Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors
| Autor: | Moses C. Kiti, Michele Tizzoni, Ciro Cattuto, Dorothy C. Koech, Patrick K. Munywoki, Luca Cappa, Milosch Meriac, D. James Nokes, Alain Barrat, Timothy M. Kinyanjui, André Panisson |
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| Přispěvatelé: | Data Science Laboratory (ISI), ISI Foundation Institute for Scientific Interchange, CPT - E5 Physique statistique et systèmes complexes, Centre de Physique Théorique - UMR 7332 (CPT), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Předmět: |
0301 basic medicine
contact patterns Population Developing country Distribution (economics) Context (language use) wearable proximity sensors infectious disease control 03 medical and health sciences respiratory infections 0302 clinical medicine RA0421 Environmental health 030212 general & internal medicine [PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech] education Disease burden ComputingMilieux_MISCELLANEOUS education.field_of_study Data collection Community engagement contact networks business.industry 1. No poverty households Regular Article Focus group Computer Science Applications Computational Mathematics 030104 developmental biology Geography Modeling and Simulation business |
| Zdroj: | Europe PubMed Central EPJ Data Science EPJ Data Science, EDP Sciences, 2016, 5, pp.21. ⟨10.1140/epjds/s13688-016-0084-2⟩ Epj Data Science Kiti, M C, Tizzoni, M, Kinyanjui, T M, Koech, D C, Munywoki, P K, Meriac, M, Cappa, L, Panisson, A, Barrat, A, Cattuto, C & Nokes, D J 2016, ' Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors ', EPJ Data Science, vol. 5, 21 . https://doi.org/10.1140/epjds/s13688-016-0084-2 EPJ Data Science, 2016, 5, pp.21. ⟨10.1140/epjds/s13688-016-0084-2⟩ |
| ISSN: | 2193-1127 |
| DOI: | 10.1140/epjds/s13688-016-0084-2 |
| Popis: | Close proximity interactions between individuals influence how infections spread. Quantifying close contacts in developing world settings, where such data is sparse yet disease burden is high, can provide insights into the design of intervention strategies such as vaccination. Recent technological advances have enabled collection of time-resolved face-to-face human contact data using radio frequency proximity sensors. The acceptability and practicalities of using proximity devices within the developing country setting have not been investigated. We present and analyse data arising from a prospective study of 5 households in rural Kenya, followed through 3 consecutive days. Pre-study focus group discussions with key community groups were held. All residents of selected households carried wearable proximity sensors to collect data on their close ( |
| Databáze: | OpenAIRE |
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