1
|
Diexer S, Teslya A, Buskens V, Matser A, Stein M, Kretzschmar ME. Improving web-based respondent-driven sampling performance among men who have sex with men in the Netherlands. PLOS DIGITAL HEALTH 2023; 2:e0000192. [PMID: 36812647 PMCID: PMC9931300 DOI: 10.1371/journal.pdig.0000192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/04/2023] [Indexed: 02/11/2023]
Abstract
Respondent-driven sampling (RDS) uses the social network of participants to sample people of populations that can be challenging to engage. While in this context RDS offers improvements on standard sampling methods, it does not always generate a sufficiently large sample. In this study we aimed to identify preferences of men who have sex with men (MSM) in the Netherlands regarding surveys and recruitment to studies with the subsequent goal of improving the performance of web-based RDS in MSM. A questionnaire about preferences with respect to various aspects of an web-based RDS study was circulated among participants of the Amsterdam Cohort Studies, a study among MSM. The duration of a survey and the type and amount of participation reward were explored. Participants were also asked about their preferences regarding invitation and recruitment methods. We used multi-level and rank-ordered logistic regression to analyze the data and identify the preferences. The majority of the 98 participants were older than 45 years (59.2%), were born in the Netherlands (84.7%), and had a university degree (77.6%). Participants did not have a preference regarding the type of participation reward, but they preferred to spend less time on a survey and to get a higher monetary reward. Sending a personal email was the preferred option to getting invited or inviting someone to a study, while using Facebook messenger was the least preferred option. There are differences between age groups: monetary rewards were less important to older participants (45+) and younger participants (18-34) more often preferred SMS/WhatsApp to recruit others. When designing a web-based RDS study for MSM, it is important to balance the duration of the survey and the monetary reward. If the study takes more of a participants time, it might be beneficial to provide a higher incentive. To optimize expected participation, the recruitment method should be selected based on the targeted population group.
Collapse
Affiliation(s)
- Sophie Diexer
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- * E-mail:
| | - Alexandra Teslya
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Vincent Buskens
- Department of Sociology, Utrecht University, Utrecht, The Netherlands
| | - Amy Matser
- Department of Infectious Diseases, Public Health Service (GGD) of Amsterdam, Amsterdam, The Netherlands
- Department of Internal Medicine, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Academic Medical Center, Amsterdam, The Netherlands
| | - Mart Stein
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Mirjam E. Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| |
Collapse
|
2
|
Nixon E, Silvonen T, Barreaux A, Kwiatkowska R, Trickey A, Thomas A, Ali B, Treneman-Evans G, Christensen H, Brooks-Pollock E, Denford S. A mixed methods analysis of participation in a social contact survey. Epidemics 2022; 41:100635. [PMID: 36182804 PMCID: PMC7615368 DOI: 10.1016/j.epidem.2022.100635] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 07/28/2022] [Accepted: 09/21/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Social contact survey data forms a core component of modern epidemic models: however, there has been little assessment of the potential biases in such data. METHODS We conducted focus groups with university students who had (n = 13) and had never (n = 14) completed a social contact survey during the COVID-19 pandemic. Qualitative findings were explored quantitatively by analysing participation data. RESULTS The opportunity to contribute to COVID-19 research, to be heard and feel useful were frequently reported motivators for participating in the contact survey. Reductions in survey engagement following lifting of COVID-19 restrictions may have occurred because the research was perceived to be less critical and/or because the participants were busier and had more contacts. Having a high number of contacts to report, uncertainty around how to report each contact, and concerns around confidentiality were identified as factors leading to inaccurate reporting. Focus groups participants thought that financial incentives or provision of study results would encourage participation. CONCLUSIONS Incentives could improve engagement with social contact surveys. Qualitative research can inform the format, timing, and wording of surveys to optimise completion and accuracy.
Collapse
Affiliation(s)
- Emily Nixon
- School of Biological Sciences, University of Bristol, Bristol, UK; School of Population Health Sciences, University of Bristol, Bristol, UK; Department of Mathematical Sciences, University of Liverpool, Liverpool, UK.
| | - Taru Silvonen
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Antoine Barreaux
- Bristol Veterinary School, University of Bristol, Bristol, UK; INTERTRYP (Univ. Montpellier, CIRAD, IRD), Montpellier, France
| | - Rachel Kwiatkowska
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Adam Trickey
- School of Population Health Sciences, University of Bristol, Bristol, UK
| | - Amy Thomas
- School of Population Health Sciences, University of Bristol, Bristol, UK
| | - Becky Ali
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Georgia Treneman-Evans
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Hannah Christensen
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Ellen Brooks-Pollock
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Sarah Denford
- School of Population Health Sciences, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| |
Collapse
|
3
|
Pham PN, Keegan K, Johnston LG, Rodas J, Restrepo MA, Wei C, Vinck P. Assessing the impact of the COVID-19 pandemic among Venezuelan refugees and migrants in Colombia using respondent-driven sampling (RDS). BMJ Open 2022; 12:e054820. [PMID: 36198458 PMCID: PMC9534778 DOI: 10.1136/bmjopen-2021-054820] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVES To determine factors associated with adherence to COVID-19 mitigation measures, related symptoms and testing, as well as pandemic-related income loss among Venezuelan refugee and migrant adults in urban and border areas of Colombia. DESIGN Phone-based respondent-driven sampling SETTING: Bogotá and Norte de Santander, Colombia. PARTICIPANTS 605 adult Venezuelan refugees and migrants residing in Bogotá (n=305) and Norte de Santander (n=300), who arrived in Colombia after 2014 and completed the survey in August and September 2020. PRIMARY AND SECONDARY OUTCOME MEASURES Full COVID-19 compliance (vs incomplete or no compliance), any COVID-19-related symptoms (vs none) and income loss due to isolation measures in Colombia (vs no income change or increase in income). RESULTS Older age was associated with lower odds of compliance with physical distancing measures (0.94, 0.90-0.99; p=0.01) for those in Bogotá. Nearly 15% of refugees and migrants in both locations (81 of 605) experienced at least one symptom consistent with COVID-19. Having a health condition was associated with higher odds of experiencing COVID-19-related symptoms in Bogotá (4.00, 1.22-13.06; p=0.02) and Norte de Santander (6.99, 1.95-24.99; p=0.003). Around 8% in both locations (48 of 605) were tested for COVID-19. Around 90% in both locations (537 of 605) had trouble earning an income after the introduction of isolation measures, and the median reported monthly income decreased by half in Bogotá and by 30% in Norte de Santander. A higher level of education (3.46, 1.02-11.75; p=0.05) was associated with higher odds of income loss among participants in Norte de Santander. CONCLUSIONS Results indicate high compliance with COVID-19 mitigation measures, low testing rates and high pandemic-related income loss among Venezuelan refugees and migrants in Colombia. This study provides insights into a hard-to-reach refugee and migrant population in Colombia; additional study on the effects of the pandemic on hidden populations is warranted.
