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Zozmann H, Schüler L, Fu X, Gawel E. Autonomous and policy-induced behavior change during the COVID-19 pandemic: Towards understanding and modeling the interplay of behavioral adaptation. PLoS One 2024; 19:e0296145. [PMID: 38696526 PMCID: PMC11065316 DOI: 10.1371/journal.pone.0296145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/07/2024] [Indexed: 05/04/2024] Open
Abstract
Changes in human behaviors, such as reductions of physical contacts and the adoption of preventive measures, impact the transmission of infectious diseases considerably. Behavioral adaptations may be the result of individuals aiming to protect themselves or mere responses to public containment measures, or a combination of both. What drives autonomous and policy-induced adaptation, how they are related and change over time is insufficiently understood. Here, we develop a framework for more precise analysis of behavioral adaptation, focusing on confluence, interactions and time variance of autonomous and policy-induced adaptation. We carry out an empirical analysis of Germany during the fall of 2020 and beyond. Subsequently, we discuss how behavioral adaptation processes can be better represented in behavioral-epidemiological models. We find that our framework is useful to understand the interplay of autonomous and policy-induced adaptation as a "moving target". Our empirical analysis suggests that mobility patterns in Germany changed significantly due to both autonomous and policy-induced adaption, with potentially weaker effects over time due to decreasing risk signals, diminishing risk perceptions and an erosion of trust in the government. We find that while a number of simulation and prediction models have made great efforts to represent behavioral adaptation, the interplay of autonomous and policy-induced adaption needs to be better understood to construct convincing counterfactual scenarios for policy analysis. The insights presented here are of interest to modelers and policy makers aiming to understand and account for behaviors during a pandemic response more accurately.
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Affiliation(s)
- Heinrich Zozmann
- Department Economics, UFZ–Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Lennart Schüler
- Center for Advanced Systems Understanding (CASUS), Görlitz, Germany
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- Research Data Management—RDM, UFZ–Helmholtz Centre for Environmental Research, Leipzig, Germany
- Department Monitoring and Exploration Technologies, UFZ–Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Xiaoming Fu
- Center for Advanced Systems Understanding (CASUS), Görlitz, Germany
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
| | - Erik Gawel
- Department Economics, UFZ–Helmholtz Centre for Environmental Research, Leipzig, Germany
- Institute for Infrastructure and Resources Management, Leipzig University, Leipzig, Germany
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2
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Moilanen KL, Ni Y, Turiano NA. U.S. College Students' Sexual Risk Behaviors Before and During the Early COVID-19 Pandemic. JOURNAL OF SEX RESEARCH 2024; 61:750-766. [PMID: 37676778 PMCID: PMC10918033 DOI: 10.1080/00224499.2023.2246160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
The present study describes changes in young adults' sexual behaviors during the early COVID-19 pandemic. Latent class growth analyses (LCGAs) conducted with four waves of data collected between July 2019 to May 2020 in N = 775 college students (Mage = 18.61, SD = 0.33; 50.3% female, 90.2% White) revealed the presence of high- and low-risk classes in separate models for oral, vaginal, and anal sexual risk taking. As anticipated, vaginal and oral risk taking declined in spring 2020. Membership in high-risk trajectories was attributable to high COVID-19-related financial problems, early sexual debut, low self-control, and being in a romantic relationship. Other COVID-19 factors and demographic control variables were not linked to trajectory membership. Thus, while many young adults' sexual risk taking changed during the early pandemic, their perceptions of and experiences with COVID-19 were not predictive of sexual risk trajectory membership.
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Affiliation(s)
| | - Yue Ni
- Department of Human Development and Family Sciences, Oregon State University
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3
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Liu J, Kassas B, Lai J, Kropp J, Gao Z. Understanding the role of risk preferences and perceptions in vaccination decisions and post-vaccination behaviors among U.S. households. Sci Rep 2024; 14:3190. [PMID: 38326338 PMCID: PMC10850518 DOI: 10.1038/s41598-024-52408-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 01/18/2024] [Indexed: 02/09/2024] Open
Abstract
COVID-19 vaccines play a critical role in protecting against infection and transmission of the virus. Therefore, understanding public perceptions of COVID-19 vaccines is essential for successful vaccine promotion. Previous literature reported strong associations between vaccination decisions and several sociodemographic variables. However, knowledge about how behavioral factors, including risk perceptions and preferences, impact individuals' attitudes towards receiving COVID-19 vaccination is currently lacking. Using data from a nationally representative survey of 1050 US adults, this study investigates the correlation between individuals' decisions to receive COVID-19 vaccination and both their risk perceptions and preferences. Additionally, we investigate post-vaccination behavior by measuring individuals' participation in three different groups of activities that vary by their degree of social exposure. We find strong correlations between vaccination decisions and four measures of risk preference and risk perception. We also find associations between the four risk measures and individuals' behaviors post-vaccination. We shed light on the main factors discouraging the uptake of COVID-19 vaccines, as well as public opinions regarding the performance of different organizations in addressing the COVID-19 pandemic, and grocery store policies to prevent COVID-19 infections. Our study provides critical information that can help policymakers communicate more effectively with the public and promote vaccine uptake among population groups and geographic areas with higher anti-vaccine sentiments.
