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Osei I, Mendy E, van Zandvoort K, Jobe O, Sarwar G, Wutor BM, Flasche S, Mohammed NI, Bruce J, Greenwood B, Mackenzie GA. Directly observed social contact patterns among school children in rural Gambia. Epidemics 2024; 49:100790. [PMID: 39270441 DOI: 10.1016/j.epidem.2024.100790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Revised: 09/03/2024] [Accepted: 09/04/2024] [Indexed: 09/15/2024] Open
Abstract
INTRODUCTION School-aged children play a major role in the transmission of many respiratory pathogens due to high rate of close contacts in schools. The validity and accuracy of proxy-reported contact data may be limited, particularly for children when attending school. We observed social contacts within schools and assessed the accuracy of proxy-reported versus observed physical contact data among students in rural Gambia. METHODS We enrolled school children who had also been recruited to a survey of Streptococcus pneumoniae carriage and social contacts. We visited participants at school and observed their contact patterns within and outside the classroom for two hours. We recorded the contact type, gender and approximate age of the contactee, and class size. We calculated age-stratified contact matrices to determine in-school contact patterns. We compared proxy-reported estimated physical contacts for the subset of participants (18 %) randomised to be observed on the same day for which the parent or caregiver reported the school contacts. RESULTS We recorded 3822 contacts for 219 participants from 114 schools. The median number of contacts was 15 (IQR: 11-20). Contact patterns were strongly age-assortative, and mainly involved physical touch (67.5 %). Those aged 5-9 years had the highest mean number of contacts [19.0 (95 %CI: 16.7-21.3)] while the ≥ 15-year age group had fewer contacts [12.8 (95 %CI: 10.9-14.7)]. Forty (18 %) participants had their school-observed contact data collected on the same day as their caregiver reported their estimated physical contacts at school; only 22.5 % had agreement within ±2 contacts between the observed and reported contacts. Fifty-eight percent of proxy-reported contacts were under-estimates. CONCLUSIONS Social contact rates observed among pupils at schools in rural Gambia were high, strongly age-assortative, and physical. Reporting of school contacts by proxies may underestimate the effect of school-age children in modelling studies of transmission of infections. New approaches are needed to quantify contacts within schools.
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Affiliation(s)
- Isaac Osei
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia; Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
| | - Emmanuel Mendy
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia
| | - Kevin van Zandvoort
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Olimatou Jobe
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia
| | - Golam Sarwar
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia
| | - Baleng Mahama Wutor
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia
| | - Stefan Flasche
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre of Global Health, Charite - Universitätsmedizin, Berlin, Germany
| | - Nuredin I Mohammed
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia
| | - Jane Bruce
- Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Brian Greenwood
- Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Grant A Mackenzie
- Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine, the Gambia; Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK; Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, University of Melbourne, Australia
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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.
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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
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Hoang TV, Coletti P, Kifle YW, Kerckhove KV, Vercruysse S, Willem L, Beutels P, Hens N. Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011. BMC Infect Dis 2021; 21:274. [PMID: 33736606 PMCID: PMC7971398 DOI: 10.1186/s12879-021-05949-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 03/02/2021] [Indexed: 01/10/2023] Open
Abstract
Background In 2010-2011, we conducted a social contact survey in Flanders, Belgium, aimed at improving and extending the design of the first social contact survey conducted in Belgium in 2006. This second social contact survey aimed to enable, for the first time, the estimation of social mixing patterns for an age range of 0 to 99 years and the investigation of whether contact rates remain stable over this 5-year time period. Methods Different data mining techniques are used to explore the data, and the age-specific number of social contacts and the age-specific contact rates are modelled using a generalized additive models for location, scale and shape (GAMLSS) model. We compare different matrices using assortativeness measures. The relative change in the basic reproduction number (R0) and the ratio of relative incidences with 95% bootstrap confidence intervals (BCI) are employed to investigate and quantify the impact on epidemic spread due to differences in sex, day of the week, holiday vs. regular periods and changes in mixing patterns over the 5-year time gap between the 2006 and 2010-2011 surveys. Finally, we compare the fit of the contact matrices in 2006 and 2010-2011 to Varicella serological data. Results All estimated contact patterns featured strong homophily in age and sex, especially for small children and adolescents. A 30% (95% BCI [17%; 37%]) and 29% (95% BCI [14%; 40%]) reduction in R0 was observed for weekend versus weekdays and for holiday versus regular periods, respectively. Significantly more interactions between people aged 60+ years and their grandchildren were observed on holiday and weekend days than on regular weekdays. Comparing contact patterns using different methods did not show any substantial differences over the 5-year time period under study. Conclusions The second social contact survey in Flanders, Belgium, endorses the findings of its 2006 predecessor and adds important information on the social mixing patterns of people older than 60 years of age. Based on this analysis, the mixing patterns of people older than 60 years exhibit considerable heterogeneity, and overall, the comparison of the two surveys shows that social contact rates can be assumed stable in Flanders over a time span of 5 years. Supplementary Information The online version contains supplementary material available at (10.1186/s12879-021-05949-4).
