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Duval A, Leclerc QJ, Guillemot D, Temime L, Opatowski L. An algorithm to build synthetic temporal contact networks based on close-proximity interactions data. PLoS Comput Biol 2024; 20:e1012227. [PMID: 38870216 PMCID: PMC11207132 DOI: 10.1371/journal.pcbi.1012227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 06/26/2024] [Accepted: 06/04/2024] [Indexed: 06/15/2024] Open
Abstract
Small populations (e.g., hospitals, schools or workplaces) are characterised by high contact heterogeneity and stochasticity affecting pathogen transmission dynamics. Empirical individual contact data provide unprecedented information to characterize such heterogeneity and are increasingly available, but are usually collected over a limited period, and can suffer from observation bias. We propose an algorithm to stochastically reconstruct realistic temporal networks from individual contact data in healthcare settings (HCS) and test this approach using real data previously collected in a long-term care facility (LTCF). Our algorithm generates full networks from recorded close-proximity interactions, using hourly inter-individual contact rates and information on individuals' wards, the categories of staff involved in contacts, and the frequency of recurring contacts. It also provides data augmentation by reconstructing contacts for days when some individuals are present in the HCS without having contacts recorded in the empirical data. Recording bias is formalized through an observation model, to allow direct comparison between the augmented and observed networks. We validate our algorithm using data collected during the i-Bird study, and compare the empirical and reconstructed networks. The algorithm was substantially more accurate to reproduce network characteristics than random graphs. The reconstructed networks reproduced well the assortativity by ward (first-third quartiles observed: 0.54-0.64; synthetic: 0.52-0.64) and the hourly staff and patient contact patterns. Importantly, the observed temporal correlation was also well reproduced (0.39-0.50 vs 0.37-0.44), indicating that our algorithm could recreate a realistic temporal structure. The algorithm consistently recreated unobserved contacts to generate full reconstructed networks for the LTCF. To conclude, we propose an approach to generate realistic temporal contact networks and reconstruct unobserved contacts from summary statistics computed using individual-level interaction networks. This could be applied and extended to generate contact networks to other HCS using limited empirical data, to subsequently inform individual-based epidemic models.
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Affiliation(s)
- Audrey Duval
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
- Laboratoire Modélisation, Epidémiologie et Surveillance des Risques Sanitaires (MESuRS), Conservatoire National des Arts et Métiers, Paris, France
| | - Quentin J. Leclerc
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
- Laboratoire Modélisation, Epidémiologie et Surveillance des Risques Sanitaires (MESuRS), Conservatoire National des Arts et Métiers, Paris, France
| | - Didier Guillemot
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
- AP-HP, Paris Saclay, Department of Public Health, Medical Information, Clinical research, Garches, France
| | - Laura Temime
- Laboratoire Modélisation, Epidémiologie et Surveillance des Risques Sanitaires (MESuRS), Conservatoire National des Arts et Métiers, Paris, France
- Institut Pasteur, Conservatoire National des Arts et Métiers, Unité PACRI, Paris, France
| | - Lulla Opatowski
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
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Robsky KO, Tram KH, Dowdy DW, Zelner J. Methods for measuring short-term geographical mobility used in infectious disease research: a scoping review protocol. BMJ Open 2023; 13:e072439. [PMID: 37793932 PMCID: PMC10551932 DOI: 10.1136/bmjopen-2023-072439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 08/30/2023] [Indexed: 10/06/2023] Open
Abstract
INTRODUCTION Geographical mobility, the movement of individuals or populations, may increase an individual's risk of acquiring or transmitting infectious diseases, including HIV, tuberculosis, malaria and COVID-19. Many studies have collected information on short-term mobility through self-reported travel histories or using GPS trackers, but there has been no consistent conceptualisation and operationalisation of such geographical mobility in global health research. This protocol aims to describe and synthesise different approaches to measuring short-term mobility. METHODS AND ANALYSIS We will search three databases (PubMed, Embase and Global Health) for peer-reviewed articles. After removing duplicates, two reviewers will first screen the titles and abstracts and then proceed to full-text screening. We will include studies that measure mobility at the individual level in the context of infectious diseases, including clinical trials, epidemiological studies and analyses of register data. Additional articles for inclusion may be identified through review of references in selected papers. We will summarise the method of data collection (GPS trackers, cellphones, retrospective self-report, travel journal, etc) and the specific measures used (overnight travel, having a secondary residence, travel outside of district, etc). ETHICS AND DISSEMINATION This study consists of reviewing and abstracting existing data from publicly available materials, and therefore does not require ethical approval. The results of this study will be submitted for peer reviewed publication and may be presented at a relevant global health conference.
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Affiliation(s)
- Katherine O Robsky
- Center for Global Health Practice and Impact, Georgetown University, Washington, District of Columbia, USA
| | - Khai Hoan Tram
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - David W Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jon Zelner
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
- Center for Social Epidemiology and Population Health, University of Michigan, Ann Arbor, Michigan, USA
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Leung WTM, Meeyai A, Holt HR, Khieu B, Chhay T, Seng S, Pok S, Chiv P, Drake T, Rudge JW. Social contact patterns relevant for infectious disease transmission in Cambodia. Sci Rep 2023; 13:5542. [PMID: 37015945 PMCID: PMC10072808 DOI: 10.1038/s41598-023-31485-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 03/13/2023] [Indexed: 04/06/2023] Open
Abstract
Social mixing patterns are key determinants of infectious disease transmission. Mathematical models parameterised with empirical data from contact pattern surveys have played an important role in understanding epidemic dynamics and informing control strategies, including for SARS-CoV-2. However, there is a paucity of data on social mixing patterns in many settings. We conducted a community-based survey in Cambodia in 2012 to characterise mixing patterns and generate setting-specific contact matrices according to age and urban/rural populations. Data were collected using a diary-based approach from 2016 participants, selected by stratified random sampling. Contact patterns were highly age-assortative, with clear intergenerational mixing between household members. Both home and school were high-intensity contact settings, with 27.7% of contacts occurring at home with non-household members. Social mixing patterns differed between rural and urban residents; rural participants tended to have more intergenerational mixing, and a higher number of contacts outside of home, work or school. Participants had low spatial mobility, with 88% of contacts occurring within 1 km of the participants' homes. These data broaden the evidence-base on social mixing patterns in low and middle-income countries and Southeast Asia, and highlight within-country heterogeneities which may be important to consider when modelling the dynamics of pathogens transmitted via close contact.
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Affiliation(s)
- William T M Leung
- Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK
| | - Aronrag Meeyai
- Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK
- Department of Epidemiology, Faculty of Mahidol Public Health, Mahidol University, Bangkok, 10400, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK
| | - Hannah R Holt
- Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK.
| | - Borin Khieu
- Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia
| | - Ty Chhay
- Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia
| | - Sokeyra Seng
- Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia
| | - Samkol Pok
- Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia
- National Institute of Science, Technology and Innovation, Ministry of Industry, Science, Technology and Innovation, National Road 2, Phnom Penh, Cambodia
| | - Phiny Chiv
- Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia
| | - Tom Drake
- Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK
| | - James W Rudge
- Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK
- Department of Epidemiology, Faculty of Mahidol Public Health, Mahidol University, Bangkok, 10400, Thailand
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Franklin RS, Delmelle EC, Andris C, Cheng T, Dodge S, Franklin J, Heppenstall A, Kwan M, Li W, McLafferty S, Miller JA, Munroe DK, Nelson T, Öner Ö, Pumain D, Stewart K, Tong D, Wentz EA. Making Space in Geographical Analysis. GEOGRAPHICAL ANALYSIS 2023; 55:325-341. [PMID: 38505735 PMCID: PMC10947325 DOI: 10.1111/gean.12325] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 01/13/2022] [Accepted: 03/08/2022] [Indexed: 03/21/2024]
Abstract
In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter for all. We emphasize key aspects of the field, including accessibility, urban change, and spatial interaction and behavior, providing a high-level research agenda that indicates a variety of gaps and routes for future research that will not only lead to more equitable and aware solutions to local and global challenges, but also innovative and novel research methods, concepts, and data. We close with a set of representation and inclusion challenges to our discipline, researchers, and publication outlets.
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Affiliation(s)
- Rachel S. Franklin
- Centre for Urban and Regional Development Studies (CURDS)School of Geography, Politics and SociologyNewcastle UniversityNewcastle upon TyneUK
- Alan Turing Institute for AI and Data ScienceThe British LibraryLondonUK
| | - Elizabeth C. Delmelle
- Department of Geography and Earth SciencesUniversity of North Carolina at CharlotteCharlotteNorth CarolinaUSA
| | - Clio Andris
- School of City and Regional PlanningSchool of Interactive ComputingGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Tao Cheng
- SpaceTimeLabDepartment of CivilEnvironmental and Geomatic EngineeringUniversity College London (UCL)LondonUK
| | - Somayeh Dodge
- Department of GeographyUniversity of California Santa BarbaraSanta BarbaraCaliforniaUSA
| | - Janet Franklin
- Department of Botany and Plant SciencesUniversity of CaliforniaRiversideCaliforniaUSA
| | - Alison Heppenstall
- Alan Turing Institute for AI and Data ScienceThe British LibraryLondonUK
- School of Political and Social SciencesMRC/CSO Social and Public Health Sciences UnitUniversity of GlasgowGlasgowUK
| | - Mei‐Po Kwan
- Department of Geography and Resource Management and Institute of Space and Earth Information ScienceThe Chinese University of Hong KongHong KongChina
| | - WenWen Li
- School of Geographical Sciences and Urban PlanningArizona State UniversityTempeArizonaUSA
| | - Sara McLafferty
- Department of Geography & Geographic Information ScienceUniversity of Illinois Urbana‐ChampaignChampaignIllinoisUSA
| | - Jennifer A. Miller
- Department of Geography and the EnvironmentThe University of Texas at AustinAustinTexasUSA
| | - Darla K. Munroe
- Department of GeographyThe Ohio State UniversityColumbusOhioUSA
| | - Trisalyn Nelson
- Department of GeographyUniversity of California Santa BarbaraSanta BarbaraCaliforniaUSA
| | - Özge Öner
- Department of Land EconomyUniversity of CambridgeCambridgeUK
| | - Denise Pumain
- University Paris I Pantheon Sorbonne and CNRSParisFrance
| | - Kathleen Stewart
- Department of Geographical SciencesUniversity of MarylandCollege Park, MarylandUSA
| | - Daoqin Tong
- School of Geographical Sciences and Urban PlanningArizona State UniversityTempeArizonaUSA
| | - Elizabeth A. Wentz
- School of Geographical Sciences and Urban PlanningArizona State UniversityTempeArizonaUSA
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Li Y, Mao N, Guo L, Guo L, Chen L, Zhao L, Wang Q, Long E. Review of animal transmission experiments of respiratory viruses: Implications for transmission risk of SARS-COV-2 in humans via different routes. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023. [PMID: 36973964 DOI: 10.1111/risa.14129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
Exploring transmission risk of different routes has major implications for epidemic control. However, disciplinary boundaries have impeded the dissemination of epidemic information, have caused public panic about "air transmission," "air-conditioning transmission," and "environment-to-human transmission," and have triggered "hygiene theater." Animal experiments provide experimental evidence for virus transmission, but more attention is paid to whether transmission is driven by droplets or aerosols and using the dichotomy to describe most transmission events. Here, according to characteristics of experiment setups, combined with patterns of human social interactions, we reviewed and grouped animal transmission experiments into four categories-close contact, short-range, fomite, and aerosol exposure experiments-and provided enlightenment, with experimental evidence, on the transmission risk of severe acute respiratory syndrome coronavirus (SARS-COV-2) in humans via different routes. When referring to "air transmission," context should be showed in elaboration results, rather than whether close contact, short or long range is uniformly described as "air transmission." Close contact and short range are the major routes. When face-to-face, unprotected, horizontally directional airflow does promote transmission, due to virus decay and dilution in air, the probability of "air conditioning transmission" is low; the risk of "environment-to-human transmission" highly relies on surface contamination and human behavior based on indirect path of "fomite-hand-mucosa or conjunctiva" and virus decay on surfaces. Thus, when discussing the transmission risk of SARS-CoV-2, we should comprehensively consider the biological basis of virus transmission, environmental conditions, and virus decay. Otherwise, risk of certain transmission routes, such as long-range and fomite transmission, will be overrated, causing public excessive panic, triggering ineffective actions, and wasting epidemic prevention resources.