Collapse
Affiliation(s)
- Phuong N Pham
- Department of Emergency Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Katrina Keegan
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | | | | | | | - Carol Wei
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Patrick Vinck
- Department of Emergency Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| |
Collapse
|
4
|
Mousa A, Winskill P, Watson OJ, Ratmann O, Monod M, Ajelli M, Diallo A, Dodd PJ, Grijalva CG, Kiti MC, Krishnan A, Kumar R, Kumar S, Kwok KO, Lanata CF, le Polain de Waroux O, Leung K, Mahikul W, Melegaro A, Morrow CD, Mossong J, Neal EF, Nokes DJ, Pan-Ngum W, Potter GE, Russell FM, Saha S, Sugimoto JD, Wei WI, Wood RR, Wu J, Zhang J, Walker P, Whittaker C. Social contact patterns and implications for infectious disease transmission: a systematic review and meta-analysis of contact surveys. eLife 2021; 10:70294. [PMID: 34821551 PMCID: PMC8765757 DOI: 10.7554/elife.70294] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 11/24/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focused on high-income settings. Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys, we explored how contact characteristics (number, location, duration, and whether physical) vary across income settings. Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income strata on the frequency, duration, and type of contacts individuals made. Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens and the effectiveness of different non-pharmaceutical interventions. Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1). Infectious diseases, particularly those caused by airborne pathogens like SARS-CoV-2, spread by social contact, and understanding how people mix is critical in controlling outbreaks. To explore these patterns, researchers typically carry out large contact surveys. Participants are asked for personal information (such as gender, age and occupation), as well as details of recent social contacts, usually those that happened in the last 24 hours. This information includes, the age and gender of the contact, where the interaction happened, how long it lasted, and whether it involved physical touch. These kinds of surveys help scientists to predict how infectious diseases might spread. But there is a problem: most of the data come from high-income countries, and there is evidence to suggest that social contact patterns differ between places. Therefore, data from these countries might not be useful for predicting how infections spread in lower-income regions. Here, Mousa et al. have collected and combined data from 27 contact surveys carried out before the COVID-19 pandemic to see how baseline social interactions vary between high- and lower-income settings. The comparison revealed that, in higher-income countries, the number of daily contacts people made decreased with age. But, in lower-income countries, younger and older individuals made similar numbers of contacts and mixed with all age groups. In higher-income countries, more contacts happened at work or school, while in low-income settings, more interactions happened at home and people were also more likely to live in larger, intergenerational households. Mousa et al. also found that gender affected how long contacts lasted and whether they involved physical contact, both of which are key risk factors for transmitting airborne pathogens. These findings can help researchers to predict how infectious diseases might spread in different settings. They can also be used to assess how effective non-medical restrictions, like shielding of the elderly and workplace closures, will be at reducing transmissions in different parts of the world.
Collapse
Affiliation(s)
- Andria Mousa
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Oliver John Watson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Oliver Ratmann
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Mélodie Monod
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Marco Ajelli
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, United States
| | - Aldiouma Diallo
- VITROME, Institut de Recherche pour le Developpement, Dakar, Senegal
| | - Peter J Dodd
- School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom
| | - Carlos G Grijalva
- Division of Pharmacoepidemiology, Department of Health Policy, Vanderbilt University Medical Center, Nashville, United States
| | | | - Anand Krishnan
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Supriya Kumar
- Bill and Melinda Gates Foundation, Seattle, WA, United States
| | - Kin O Kwok
- JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | | | | | - Kathy Leung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Wiriya Mahikul
- Faculty of Medicine and Public Health, HRH Princess Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Alessia Melegaro
- Dondena Centre for Research on Social Dynamics and Public Policy, Department of Social and Political Sciences, Bocconi University, Milano, Italy
| | - Carl D Morrow
- Desmond Tutu HIV Centre, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Eleanor Fg Neal
- Infection and Immunity, Murdoch Children's Research Institute, Victoria, Australia
| | - D James Nokes
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | - Gail E Potter
- National Institute for Allergies and Infectious Diseases, National Institutes of Health, Rockville, United States
| | - Fiona M Russell
- Infection and Immunity, Murdoch Children's Research Institute, Victoria, Australia
| | - Siddhartha Saha
- US Centers for Disease Control and Prevention, New Delhi, India
| | - Jonathan D Sugimoto
- Seattle Epidemiologic Research and Information Center, United States Department of Veterans Affairs, Seattle, United States
| | - Wan In Wei
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Robin R Wood
- Desmond Tutu HIV Centre, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Joseph Wu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Juanjuan Zhang
- School of Public Health, Fudan University, Shanghai, China
| | - Patrick Walker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| |
Collapse
|
5
|
Del Fava E, Adema I, Kiti MC, Poletti P, Merler S, Nokes DJ, Manfredi P, Melegaro A. Individual's daily behaviour and intergenerational mixing in different social contexts of Kenya. Sci Rep 2021; 11:21589. [PMID: 34732732 PMCID: PMC8566563 DOI: 10.1038/s41598-021-00799-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 10/15/2021] [Indexed: 12/20/2022] Open
Abstract
We investigated contact patterns in diverse social contexts in Kenya and the daily behaviours that may play a pivotal role in infection transmission to the most vulnerable leveraging novel data from a 2-day survey on social contacts and time use (TU) from a sample of 1407 individuals (for a total of 2705 person days) from rural, urban formal, and informal settings. We used TU data to build six profiles of daily behaviour based on the main reported activities, i.e., Homestayers (71.1% of person days), Workers (9.3%), Schoolers (7.8%), or locations at increasing distance from home, i.e., Walkers (6.6%), Commuters (4.6%), Travelers (0.6%). In the rural setting, we observed higher daily contact numbers (11.56, SD 0.23) and percentages of intergenerational mixing with older adults (7.5% of contacts reported by those younger than 60 years vs. less than 4% in the urban settings). Overall, intergenerational mixing with older adults was higher for Walkers (7.3% of their reported contacts), Commuters (8.7%), and Homestayers (5.1%) than for Workers (1.5%) or Schoolers (3.6%). These results could be instrumental in defining effective interventions that acknowledge the heterogeneity in social contexts and daily routines, either in Kenya or other demographically and culturally similar sub-Saharan African settings.
Collapse
Affiliation(s)
- Emanuele Del Fava
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy
- Max Planck Institute for Demographic Research, Rostock, Germany
| | - Irene Adema
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Moses C Kiti
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | | | - D James Nokes
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- School of Life Sciences and Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, UK
| | | | - Alessia Melegaro
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy.
- Department of Social and Political Sciences, Bocconi University, Milan, Italy.
| |
Collapse
|
6
|
Lopez D, Mohan B, Boone L, Matta J. Preserving Multiple Homophilies in a Network Configuration Model. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1781-1786. [PMID: 34891632 DOI: 10.1109/embc46164.2021.9629746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Respondent-driven sampling (RDS) is a popular method for surveying hidden populations based on friendships and existing social network connections. In such a survey the underlying hidden network remains largely unknown. However, it is useful to estimate its size as well as the relative proportions of surveyed features. The fact that linked network participants are likely to share common features is called homophily, and is an important property in understanding the topology of social networks. In this paper we present a methodology that scales up RDS data to model the underlying hidden population in a way that preserves multiple homophilies among different features. We test our model using 46 features of the population sampled by the SATHCAP RDS survey. Our network generation methodology successfully preserves the homophilic associations in a randomly generated Barabasi-Albert network. Having created a realistic model of the expanded SATHCAP network, we test our model by simulating RDS surveys over it, and comparing the resulting sub-networks with SATHCAP. In our generated network, we preserve 85% of homophilies to under 2% error. In our simulated RDS surveys we preserve 85% of homophilies to under 15% error.