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Affiliation(s)
- Thang Van Hoang
- I-Biostat, Data Science Institute, Hasselt University, Martelarenlaan 42, Hasselt, 3500, Belgium.
| | - Pietro Coletti
- I-Biostat, Data Science Institute, Hasselt University, Martelarenlaan 42, Hasselt, 3500, Belgium
| | - Yimer Wasihun Kifle
- The Janssen Pharmaceutical Companies of Johnson & Johnson, Antwerpen, Belgium
| | - Kim Van Kerckhove
- I-Biostat, Data Science Institute, Hasselt University, Martelarenlaan 42, Hasselt, 3500, Belgium
| | - Sarah Vercruysse
- I-Biostat, Data Science Institute, Hasselt University, Martelarenlaan 42, Hasselt, 3500, Belgium
| | - Lander Willem
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Diseases Institute, University of Antwerp, Universiteitsplein 1, Antwerp, 2610, Belgium
| | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Diseases Institute, University of Antwerp, Universiteitsplein 1, Antwerp, 2610, Belgium.,School of Public health and Community Medicine, University of New South Wales, Sydney, 2052, Australia
| | - Niel Hens
- I-Biostat, Data Science Institute, Hasselt University, Martelarenlaan 42, Hasselt, 3500, Belgium.,Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Diseases Institute, University of Antwerp, Universiteitsplein 1, Antwerp, 2610, Belgium
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Abdalrouf A, Ibrahim A, Abdulmogith M, Yousif A, Al Okeil N, Al Otaibi A, Albattal S, AlAbood A, Maher M, AlRasheed A, Kofi M. The effectiveness of visual triaging and testing of suspected COVID-19 cases in primary care setting in Saudi Arabia. J Family Med Prim Care 2021; 10:4277-4285. [PMID: 35136802 PMCID: PMC8797076 DOI: 10.4103/jfmpc.jfmpc_652_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 08/14/2021] [Accepted: 08/30/2021] [Indexed: 01/19/2023] Open
Abstract
Introduction: Asymptomatic individuals could be a source of spreading the infection, especially in their households. Triaging and testing an individual for coronavirus disease (COVID-19) infection rely on the criteria included in the adopted triaging instrument, and adopted case definition of a suspected case. They both may need to be reviewed and modified to make them more effective in making the right decision. Methods: A cross-sectional study was used to find out the effectiveness of triaging instrument and the case definition used in the fever clinic (FC) in one of our primary care centers. The data of 630 randomly selected participants who were tested in our center between April 12 and August 12 2020 were analyzed. Results: About 36.8% of the 630 tested participants were positive for COVID-19. Symptomatic patients were 3.93 (95% CI; 2.58, 5.98; P < 0.001) times more likely to test positive than asymptomatic ones. The participants with a history of contact with a COVID-19 confirmed case were 1.47 (95% CI; 1.03, 2.10; P = 0.032) times more likely to test positive compared to those without such history. Symptomatic with and without history of contact were 8.40 (95% CI; 3.23, 21.86; P < 0.001) and 4.91 (95% CI; 1.84, 13.09; P < 0.001) times more likely to test positive compared to asymptomatic contact, respectively. Moreover, patients with comorbidity were also 1.85 (95% CI; 1.31, 2.60; P < 0.001) times more likely to test positive than healthy ones. The mean of the number of the households, and the mean of the number of households tested positive significantly exceeded the means of those tested negative by 1.03 (95% CI; 0.48, 1.57; P < 0.001), and 0.98 (95% CI; 0.68, 1.28; P < 0.001), respectively. From the studied triaging items only symptoms, comorbidities, and the number of households tested positive were independently associated with testing positive. Moreover, from studied symptoms, only fever, cough, myalgia, and loss of taste and smell were independently associated with testing positive. Finally, from the studied comorbidities, only diabetes mellitus was independently associated with testing positive. Conclusion: At the time of outbreak and pandemic, people get worried and need to be reassured, and contacts would then seek testing. However, resources including manpower, material, and money need to be protected and used wisely. Thus, the adoption of an evidence-based updated testing policy is crucially needed. Furthermore, early identification of the potential sources of the infection is also crucially needed to control the spreading of the infection.