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Affiliation(s)
- Jianhui Liu
- Food and Resource Economics Department, Institute of Food and Agricultural Sciences, University of Florida, 2120 McCarty B, Gainesville, FL, 32611, USA
| | - Bachir Kassas
- Food and Resource Economics Department, Institute of Food and Agricultural Sciences, University of Florida, 1099 McCarty B, Gainesville, FL, 32611, USA.
| | - John Lai
- Food and Resource Economics Department, Institute of Food and Agricultural Sciences, University of Florida, 1109 McCarty B, Gainesville, FL, 32611, USA
| | - Jaclyn Kropp
- Food and Resource Economics Department, Institute of Food and Agricultural Sciences, University of Florida, 1157 McCarty B, Gainesville, FL, 32611, USA
| | - Zhifeng Gao
- Food and Resource Economics Department, Institute of Food and Agricultural Sciences, University of Florida, 1155 McCarty A, Gainesville, FL, 32611, USA
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Martin-Lapoirie D, McColl K, Gallopel-Morvan K, Arwidson P, Raude J. Health protective behaviours during the COVID-19 pandemic: Risk adaptation or habituation? Soc Sci Med 2024; 342:116531. [PMID: 38194726 DOI: 10.1016/j.socscimed.2023.116531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 12/13/2023] [Accepted: 12/17/2023] [Indexed: 01/11/2024]
Abstract
Many epidemiological works show that human behaviours play a fundamental role in the spread of infectious diseases. However, we still do not know much about how people modify their Health Protective Behaviours (HPB), such as hygiene or social distancing measures, over time in response to the health threat during an epidemic. In this study, we examined the role of the epidemiological context in engagement in HPB through two possible mechanisms highlighted by research into decision-making under risk: risk adaptation and risk habituation. These two different mechanisms were assumed to explain to a large extent the temporal variations in the public's responsiveness to the health threat during the COVID-19 pandemic. To test them, we used self-reported data collected through a series of 25 cross-sectional surveys conducted in France among representative samples of the adult population, from March 2020 to September 2021 (N = 50,019). Interestingly, we found that both mechanisms accounted relatively well for the temporal variation in the adoption of social distancing during the pandemic, which is remarkable given their different assumptions about the underlying social cognitive processes involved in response to a health threat. These results suggest that strengthening the incentives to encourage people to maintain health protective behaviours and to counter risk habituation effects is crucial to disease control and prevention over time.
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Affiliation(s)
- Dylan Martin-Lapoirie
- Centre d'Économie de la Sorbonne, CNRS, Université Paris 1 Panthéon-Sorbonne, Paris, France.
| | - Kathleen McColl
- EHESP, CNRS, Inserm, Arènes - UMR 6051, RSMS (Recherche sur les Services et Management en Santé) - U 1309, Université de Rennes, Rennes, France.
| | - Karine Gallopel-Morvan
- EHESP, CNRS, Inserm, Arènes - UMR 6051, RSMS (Recherche sur les Services et Management en Santé) - U 1309, Université de Rennes, Rennes, France.
| | - Pierre Arwidson
- Direction de la Prévention de la Santé, Santé Publique France, Saint-Maurice, France.
| | - Jocelyn Raude
- EHESP, CNRS, Inserm, Arènes - UMR 6051, RSMS (Recherche sur les Services et Management en Santé) - U 1309, Université de Rennes, Rennes, France.