Collapse
|
7
|
Mousa A, Winskill P, Watson OJ, Ratmann O, Monod M, Ajelli M, Diallo A, Dodd PJ, Grijalva CG, Kiti MC, Krishnan A, Kumar R, Kumar S, Kwok KO, Lanata CF, Le Polain de Waroux O, Leung K, Mahikul W, Melegaro A, Morrow CD, Mossong J, Neal EFG, Nokes DJ, Pan-ngum W, Potter GE, Russell FM, Saha S, Sugimoto JD, Wei WI, Wood RR, Wu JT, Zhang J, Walker PGT, Whittaker C. Social Contact Patterns and Implications for Infectious Disease Transmission: A Systematic Review and Meta-Analysis of Contact Surveys. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.06.10.21258720. [PMID: 34159341 PMCID: PMC8219108 DOI: 10.1101/2021.06.10.21258720] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focussed on high-income settings. METHODS Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys we explored how contact characteristics (number, location, duration and whether physical) vary across income settings. RESULTS Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age-groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, but low-income settings were characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income-strata on the frequency, duration and type of contacts individuals made. CONCLUSIONS These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions. FUNDING This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).
Collapse
Affiliation(s)
- Andria Mousa
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Oliver Ratmann
- Department of Mathematics, Imperial College London, London, UK
| | - Mélodie Monod
- Department of Mathematics, Imperial College London, London, UK
| | - Marco Ajelli
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA
| | - Aldiouma Diallo
- VITROME, Institut de Recherche pour le Developpement, Senegal
| | - Peter J Dodd
- School of Health and Related Research, University of Sheffield, UK
| | - Carlos G Grijalva
- Division of Pharmacoepidemiology, Department of Health Policy. Vanderbilt University Medical Center. Nashville, TN, USA
| | | | - Anand Krishnan
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| | | | - Kin On Kwok
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute of The Chinese University of Hong Kong, Shenzhen, China
| | - Claudio F Lanata
- Instituto de Investigación Nutricional, Lima, Peru
- Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | | | - Kathy Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, New Territories, Hong Kong SAR, China
| | - Wiriya Mahikul
- Faculty of Medicine and Public Health, HRH Princess Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok 10210, Thailand
| | - Alessia Melegaro
- Dondena Centre for Research on Social Dynamics and Public Policy, Department of Social and Political Sciences, Bocconi University, Milan, Italy
| | - Carl D Morrow
- Desmond Tutu HIV Centre, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa
- Centre for Infectious Disease Epidemiology and Research (CIDER), School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town South Africa
| | | | - Eleanor FG Neal
- Infection & Immunity, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - David J Nokes
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- School of Life Sciences, University of Warwick, Coventry UK
| | - Wirichada Pan-ngum
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Gail E Potter
- National Institute for Allergies and Infectious Diseases, National Institutes of Health, Rockville MD, USA
- The Emmes Company, Rockville MD, USA
| | - Fiona M Russell
- Infection & Immunity, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Siddhartha Saha
- Influenza Programme, US Centers for Disease Control and Prevention, India Office, US Embassy, New Delhi
| | - Jonathan D Sugimoto
- Seattle Epidemiologic Research and Information Center, Cooperative Studies Program, Office of Research and Development, United States Department of Veterans Affairs, USA
- Department of Epidemiology, University of Washington, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Wan In Wei
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Robin R Wood
- Desmond Tutu HIV Centre, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa
| | - Joseph T Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, New Territories, Hong Kong SAR, China
| | - Juanjuan Zhang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Patrick GT Walker
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| |
Collapse
|
8
|
Helms YB, Hamdiui N, Eilers R, Hoebe C, Dukers-Muijrers N, van den Kerkhof H, Timen A, Stein ML. Online respondent-driven detection for enhanced contact tracing of close-contact infectious diseases: benefits and barriers for public health practice. BMC Infect Dis 2021; 21:358. [PMID: 33863279 PMCID: PMC8051831 DOI: 10.1186/s12879-021-06052-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 04/05/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Online respondent-driven detection (RDD) is a novel method of case finding that can enhance contact tracing (CT). However, the advantages and challenges of RDD for CT have not yet been investigated from the perspective of public health professionals (PHPs). Therefore, it remains unclear if, and under what circumstances, PHPs are willing to apply RDD for CT. METHODS Between March and April 2019, we conducted semi-structured interviews with Dutch PHPs responsible for CT in practice. Questions were derived from the 'diffusion of innovations' theory. Between May and June 2019, we distributed an online questionnaire among 260 Dutch PHPs to quantify the main qualitative findings. Using different hypothetical scenarios, we assessed anticipated advantages and challenges of RDD, and PHPs' intention to apply RDD for CT. RESULTS Twelve interviews were held, and 70 PHPs completed the online questionnaire. A majority of questionnaire respondents (71%) had a positive intention towards using RDD for CT. Anticipated advantages of RDD were 'accommodating easy and autonomous participation in CT of index cases and contact persons', and 'reaching contact persons more efficiently'. Anticipated challenges were 'limited opportunities for PHPs to support, motivate, and coordinate the execution of CT', 'not being able to adequately convey measures to index cases and contact persons', and 'anticipated unrest among index cases and contact persons'. Circumstances under which PHPs anticipated RDD applicable for CT included index cases and contact persons being reluctant to share information directly with PHPs, digitally skilled and literate persons being involved, and large scale CT. Circumstances under which PHPs anticipated RDD less applicable for CT included severe consequences of missing information or contact persons for individual or public health, involvement of complex or impactful measures for index cases and contact persons, and a disease being perceived as severe or sensitive by index cases and their contact persons. CONCLUSIONS PHPs generally perceived RDD as a potentially beneficial method for public health practice, that may help overcome challenges present in traditional CT, and could be used during outbreaks of infectious diseases that spread via close contact. The circumstances under which CT is performed, appear to strongly influence PHPs' intention to use RDD for CT.