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Affiliation(s)
- Ying Li
- MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China
| | - Ning Mao
- MOE Key Laboratory of Deep Earth Science and Engineering, Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Lei Guo
- MOE Key Laboratory of Deep Earth Science and Engineering, Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Luyao Guo
- MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China
| | - Linlin Chen
- MOE Key Laboratory of Deep Earth Science and Engineering, Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Li Zhao
- China Academy of Building Research, Beijing, China
| | - Qingqin Wang
- China Academy of Building Research, Beijing, China
| | - Enshen Long
- MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China
- MOE Key Laboratory of Deep Earth Science and Engineering, Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
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Bridgen JR, Jewell C, Read JM. Social mixing patterns in the UK following the relaxation of COVID-19 pandemic restrictions, July-August 2020: a cross-sectional online survey. BMJ Open 2022; 12:e059231. [PMID: 36523221 PMCID: PMC9748508 DOI: 10.1136/bmjopen-2021-059231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES To quantify and characterise non-household contact and to identify the effect of shielding and isolating on contact patterns. DESIGN Cross-sectional study. SETTING AND PARTICIPANTS Anyone living in the UK was eligible to take part in the study. We recorded 5143 responses to the online questionnaire between 28 July 2020 and 14 August 2020. OUTCOME MEASURES Our primary outcome was the daily non-household contact rate of participants. Secondary outcomes were propensity to leave home over a 7 day period, whether contacts had occurred indoors or outdoors locations visited, the furthest distance travelled from home, ability to socially distance and membership of support bubble. RESULTS The mean rate of non-household contacts per person was 2.9 d-1. Participants attending a workplace (adjusted incidence rate ratio (aIRR) 3.33, 95% CI 3.02 to 3.66), self-employed (aIRR 1.63, 95% CI 1.43 to 1.87) or working in healthcare (aIRR 5.10, 95% CI 4.29 to 6.10) reported significantly higher non-household contact rates than those working from home. Participants self-isolating as a precaution or following Test and Trace instructions had a lower non-household contact rate than those not self-isolating (aIRR 0.58, 95% CI 0.43 to 0.79). We found limited evidence that those shielding had reduced non-household contacts compared with non-shielders. CONCLUSION The daily rate of non-household interactions remained lower than prepandemic levels measured by other studies, suggesting continued adherence to social distancing guidelines. Individuals attending a workplace in-person or employed as healthcare professionals were less likely to maintain social distance and had a higher non-household contact rate, possibly increasing their infection risk. Shielding and self-isolating individuals required greater support to enable them to follow the government guidelines and reduce non-household contact and therefore their risk of infection.
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Affiliation(s)
- Jessica Re Bridgen
- Lancaster Medical School, Lancaster University Faculty of Health and Medicine, Lancaster, UK
| | - Chris Jewell
- Lancaster Medical School, Lancaster University Faculty of Health and Medicine, Lancaster, UK
| | - Jonathan M Read
- Lancaster Medical School, Lancaster University Faculty of Health and Medicine, Lancaster, UK
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Goldsmith JJ, Campbell PT, Villanueva-Cabezas JP, Chisholm RH, McKinnon M, Gurruwiwi GG, Dhurrkay RG, Dockery AM, Geard N, Tong SYC, McVernon J, Gibney KB. Capturing Household Structure and Mobility within and between Remote Aboriginal Communities in Northern Australia Using Longitudinal Data: A Pilot Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:12002. [PMID: 36231301 PMCID: PMC9566160 DOI: 10.3390/ijerph191912002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/13/2022] [Accepted: 09/20/2022] [Indexed: 06/16/2023]
Abstract
UNLABELLED Cultural practices and development level can influence a population's household structures and mixing patterns. Within some populations, households can be organized across multiple dwellings. This likely affects the spread of infectious disease through these communities; however, current demographic data collection tools do not record these data. METHODS Between June and October 2018, the Contact And Mobility Patterns in remote Aboriginal Australian communities (CAMP-remote) pilot study recruited Aboriginal mothers with infants in a remote northern Australian community to complete a monthly iPad-based contact survey. RESULTS Thirteen mother-infant pairs (participants) completed 69 study visits between recruitment and the end of May 2019. Participants reported they and their other children slept in 28 dwellings during the study. The median dwelling occupancy, defined as people sleeping in the same dwelling on the previous night, was ten (range: 3.5-25). Participants who completed at least three responses (n = 8) slept in a median of three dwellings (range: 2-9). Each month, a median of 28% (range: 0-63%) of the participants travelled out of the community. Including these data in disease transmission models amplified estimates of infectious disease spread in the study community, compared to models parameterized using census data. CONCLUSIONS The lack of data on mixing patterns in populations where households can be organized across dwellings may impact the accuracy of infectious disease models for these communities and the efficacy of public health actions they inform.
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Affiliation(s)
- Jessie J. Goldsmith
- Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
| | - Patricia T. Campbell
- Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC 3010, Australia
| | - Juan Pablo Villanueva-Cabezas
- Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
| | - Rebecca H. Chisholm
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC 3010, Australia
- Department of Mathematical and Physical Sciences, La Trobe University, Bundoora, VIC 3086, Australia
| | - Melita McKinnon
- Wellbeing and Preventable Chronic Diseases Division, Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia
| | - George G. Gurruwiwi
- Wellbeing and Preventable Chronic Diseases Division, Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia
| | - Roslyn G. Dhurrkay
- Wellbeing and Preventable Chronic Diseases Division, Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia
| | - Alfred M. Dockery
- Bankwest Curtin Economics Centre, Curtin University, Bentley, WA 6102, Australia
| | - Nicholas Geard
- School of Computing and Information Systems, Faculty of Engineering and Information Technology, University of Melbourne, Parkville, VIC 3010, Australia
| | - Steven Y. C. Tong
- Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
- Victorian Infectious Diseases Service, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Parkville, VIC 3050, Australia
| | - Jodie McVernon
- Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
- Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - Katherine B. Gibney
- Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
- Victorian Infectious Diseases Service, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Parkville, VIC 3050, Australia
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Thindwa D, Jambo KC, Ojal J, MacPherson P, Dennis Phiri M, Pinsent A, Khundi M, Chiume L, Gallagher KE, Heyderman RS, Corbett EL, French N, Flasche S. Social mixing patterns relevant to infectious diseases spread by close contact in urban Blantyre, Malawi. Epidemics 2022; 40:100590. [PMID: 35691100 PMCID: PMC9176177 DOI: 10.1016/j.epidem.2022.100590] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 05/08/2022] [Accepted: 05/30/2022] [Indexed: 01/21/2023] Open
Abstract
INTRODUCTION Understanding human mixing patterns relevant to infectious diseases spread through close contact is vital for modelling transmission dynamics and optimisation of disease control strategies. Mixing patterns in low-income countries like Malawi are not well known. METHODOLOGY We conducted a social mixing survey in urban Blantyre, Malawi between April and July 2021 (between the 2nd and 3rd wave of COVID-19 infections). Participants living in densely-populated neighbourhoods were randomly sampled and, if they consented, reported their physical and non-physical contacts within and outside homes lasting at least 5 min during the previous day. Age-specific mixing rates were calculated, and a negative binomial mixed effects model was used to estimate determinants of contact behaviour. RESULTS Of 1201 individuals enroled, 702 (58.5%) were female, the median age was 15 years (interquartile range [IQR] 5-32) and 127 (10.6%) were HIV-positive. On average, participants reported 10.3 contacts per day (range: 1-25). Mixing patterns were highly age-assortative, particularly those within the community and with skin-to-skin contact. Adults aged 20-49 y reported the most contacts (median:11, IQR: 8-15) of all age groups; 38% (95%CI: 16-63) more than infants (median: 8, IQR: 5-10), who had the least contacts. Household contact frequency increased by 3% (95%CI: 2-5) per additional household member. Unemployed participants had 15% (95%CI: 9-21) fewer contacts than other adults. Among long range (>30 m away from home) contacts, secondary school children had the largest median contact distance from home (257 m, IQR 78-761). HIV-positive status in adults >=18 years-old was not associated with changed contact patterns (rate ratio: 1.01, 95%CI: (0.91-1.12)). During this period of relatively low COVID-19 incidence in Malawi, 301 (25.1%) individuals stated that they had limited their contact with others due to COVID-19 precautions; however, their reported contacts were 8% (95%CI: 1-13) higher. CONCLUSION In urban Malawi, contact rates, are high and age-assortative, with little reported behavioural change due to either HIV-status or COVID-19 circulation. This highlights the limits of contact-restriction-based mitigation strategies in such settings and the need for pandemic preparedness to better understand how contact reductions can be enabled and motivated.
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Affiliation(s)
- Deus Thindwa
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK; Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi.
| | - Kondwani C Jambo
- Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
| | - John Ojal
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK; KEMRI-Wellcome Research Programme, Geographic Medicine Centre, Kilifi, Kenya
| | - Peter MacPherson
- Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK; Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK
| | - Mphatso Dennis Phiri
- Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
| | | | - McEwen Khundi
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK; Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi
| | - Lingstone Chiume
- Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi
| | - Katherine E Gallagher
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK; KEMRI-Wellcome Research Programme, Geographic Medicine Centre, Kilifi, Kenya
| | - Robert S Heyderman
- NIHR Global Health Research Unit on Mucosal Pathogens, Research Department of Infection, Division of Infection and Immunity, University College London, London, UK
| | - Elizabeth L Corbett
- Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK
| | - Neil French
- Malawi-Liverpool-Wellcome Clinical Research Programme, Blantyre, Malawi; Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, UK
| | - Stefan Flasche
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
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9
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Zheng B, Zhu W, Pan J, Wang W. Patterns of human social contact and mask wearing in high-risk groups in China. Infect Dis Poverty 2022; 11:69. [PMID: 35717198 PMCID: PMC9206088 DOI: 10.1186/s40249-022-00988-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 05/16/2022] [Indexed: 12/04/2022] Open
Abstract
Background The pandemic of coronavirus disease 2019 (COVID-19) has changed human behavior in areas such as contact patterns and mask-wearing frequency. Exploring human–human contact patterns and mask-wearing habits in high-risk groups is an essential step in fully understanding the transmission of respiratory infection-based diseases. This study had aims to quantify local human–human (H–H) contacts in high-risk groups in representative provinces of China and to explore the occupation-specific assortativity and heterogeneity of social contacts. Methods Delivery workers, medical workers, preschoolers, and students from Qinghai, Shanghai, and Zhejiang were recruited to complete an online questionnaire that queried general information, logged contacts, and assessed the willingness to wear a mask in different settings. The “group contact” was defined as contact with a group at least 20 individuals. The numbers of contacts across different characteristics were assessed and age-specific contact matrices were established. A generalized additive mixed model was used to analyze the associations between the number of individual contacts and several characteristics. The factors influencing the frequency of mask wearing were evaluated with a logistic regression model. Results A total of 611,287 contacts were reported by 15,635 participants. The frequency of daily individual contacts averaged 3.14 (95% confidence interval: 3.13–3.15) people per day, while that of group contacts was 37.90 (95% CI: 37.20–38.70). Skin-to-skin contact and long-duration contact were more likely to occur at home or among family members. Contact matrices of students were the most assortative (all contacts q-index = 0.899, 95% CI: 0.894–0.904). Participants with larger household sizes reported having more contacts. Higher household income per capita was significantly associated with a greater number of contacts among preschoolers (P50,000–99,999 = 0.033) and students (P10,000–29,999 = 0.017). In each of the public places, the frequency of mask wearing was highest for delivery workers. For preschoolers and students with more contacts, the proportion of those who reported always wearing masks was lower (P < 0.05) in schools/workplaces and public transportation than preschoolers and students with fewer contacts. Conclusions Contact screening efforts should be concentrated in the home, school, and workplace after an outbreak of an epidemic, as more than 75% of all contacts, on average, will be found in such places. Efforts should be made to improve the mask-wearing rate and age-specific health promotion measures aimed at reducing transmission for the younger demographic. Age-stratified and occupation-specific social contact research in high-risk groups could help inform policy-making decisions during the post-relaxation period of the COVID-19 pandemic. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s40249-022-00988-8.