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Chaw L, Koh WC, Jamaludin SA, Naing L, Alikhan MF, Wong J. Analysis of SARS-CoV-2 Transmission in Different Settings, Brunei. Emerg Infect Dis 2020; 26:2598-2606. [PMID: 33035448 PMCID: PMC7588541 DOI: 10.3201/eid2611.202263] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
We report the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across different settings in Brunei. An initial cluster of SARS-CoV-2 cases arose from 19 persons who had attended the Tablighi Jama’at gathering in Malaysia, resulting in 52 locally transmitted cases. The highest nonprimary attack rates (14.8%) were observed from a subsequent religious gathering in Brunei and in households of attendees (10.6%). Household attack rates from symptomatic case-patients were higher (14.4%) than from asymptomatic (4.4%) or presymptomatic (6.1%) case-patients. Workplace and social settings had attack rates of <1%. Our analyses highlight that transmission of SARS-CoV-2 varies depending on environmental, behavioral, and host factors. We identify red flags for potential superspreading events, specifically densely populated gatherings with prolonged exposure in enclosed settings, persons with recent travel history to areas with active SARS-CoV-2 infections, and group behaviors. We propose differentiated testing strategies to account for differing transmission risk.
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Abstract
BACKGROUND Researchers increasingly use social contact data to inform models for infectious disease spread with the aim of guiding effective policies about disease prevention and control. In this article, we undertake a systematic review of the study design, statistical analyses, and outcomes of the many social contact surveys that have been published. METHODS We systematically searched PubMed and Web of Science for articles regarding social contact surveys. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines as closely as possible. RESULTS In total, we identified 64 social contact surveys, with more than 80% of the surveys conducted in high-income countries. Study settings included general population (58%), schools or universities (37%), and health care/conference/research institutes (5%). The largest number of studies did not focus on a specific age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective (45%) and prospective (41%) designs were used most often with 6% using both for comparison purposes. The definition of a contact varied among surveys, e.g., a nonphysical contact may require conversation, close proximity, or both. We identified age, time schedule (e.g., weekday/weekend), and household size as relevant determinants of contact patterns across a large number of studies. CONCLUSIONS We found that the overall features of the contact patterns were remarkably robust across several countries, and irrespective of the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, definition of contact), we could identify recommendations for future contact data surveys that may be used to facilitate comparison between studies.
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Munasinghe L, Asai Y, Nishiura H. Quantifying heterogeneous contact patterns in Japan: a social contact survey. Theor Biol Med Model 2019; 16:6. [PMID: 30890153 PMCID: PMC6425701 DOI: 10.1186/s12976-019-0102-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 03/05/2019] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Social contact surveys can greatly help in quantifying the heterogeneous patterns of infectious disease transmission. The present study aimed to conduct a contact survey in Japan, offering estimates of contact by age and location and validating a social contact matrix using a seroepidemiological dataset of influenza. METHODS An internet-based questionnaire survey was conducted, covering all 47 prefectures in Japan and including a total of 1476 households. The social contact matrix was quantified assuming reciprocity and using the maximum likelihood method. By imposing several parametric assumptions for the next-generation matrix, the empirical seroepidemiological data of influenza A (H1N1) 2009 was analysed and we estimated the basic reproduction number, R0. RESULTS In total, the reported number of contacts on weekdays was 10,682 whereas that on weekend days was 8867. Strong age-dependent assortativity was identified. Forty percent of weekday contacts took place at schools or workplaces, but that declined to 14% on weekends. Accounting for the age-dependent heterogeneity with the known social contact matrix, the minimum value of the Akaike information criterion was obtained and R0 was estimated at 1.45 (95% confidence interval: 1.42, 1.49). CONCLUSIONS Survey datasets will be useful for parameterizing the heterogeneous transmission model of various directly transmitted infectious diseases in Japan. Age-dependent assortativity, especially among children, along with numerous contacts in school settings on weekdays implies the potential effectiveness of school closure.