Collapse
Affiliation(s)
- Yannick B Helms
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Nora Hamdiui
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
- Department of Primary and Community Care, Radboud University Medical Centre, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Renske Eilers
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Christian Hoebe
- Department of Sexual Health, Infectious Diseases, and Environmental Health, South Limburg Public Health Service, Heerlen, The Netherlands
- Department of Social Medicine and Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Nicole Dukers-Muijrers
- Department of Sexual Health, Infectious Diseases, and Environmental Health, South Limburg Public Health Service, Heerlen, The Netherlands
- Department of Health Promotion, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Hans van den Kerkhof
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Aura Timen
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
- Athena Institute for Research on Innovation and Communication in Health and Life Sciences, VU University Amsterdam, Amsterdam, The Netherlands
| | - Mart L Stein
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| |
Collapse
|
9
|
Helms YB, Hamdiui N, Kretzschmar MEE, Rocha LEC, van Steenbergen JE, Bengtsson L, Thorson A, Timen A, Stein ML. Applications and Recruitment Performance of Web-Based Respondent-Driven Sampling: Scoping Review. J Med Internet Res 2021; 23:e17564. [PMID: 33448935 PMCID: PMC7846441 DOI: 10.2196/17564] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 06/26/2020] [Accepted: 07/19/2020] [Indexed: 11/13/2022] Open
Abstract
Background Web-based respondent-driven sampling is a novel sampling method for the recruitment of participants for generating population estimates, studying social network characteristics, and delivering health interventions. However, the application, barriers and facilitators, and recruitment performance of web-based respondent-driven sampling have not yet been systematically investigated. Objective Our objectives were to provide an overview of published research using web-based respondent-driven sampling and to investigate factors related to the recruitment performance of web-based respondent-driven sampling. Methods We conducted a scoping review on web-based respondent-driven sampling studies published between 2000 and 2019. We used the process evaluation of complex interventions framework to gain insights into how web-based respondent-driven sampling was implemented, what mechanisms of impact drove recruitment, what the role of context was in the study, and how these components together influenced the recruitment performance of web-based respondent-driven sampling. Results We included 18 studies from 8 countries (high- and low-middle income countries), in which web-based respondent-driven sampling was used for making population estimates (n=12), studying social network characteristics (n=3), and delivering health-related interventions (n=3). Studies used web-based respondent-driven sampling to recruit between 19 and 3448 participants from a variety of target populations. Studies differed greatly in the number of seeds recruited, the proportion of successfully recruiting participants, the number of recruitment waves, the type of incentives offered to participants, and the duration of data collection. Studies that recruited relatively more seeds, through online platforms, and with less rigorous selection procedures reported relatively low percentages of successfully recruiting seeds. Studies that did not offer at least one guaranteed material incentive reported relatively fewer waves and lower percentages of successfully recruiting participants. The time of data collection was shortest in studies with university students. Conclusions Web-based respondent-driven sampling can be successfully applied to recruit individuals for making population estimates, studying social network characteristics, and delivering health interventions. In general, seed and peer recruitment may be enhanced by rigorously selecting and motivating seeds, offering at least one guaranteed material incentive, and facilitating adequate recruitment options regarding the target population’s online connectedness and communication behavior. Potential trade-offs should be taken into account when implementing web-based respondent-driven sampling, such as having less opportunities to implement rigorous seed selection procedures when recruiting many seeds, as well as issues around online rather than physical participation, such as the risk of cheaters participating repeatedly.
Collapse
Affiliation(s)
- Yannick B Helms
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Nora Hamdiui
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Department of Primary and Community Care, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, Netherlands
| | - Mirjam E E Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Luis E C Rocha
- Department of Economics & Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Jim E van Steenbergen
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Centre for Infectious Diseases, Leiden University Medical Centre, Leiden, Netherlands
| | | | - Anna Thorson
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Aura Timen
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Athena Institute for Research on Innovation and Communication in Health and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Mart L Stein
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands
| |
Collapse
|
10
|
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.
Collapse
|
11
|
Abstract
Previous research on respiratory infection transmission among university students has primarily focused on influenza. In this study, we explore potential transmission events for multiple respiratory pathogens in a social contact network of university students. University students residing in on-campus housing (n = 590) were followed for the development of influenza-like illness for 10-weeks during the 2012-13 influenza season. A contact network was built using weekly self-reported contacts, class schedules, and housing information. We considered a transmission event to have occurred if students were positive for the same pathogen and had a network connection within a 14-day period. Transmitters were individuals who had onset date prior to their infected social contact. Throat and nasal samples were analysed for multiple viruses by RT-PCR. Five viruses were involved in 18 transmission events (influenza A, parainfluenza virus 3, rhinovirus, coronavirus NL63, respiratory syncytial virus). Transmitters had higher numbers of co-infections (67%). Identified transmission events had contacts reported in small classes (33%), dormitory common areas (22%) and dormitory rooms (17%). These results suggest that targeting person-to-person interactions, through measures such as isolation and quarantine, could reduce transmission of respiratory infections on campus.
Collapse
|
12
|
Mahikul W, Kripattanapong S, Hanvoravongchai P, Meeyai A, Iamsirithaworn S, Auewarakul P, Pan-ngum W. Contact Mixing Patterns and Population Movement among Migrant Workers in an Urban Setting in Thailand. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E2237. [PMID: 32225022 PMCID: PMC7177916 DOI: 10.3390/ijerph17072237] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 03/16/2020] [Accepted: 03/17/2020] [Indexed: 12/24/2022]
Abstract
Data relating to contact mixing patterns among humans are essential for the accurate modeling of infectious disease transmission dynamics. Here, we describe contact mixing patterns among migrant workers in urban settings in Thailand, based on a survey of 369 migrant workers of three nationalities. Respondents recorded their demographic data, including age, sex, nationality, workplace, income, and education. Each respondent chose a single day to record their contacts; this resulted in a total of more than 8300 contacts. The characteristics of contacts were recorded, including their age, sex, nationality, location of contact, and occurrence of physical contact. More than 75% of all contacts occurred among migrants aged 15 to 39 years. The contacts were highly clustered in this age group among migrant workers of all three nationalities. There were far fewer contacts between migrant workers with younger and older age groups. The pattern varied slightly among different nationalities, which was mostly dependent upon the types of jobs taken. Half of migrant workers always returned to their home country at most once a year and on a seasonal basis. The present study has helped us gain a better understanding of contact mixing patterns among migrant workers in urban settings. This information is useful both when simulating disease epidemics and for guiding optimal disease control strategies among this vulnerable section of the population.
Collapse
Affiliation(s)
- Wiriya Mahikul
- Department of Fundamentals of Public Health, Faculty of Public Health, Burapha University, Chon Buri 20131, Thailand;
| | | | - Piya Hanvoravongchai
- Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand;
| | - Aronrag Meeyai
- Department of Epidemiology, Faculty of Public Health, Mahidol University, Bangkok 10400, Thailand;
- Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Sopon Iamsirithaworn
- Department of Disease Control, Ministry of Public Health, Bangkok 11000, Thailand;
| | - Prasert Auewarakul
- Institute of Molecular Biosciences (MB), Mahidol University, Nakhon Pathom 73170, Thailand;
| | - Wirichada Pan-ngum
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University Bangkok, Bangkok 10400, Thailand
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand
| |
Collapse
|
13
|
Kiti MC, Melegaro A, Cattuto C, Nokes DJ. Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors. Wellcome Open Res 2019; 4:84. [PMID: 31489381 PMCID: PMC6719676 DOI: 10.12688/wellcomeopenres.15268.2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/19/2019] [Indexed: 11/28/2022] Open
Abstract
Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.
Collapse
Affiliation(s)
- Moses Chapa Kiti
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, 80108, Kenya
| | - Alessia Melegaro
- Department of Social and Political Sciences, Bocconi University, Milan, Italy
| | - Ciro Cattuto
- Data Science Laboratory, Institute for Scientific Interchange Foundation, Turin, Italy
| | - David James Nokes
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, 80108, Kenya.,Zeeman Institute of Systems Biology and Infectious Disease Research, University of Warwick, Coventry, UK.,School of Life Sciences, University of Warwick, Coventry, UK
| |
Collapse
|
14
|
Potter GE, Wong J, Sugimoto J, Diallo A, Victor JC, Neuzil K, Halloran ME. Networks of face-to-face social contacts in Niakhar, Senegal. PLoS One 2019; 14:e0220443. [PMID: 31386686 PMCID: PMC6684077 DOI: 10.1371/journal.pone.0220443] [Citation(s) in RCA: 6] [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: 09/25/2018] [Accepted: 07/15/2019] [Indexed: 11/30/2022] Open
Abstract
We present the first analysis of face-to-face contact network data from Niakhar, Senegal. Participants in a cluster-randomized influenza vaccine trial were interviewed about their contact patterns when they reported symptoms during their weekly household surveillance visit. We employ a negative binomial model to estimate effects of covariates on contact degree. We estimate the mean contact degree for asymptomatic Niakhar residents to be 16.5 (95% C.I. 14.3, 18.7) in the morning and 14.8 in the afternoon (95% C.I. 12.7, 16.9). We estimate that symptomatic people make 10% fewer contacts than asymptomatic people (95% C.I. 5%, 16%; p = 0.006), and those aged 0-5 make 33% fewer contacts than adults (95% C.I. 29%, 37%; p < 0.001). By explicitly modelling the partial rounding pattern observed in our data, we make inference for both the underlying (true) distribution of contacts as well as for the reported distribution. We created an estimator for homophily by compound (household) membership and estimate that 48% of contacts by symptomatic people are made to their own compound members in the morning (95% CI, 45%, 52%) and 60% in the afternoon/evening (95% CI, 56%, 64%). We did not find a significant effect of symptom status on compound homophily. We compare our findings to those from other countries and make design recommendations for future surveys.
