Evidence map›Paper›PMID 28099479›Full record

ArticlePloS one2017

Social Contact Structures and Time Use Patterns in the Manicaland Province of Zimbabwe.

Alessia Melegaro, Emanuele Del Fava, Piero Poletti, Stefano Merler, Constance Nyamukapa, John Williams, Simon Gregson, Piero Manfredi

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Alessia MelegaroCarlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy.ORCID http://orcid.org/0000-0003-2221-8898
Emanuele Del FavaCarlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy.
Piero PolettiCarlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy.
Stefano MerlerCenter for Information Technology, Bruno Kessler Foundation, Trento, Italy.
Constance NyamukapaDepartment of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
John WilliamsDepartment of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Simon GregsonDepartment of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Piero ManfrediDepartment of Economics and Management, University of Pisa, Pisa, Italy.

Funding

European Research Council 283955
6 · The paper itself

Abstract

backgroundPatterns 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

findingsWe 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.

conclusionsWith 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.

Indexed as

Interpersonal RelationsSocial BehaviorAdolescentAdultAgingChildChild, PreschoolCommunicable DiseasesFemaleHumansInfantMaleMiddle AgedPopulation DensitySurveys and QuestionnairesYoung Adult

Identifiers

PMID28099479
PMCPMC5242544

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.