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Affiliation(s)
- Bo Zheng
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Wenlong Zhu
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China
| | - Jinhua Pan
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China.,Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Weibing Wang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China. .,Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China. .,Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, 200032, China.
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10
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Reconstructing social mixing patterns via weighted contact matrices from online and representative surveys. Sci Rep 2022; 12:4690. [PMID: 35304478 PMCID: PMC8931780 DOI: 10.1038/s41598-022-07488-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 02/01/2022] [Indexed: 12/02/2022] Open
Abstract
The unprecedented behavioural responses of societies have been evidently shaping the COVID-19 pandemic, yet it is a significant challenge to accurately monitor the continuously changing social mixing patterns in real-time. Contact matrices, usually stratified by age, summarise interaction motifs efficiently, but their collection relies on conventional representative survey techniques, which are expensive and slow to obtain. Here we report a data collection effort involving over [Formula: see text] of the Hungarian population to simultaneously record contact matrices through a longitudinal online and sequence of representative phone surveys. To correct non-representative biases characterising the online data, by using census data and the representative samples we develop a reconstruction method to provide a scalable, cheap, and flexible way to dynamically obtain closer-to-representative contact matrices. Our results demonstrate that although some conventional socio-demographic characters correlate significantly with the change of contact numbers, the strongest predictors can be collected only via surveys techniques and combined with census data for the best reconstruction performance. We demonstrate the potential of combined online-offline data collections to understand the changing behavioural responses determining the future evolution of the outbreak, and to inform epidemic models with crucial data.
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11
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Andrejko KL, Head JR, Lewnard JA, Remais JV. Longitudinal social contacts among school-aged children during the COVID-19 pandemic: the Bay Area Contacts among Kids (BACK) study. BMC Infect Dis 2022; 22:242. [PMID: 35272626 PMCID: PMC8907906 DOI: 10.1186/s12879-022-07218-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 02/28/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The San Francisco Bay Area was the first region in the United States to enact school closures to mitigate SARS-CoV-2 transmission. The effects of closures on contact patterns for schoolchildren and their household members remain poorly understood. METHODS We conducted serial cross-sectional surveys (May 2020, September 2020, February 2021) of Bay Area households with children to estimate age-structured daily contact rates for children and their adult household members. We examined changes in contact rates over the course of the COVID-19 pandemic, including after vaccination of household members, and compared contact patterns by household demographics using generalized estimating equations clustered by household. RESULTS We captured contact histories for 1,967 households on behalf of 2,674 children, comprising 15,087 non-household contacts over the three waves of data collection. Shortly after the start of shelter-in-place orders in May 2020, daily contact rates were higher among children from Hispanic families (1.52 more contacts per child per day; [95% CI: 1.14-2.04]), households whose parents were unable to work from home (1.82; [1.40-2.40]), and households with income < $150,000 (1.75; [1.33-2.33]), after adjusting for other demographic characteristics and household clustering. Between May and August 2020, non-household contacts of children increased by 145% (ages 5-12) and 172% (ages 13-17), despite few children returning to in-person instruction. Non-household contact rates among children were higher-by 1.75 [1.28-2.40] and 1.42 [0.89-2.24] contacts per child per day in 5-12 and 13-17 age groups, respectively, in households where at least one adult was vaccinated against COVID-19, compared to children's contact rates in unvaccinated households. CONCLUSIONS Child contact rates rebounded despite schools remaining closed, as parents obtained childcare, children engaged in contact in non-school settings, and family members were vaccinated. The waning reductions observed in non-household contact rates of schoolchildren and their family members during a prolonged school closure suggests the strategy may be ineffective for long-term SARS-CoV-2 transmission mitigation. Reductions in age-assortative contacts were not as apparent amongst children from lower income households or households where adults could not work from home. Heterogeneous reductions in contact patterns raise concerning racial, ethnic and income-based inequities associated with long-term school closures as a COVID-19 mitigation strategy.
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Affiliation(s)
- Kristin L Andrejko
- Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
| | - Jennifer R Head
- Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
| | - Joseph A Lewnard
- Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA.,Division of Infectious Diseases & Vaccinology, School of Public Health, University of California, Berkeley, CA, USA.,Center for Computational Biology, College of Engineering, University of California, Berkeley, CA, USA
| | - Justin V Remais
- Division of Environmental Health Sciences, University of California, Berkeley, CA, USA.
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12
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Fu YC, Chan TC, Chu YH, Hwang JS. Using contact tracing from interlocking diaries to map mood contagion along network chains. Sci Rep 2022; 12:3400. [PMID: 35233037 PMCID: PMC8888769 DOI: 10.1038/s41598-022-07402-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 02/15/2022] [Indexed: 11/11/2022] Open
Abstract
Both viruses and moods are transmitted through interpersonal contacts, but it has been extremely difficult to track each unique chain of contacts through which particular moods diffuse. By analyzing 56,060 contact records from 113 interlocking, yearlong diaries collected through a web-based platform in Taiwan, we traced mood states before and after each specific contact along a triplet of persons where B contacts C and subsequently contacts A. Multilevel analyses show that both positive and negative emotions are contagious, but the two paths diverge markedly in how the diffusion stops. Positive contact between C and B (which leads to improved mood for B) spreads to A through B’s contact with A, making A feel better afterward, regardless of whether B’s mood deteriorated between the two interactions. Negative contact between C and B (which leads to worsened mood for B) also spreads to A, making A feel worse after the contact with B. However, the spread of a negative mood discontinues if B’s mood improved between the two contacts. The different patterns of diffusion suggest that a negative mood is harder to disperse, probably because people generally make efforts to keep their negative emotions from spreading to others.
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Affiliation(s)
- Yang-Chih Fu
- Institute of Sociology, Academia Sinica, Taipei, Taiwan
| | - Ta-Chien Chan
- Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.,Institute of Public Health, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Hua Chu
- Institute of Data Science and Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jing-Shiang Hwang
- Institute of Statistical Science, Academia Sinica, 128 Academia Rd. Sec. 2, Nankang 115, Taipei, Taiwan.
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13
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Lovell-Read FA, Shen S, Thompson RN. Estimating local outbreak risks and the effects of non-pharmaceutical interventions in age-structured populations: SARS-CoV-2 as a case study. J Theor Biol 2022; 535:110983. [PMID: 34915042 PMCID: PMC8670853 DOI: 10.1016/j.jtbi.2021.110983] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 12/02/2021] [Accepted: 12/07/2021] [Indexed: 12/12/2022]
Abstract
During the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) including school closures, workplace closures and social distancing policies have been employed worldwide to reduce transmission and prevent local outbreaks. However, transmission and the effectiveness of NPIs depend strongly on age-related factors including heterogeneities in contact patterns and pathophysiology. Here, using SARS-CoV-2 as a case study, we develop a branching process model for assessing the risk that an infectious case arriving in a new location will initiate a local outbreak, accounting for the age distribution of the host population. We show that the risk of a local outbreak depends on the age of the index case, and we explore the effects of NPIs targeting individuals of different ages. Social distancing policies that reduce contacts outside of schools and workplaces and target individuals of all ages are predicted to reduce local outbreak risks substantially, whereas school closures have a more limited impact. In the scenarios considered here, when different NPIs are used in combination the risk of local outbreaks can be eliminated. We also show that heightened surveillance of infectious individuals reduces the level of NPIs required to prevent local outbreaks, particularly if enhanced surveillance of symptomatic cases is combined with efforts to find and isolate nonsymptomatic infected individuals. Our results reflect real-world experience of the COVID-19 pandemic, during which combinations of intense NPIs have reduced transmission and the risk of local outbreaks. The general modelling framework that we present can be used to estimate local outbreak risks during future epidemics of a range of pathogens, accounting fully for age-related factors.
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Affiliation(s)
| | - Silvia Shen
- Mathematical Institute, University of Oxford, Oxford, United Kingdom; Pembroke College, University of Oxford, Oxford, United Kingdom
| | - Robin N Thompson
- Mathematics Institute, University of Warwick, Coventry, United Kingdom; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
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14
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Ventura PC, Aleta A, Aparecido Rodrigues F, Moreno Y. Modeling the effects of social distancing on the large-scale spreading of diseases. Epidemics 2022; 38:100544. [DOI: 10.1016/j.epidem.2022.100544] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 12/21/2021] [Accepted: 02/09/2022] [Indexed: 12/12/2022] Open
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15
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Kar SS, Krishnamoorthy Y, Sivanantham P, Anandraj J, Gnanadhas J. Effect of COVID-19 driven lockdown on social contact pattern in Puducherry, India: A longitudinal study. J Postgrad Med 2022; 68:138-147. [PMID: 35708395 PMCID: PMC9733513 DOI: 10.4103/jpgm.jpgm_1085_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Objective This study was undertaken to assess the change in social contact and transmission dynamics among adults in the Puducherry district during the different phases of country-wide lockdown. Methods Adults aged 18-69 years in Puducherry were assessed for frequency and duration of contacts in the following time points: prior to lockdown (March 2020), during lockdown, immediate post-lockdown (April, June 2020), and seven months post-lockdown (February 2021). Adjusted incidence rate ratios (aIRR) were obtained using a generalized estimating equation. We also assessed the exponential trajectory of the time-varying reproduction number (Rt) during and after lockdown. Results Compared to pre-lockdown phase, frequency of social contacts during 1st week, 4th week of lockdown, and immediate post-lockdown were reduced by 89% (aIRR = 0.11; 95% CI: 0.09-0.13), 40% (aIRR = 0.60; 95% CI: 0.52-0.69) and 91% (aIRR = 0.09; 95% CI: 0.07-0.10) respectively. However, the decline was not statistically significant at seven months post-lockdown. Correspondingly, we observed an initial spike in Rt during the lockdown phase followed by a gradual decline during the immediate post-lockdown phase. However, seven months post-lockdown, Rt has increased again. Conclusion The study showed high compliance to the lockdown measures in Puducherry during the lockdown and immediate post-lockdown periods. However, as the lockdown measures were relaxed, the contact rate returned to the pre-lockdown state.
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Affiliation(s)
- SS Kar
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India,Address for correspondence: Dr. Kar SS, E-mail:
| | - Y Krishnamoorthy
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - P Sivanantham
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - J Anandraj
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - J Gnanadhas
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
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16
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Alam MJ, Habib N, Holmes D, Habib MA. Pedestrian movement modelling for a commercial street considering COVID-19 social distancing strategies. PROCEDIA COMPUTER SCIENCE 2022; 201:64-71. [PMID: 35502241 PMCID: PMC9044728 DOI: 10.1016/j.procs.2022.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This research attempts to understand the impacts of social distancing on dense urban pedestrian environments through pedestrian movement simulations. It develops a pedestrian microsimulation modelling framework that evaluates three scenarios for a commercial street in the Halifax Regional Municipality (HRM). The Business-as-Usual scenario mimics pre-COVID conditions with no social distancing protocols. Pandemic Scenario# 1 represents social distancing without any changes in the pedestrian infrastructure. The HRM has adopted a mobility response plan for COVID-19, this generates Pandemic Scenario# 2 depicting the widened sidewalks within the pedestrian microsimulation model. The results reveal that the social distancing strategy in the pandemic scenarios significantly improved pedestrian flow in terms of the reduction in contact violations. These violations are described as instances in which a pedestrian violates the 2 m social distancing rule. The simulation of the first pandemic scenario (no sidewalk enhancement) showed a significant reduction of 43% in the number of contact violations during the one-hour pedestrian simulation of the street. The second pandemic scenario showed a 68% decrease in violations. The conclusions derived from this research support the actions of the municipality as the simulation results indicate that an increase in sidewalk width can influence contact rates and time travelled. When comparing the two pandemic scenarios, the scenario that incorporated wider sidewalks showed a decrease in total travel time and contact rates.