Collapse
Affiliation(s)
- Gail E. Potter
- The Emmes Company, Rockville, MD, United States of America
- California Polytechnic State University, San Luis Obispo, CA, United States of America
| | - Jimmy Wong
- California Polytechnic State University, San Luis Obispo, CA, United States of America
| | - Jonathan Sugimoto
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Aldiouma Diallo
- Institut de Recherche pour le Développement, Niakhar, Senegal
| | | | - Kathleen Neuzil
- University of Maryland Center for Vaccine Development, Baltimore, MD, United States of America
| | - M. Elizabeth Halloran
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| |
Collapse
|
15
|
Kiti MC, Melegaro A, Cattuto C, Nokes DJ. Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors. Wellcome Open Res 2019; 4:84. [DOI: 10.12688/wellcomeopenres.15268.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2019] [Indexed: 11/20/2022] Open
Abstract
Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.
Collapse
|
16
|
Soudani N, Caniza MA, Assaf-Casals A, Shaker R, Lteif M, Su Y, Tang L, Akel I, Muwakkit S, Chmaisse A, Homsi M, Dbaibo G, Zaraket H. Prevalence and characteristics of acute respiratory virus infections in pediatric cancer patients. J Med Virol 2019; 91:1191-1201. [PMID: 30763464 PMCID: PMC7166696 DOI: 10.1002/jmv.25432] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 01/30/2019] [Accepted: 02/12/2019] [Indexed: 01/09/2023]
Abstract
Background Patients with pediatric cancer have a higher risk of morbidity and mortality because of respiratory viral infections than other patient populations. Objectives To investigate the causative viruses of respiratory infections and their burden among patients with pediatric cancer in Lebanon. Study design Nasopharyngeal swabs along with clinical and demographic data were collected from patients with pediatric cancer presenting febrile episodes with upper respiratory tract symptoms. Total nucleic acid was extracted from specimens followed by the real‐time PCR analysis targeting 14 respiratory viruses to estimate the frequency of infections. Results We obtained 89 nasopharyngeal swabs from patients with pediatric cancer (mean age, 5.8 ± 4.2 years). Real‐time PCR confirmed viral infection in 77 swabs (86.5%). Among these, 151 respiratory viruses were detected. Several viruses cocirculated within the same period; respiratory syncytial virus (RSV) being the most common (45.45%), followed by parainfluenza virus (PIV; 26%), influenza type B (26%), human metapneumovirus (24.6%), and human coronavirus (HCoV; 24.6%). Coinfections were detected in 55% of the subjects, and most of them involved RSV with one or more other viruses. A strong correlation was found between PIV, Flu (influenza of any type), RSV, and HCoV with the incidence of coinfections. RSV was associated with lower respiratory tract infections, nasal congestion, bronchitis, and bacteremia. HCoV was associated with bronchiolitis; rhinovirus was associated with hospital admission. Conclusion Patients with pediatric cancer have a high burden of respiratory viral infections and a high incidence of coinfections. Molecular diagnostics can improve management of febrile episodes and reduce antibiotic use. Respiratory viruses are leading cause of ARTI in pediatric cancer patients. Coinfections are common among febrile pediatric cancer patients. RSV was the most common in mono‐ and coinfections among pediatric cancer patients. RSV, PIV, Flu, HCoV are associated with coinfections. Molecular diagnostics permit rapid and sensitive diagnostics and limit antibiotic abuse.
Collapse
Affiliation(s)
- Nadia Soudani
- Department of Experimental Pathology, Immunology and Microbiology, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Department of Biology, Faculty of Sciences, EDST, Lebanese University, Lebanon
| | - Miguela A Caniza
- Department of Infectious Diseases, St Jude Children's Research Hospital, Memphis, Tennessee.,Department of Global Pediatric Medicine, St Jude Children's Research Hospital, Memphis, Tennessee
| | - Aia Assaf-Casals
- Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Department of Pediatrics and Adolescent Medicine, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| | - Rouba Shaker
- Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Department of Pediatrics and Adolescent Medicine, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| | - Mireille Lteif
- Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Department of Pediatrics and Adolescent Medicine, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| | - Yin Su
- Department of Biostatistics, St Jude Children's Research Hospital, Memphis, Tennessee
| | - Li Tang
- Department of Biostatistics, St Jude Children's Research Hospital, Memphis, Tennessee
| | - Imad Akel
- Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Department of Pediatrics and Adolescent Medicine, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| | - Samar Muwakkit
- Department of Pediatrics and Adolescent Medicine, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Children's Cancer Center of Lebanon, American University of Beirut, Beirut, Lebanon
| | - Ahmad Chmaisse
- Department of Experimental Pathology, Immunology and Microbiology, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| | - Maysam Homsi
- Department of Global Pediatric Medicine, St Jude Children's Research Hospital, Memphis, Tennessee
| | - Ghassan Dbaibo
- Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Department of Pediatrics and Adolescent Medicine, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| | - Hassan Zaraket
- Department of Experimental Pathology, Immunology and Microbiology, American University of Beirut Faculty of Medicine, Beirut, Lebanon.,Center for Infectious Diseases Research, American University of Beirut Faculty of Medicine, Beirut, Lebanon
| |
Collapse
|
17
|
Jonsson J, Stein M, Johansson G, Bodin T, Strömdahl S. A performance assessment of web-based respondent driven sampling among workers with precarious employment in Sweden. PLoS One 2019; 14:e0210183. [PMID: 30629661 PMCID: PMC6328181 DOI: 10.1371/journal.pone.0210183] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 12/18/2018] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES Precarious employment (PE) is a social determinant of poor health of workers. However, this population usually lack a sampling frame, making it challenging to identify the characteristics of this group. Web-based respondent driven sampling (webRDS) recruits individuals online through the social network and can provide population estimates. This study aims to assess the performance of webRDS in a population of workers with PE. METHOD WebRDS was used for recruitment and data collection in the PRecarious EMployment In Stockholm (PREMIS) study. Cross-sectional questionnaire data was collected between November 2016 and May 2017. Eligible participants were living and/or working in Stockholm County, 18-65 years old, had a personal identification number and were currently employed. WebRDS performance was assessed by the total sample size, length of recruitment chains, sample composition, sample proportions and estimated RDSII population proportions with confidence intervals. RESULTS The webRDS process resulted in a sample of 358 recruits and a total sample of 415 participants, recruited over 1-15 waves. Of the participating seeds and recruits, 60% and 48%, respectively, successfully recruited at least one peer. The sample composition stabilized for all variables assessed. The sample proportions and RDSII estimates differed by 1-8% and the confidence intervals included the sample proportions for all variables except one. CONCLUSIONS WebRDS successfully recruited a sufficient sample of workers with precarious employment from which population estimates could be made. Future studies should consider implementing webRDS on a national level in order to further study this population.