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Affiliation(s)
- Lankeshwara Munasinghe
- Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Sapporo, Japan
| | - Yusuke Asai
- Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Sapporo, Japan
| | - Hiroshi Nishiura
- Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Sapporo, Japan
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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.
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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
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Rattanaumpawan P, Boonyasiri A, Vong S, Thamlikitkul V. Systematic review of electronic surveillance of infectious diseases with emphasis on antimicrobial resistance surveillance in resource-limited settings. Am J Infect Control 2018; 46:139-146. [PMID: 29029814 DOI: 10.1016/j.ajic.2017.08.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 08/07/2017] [Accepted: 08/07/2017] [Indexed: 12/24/2022]
Abstract
BACKGROUND Electronic surveillance of infectious diseases involves rapidly collecting, collating, and analyzing vast amounts of data from interrelated multiple databases. Although many developed countries have invested in electronic surveillance for infectious diseases, the system still presents a challenge for resource-limited health care settings. METHODS We conducted a systematic review by performing a comprehensive literature search on MEDLINE (January 2000-December 2015) to identify studies relevant to electronic surveillance of infectious diseases. Study characteristics and results were extracted and systematically reviewed by 3 infectious disease physicians. RESULTS A total of 110 studies were included. Most surveillance systems were developed and implemented in high-income countries; less than one-quarter were conducted in low-or middle-income countries. Information technologies can be used to facilitate the process of obtaining laboratory, clinical, and pharmacologic data for the surveillance of infectious diseases, including antimicrobial resistance (AMR) infections. These novel systems require greater resources; however, we found that using electronic surveillance systems could result in shorter times to detect targeted infectious diseases and improvement of data collection. CONCLUSIONS This study highlights a lack of resources in areas where an effective, rapid surveillance system is most needed. The availability of information technology for the electronic surveillance of infectious diseases, including AMR infections, will facilitate the prevention and containment of such emerging infectious diseases.
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Affiliation(s)
- Pinyo Rattanaumpawan
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Adhiratha Boonyasiri
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Sirenda Vong
- World Health Organization Regional Office for South-East Asia, New Delhi, India
| | - Visanu Thamlikitkul
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
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Koppeschaar CE, Colizza V, Guerrisi C, Turbelin C, Duggan J, Edmunds WJ, Kjelsø C, Mexia R, Moreno Y, Meloni S, Paolotti D, Perrotta D, van Straten E, Franco AO. Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe. JMIR Public Health Surveill 2017; 3:e66. [PMID: 28928112 PMCID: PMC5627046 DOI: 10.2196/publichealth.7429] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 06/23/2017] [Accepted: 06/26/2017] [Indexed: 11/13/2022] Open
Abstract
Background The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries. Objective In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system. Methods Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone. Results In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time. Conclusions Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.
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Affiliation(s)
| | - Vittoria Colizza
- UPMC Univ Paris 06, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Sorbonne Universités, Paris, France
| | - Caroline Guerrisi
- UPMC Univ Paris 06, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Sorbonne Universités, Paris, France
| | - Clément Turbelin
- UPMC Univ Paris 06, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Sorbonne Universités, Paris, France
| | - Jim Duggan
- School of Engineering and Informatics, National University of Ireland, Galway, Ireland
| | - W John Edmunds
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Ricardo Mexia
- Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisbon, Portugal
| | - Yamir Moreno
- Institute for Biocomputation and Physics of Complex Systems, Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
| | - Sandro Meloni
- Institute for Biocomputation and Physics of Complex Systems, Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
| | | | | | | | - Ana O Franco
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.,Instituto Gulbenkian de Ciência, Oeiras, Portugal
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