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17
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Avraam D, Obradovich N, Pescetelli N, Cebrian M, Rutherford A. The network limits of infectious disease control via occupation-based targeting. Sci Rep 2021; 11:22855. [PMID: 34819577 PMCID: PMC8613398 DOI: 10.1038/s41598-021-02226-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 11/08/2021] [Indexed: 01/08/2023] Open
Abstract
Policymakers commonly employ non-pharmaceutical interventions to reduce the scale and severity of pandemics. Of non-pharmaceutical interventions, physical distancing policies-designed to reduce person-to-person pathogenic spread - have risen to recent prominence. In particular, stay-at-home policies of the sort widely implemented around the globe in response to the COVID-19 pandemic have proven to be markedly effective at slowing pandemic growth. However, such blunt policy instruments, while effective, produce numerous unintended consequences, including potentially dramatic reductions in economic productivity. In this study, we develop methods to investigate the potential to simultaneously contain pandemic spread while also minimizing economic disruptions. We do so by incorporating both occupational and contact network information contained within an urban environment, information that is commonly excluded from typical pandemic control policy design. The results of our methods suggest that large gains in both economic productivity and pandemic control might be had by the incorporation and consideration of simple-to-measure characteristics of the occupational contact network. We find evidence that more sophisticated, and more privacy invasive, measures of this network do not drastically increase performance.
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Affiliation(s)
- Demetris Avraam
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
| | - Nick Obradovich
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany
| | - Niccolò Pescetelli
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany
| | - Manuel Cebrian
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
| | - Alex Rutherford
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
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18
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van Leeuwen E, Sandmann F. Augmenting contact matrices with time-use data for fine-grained intervention modelling of disease dynamics: A modelling analysis. Stat Methods Med Res 2021; 31:1704-1715. [PMID: 34468236 DOI: 10.1177/09622802211037078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Social distancing is an important public health intervention to reduce or interrupt the sustained community transmission of emerging infectious pathogens, such as severe acute respiratory syndrome-coronavirus-2 during the coronavirus disease 2019 pandemic. Contact matrices are typically used when evaluating such public health interventions to account for the heterogeneity in social mixing of individuals, but the surveys used to obtain the number of contacts often lack detailed information on the time individuals spend on daily activities. The present work addresses this problem by combining the large-scale empirical data of a social contact survey and a time-use survey to estimate contact matrices by age group (0--15, 16--24, 25-44, 45-64, 65+ years) and daily activity (work, schooling, transportation, and four leisure activities: social visits, bar/cafe/restaurant visits, park visits, and non-essential shopping). This augmentation allows exploring the impact of fewer contacts when individuals reduce the time they spend on selected daily activities as well as when lifting such restrictions again. For illustration, the derived matrices were then applied to an age-structured dynamic-transmission model of coronavirus disease 2019. Findings show how contact matrices can be successfully augmented with time-use data to inform the relative reductions in contacts by activity, which allows for more fine-grained mixing patterns and infectious disease modelling.
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Affiliation(s)
- Edwin van Leeuwen
- Statistics, Modelling and Economics Department, 371011Public Health England, UK
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- Statistics, Modelling and Economics Department, 371011Public Health England, UK
| | - Frank Sandmann
- Statistics, Modelling and Economics Department, 371011Public Health England, UK.,Department of Infectious Disease Epidemiology, 4906London School of Hygiene and Tropical Medicine, UK
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19
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Prem K, Zandvoort KV, Klepac P, Eggo RM, Davies NG, Cook AR, Jit M. Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era. PLoS Comput Biol 2021. [PMID: 34310590 DOI: 10.1101/2020.07.22.20159772] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023] Open
Abstract
Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.
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Affiliation(s)
- Kiesha Prem
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Kevin van Zandvoort
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Petra Klepac
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Rosalind M Eggo
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Nicholas G Davies
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
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20
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Prem K, van Zandvoort K, Klepac P, Eggo RM, Davies NG, Cook AR, Jit M. Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era. PLoS Comput Biol 2021; 17:e1009098. [PMID: 34310590 PMCID: PMC8354454 DOI: 10.1371/journal.pcbi.1009098] [Citation(s) in RCA: 77] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 08/10/2021] [Accepted: 05/20/2021] [Indexed: 01/08/2023] Open
Abstract
Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.
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Affiliation(s)
- Kiesha Prem
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Kevin van Zandvoort
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Petra Klepac
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Rosalind M. Eggo
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Nicholas G. Davies
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | | | - Alex R. Cook
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
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21
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Prem K, Zandvoort KV, Klepac P, Eggo RM, Davies NG, Cook AR, Jit M. Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era. PLoS Comput Biol 2021; 17:e1009098. [PMID: 34310590 DOI: 10.5281/zenodo.4889500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 08/10/2021] [Accepted: 05/20/2021] [Indexed: 05/20/2023] Open
Abstract
Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.
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Affiliation(s)
- Kiesha Prem
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Kevin van Zandvoort
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Petra Klepac
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Rosalind M Eggo
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Nicholas G Davies
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
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22
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Horton KC, Hoey AL, Béraud G, Corbett EL, White RG. Systematic Review and Meta-Analysis of Sex Differences in Social Contact Patterns and Implications for Tuberculosis Transmission and Control. Emerg Infect Dis 2021; 26:910-919. [PMID: 32310063 PMCID: PMC7181919 DOI: 10.3201/eid2605.190574] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Social contact patterns might contribute to excess burden of tuberculosis in men. We conducted a study of social contact surveys to evaluate contact patterns relevant to tuberculosis transmission. Available data describe 21 surveys in 17 countries and show profound differences in sex-based and age-based patterns of contact. Adults reported more adult contacts than children. Children preferentially mixed with women in all surveys (median sex assortativity 58%, interquartile range [IQR] 57%–59% for boys, 61% [IQR 60%–63%] for girls). Men and women reported sex-assortative mixing in 80% and 95% of surveys (median sex assortativity 56% [IQR 54%–58%] for men, 59% [IQR 57%–63%] for women). Sex-specific patterns of contact with adults were similar at home and outside the home for children; adults reported greater sex assortativity outside the home in most surveys. Sex assortativity in adult contacts likely contributes to sex disparities in adult tuberculosis burden by amplifying incidence among men.
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23
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Kleynhans J, Tempia S, McMorrow ML, von Gottberg A, Martinson NA, Kahn K, Moyes J, Mkhencele T, Lebina L, Gómez-Olivé FX, Wafawanaka F, Mathunjwa A, Cohen C. A cross-sectional study measuring contact patterns using diaries in an urban and a rural community in South Africa, 2018. BMC Public Health 2021; 21:1055. [PMID: 34078327 PMCID: PMC8172361 DOI: 10.1186/s12889-021-11136-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 05/24/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Describing contact patterns is crucial to understanding infectious disease transmission dynamics and guiding targeted transmission mitigation interventions. Data on contact patterns in Africa, especially South Africa, are limited. We measured and compared contact patterns in a rural and urban community, South Africa. We assessed participant and contact characteristics associated with differences in contact rates. METHODS We conducted a cross-sectional study nested in a prospective household cohort study. We interviewed participants to collect information on persons in contact with for one day. We described self-reported contact rates as median number people contacted per day, assessed differences in contact rates based on participant characteristics using quantile regression, and used a Poisson model to assess differences in contact rates based on contact characteristics within age groups. We also calculated cumulative person hours in contact within age groups at different locations. RESULTS We conducted 535 interviews (269 rural, 266 urban), with 17,252 contacts reported. The overall contact rate was 14 (interquartile range (IQR) 9-33) contacts per day. Those ≤18 years had higher contact rates at the rural site (coefficient 17, 95% confidence interval (95%CI) 10-23) compared to the urban site, for those aged 14-18 years (13, 95%CI 3-23) compared to < 7 years. No differences were observed for adults. There was a strong age-based mixing, with age groups interacting more with similar age groups, but also interaction of participants of all ages with adults. Children aged 14-18 years had the highest cumulative person hours in contact (116.3 rural and 76.4 urban). CONCLUSIONS Age played an important role in the number and duration of contact events, with children at the rural site having almost double the contact rate compared to the urban site. These contact rates can be utilized in mathematical models to assess transmission dynamics of infectious diseases in similar communities.
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Affiliation(s)
- Jackie Kleynhans
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Stefano Tempia
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa
- MassGenics, Duluth, Georgia, USA
| | - Meredith L McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa
- United States Public Health Service, Rockville, MD, USA
| | - Anne von Gottberg
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Neil A Martinson
- Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Johannesburg, South Africa
- Johns Hopkins University Center for Tuberculosis Research, Baltimore, MD, USA
- Department of Science and Technology/National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, University of the Witwatersrand, Johannesburg, South Africa
| | - Kathleen Kahn
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Thulisa Mkhencele
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Limakatso Lebina
- Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Johannesburg, South Africa
| | - F Xavier Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Floidy Wafawanaka
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Azwifarwi Mathunjwa
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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24
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Rainey JJ, Koch DB, Chen YH, Yuan J, Cheriyadat A. Using video-analysis technology to estimate social mixing and simulate influenza transmission at a mass gathering. Epidemics 2021; 36:100466. [PMID: 34052665 DOI: 10.1016/j.epidem.2021.100466] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 03/20/2020] [Accepted: 05/10/2021] [Indexed: 11/26/2022] Open
Abstract
Mass gatherings create settings conducive to infectious disease transmission. Empirical data to model infectious disease transmission at mass gatherings are limited. Video-analysis technology could be used to generate data on social mixing patterns needed for simulating influenza transmission at mass gatherings. We analyzed short video recordings of persons attending the GameFest event at a university in Troy, New York, in April 2013 to demonstrate the feasibility of this approach. Attendees were identified and tracked during three randomly selected time periods using an object-tracking algorithm. Tracks were analyzed to calculate the number and duration of unique pairwise contacts. A contact occurred each time two attendees were within 2 m of each other. We built and tested an agent-based stochastic influenza simulation model assuming two scenarios of mixing patterns in a geospatially accurate representation of the event venue -one calibrated to the mean cumulative contact duration estimated from GameFest video recordings and the other using a uniform mixing pattern. We compared one-hour attack rates (i.e., becoming infected) generated from these two scenarios following the introduction of a single infectious seed. Across the video recordings, 278 attendees were identified and tracked, resulting in 1,247 unique pairwise contacts with a cumulative mean contact duration of 74.76 s (SD: 80.71). The one-hour simulated mean attack rates were 2.17 % (95 % CI:1.45 - 2.82) and 0.21 % (95 % CI: 0.14 - 0.28) in the calibrated and uniform mixing model scenarios, respectively. We simulated influenza transmission at the GameFest event using social mixing data objectively captured through video-analysis technology. Microlevel geospatially accurate simulations can be used to assess the layout of event venues on social mixing and disease transmission. Future work can expand on this demonstration project to larger spatial and temporal scenes in more diverse settings.
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Affiliation(s)
- Jeanette J Rainey
- Division of Global Quarantine and Migration, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Daniel B Koch
- Oak Ridge National Laboratory, One Bethel Valley Road, PO Box 2008, Oak Ridge, TN, 37831, USA.
| | | | - Jiangye Yuan
- Oak Ridge National Laboratory, One Bethel Valley Road, PO Box 2008, Oak Ridge, TN, 37831, USA.
| | - Anil Cheriyadat
- Oak Ridge National Laboratory, One Bethel Valley Road, PO Box 2008, Oak Ridge, TN, 37831, USA.