Collapse
Affiliation(s)
- Johanna Jonsson
- Institute of Environmental Medicine, Unit of Occupational Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Mart Stein
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Gun Johansson
- Institute of Environmental Medicine, Unit of Occupational Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Theo Bodin
- Institute of Environmental Medicine, Unit of Occupational Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Susanne Strömdahl
- Department of Public Health, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| |
Collapse
|
18
|
Stein ML, Buskens V, van der Heijden PGM, van Steenbergen JE, Wong A, Bootsma MCJ, Kretzschmar MEE. A stochastic simulation model to study respondent-driven recruitment. PLoS One 2018; 13:e0207507. [PMID: 30440047 PMCID: PMC6237413 DOI: 10.1371/journal.pone.0207507] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 11/01/2018] [Indexed: 11/19/2022] Open
Abstract
Respondent-driven detection is a chain recruitment method used to sample contact persons of infected persons in order to enhance case finding. It starts with initial individuals, so-called seeds, who are invited for participation. Afterwards, seeds receive a fixed number of coupons to invite individuals with whom they had contact during a specific time period. Recruitees are then asked to do the same, resulting in successive waves of contact persons who are connected in one recruitment tree. However, often the majority of participants fail to invite others, or invitees do not accept an invitation, and recruitment stops after several waves. A mathematical model can help to analyse how various factors influence peer recruitment and to understand under which circumstances sustainable recruitment is possible. We implemented a stochastic simulation model, where parameters were suggested by empirical data from an online survey, to determine the thresholds for obtaining large recruitment trees and the number of waves needed to reach a steady state in the sample composition for individual characteristics. We also examined the relationship between mean and variance of the number of invitations sent out by participants and the probability of obtaining a large recruitment tree. Our main finding is that a situation where participants send out any number of coupons between one and the maximum number is more effective in reaching large recruitment trees, compared to a situation where the majority of participants does not send out any invitations and a smaller group sends out the maximum number of invitations. The presented model is a helpful tool that can assist public health professionals in preparing research and contact tracing using online respondent-driven detection. In particular, it can provide information on the required minimum number of successfully sent invitations to reach large recruitment trees, a certain sample composition or certain number of waves.
Collapse
Affiliation(s)
- Mart L. Stein
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Utrecht, The Netherlands
| | - Vincent Buskens
- Department of Sociology, Faculty of Social and Behavioural Sciences, University Utrecht, Utrecht, The Netherlands
| | - Peter G. M. van der Heijden
- Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, University Utrecht, Utrecht, The Netherlands
- Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, United Kingdom
| | - Jim E. van Steenbergen
- National Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Utrecht, The Netherlands
- Centre of Infectious Diseases, Leiden University Medical Centre, Leiden, The Netherlands
| | - Albert Wong
- Department of Statistics, Informatics and Mathematical Modelling, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Martin C. J. Bootsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Mathematics, Faculty of Sciences, Utrecht University, Utrecht, The Netherlands
| | - Mirjam E. E. Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Centre for Infectious, Disease Control, RIVM, Bilthoven, Utrecht, The Netherlands
| |
Collapse
|
19
|
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.
Collapse
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.
| |
Collapse
|
20
|
Crawford FW, Aronow PM, Zeng L, Li J. Identification of Homophily and Preferential Recruitment in Respondent-Driven Sampling. Am J Epidemiol 2018; 187:153-160. [PMID: 28605424 PMCID: PMC5860647 DOI: 10.1093/aje/kwx208] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 03/08/2017] [Accepted: 03/09/2017] [Indexed: 11/12/2022] Open
Abstract
Respondent-driven sampling (RDS) is a link-tracing procedure used in epidemiologic research on hidden or hard-to-reach populations in which subjects recruit others via their social networks. Estimates from RDS studies may have poor statistical properties due to statistical dependence in sampled subjects' traits. Two distinct mechanisms account for dependence in an RDS study: homophily, the tendency for individuals to share social ties with others exhibiting similar characteristics, and preferential recruitment, in which recruiters do not recruit uniformly at random from their network alters. The different effects of network homophily and preferential recruitment in RDS studies have been a source of confusion and controversy in methodological and empirical research in epidemiology. In this work, we gave formal definitions of homophily and preferential recruitment and showed that neither is identified in typical RDS studies. We derived nonparametric identification regions for homophily and preferential recruitment and showed that these parameters were not identified unless the network took a degenerate form. The results indicated that claims of homophily or recruitment bias measured from empirical RDS studies may not be credible. We applied our identification results to a study involving both a network census and RDS on a population of injection drug users in Hartford, Connecticut (2012-2013).
Collapse
Affiliation(s)
- Forrest W Crawford
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut
- Yale School of Management, New Haven, Connecticut
| | - Peter M Aronow
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
- Department of Political Science, Yale University, New Haven, Connecticut
- Yale School of Management, New Haven, Connecticut
| | - Li Zeng
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
| | - Jianghong Li
- Institute for Community Research, Hartford, Connecticut
| |
Collapse
|
21
|
Development of prediction models for upper and lower respiratory and gastrointestinal tract infections using social network parameters in middle-aged and older persons -The Maastricht Study. Epidemiol Infect 2017; 146:533-543. [PMID: 28946936 PMCID: PMC5892426 DOI: 10.1017/s0950268817002187] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
The ability to predict upper respiratory infections (URI), lower respiratory infections (LRI), and gastrointestinal tract infections (GI) in independently living older persons would greatly benefit population and individual health. Social network parameters have so far not been included in prediction models. Data were obtained from The Maastricht Study, a population-based cohort study (N = 3074, mean age (±s.d.) 59.8 ± 8.3, 48.8% women). We used multivariable logistic regression analysis to develop prediction models for self-reported symptomatic URI, LRI, and GI (past 2 months). We determined performance of the models by quantifying measures of discriminative ability and calibration. Overall, 953 individuals (31.0%) reported URI, 349 (11.4%) LRI, and 380 (12.4%) GI. The area under the curve was 64.7% (95% confidence interval (CI) 62.6-66.8%) for URI, 71.1% (95% CI 68.4-73.8) for LRI, and 64.2% (95% CI 61.3-67.1%) for GI. All models had good calibration (based on visual inspection of calibration plot, and Hosmer-Lemeshow goodness-of-fit test). Social network parameters were strong predictors for URI, LRI, and GI. Using social network parameters in prediction models for URI, LRI, and GI seems highly promising. Such parameters may be used as potential determinants that can be addressed in a practical intervention in older persons, or in a predictive tool to compute an individual's probability of infections.
