/),
which
permits
unrestricte
d use, distribu
tion, and
reproduction
in any medium,
provided
the original
author
and source
are credited.
2017
Melega
ro et al. This is an open
access
article
distributed
under
the terms
of the
Creative
Commons
Attribution
License (https://creativecommons.org/licenses/by/4.0/),
which
permits
unrestricte
d use, distribu
tion, and
reproduction
in any medium,
provided
the original
author
and source
are credited.
Sponsor
Wellcome Trust
Commission of the European Communities
Identifier
http://www.ncbi.nlm.nih.gov/pubmed/28099479
PII: PONE-D-16-34135
Grant Number
084401/Z/07/Z
283955
Subjects
General Science & Technology
MD Multidisciplinary
Publication Status
Published
Coverage Spatial
United States
Article Number
e0170459