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25
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Glynn JR, McLean E, Malava J, Dube A, Katundu C, Crampin AC, Geis S. Effect of Acute Illness on Contact Patterns, Malawi, 2017. Emerg Infect Dis 2021; 26:44-50. [PMID: 31855144 PMCID: PMC6924881 DOI: 10.3201/eid2601.181539] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
The way persons interact when ill could profoundly affect transmission of infectious agents. To obtain data on these patterns in Africa, we recorded self-reported named contacts and opportunities for casual contact in rural northern Malawi. We interviewed 384 patients and 257 caregivers about contacts over three 24-hour periods: day of the clinic visit for acute illness, the next day, and 2 weeks later when well. For participants of all ages, the number of adult contacts and the proportion using public transportation was higher on the day of the clinic visit than later when well. Compared with the day after the clinic visit, well participants (2 weeks later) named a mean of 0.4 extra contacts; the increase was larger for indoor or prolonged contacts. When well, participants were more likely to visit other houses and congregate settings. When ill, they had more visitors at home. These findings could help refine models of infection spread.
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26
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Gosak M, Kraemer MUG, Nax HH, Perc M, Pradelski BSR. Endogenous social distancing and its underappreciated impact on the epidemic curve. Sci Rep 2021; 11:3093. [PMID: 33542416 PMCID: PMC7862686 DOI: 10.1038/s41598-021-82770-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 01/21/2021] [Indexed: 12/18/2022] Open
Abstract
Social distancing is an effective strategy to mitigate the impact of infectious diseases. If sick or healthy, or both, predominantly socially distance, the epidemic curve flattens. Contact reductions may occur for different reasons during a pandemic including health-related mobility loss (severity of symptoms), duty of care for a member of a high-risk group, and forced quarantine. Other decisions to reduce contacts are of a more voluntary nature. In particular, sick people reduce contacts consciously to avoid infecting others, and healthy individuals reduce contacts in order to stay healthy. We use game theory to formalize the interaction of voluntary social distancing in a partially infected population. This improves the behavioral micro-foundations of epidemiological models, and predicts differential social distancing rates dependent on health status. The model's key predictions in terms of comparative statics are derived, which concern changes and interactions between social distancing behaviors of sick and healthy. We fit the relevant parameters for endogenous social distancing to an epidemiological model with evidence from influenza waves to provide a benchmark for an epidemic curve with endogenous social distancing. Our results suggest that spreading similar in peak and case numbers to what partial immobilization of the population produces, yet quicker to pass, could occur endogenously. Going forward, eventual social distancing orders and lockdown policies should be benchmarked against more realistic epidemic models that take endogenous social distancing into account, rather than be driven by static, and therefore unrealistic, estimates for social mixing that intrinsically overestimate spreading.
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Affiliation(s)
- Marko Gosak
- Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000, Maribor, Slovenia
- Faculty od Medicine, University of Maribor, Taborska ulica 8, 2000, Maribor, Slovenia
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, Mansfield Road, Oxford, OX1 3SZ, UK
- Harvard Medical School, 25 Shattuck St, Boston, 02115, USA
| | - Heinrich H Nax
- Behavioral Game Theory, ETH Zurich, Clausiusstrasse 37, 8092, Zurich, Switzerland.
- Institute of Sociology, University of Zurich, Andreasstrasse 15, 8050, Zurich, Switzerland.
| | - Matjaž Perc
- Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000, Maribor, Slovenia
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Complexity Science Hub Vienna, Josefstädterstraße 39, 1080, Vienna, Austria
| | - Bary S R Pradelski
- Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG, 38000, Grenoble, France
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27
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Sypsa V, Roussos S, Paraskevis D, Lytras T, Tsiodras S, Hatzakis A. Effects of Social Distancing Measures during the First Epidemic Wave of Severe Acute Respiratory Syndrome Infection, Greece. Emerg Infect Dis 2021; 27:452-462. [PMID: 33496221 PMCID: PMC7853557 DOI: 10.3201/eid2702.203412] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Greece imposed a nationwide lockdown in March 2020 to mitigate transmission of severe acute respiratory syndrome coronavirus 2 during the first epidemic wave. We conducted a survey on age-specific social contact patterns to assess effects of physical distancing measures and used a susceptible-exposed-infectious-recovered model to simulate the epidemic. Because multiple distancing measures were implemented simultaneously, we assessed their overall effects and the contribution of each measure. Before measures were implemented, the estimated basic reproduction number (R0) was 2.38 (95% CI 2.01-2.80). During lockdown, daily contacts decreased by 86.9% and R0 decreased by 81.0% (95% credible interval [CrI] 71.8%-86.0%); each distancing measure decreased R0 by 10%-24%. By April 26, the attack rate in Greece was 0.12% (95% CrI 0.06%-0.26%), one of the lowest in Europe, and the infection fatality ratio was 1.12% (95% CrI 0.55%-2.31%). Multiple social distancing measures contained the first epidemic wave in Greece.
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28
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Grantz KH, Cummings DAT, Zimmer S, Vukotich Jr. C, Galloway D, Schweizer ML, Guclu H, Cousins J, Lingle C, Yearwood GMH, Li K, Calderone P, Noble E, Gao H, Rainey J, Uzicanin A, Read JM. Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. Sci Rep 2021; 11:2319. [PMID: 33504823 PMCID: PMC7840989 DOI: 10.1038/s41598-021-81673-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 12/23/2020] [Indexed: 01/30/2023] Open
Abstract
Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.
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Affiliation(s)
- Kyra H. Grantz
- grid.15276.370000 0004 1936 8091Department of Biology, University of Florida, Gainesville, FL 32611 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611 USA ,grid.21107.350000 0001 2171 9311Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 USA
| | - Derek A. T. Cummings
- grid.15276.370000 0004 1936 8091Department of Biology, University of Florida, Gainesville, FL 32611 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611 USA ,grid.21107.350000 0001 2171 9311Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 USA
| | - Shanta Zimmer
- grid.21925.3d0000 0004 1936 9000Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 USA ,grid.241116.10000000107903411Department of Medicine, University of Colorado School of Medicine, Denver, CO 80045 USA
| | - Charles Vukotich Jr.
- grid.21925.3d0000 0004 1936 9000Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 USA
| | - David Galloway
- grid.21925.3d0000 0004 1936 9000Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15213 USA
| | - Mary Lou Schweizer
- grid.21925.3d0000 0004 1936 9000Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 USA
| | - Hasan Guclu
- grid.21925.3d0000 0004 1936 9000Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.411776.20000 0004 0454 921XPresent Address: Department of Biostatistics and Medical Informatics, School of Medicine, Istanbul Medeniyet University, Istanbul, Turkey
| | - Jennifer Cousins
- grid.21925.3d0000 0004 1936 9000Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Present Address: Department of Psychology, University of Pittsburgh, Pittsburgh, PA USA
| | - Carrie Lingle
- grid.21925.3d0000 0004 1936 9000Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15213 USA ,Present Address: Toledo Lucas County Health Department, Toledo, OH USA
| | - Gabby M. H. Yearwood
- grid.21925.3d0000 0004 1936 9000Department of Anthropology, University of Pittsburgh, Pittsburgh, PA 15213 USA
| | - Kan Li
- grid.21925.3d0000 0004 1936 9000Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15213 USA ,Present Address: Merck Pharmaceuticals, Philadelphia, PA USA
| | - Patti Calderone
- grid.21925.3d0000 0004 1936 9000Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 USA
| | - Eva Noble
- grid.21107.350000 0001 2171 9311Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 USA
| | - Hongjiang Gao
- grid.416738.f0000 0001 2163 0069Division of Global Migration and Quarantine, US Centers for Disease Control and Prevention, Atlanta, GA 30033 USA
| | - Jeanette Rainey
- grid.416738.f0000 0001 2163 0069Division of Global Migration and Quarantine, US Centers for Disease Control and Prevention, Atlanta, GA 30033 USA ,grid.416738.f0000 0001 2163 0069Present Address: Division of Global Health Protection, US Centers for Disease Control and Prevention, Atlanta, GA USA
| | - Amra Uzicanin
- grid.416738.f0000 0001 2163 0069Division of Global Migration and Quarantine, US Centers for Disease Control and Prevention, Atlanta, GA 30033 USA
| | - Jonathan M. Read
- grid.9835.70000 0000 8190 6402Centre for Health Informatics Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, LA1 4YW UK ,grid.10025.360000 0004 1936 8470Institute of Infection and Global Health, University of Liverpool, Liverpool, L69 7BE UK
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29
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Zivich PN, Huang W, Walsh A, Dutta P, Eisenberg M, Aiello AE. Measuring office workplace interactions and hand hygiene behaviors through electronic sensors: A feasibility study. PLoS One 2021; 16:e0243358. [PMID: 33465139 PMCID: PMC7815125 DOI: 10.1371/journal.pone.0243358] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 11/19/2020] [Indexed: 01/06/2023] Open
Abstract
Office-based workplaces are an important but understudied context for infectious disease transmission. We examined the feasibility of two different sensors (Opos and Bluetooth beacons) for collecting person-to-person contacts and hand hygiene in office-based workplaces. Opo is an interaction sensor that captures sensor-to-sensor interactions through ultrasonic frequencies, which correspond to face-to-face contacts between study participants. Opos were additionally used to measure hand hygiene events by affixing sensors to soap and alcohol-based hand sanitizer dispensers. Bluetooth beacons were used in conjunction with a smartphone application and recorded proximity contacts between study participants. Participants in two office sites were followed for one-week in their workplace in March 2018. Contact patterns varied by time of day and day of the week. Face-to-face contacts were of shorter mean duration than proximity contacts. Supervisors had fewer proximity contacts but more face-to-face contacts than non-supervisors. Self-reported hand hygiene was substantively higher than sensor-collected hand hygiene events and duration of hand washing events was short (median: 9 seconds, range: 2.5-33 seconds). Given that office settings are key environments in which working age populations spend a large proportion of their time and interactions, a better characterization of empirical social networks and hand hygiene behaviors for workplace interactions are needed to mitigate outbreaks and prepare for pandemics. Our study demonstrates that implementing sensor technologies for tracking interactions and behaviors in offices is feasible and can provide new insights into real-world social networks and hygiene practices. We identified key social interactions, variability in hand hygiene, and differences in interactions by workplace roles. High-resolution network data will be essential for identifying the most effective ways to mitigate infectious disease transmission and develop pandemic preparedness plans for the workplace setting.
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Affiliation(s)
- Paul N. Zivich
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, Chapel Hill, North Carolina, United States of America
| | - Will Huang
- College of Engineering, University of California, Berkley, California, United States of America
| | - Ali Walsh
- Department of Systems, Populations, and Leadership, University of Michigan School of Nursing, Ann Arbor, Michigan, United States of America
| | - Prabal Dutta
- College of Engineering, University of California, Berkley, California, United States of America
| | - Marisa Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Allison E. Aiello
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, Chapel Hill, North Carolina, United States of America
- * E-mail:
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30
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Wey A, Champneys A, Dyson RJ, Alwan NA, Barker M. The benefits of peer transparency in safe workplace operation post pandemic lockdown. J R Soc Interface 2021; 18:20200617. [PMID: 33501885 PMCID: PMC7879750 DOI: 10.1098/rsif.2020.0617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 01/06/2021] [Indexed: 11/12/2022] Open
Abstract
The benefits of different levels of engagement with test, trace and isolate procedures are investigated for a pandemic in which there is little population immunity, in terms of productivity and public health. Simple mathematical modelling is used in the context of a single, relatively closed workplace such as a factory or back-office where, in normal operation, each worker has lengthy interactions with a fixed set of colleagues. A discrete-time SEIR model on a fixed interaction graph is simulated with parameters that are motivated by the recent COVID-19 pandemic in the UK during a post-peak phase, including a small risk of viral infection from outside the working environment. Two kinds of worker are assumed, transparents who regularly test, share their results with colleagues and isolate as soon as a contact tests positive for the disease, and opaques who do none of these. Moreover, the simulations are constructed as a 'playable model' in which the transparency level, disease parameters and mean interaction degree can be varied by the user. The model is also analysed in the continuum limit. All simulations point to the double benefit of transparency in both maximizing productivity and minimizing overall infection rates. Based on these findings, public policy implications are discussed for how to incentivise this mutually beneficial behaviour in different kinds of workplace, and simple recommendations are made.