Collapse
|
22
|
Melegaro A, Del Fava E, Poletti P, Merler S, Nyamukapa C, Williams J, Gregson S, Manfredi P. Social Contact Structures and Time Use Patterns in the Manicaland Province of Zimbabwe. PLoS One 2017; 12:e0170459. [PMID: 28099479 PMCID: PMC5242544 DOI: 10.1371/journal.pone.0170459] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 01/05/2017] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Patterns of person-to-person contacts relevant for infectious diseases transmission are still poorly quantified in Sub-Saharan Africa (SSA), where socio-demographic structures and behavioral attitudes are expected to be different from those of more developed countries. METHODS AND FINDINGS We conducted a diary-based survey on daily contacts and time-use of individuals of different ages in one rural and one peri-urban site of Manicaland, Zimbabwe. A total of 2,490 diaries were collected and used to derive age-structured contact matrices, to analyze time spent by individuals in different settings, and to identify the key determinants of individuals' mixing patterns. Overall 10.8 contacts per person/day were reported, with a significant difference between the peri-urban and the rural site (11.6 versus 10.2). A strong age-assortativeness characterized contacts of school-aged children, whereas the high proportion of extended families and the young population age-structure led to a significant intergenerational mixing at older ages. Individuals spent on average 67% of daytime at home, 2% at work, and 9% at school. Active participation in school and work resulted the key drivers of the number of contacts and, similarly, household size, class size, and time spent at work influenced the number of home, school, and work contacts, respectively. We found that the heterogeneous nature of home contacts is critical for an epidemic transmission chain. In particular, our results suggest that, during the initial phase of an epidemic, about 50% of infections are expected to occur among individuals younger than 12 years and less than 20% among individuals older than 35 years. CONCLUSIONS With the current work, we have gathered data and information on the ways through which individuals in SSA interact, and on the factors that mostly facilitate this interaction. Monitoring these processes is critical to realistically predict the effects of interventions on infectious diseases dynamics.
Collapse
Affiliation(s)
- Alessia Melegaro
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy
- Department of Policy Analysis and Public Management, Bocconi University, Milano, Italy
| | - Emanuele Del Fava
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy
| | - Piero Poletti
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy
- Center for Information Technology, Bruno Kessler Foundation, Trento, Italy
| | - Stefano Merler
- Center for Information Technology, Bruno Kessler Foundation, Trento, Italy
| | - Constance Nyamukapa
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Biomedical Research and Training Institute, Harare, Zimbabwe
| | - John Williams
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Simon Gregson
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Biomedical Research and Training Institute, Harare, Zimbabwe
| | - Piero Manfredi
- Department of Economics and Management, University of Pisa, Pisa, Italy
| |
Collapse
|
23
|
Abstract
Respondent-driven sampling (RDS) is a chain-referral method for sampling members of hidden or hard-to-reach populations, such as sex workers, homeless people, or drug users, via their social networks. Most methodological work on RDS has focused on inference of population means under the assumption that subjects' network degree determines their probability of being sampled. Criticism of existing estimators is usually focused on missing data: the underlying network is only partially observed, so it is difficult to determine correct sampling probabilities. In this article, the author shows that data collected in ordinary RDS studies contain information about the structure of the respondents' social network. The author constructs a continuous-time model of RDS recruitment that incorporates the time series of recruitment events, the pattern of coupon use, and the network degrees of sampled subjects. Together, the observed data and the recruitment model place a well-defined probability distribution on the recruitment-induced subgraph of respondents. The author shows that this distribution can be interpreted as an exponential random graph model and develops a computationally efficient method for estimating the hidden graph. The author validates the method using simulated data and applies the technique to an RDS study of injection drug users in St. Petersburg, Russia.
Collapse
|
24
|
Kiti MC, Tizzoni M, Kinyanjui TM, Koech DC, Munywoki PK, Meriac M, Cappa L, Panisson A, Barrat A, Cattuto C, Nokes DJ. Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors. EPJ DATA SCIENCE 2016; 5:21. [PMID: 27471661 PMCID: PMC4944592 DOI: 10.1140/epjds/s13688-016-0084-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Accepted: 06/06/2016] [Indexed: 06/06/2023]
Abstract
UNLABELLED Close proximity interactions between individuals influence how infections spread. Quantifying close contacts in developing world settings, where such data is sparse yet disease burden is high, can provide insights into the design of intervention strategies such as vaccination. Recent technological advances have enabled collection of time-resolved face-to-face human contact data using radio frequency proximity sensors. The acceptability and practicalities of using proximity devices within the developing country setting have not been investigated. We present and analyse data arising from a prospective study of 5 households in rural Kenya, followed through 3 consecutive days. Pre-study focus group discussions with key community groups were held. All residents of selected households carried wearable proximity sensors to collect data on their close (<1.5 metres) interactions. Data collection for residents of three of the 5 households was contemporaneous. Contact matrices and temporal networks for 75 individuals are defined and mixing patterns by age and time of day in household contacts determined. Our study demonstrates the stability of numbers and durations of contacts across days. The contact durations followed a broad distribution consistent with data from other settings. Contacts within households occur mainly among children and between children and adults, and are characterised by daily regular peaks in the morning, midday and evening. Inter-household contacts are between adults and more sporadic when measured over several days. Community feedback indicated privacy as a major concern especially regarding perceptions of non-participants, and that community acceptability required thorough explanation of study tools and procedures. Our results show for a low resource setting how wearable proximity sensors can be used to objectively collect high-resolution temporal data without direct supervision. The methodology appears acceptable in this population following adequate community engagement on study procedures. A target for future investigation is to determine the difference in contact networks within versus between households. We suggest that the results from this study may be used in the design of future studies using similar electronic devices targeting communities, including households and schools, in the developing world context. ELECTRONIC SUPPLEMENTARY MATERIAL The online version of this article (doi:10.1140/epjds/s13688-016-0084-2) contains supplementary material.
Collapse
Affiliation(s)
- Moses C Kiti
- />KEMRI - Wellcome Trust Research Programme, Kilifi, Kenya
| | - Michele Tizzoni
- />Data Science Laboratory, ISI Foundation, Via Alassio 11/c, Torino, 10126 Italy
| | - Timothy M Kinyanjui
- />KEMRI - Wellcome Trust Research Programme, Kilifi, Kenya
- />School of Mathematics, The University of Manchester, Manchester, UK
| | | | | | | | - Luca Cappa
- />Data Science Laboratory, ISI Foundation, Via Alassio 11/c, Torino, 10126 Italy
| | - André Panisson
- />Data Science Laboratory, ISI Foundation, Via Alassio 11/c, Torino, 10126 Italy
| | - Alain Barrat
- />Data Science Laboratory, ISI Foundation, Via Alassio 11/c, Torino, 10126 Italy
- />Aix-Marseille Université, Université de Toulon, CNRS, CPT, UMR 7332, Marseille, 13288 France
| | - Ciro Cattuto
- />Data Science Laboratory, ISI Foundation, Via Alassio 11/c, Torino, 10126 Italy
| | - D James Nokes
- />KEMRI - Wellcome Trust Research Programme, Kilifi, Kenya
- />School of Life Sciences and WIDER, University of Warwick, Coventry, UK
| |
Collapse
|
25
|
Stein ML, van der Heijden PGM, Buskens V, van Steenbergen JE, Bengtsson L, Koppeschaar CE, Thorson A, Kretzschmar MEE. Tracking social contact networks with online respondent-driven detection: who recruits whom? BMC Infect Dis 2015; 15:522. [PMID: 26573658 PMCID: PMC4647802 DOI: 10.1186/s12879-015-1250-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Accepted: 10/28/2015] [Indexed: 01/13/2023] Open
Abstract
Background Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven detection can provide relevant epidemiological data on numbers of contact persons and dynamics of contacts between pairs of individuals. We aimed to analyse contact networks with respect to sociodemographic and geographical characteristics, vaccine-induced immunity and self-reported symptoms. Methods In 2014, volunteers from two large participatory surveillance panels in the Netherlands and Belgium were invited for a survey. Participants were asked to record numbers of contacts at different locations and self-reported influenza-like-illness symptoms, and to invite 4 individuals they had met face to face in the preceding 2 weeks. We calculated correlations between linked individuals to investigate mixing patterns. Results In total 1560 individuals completed the survey who reported in total 30591 contact persons; 488 recruiter-recruit pairs were analysed. Recruitment was assortative by age, education, household size, influenza vaccination status and sentiments, indicating that participants tended to recruit contact persons similar to themselves. We also found assortative recruitment by symptoms, reaffirming our objective of sampling contact persons whom a participant may infect or by whom a participant may get infected in case of an outbreak. Recruitment was random by sex and numbers of contact persons. Relationships between pairs were influenced by the spatial distribution of peer recruitment. Conclusions Although complex mechanisms influence online peer recruitment, the observed statistical relationships reflected the observed contact network patterns in the general population relevant for the transmission of respiratory pathogens. This provides useful and innovative input for predictive epidemic models relying on network information. Electronic supplementary material The online version of this article (doi:10.1186/s12879-015-1250-z) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Mart L Stein
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. .,Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - Peter G M van der Heijden
- Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, University Utrecht, Utrecht, The Netherlands. .,Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, UK.
