Literature DB >> 26847017

Relevance of workplace social mixing during influenza pandemics: an experimental modelling study of workplace cultures.

T Timpka1, H Eriksson2, E Holm3, M Strömgren3, J Ekberg1, A Spreco1, Ö Dahlström4.   

Abstract

Workplaces are one of the most important regular meeting places in society. The aim of this study was to use simulation experiments to examine the impact of different workplace cultures on influenza dissemination during pandemics. The impact is investigated by experiments with defined social-mixing patterns at workplaces using semi-virtual models based on authentic sociodemographic and geographical data from a North European community (population 136 000). A simulated pandemic outbreak was found to affect 33% of the total population in the community with the reference academic-creative workplace culture; virus transmission at the workplace accounted for 10·6% of the cases. A model with a prevailing industrial-administrative workplace culture generated 11% lower incidence than the reference model, while the model with a self-employed workplace culture (also corresponding to a hypothetical scenario with all workplaces closed) produced 20% fewer cases. The model representing an academic-creative workplace culture with restricted workplace interaction generated 12% lower cumulative incidence compared to the reference model. The results display important theoretical associations between workplace social-mixing cultures and community-level incidence rates during influenza pandemics. Social interaction patterns at workplaces should be taken into consideration when analysing virus transmission patterns during influenza pandemics.

Entities:  

Keywords:  Epidemiology; infectious disease control; influenza; medical informatics (veterinary and medical); modelling

Mesh:

Year:  2016        PMID: 26847017      PMCID: PMC9150599          DOI: 10.1017/S0950268816000169

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   4.434


  39 in total

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3.  Ontology based modeling of pandemic simulation scenarios.

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Journal:  Stud Health Technol Inform       Date:  2007

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Authors:  Supriya Kumar; John J Grefenstette; David Galloway; Steven M Albert; Donald S Burke
Journal:  Am J Public Health       Date:  2013-06-13       Impact factor: 9.308

7.  Is population structure sufficient to generate area-level inequalities in influenza rates? An examination using agent-based models.

Authors:  Supriya Kumar; Kaitlin Piper; David D Galloway; James L Hadler; John J Grefenstette
Journal:  BMC Public Health       Date:  2015-09-23       Impact factor: 3.295

8.  Contact profiles in eight European countries and implications for modelling the spread of airborne infectious diseases.

Authors:  Mirjam Kretzschmar; Rafael T Mikolajczyk
Journal:  PLoS One       Date:  2009-06-17       Impact factor: 3.240

9.  Simulation suggests that rapid activation of social distancing can arrest epidemic development due to a novel strain of influenza.

Authors:  Joel K Kelso; George J Milne; Heath Kelly
Journal:  BMC Public Health       Date:  2009-04-29       Impact factor: 3.295

10.  FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

Authors:  John J Grefenstette; Shawn T Brown; Roni Rosenfeld; Jay DePasse; Nathan T B Stone; Phillip C Cooley; William D Wheaton; Alona Fyshe; David D Galloway; Anuroop Sriram; Hasan Guclu; Thomas Abraham; Donald S Burke
Journal:  BMC Public Health       Date:  2013-10-08       Impact factor: 3.295

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  3 in total

1.  Effectiveness of workplace social distancing measures in reducing influenza transmission: a systematic review.

Authors:  Faruque Ahmed; Nicole Zviedrite; Amra Uzicanin
Journal:  BMC Public Health       Date:  2018-04-18       Impact factor: 3.295

2.  COVID surveillance robot: Monitoring social distancing constraints in indoor scenarios.

Authors:  Adarsh Jagan Sathyamoorthy; Utsav Patel; Moumita Paul; Yash Savle; Dinesh Manocha
Journal:  PLoS One       Date:  2021-12-01       Impact factor: 3.240

3.  Evaluating the impact of the weather conditions on the influenza propagation.

Authors:  David E Singh; Maria-Cristina Marinescu; Jesus Carretero; Concepcion Delgado-Sanz; Diana Gomez-Barroso; Amparo Larrauri
Journal:  BMC Infect Dis       Date:  2020-04-05       Impact factor: 3.090

  3 in total

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