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Affiliation(s)
- Arkady Wey
- Industrially Focused Mathematical Modelling (InFoMM) EPSRC Centre for Doctoral Training, Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK
| | - Alan Champneys
- Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TR, UK
| | - Rosemary J. Dyson
- School of Mathematics, University of Birmingham, Birmingham B15 2TT, UK
| | - Nisreen A. Alwan
- School of Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton SO16 6YD, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
- NIHR Applied Research Collaboration (ARC) Wessex, Southampton, UK
| | - Mary Barker
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
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31
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Abstract
BACKGROUND Researchers increasingly use social contact data to inform models for infectious disease spread with the aim of guiding effective policies about disease prevention and control. In this article, we undertake a systematic review of the study design, statistical analyses, and outcomes of the many social contact surveys that have been published. METHODS We systematically searched PubMed and Web of Science for articles regarding social contact surveys. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines as closely as possible. RESULTS In total, we identified 64 social contact surveys, with more than 80% of the surveys conducted in high-income countries. Study settings included general population (58%), schools or universities (37%), and health care/conference/research institutes (5%). The largest number of studies did not focus on a specific age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective (45%) and prospective (41%) designs were used most often with 6% using both for comparison purposes. The definition of a contact varied among surveys, e.g., a nonphysical contact may require conversation, close proximity, or both. We identified age, time schedule (e.g., weekday/weekend), and household size as relevant determinants of contact patterns across a large number of studies. CONCLUSIONS We found that the overall features of the contact patterns were remarkably robust across several countries, and irrespective of the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, definition of contact), we could identify recommendations for future contact data surveys that may be used to facilitate comparison between studies.
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Grantz KH, Cummings DAT, Zimmer S, Vukotich C, Galloway D, Schweizer ML, Guclu H, Cousins J, Lingle C, Yearwood GMH, Li K, Calderone PA, Noble E, Gao H, Rainey J, Uzicanin A, Read JM. Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.07.12.20151696. [PMID: 32699859 PMCID: PMC7373148 DOI: 10.1101/2020.07.12.20151696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.
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Zhang N, Chen W, Chan PT, Yen HL, Tang JWT, Li Y. Close contact behavior in indoor environment and transmission of respiratory infection. INDOOR AIR 2020; 30:645-661. [PMID: 32259319 DOI: 10.1111/ina.12673] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 02/29/2020] [Accepted: 03/25/2020] [Indexed: 05/05/2023]
Abstract
Close contact was first identified as the primary route of transmission for most respiratory infections in the early 20th century. In this review, we synthesize the existing understanding of the mechanisms of close contact transmission. We focus on two issues: the mechanism of transmission in close contact, namely the transmission of the expired particles between two people, and the physical parameters of close contact that affect the exposure of particles from one individual to another, or how the nature of close contact plays a role in transmission. We propose the existence of three sub-routes of transmission: short-range airborne, large droplets, and immediate body-surface contact. We also distinguish a "body contact," which is defined with an interpersonal distance of zero, from a close contact. We demonstrate herein that the short-range airborne sub-route may be most common. The timescales over which data should be collected to assess the transmission risk during close contact events are much shorter than those required for the distant airborne or fomite routes. The current paucity of high-resolution data over short distances and timescales makes it very difficult to assess the risk of infection in these circumstances.
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Affiliation(s)
- Nan Zhang
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Wenzhao Chen
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Pak-To Chan
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Hui-Ling Yen
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Julian Wei-Tze Tang
- Clinical Microbiology, University Hospitals of Leicester NHS Trust, Leicester, UK
- Respiratory Sciences, University of Leicester, Leicester, UK
| | - Yuguo Li
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
- School of Public Health, The University of Hong Kong, Hong Kong, China
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Oh HS, Yang Y, Ryu M. Development of a Social Contact Survey Instrument Relevant to the Spread of Infectious Disease and Its Application in a Pilot Study Among Korean Adults. J Prev Med Public Health 2020; 53:106-116. [PMID: 32268465 PMCID: PMC7142013 DOI: 10.3961/jpmph.19.251] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/22/2020] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES This study aimed to develop a valid social contact survey instrument and to verify its feasibility for use among Korean adults. METHODS The Delphi technique was used to develop an instrument to assess social contacts, which was then applied in a cross-sectional pilot study. A panel of 15 medical professionals reviewed the feasibility and validity of each item. The minimum content validity ratio was 0.49. Thirty participants used the developed measure to record contacts during a 24-hour period. RESULTS After a systematic review, the survey instrument (parts I and II) was developed. Part I assessed social contact patterns over a 24-hour period, and part II assessed perceptions of contacts in daily life and preventive behaviors (hand hygiene and coughing etiquette). High validity and feasibility were found. In the pilot study, the 30 participants had a combined total of 198 contacts (mean, 6.6 daily contacts per person). The participants' age (p=0.012), occupation (p<0.001), household size (p<0.001), education (p<0.001), personal income (p=0.003), and household income (p<0.001) were significantly associated with the number of contacts. Contacts at home, of long duration, and of daily frequency were relatively likely to be physical. Assortative mixing was observed between individuals in their 20s and 50s. Contact type differed by location, duration, and frequency (p<0.001). CONCLUSIONS The developed social contact survey instrument demonstrated high validity and feasibility, suggesting that it is viable for implementation.
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Affiliation(s)
- Hyang Soon Oh
- Department of Nursing, College of Life Science and Natural Resources, Sunchon National University, Suncheon, Korea
| | - Youngran Yang
- Research Institute of Nursing Science, Jeonbuk National University College of Nursing, Jeonju, Korea
| | - Mikyung Ryu
- Graduate School of Education, Kyung Hee University, Seoul, Korea
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Gastañaduy PA, Funk S, Lopman BA, Rota PA, Gambhir M, Grenfell B, Paul P. Factors Associated With Measles Transmission in the United States During the Postelimination Era. JAMA Pediatr 2020; 174:56-62. [PMID: 31738391 PMCID: PMC6865326 DOI: 10.1001/jamapediatrics.2019.4357] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Measles cases and outbreaks continue to occur in the United States after the introduction of measles from endemic settings. OBJECTIVE To discern the factors associated with measles transmission in the United States after measles had been eliminated. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study was conducted from January 1, 2001, to December 31, 2017, in the United States among US residents and international visitors with confirmed measles. A maximum likelihood algorithm that uses the observed dates of rash onset and the known distribution of the serial interval (time between symptom onset in related consecutive cases) was applied to outbreak notification data to estimate the effective reproduction number (R), or the mean number of new infections generated per case. Transmissibility was assessed by comparing R based on the characteristics of primary and secondary cases of measles. EXPOSURES Measles virus. MAIN OUTCOMES AND MEASURES Effective reproduction number (R), or the mean number of successful transmission events per case of measles (ie, the mean number of persons to whom each patient with measles spreads measles). RESULTS A total of 2218 individuals with confirmed measles cases (1025 female, 1176 male, and 17 sex not reported; median age, 15 years [range, 0-89 years]) reported from 2001 to 2017 were evaluated. Among patients who received no doses of measles vaccine, R was 0.76 (95% CI, 0.71-0.81); among patients who received 1 dose of measles vaccine, R was 0.17 (95% CI, 0.11-0.26); among patients who received 2 doses or more of measles vaccine, R was 0.27 (95% CI, 0.17-0.39); and among patients with unknown vaccination status, R was 0.52 (95% CI, 0.44-0.60). Among patients born before 1957, R was 0.35 (95% CI, 0.20-0.58), and among those born on or after 1957, R was 0.64 (95% CI, 0.61-0.68). R was higher when primary and secondary cases of measles were patients aged 5 to 17 years (0.36 [95% CI, 0.31-0.42]) compared with assortative transmission in other age groups (<1 year, 0.14 [95% CI, 0.10-0.20]; 1-4 years, 0.25 [95% CI, 0.20-0.30]; 18-29 years, 0.19 [95% CI, 0.15-0.24]; 30-49 years, 0.15 [95% CI, 0.11-0.20]; ≥50 years, 0.04 [95% CI, 0.01-0.10]). CONCLUSIONS AND RELEVANCE The findings of this study support having high targets for 2-dose measles vaccine coverage, particularly among school-aged children in the United States.
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Affiliation(s)
- Paul A. Gastañaduy
- Division of Viral Diseases, National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Sebastian Funk
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Paul A. Rota
- Division of Viral Diseases, National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manoj Gambhir
- Epidemiological Modelling Unit, Monash University, Melbourne, Victoria, Australia,Health Modelling and Analytics Team, IBM Research Australia, Melbourne, Victoria, Australia
| | - Bryan Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey
| | - Prabasaj Paul
- Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
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Funk S, Knapp JK, Lebo E, Reef SE, Dabbagh AJ, Kretsinger K, Jit M, Edmunds WJ, Strebel PM. Combining serological and contact data to derive target immunity levels for achieving and maintaining measles elimination. BMC Med 2019; 17:180. [PMID: 31551070 PMCID: PMC6760101 DOI: 10.1186/s12916-019-1413-7] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 08/20/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Vaccination has reduced the global incidence of measles to the lowest rates in history. However, local interruption of measles virus transmission requires sustained high levels of population immunity that can be challenging to achieve and maintain. The herd immunity threshold for measles is typically stipulated at 90-95%. This figure does not easily translate into age-specific immunity levels required to interrupt transmission. Previous estimates of such levels were based on speculative contact patterns based on historical data from high-income countries. The aim of this study was to determine age-specific immunity levels that would ensure elimination of measles when taking into account empirically observed contact patterns. METHODS We combined estimated immunity levels from serological data in 17 countries with studies of age-specific mixing patterns to derive contact-adjusted immunity levels. We then compared these to case data from the 10 years following the seroprevalence studies to establish a contact-adjusted immunity threshold for elimination. We lastly combined a range of hypothetical immunity profiles with contact data from a wide range of socioeconomic and demographic settings to determine whether they would be sufficient for elimination. RESULTS We found that contact-adjusted immunity levels were able to predict whether countries would experience outbreaks in the decade following the serological studies in about 70% of countries. The corresponding threshold level of contact-adjusted immunity was found to be 93%, corresponding to an average basic reproduction number of approximately 14. Testing different scenarios of immunity with this threshold level using contact studies from around the world, we found that 95% immunity would have to be achieved by the age of five and maintained across older age groups to guarantee elimination. This reflects a greater level of immunity required in 5-9-year-olds than established previously. CONCLUSIONS The immunity levels we found necessary for measles elimination are higher than previous guidance. The importance of achieving high immunity levels in 5-9-year-olds presents both a challenge and an opportunity. While such high levels can be difficult to achieve, school entry provides an opportunity to ensure sufficient vaccination coverage. Combined with observations of contact patterns, further national and sub-national serological studies could serve to highlight key gaps in immunity that need to be filled in order to achieve national and regional measles elimination.