| | - Vincent Buskens
- Department of Sociology, Faculty of Social and Behavioural Sciences, University Utrecht, Utrecht, The Netherlands.
| | - Jim E van Steenbergen
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. .,Centre of Infectious Diseases, Leiden University Medical Centre, Leiden, The Netherlands.
| | - Linus Bengtsson
- Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden. .,Flowminder Foundation, Stockholm, Sweden.
| | | | - Anna Thorson
- Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden.
| | - Mirjam E E Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. .,Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| |
Collapse
|
26
|
Strömdahl S, Lu X, Bengtsson L, Liljeros F, Thorson A. Implementation of Web-Based Respondent Driven Sampling among Men Who Have Sex with Men in Sweden. PLoS One 2015; 10:e0138599. [PMID: 26426802 PMCID: PMC4591333 DOI: 10.1371/journal.pone.0138599] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 08/31/2015] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Respondent driven sampling (RDS) was designed to study 'hidden' populations, for which there are no available sampling frame. RDS has been shown to recruit far into social networks of the study population and achieve unbiased estimates when certain assumptions are fulfilled. Web-based respondent driven sampling (WebRDS) has been implemented among MSM in Vietnam and produced a sufficient sample of MSM. In order to see if WebRDS could work in a 'hidden' population in a high-income setting, we performed a WebRDS among MSM in Sweden to study a sensitive topic, sexual risk behaviour for HIV/STI and Internet use. METHODS A cross-sectional survey was implemented between July 11, 2012 and January 21, 2013 by using a WebRDS software. Men, fifteen years old or above, who reported having ever had sex with another man were included. The web-survey explored sociodemographics, sexual risk behaviour for HIV/STI and Internet use. RESULTS The WebRDS process created a sample of 123 eligible respondents. The mean age among participants was 32 years old. All respondents reported having had unprotected anal intercourse (UAI) with at least one regular and one casual sex partner during the last 12 months. On average participants reported having had UAI with three casual sexual partners and in total having had seven casual sex partners during the last 12 months. CONCLUSION The WebRDS produced a sample of Internet-using MSM in Sweden who all reported sexual risk behaviour for HIV/STI during the last 12 months. It holds promise for future online studies among MSM and a possibility to reach MSM at risk for HIV/STI with interventions or information. Some challenges were found including short recruitment chains, and further research need to address how to optimize WebRDS online recruitment methods in high income settings.
Collapse
Affiliation(s)
- Susanne Strömdahl
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Xin Lu
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
- College of Information System and Management, National University of Defense Technology, Changsha, China
| | - Linus Bengtsson
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Liljeros
- Department of Sociology, Stockholm University, Stockholm, Sweden
| | - Anna Thorson
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
27
|
A Web-Based Respondent Driven Sampling Pilot Targeting Young People at Risk for Chlamydia Trachomatis in Social and Sexual Networks with Testing: A Use Evaluation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2015; 12:9889-906. [PMID: 26308015 PMCID: PMC4555318 DOI: 10.3390/ijerph120809889] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 08/07/2015] [Accepted: 08/13/2015] [Indexed: 11/17/2022]
Abstract
Background: With the aim of targeting high-risk hidden heterosexual young people for Chlamydia trachomatis (CT) testing, an innovative web-based screening strategy using Respondent Driven Sampling (RDS) and home-based CT testing, was developed, piloted and evaluated. Methods: Two STI clinic nurses encouraged 37 CT positive heterosexual young people (aged 16–25 years), called index clients, to recruit peers from their social and sexual networks using the web-based screening strategy. Eligible peers (young, living in the study area) could request a home-based CT test and recruit other peers. Results: Twelve (40%) index clients recruited 35 peers. Two of these peers recruited other peers (n = 7). In total, 35 recruited peers were eligible for participation; ten of them (29%) requested a test and eight tested. Seven tested for the first time and one (13%) was positive. Most peers were female friends (80%). Nurses were positive about using the strategy. Conclusions: The screening strategy is feasible for targeting the hidden social network. However, uptake among men and recruitment of sex-partners is low and RDS stopped early. Future studies are needed to explore the sustainability, cost-effectiveness, and impact of strategies that target people at risk who are not effectively reached by regular health care.
Collapse
|
28
|
Stein ML, van Steenbergen JE, Buskens V, van der Heijden PGM, Koppeschaar CE, Bengtsson L, Thorson A, Kretzschmar MEE. Enhancing Syndromic Surveillance With Online Respondent-Driven Detection. Am J Public Health 2015; 105:e90-7. [PMID: 26066940 DOI: 10.2105/ajph.2015.302717] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
OBJECTIVES We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants. METHODS In 2014, volunteers from 2 large panels in the Netherlands were invited to complete a survey focusing on symptoms of upper respiratory tract infections and to invite 4 individuals they had met in the preceding 2 weeks to take part in the study. We compared sociodemographic characteristics among panel participants, individuals who volunteered for our survey, and individuals recruited via respondent-driven detection. RESULTS Starting from 1015 panel members, the survey spread through all provinces of the Netherlands and all age groups in 83 days. A total of 433 individuals completed the survey via peer recruitment. Participants who reported symptoms were 6.1% (95% confidence interval = 5.4, 6.9) more likely to invite contact persons than were participants who did not report symptoms. Participants with symptoms invited more symptomatic recruits to take part than did participants without symptoms. CONCLUSIONS Our findings suggest that online respondent-driven detection can enhance identification of symptomatic patients by making use of individuals' local social networks.
Collapse
Affiliation(s)
- Mart L Stein
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Jim E van Steenbergen
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Vincent Buskens
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Peter G M van der Heijden
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Carl E Koppeschaar
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Linus Bengtsson
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Anna Thorson
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| | - Mirjam E E Kretzschmar
- Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|