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Affiliation(s)
- Sebastian Funk
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
| | - Jennifer K. Knapp
- Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA USA
| | - Emmaculate Lebo
- Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA USA
| | - Susan E. Reef
- Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA USA
| | - Alya J. Dabbagh
- World Health Organization, Avenue Appia 20, Geneva, Switzerland
| | | | - Mark Jit
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
- Modelling and Economics Unit, National Infections Service, Public Health England, 61 Colindale Avenue, London, UK
- School of Public Health, University of Hong Kong, 7 Sassoon Road, Hong Kong SAR, China
| | - W. John Edmunds
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
| | - Peter M. Strebel
- GAVI Alliance, Chemin du Pommier 40, Le Grand-Saconnex, Switzerland
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Hilton J, Keeling MJ. Incorporating household structure and demography into models of endemic disease. J R Soc Interface 2019; 16:20190317. [PMID: 31387486 PMCID: PMC6731502 DOI: 10.1098/rsif.2019.0317] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
The spread of infectious diseases is intimately linked with the strength and type of contact between individuals. Multiple observational and modelling studies have highlighted the importance of two forms of social mixing: age structure, where the likelihood of interaction between two individuals is determined by their ages; and household structure, which recognizes the much stronger contacts and hence transmission potential within the family setting. Age structure has been ubiquitous in predictive models of both endemic and epidemic infections, in part due to the ease of assessing someone’s age. By contrast, although household structure is potentially the dominant heterogeneity, it has received less attention, in part due to an absence of the necessary methodology. Here, we develop the modelling framework necessary to predict the behaviour of endemic infections (which necessitates capturing demographic processes) in populations that possess both household and age structure. We compare two childhood infections, with measles-like and mumps-like parameters, and two populations with UK-like and Kenya-like characteristics, which allows us to disentangle the impact of epidemiology and demography. For this high-dimensional model, we predict complex nonlinear dynamics, where the dynamics of within-household outbreaks are tempered by historical waves of infection and the immunity of older individuals.
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Affiliation(s)
- Joe Hilton
- MathSys CDT, Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.,Zeeman Institute (SBIDER), University of Warwick, Coventry CV4 7AL, UK
| | - Matt J Keeling
- Zeeman Institute (SBIDER), University of Warwick, Coventry CV4 7AL, UK.,Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.,School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK
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Milwid RM, O’Sullivan TL, Poljak Z, Laskowski M, Greer AL. Comparison of the dynamic networks of four equine boarding and training facilities. Prev Vet Med 2019; 162:84-94. [DOI: 10.1016/j.prevetmed.2018.11.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 10/31/2018] [Accepted: 11/24/2018] [Indexed: 12/29/2022]
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Who interacts with whom? Social mixing insights from a rural population in India. PLoS One 2018; 13:e0209039. [PMID: 30576333 PMCID: PMC6303083 DOI: 10.1371/journal.pone.0209039] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 11/27/2018] [Indexed: 11/19/2022] Open
Abstract
Acute lower respiratory infections (ALRI) are a leading cause of morbidity and mortality globally, with most ALRI deaths occurring in children in developing countries. Computational models can be used to test the efficacy of respiratory infection prevention interventions, but require data on social mixing patterns, which are sparse in developing countries. We describe social mixing patterns among a rural community in northern India. During October 2015-February 2016, trained field workers conducted cross-sectional face-to-face standardized surveys in a convenience sample of 330 households in Faridabad District, Haryana State, India. Respondents were asked about the number, duration, and setting of social interactions during the previous 24 hours. Responses were compared by age and gender. Among the 3083 residents who were approached, 2943 (96%) participated, of whom 51% were male and the median age was 22 years (interquartile range (IQR) 9–37). Respondents reported contact (defined as having had a face-to-face conversation within 3 feet, which may or may not have included physical contact) with a median of 17 (IQR 12–25) people during the preceding 24 hours. Median total contact time per person was 36 person-hours (IQR 26–52). Female older children and adults had significantly fewer contacts than males of similar age (Kruskal-Wallis χ2 = 226.59, p<0.001), but spent a longer duration in contact with young children (Kruskal-Wallis χ2 = 27.26, p<0.001), suggesting a potentially complex pattern of differential risk of infection between genders. After controlling for household size and day of the week, respondent age was significantly associated with number and duration of contacts. These findings can be used to model the impact of interventions to reduce lower respiratory tract infections in India.
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Dias A, Geard N, Campbell PT, Warr D, McVernon J. Quantity or quality? Assessing relationships between perceived social connectedness and recorded encounters. PLoS One 2018; 13:e0208083. [PMID: 30496262 PMCID: PMC6264807 DOI: 10.1371/journal.pone.0208083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Accepted: 11/12/2018] [Indexed: 11/29/2022] Open
Abstract
Introduction Higher levels of social connectedness are associated with better physical and mental health outcomes, but measures of connectedness are often study specific. Prior research has distinguished between perceived and received (quantifiable) measures of social connectedness, with differing impacts on health, sometimes mediated by place of residence. This analysis investigated the relationship between perceptions of social support/connection and quantifiable measures of social encounters, by neighbourhood, to inform understanding of place-based differences in connectedness and health outcomes. Methods Negative binomial regression models were used to determine associations between perceptions of social connectedness (perceived community connections and social involvement) and the number of recorded daily social encounters as a proxy for received support/connectedness. Analyses were undertaken across two Local Government Areas (LGAs) in Melbourne with disparate socio-economic profiles to examine potential modification of social connectedness measures by neighbourhood of residence. Results Two measures of perceived connectedness had a clear relationship with recorded daily social encounters–feeling a sense of community belonging (RR 1.20 (1.04, 1.37), p = 0.010) and having family or friends close by (RR 1.30 (1.10,1.54), p = 0.002 “neither” compared to “disagree”, (RR 1.15 (1.04, 1.26), p = 0.006 “agree” compared to “disagree”). Involvement in a local church, sporting or social club was associated with a greater number of daily social encounters for respondents who participated a few times a year (RR 1.17 (1.05,1.32), p = 0.006) or often (RR 1.23 (1.12,1.36), p<0.001) compared to never. In the less affluent LGA, active contributions to neighbours and community through assistance and volunteering were a frequent driver of social connection. Differences in patterns between the two areas were found with some measures of perception showing stronger relationships with recorded daily encounters in one area but not the other. Conclusions These results indicate substantial complexity in the relationship between perceptions of social connectedness and recorded daily social encounters/received connectedness, meaning that one cannot be reliably extrapolated from the other. Drivers of individuals’ social connections also varied by area of residence. These findings offer new insights into potential mediators of the association between connectedness and wellbeing.
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Affiliation(s)
- Alison Dias
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Nicholas Geard
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia
- Victorian Infectious Diseases Reference Laboratory Epidemiology Unit at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Australia
| | - Patricia Therese Campbell
- Victorian Infectious Diseases Reference Laboratory Epidemiology Unit at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Australia
- Infection and Immunity Theme, Murdoch Children’s Research Institute, Royal Children’s Hospital, Melbourne, Australia
| | - Deborah Warr
- Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Jodie McVernon
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Victorian Infectious Diseases Reference Laboratory Epidemiology Unit at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne and Royal Melbourne Hospital, Melbourne, Australia
- Infection and Immunity Theme, Murdoch Children’s Research Institute, Royal Children’s Hospital, Melbourne, Australia
- * E-mail:
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Pinter-Wollman N, Jelić A, Wells NM. The impact of the built environment on health behaviours and disease transmission in social systems. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170245. [PMID: 29967306 PMCID: PMC6030577 DOI: 10.1098/rstb.2017.0245] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/25/2018] [Indexed: 01/08/2023] Open
Abstract
The environment plays an important role in disease dynamics and in determining the health of individuals. Specifically, the built environment has a large impact on the prevention and containment of both chronic and infectious disease in humans and in non-human animals. The effects of the built environment on health can be direct, for example, by influencing environmental quality, or indirect by influencing behaviours that impact disease transmission and health. Furthermore, these impacts can happen at many scales, from the individual to the society, and from the design of the plates we eat from to the design of cities. In this paper, we review the ways that the built environment affects both the prevention and the containment of chronic and infectious disease. We bring examples from both human and animal societies and attempt to identify parallels and gaps between the study of humans and animals that can be capitalized on to advance the scope and perspective of research in each respective field. By consolidating this literature, we hope to highlight the importance of built structures in determining the complex dynamics of disease and in impacting the health behaviours of both humans and animals.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.
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Affiliation(s)
- Noa Pinter-Wollman
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Andrea Jelić
- Department of Architecture, Design and Media Technology, Aalborg University, 9000 Aalborg, Denmark
| | - Nancy M Wells
- Department of Design and Environmental Analysis, Cornell University, Ithaca, NY 14853, USA
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Laager M, Mbilo C, Madaye EA, Naminou A, Léchenne M, Tschopp A, Naïssengar SK, Smieszek T, Zinsstag J, Chitnis N. The importance of dog population contact network structures in rabies transmission. PLoS Negl Trop Dis 2018; 12:e0006680. [PMID: 30067733 PMCID: PMC6089439 DOI: 10.1371/journal.pntd.0006680] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 08/13/2018] [Accepted: 07/10/2018] [Indexed: 11/19/2022] Open
Abstract
Canine rabies transmission was interrupted in N'Djaména, Chad, following two mass vaccination campaigns. However, after nine months cases resurged with re-establishment of endemic rabies transmission to pre-intervention levels. Previous analyses investigated district level spatial heterogeneity of vaccination coverage, and dog density; and importation, identifying the latter as the primary factor for rabies resurgence. Here we assess the impact of individual level heterogeneity on outbreak probability, effectiveness of vaccination campaigns and likely time to resurgence after a campaign. Geo-located contact sensors recorded the location and contacts of 237 domestic dogs in N'Djaména over a period of 3.5 days. The contact network data showed that urban dogs are socially related to larger communities and constrained by the urban architecture. We developed a network generation algorithm that extrapolates this empirical contact network to networks of large dog populations and applied it to simulate rabies transmission in N'Djaména. The model predictions aligned well with the rabies incidence data. Using the model we demonstrated, that major outbreaks are prevented when at least 70% of dogs are vaccinated. The probability of a minor outbreak also decreased with increasing vaccination coverage, but reached zero only when coverage was near total. Our results suggest that endemic rabies in N'Djaména may be explained by a series of importations with subsequent minor outbreaks. We show that highly connected dogs hold a critical role in transmission and that targeted vaccination of such dogs would lead to more efficient vaccination campaigns.
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Affiliation(s)
- Mirjam Laager
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Céline Mbilo
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | | | - Abakar Naminou
- Institut de Recherches en Elevage pour le Développement, Farcha, N’Djaména, Chad
| | - Monique Léchenne
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Aurélie Tschopp
- Veterinary Public Health Institute, Vetsuisse Faculty, University of Bern, Liebefeld, Switzerland
| | | | - Timo Smieszek
- Modelling and Economics Unit, National Infection Service, Public Health England, London, United Kingdom
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College School of Public Health, London, United Kingdom
| | - Jakob Zinsstag
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Nakul Chitnis
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
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Kucharski AJ, Wenham C, Brownlee P, Racon L, Widmer N, Eames KTD, Conlan AJK. Structure and consistency of self-reported social contact networks in British secondary schools. PLoS One 2018; 13:e0200090. [PMID: 30044816 PMCID: PMC6059423 DOI: 10.1371/journal.pone.0200090] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 06/19/2018] [Indexed: 12/02/2022] Open
Abstract
Self-reported social mixing patterns are commonly used in mathematical models of infectious diseases. It is particularly important to quantify patterns for school-age children given their disproportionate role in transmission, but it remains unclear how the structure of such social interactions changes over time. By integrating data collection into a public engagement programme, we examined self-reported contact networks in year 7 groups in four UK secondary schools. We collected data from 460 unique participants across four rounds of data collection conducted between January and June 2015, with 7,315 identifiable contacts reported in total. Although individual-level contacts varied over the study period, we were able to obtain out-of-sample accuracies of more than 90% and F-scores of 0.49-0.84 when predicting the presence or absence of social contacts between specific individuals across rounds of data collection. Network properties such as clustering and number of communities were broadly consistent within schools between survey rounds, but varied significantly between schools. Networks were assortative according to gender, and to a lesser extent school class, with the estimated clustering coefficient larger among males in all surveyed co-educational schools. Our results demonstrate that it is feasible to collect longitudinal self-reported social contact data from school children and that key properties of these data are consistent between rounds of data collection.
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Affiliation(s)
- Adam J. Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Clare Wenham
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Health Policy, London School of Economics, London, United Kingdom
| | | | - Lucie Racon
- St Bonaventure’s School, London, United Kingdom
| | - Natasha Widmer
- St Paul’s Catholic College, Burgess Hill, United Kingdom
| | - Ken T. D. Eames
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Andrew J. K. Conlan
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
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Brinkhues S, Schram MT, Hoebe CJPA, Kretzschmar MEE, Koster A, Dagnelie PC, Sep SJS, van Kuijk SMJ, Savelkoul PHM, Dukers-Muijrers NHTM. Social networks in relation to self-reported symptomatic infections in individuals aged 40-75 - the Maastricht study. BMC Infect Dis 2018; 18:300. [PMID: 29973154 PMCID: PMC6030801 DOI: 10.1186/s12879-018-3197-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 06/18/2018] [Indexed: 01/28/2023] Open
Abstract
Background Most infections are spread through social networks (detrimental effect). However, social networks may also lower infection acquisition (beneficial effect). This study aimed to examine associations between social network parameters and prevalence of self-reported upper and lower respiratory, gastrointestinal and urinary tract infections in a population aged 40–75. Methods In this population-based cross-sectional cohort study (N = 3004, mean age 60.0 ± 8.2 years, 49% women), infections within the past two months were assessed by self-administered questionnaires. Social network parameters were assessed using a name generator questionnaire. To examine the associated beneficial and detrimental network parameters, univariable and multivariable logistic regression was used. Results Participants reported an average of 10 people (alters) with whom they had 231 contacts per half year. Prevalences were 31.1% for upper respiratory, 11.5% for lower respiratory, 12.5% for gastrointestinal, and 5.7% for urinary tract infections. Larger network size, and a higher percentage of alters that were friends or acquaintances were associated with higher odds of upper respiratory, lower respiratory and/or gastrointestinal infections (detrimental). A higher total number of contacts, higher percentages of alters of the same age, and higher percentages of family members/acquaintances were associated with lower odds of upper respiratory, lower respiratory and/or gastrointestinal infections (beneficial). Conclusion We identified both detrimental and beneficial associations of social network parameters with the prevalence of infections. Our findings can be used to complement mathematical models on infection spread, as well as to optimize current infectious disease control. Electronic supplementary material The online version of this article (10.1186/s12879-018-3197-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Stephanie Brinkhues
- Department of Medical Microbiology, Maastricht University Medical Centre (MUMC+); CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands.,Department of Sexual Health, Infectious Diseases and Environmental Health, Public Health Service South Limburg, Postbus 33, 6400AA, Heerlen, The Netherlands
| | - Miranda T Schram
- Department of Medicine, Maastricht University Medical Centre (MUMC+); CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands
| | - Christian J P A Hoebe
- Department of Medical Microbiology, Maastricht University Medical Centre (MUMC+); CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands.,Department of Sexual Health, Infectious Diseases and Environmental Health, Public Health Service South Limburg, Postbus 33, 6400AA, Heerlen, The Netherlands
| | - Mirjam E E Kretzschmar
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, University Medical Centre Utrecht, Julius Centre for Health Sciences and Primary Care, Utrecht, The Netherlands
| | - Annemarie Koster
- Department of Social Medicine; CAPHRI, School for Public Health and Primary Care, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands
| | - Pieter C Dagnelie
- Department of Epidemiology, CARIM, Cardiovascular Research Institute Maastricht; CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands
| | - Simone J S Sep
- Department of Medicine, Maastricht University Medical Centre (MUMC+); CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands
| | - Sander M J van Kuijk
- Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA), Maastricht University Medical Centre (MUMC+), P.O. Box 616, 6200, MD, Maastricht, The Netherlands
| | - Paul H M Savelkoul
- Department of Medical Microbiology, Maastricht University Medical Centre (MUMC+); CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands.,Department of Medical Microbiology & Infection Control, VU University Medical Center, Amsterdam, The Netherlands
| | - Nicole H T M Dukers-Muijrers
- Department of Medical Microbiology, Maastricht University Medical Centre (MUMC+); CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands. .,Department of Sexual Health, Infectious Diseases and Environmental Health, Public Health Service South Limburg, Postbus 33, 6400AA, Heerlen, The Netherlands.
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46
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Social contact patterns of infants in deciding vaccination strategy: a prospective, cross-sectional, single-centre study. Epidemiol Infect 2018; 146:1157-1166. [DOI: 10.1017/s0950268818001048] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
AbstractSocial contact between individuals is believed to be a fundamental cause in the transmission of many respiratory tract infections. Because they have not yet been fully vaccinated, infants are at high risk for contracting whooping cough, influenza and their serious complications. Therefore, determining infant social contact patterns is an important step in protecting them from respiratory tract infection. This study included 1200 healthy infants (<12 months of age). Social contact diaries were used to estimate the frequency and nature of the infants’ social contacts. This survey also gathered information regarding the infants’ respiratory symptoms and their frequency of attendance at crowded places over a period of 1 week. The diary return rate was 83.8% (N = 1006), and there was a total of 4706 contacts reported for these infants. The median daily contact number per capita was 4 (range 1–18). The median number of contacts with adolescents was 0 (range 0–7). Of the infants, 50.3% had contact with non-household individuals. The mothers had the longest contacts with their babies. Contacts with school children, frequency of attendance at crowded places and age were determined to be significant effective factors for reporting respiratory symptoms. Results suggest that school-age siblings and the mothers should be primarily vaccinated, and parents should keep their babies away from crowded places for protecting their infants.
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le Polain de Waroux O, Cohuet S, Ndazima D, Kucharski AJ, Juan-Giner A, Flasche S, Tumwesigye E, Arinaitwe R, Mwanga-Amumpaire J, Boum Y, Nackers F, Checchi F, Grais RF, Edmunds WJ. Characteristics of human encounters and social mixing patterns relevant to infectious diseases spread by close contact: a survey in Southwest Uganda. BMC Infect Dis 2018; 18:172. [PMID: 29642869 PMCID: PMC5896105 DOI: 10.1186/s12879-018-3073-1] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 03/27/2018] [Indexed: 11/24/2022] Open
Abstract
Background Quantification of human interactions relevant to infectious disease transmission through social contact is central to predict disease dynamics, yet data from low-resource settings remain scarce. Methods We undertook a social contact survey in rural Uganda, whereby participants were asked to recall details about the frequency, type, and socio-demographic characteristics of any conversational encounter that lasted for ≥5 min (henceforth defined as ‘contacts’) during the previous day. An estimate of the number of ‘casual contacts’ (i.e. < 5 min) was also obtained. Results In total, 566 individuals were included in the study. On average participants reported having routine contact with 7.2 individuals (range 1-25). Children aged 5-14 years had the highest frequency of contacts and the elderly (≥65 years) the fewest (P < 0.001). A strong age-assortative pattern was seen, particularly outside the household and increasingly so for contacts occurring further away from home. Adults aged 25-64 years tended to travel more often and further than others, and males travelled more frequently than females. Conclusion Our study provides detailed information on contact patterns and their spatial characteristics in an African setting. It therefore fills an important knowledge gap that will help more accurately predict transmission dynamics and the impact of control strategies in such areas. Electronic supplementary material The online version of this article (10.1186/s12879-018-3073-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- O le Polain de Waroux
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | | | - D Ndazima
- Epicentre, Uganda Research Centre, Mbarara, Uganda
| | - A J Kucharski
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | | | - S Flasche
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - E Tumwesigye
- Kabwohe Medical Research Centre, Kabwohe, Uganda
| | - R Arinaitwe
- Epicentre, Uganda Research Centre, Mbarara, Uganda
| | - J Mwanga-Amumpaire
- Epicentre, Uganda Research Centre, Mbarara, Uganda.,Mbarara University Of Science and Technology (MUST), Mbarara, Uganda
| | - Y Boum
- Epicentre, Uganda Research Centre, Mbarara, Uganda
| | | | - F Checchi
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | | | - W J Edmunds
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
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48
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Abstract
Transmissibility is the defining characteristic of infectious diseases. Quantifying transmission matters for understanding infectious disease epidemiology and designing evidence-based disease control programs. Tracing individual transmission events can be achieved by epidemiological investigation coupled with pathogen typing or genome sequencing. Individual infectiousness can be estimated by measuring pathogen loads, but few studies have directly estimated the ability of infected hosts to transmit to uninfected hosts. Individuals' opportunities to transmit infection are dependent on behavioral and other risk factors relevant given the transmission route of the pathogen concerned. Transmission at the population level can be quantified through knowledge of risk factors in the population or phylogeographic analysis of pathogen sequence data. Mathematical model-based approaches require estimation of the per capita transmission rate and basic reproduction number, obtained by fitting models to case data and/or analysis of pathogen sequence data. Heterogeneities in infectiousness, contact behavior, and susceptibility can have substantial effects on the epidemiology of an infectious disease, so estimates of only mean values may be insufficient. For some pathogens, super-shedders (infected individuals who are highly infectious) and super-spreaders (individuals with more opportunities to transmit infection) may be important. Future work on quantifying transmission should involve integrated analyses of multiple data sources.
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49
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Keiser CN, Pinter-Wollman N, Ziemba MJ, Kothamasu KS, Pruitt JN. The primary case is not enough: Variation among individuals, groups and social networks modify bacterial transmission dynamics. J Anim Ecol 2018; 87:369-378. [PMID: 28692130 PMCID: PMC5871623 DOI: 10.1111/1365-2656.12729] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 06/13/2017] [Indexed: 12/26/2022]
Abstract
The traits of the primary case of an infectious disease outbreak, and the circumstances for their aetiology, potentially influence the trajectory of transmission dynamics. However, these dynamics likely also depend on the traits of the individuals with whom the primary case interacts. We used the social spider Stegodyphus dumicola to test how the traits of the primary case, group phenotypic composition and group size interact to facilitate the transmission of a GFP-labelled cuticular bacterium. We also compared bacterial transmission across experimentally generated "daisy-chain" vs. "star" networks of social interactions. Finally, we compared social network structure across groups of different sizes. Groups of 10 spiders experienced more bacterial transmission events compared to groups of 30 spiders, regardless of groups' behavioural composition. Groups containing only one bold spider experienced the lowest levels of bacterial transmission regardless of group size. We found no evidence for the traits of the primary case influencing any transmission dynamics. In a second experiment, bacteria were transmitted to more individuals in experimentally induced star networks than in daisy-chains, on which transmission never exceeded three steps. In both experimental network types, transmission success depended jointly on the behavioural traits of the interacting individuals; however, the behavioural traits of the primary case were only important for transmission on star networks. Larger social groups exhibited lower interaction density (i.e. had a low ratio of observed to possible connections) and were more modular, i.e. they had more connections between nodes within a subgroup and fewer connections across subgroups. Thus, larger groups may restrict transmission by forming fewer interactions and by isolating subgroups that interacted with the primary case. These findings suggest that accounting for the traits of single exposed hosts has less power in predicting transmission dynamics compared to the larger scale factors of the social groups in which they reside. Factors like group size and phenotypic composition appear to alter social interaction patterns, which leads to differential transmission of microbes.
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Affiliation(s)
- Carl N. Keiser
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
- Biosciences Department, Rice University, Academy of Fellows, Rice University, Houston, TX, USA
| | - Noa Pinter-Wollman
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Michael J. Ziemba
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Krishna S. Kothamasu
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan N. Pruitt
- Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA, USA
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50
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Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics. Sci Rep 2018; 8:1686. [PMID: 29374222 PMCID: PMC5786108 DOI: 10.1038/s41598-018-20008-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 01/10/2018] [Indexed: 11/21/2022] Open
Abstract
Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.
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