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Rebitschek FG, Eisenmann Y, Krippner L, Neugebauer E, Schirren CO, Schnuppe K, Hauptmann M. Protecting mass-gathering events in a pandemic with testing tracks and transparent information: an experimental study with festival guests. Psychol Health 2024:1-27. [PMID: 38251635 DOI: 10.1080/08870446.2024.2305644] [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: 01/10/2023] [Accepted: 01/10/2024] [Indexed: 01/23/2024]
Abstract
Objective. To enable future open-air festivals during a pandemic, model festivals tested restricted access and behavioural rules to prevent SARS-CoV-2 transmissions. However, the uptake of health-protective measures depends on informed acceptance, meaning people are more likely to follow measures if they understand their effectiveness and related disease risks. Design and main outcome measures. With a series of online surveys, we studied risk perceptions of 6,500 festival guests and the association of perceived effectiveness of protective behaviours with reported compliance. In a scenario-based online experiment (N = 1,958) among festival guests, we tested the effect of informing transparently about the risk-reducing potential of protective measures at festivals on the intention to attend hypothetical events. Results. We found that guests tended to overestimate infection risks while still perceiving them as low. Self-reported mask wearing and distancing at and around the festivals could not be associated with the understanding of the measures' effectiveness. However, in addition to protective measures themselves, providing transparent information about their absolute risk-reducing effect increased intentions to attend festivals that employ varying protective measures. Conclusion. Our findings suggest that the acceptance of protected festivals can be influenced by transparent information about the effectiveness of protective measures. This calls for further research on evidence-based public health communications to improve their impact.
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Affiliation(s)
- Felix G Rebitschek
- Harding Center for Risk Literacy, Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, Germany
- Max Planck Institute for Human Development, Berlin, Germany
| | - Yvonne Eisenmann
- Center for Clinical Studies, Brandenburg Medical School Theodor Fontane (MHB), Neuruppin, Germany
| | - Lena Krippner
- Harding Center for Risk Literacy, Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, Germany
| | - Edmund Neugebauer
- Faculty of Medicine and Psychology, Brandenburg Medical School Theodor Fontane (MHB), Neuruppin, Germany
| | - Clara O Schirren
- Harding Center for Risk Literacy, Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, Germany
- Max Planck Institute for Human Development, Berlin, Germany
| | - Kristin Schnuppe
- Center for Clinical Studies, Brandenburg Medical School Theodor Fontane (MHB), Neuruppin, Germany
| | - Michael Hauptmann
- Center for Clinical Studies, Brandenburg Medical School Theodor Fontane (MHB), Neuruppin, Germany
- Faculty of Medicine and Psychology, Brandenburg Medical School Theodor Fontane (MHB), Neuruppin, Germany
- Institute of Biostatistics and Registry Research, Brandenburg Medical School Theodor Fontane (MHB), Neuruppin, Germany
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6
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Park SM, Choi C, Rhee MS. One Health approach for prioritization of potential foodborne pathogens: Risk-ranking, Delphi survey, and criteria evaluation pre- and post-COVID-19 pandemic. Compr Rev Food Sci Food Saf 2024; 23:e13258. [PMID: 38284613 DOI: 10.1111/1541-4337.13258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 01/30/2024]
Abstract
Frequent foodborne illnesses with unknown causative agents highlight the need to explore zoonotic potential foodborne pathogens (PFPs). An effective PFP prioritization tool is indispensable, especially after experiencing the recent pandemic caused by zoonotic SARS-CoV-2. Risk information on pathogens (excluding 30 known foodborne pathogens) provided by governmental and international organizations was reviewed to generate a list of PFPs. Risk-ranking of PFPs was conducted based on a literature review of food poisoning or detection cases, and the ranks were determined with a decision tree. PFPs were prioritized by infectious disease (ID), veterinary medicine (VET), and food safety (FS) experts through a pre- and postpandemic Delphi survey, and key criteria in their decisions were illuminated. Among 339 PFPs, 32 rank-1 PFPs were involved in the foodborne outbreak(s). Discrepancies in opinions on prioritization between experts in different fields deepened after the pandemic. Only VET and FS experts valued the plausibility of foodborne transmission in evaluating bacteria and viruses, and a significant correlation between their selection of PFPs was found (p < .05). The impact of the pandemic induced all fields to focus more on human transmission and severity/fatality in prioritizing viruses, and only FS experts emphasized the plausibility of foodborne transmission after the pandemic. In contrast to prioritizing bacteria or viruses, ID and VET experts are unusually focused on foodborne transmission when prioritizing parasites. Criteria of consensus deduced by interdisciplinary experts with different interests and the criteria directly related to foodborne transmission should be acknowledged for adequate PFP prioritization.
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Affiliation(s)
- Sun Min Park
- Department of Biotechnology, College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
| | - Changsun Choi
- Department of Food and Nutrition, College of Biotechnology and Natural Resources, Chung-Ang University, Anseong-si, Gyeonggi, Republic of Korea
| | - Min Suk Rhee
- Department of Biotechnology, College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
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Torabi SH, Riahi SM, Ebrahimzadeh A, Salmani F. Changes in symptoms and characteristics of COVID-19 patients across different variants: two years study using neural network analysis. BMC Infect Dis 2023; 23:838. [PMID: 38017395 PMCID: PMC10683353 DOI: 10.1186/s12879-023-08813-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 11/12/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Considering the fact that COVID-19 has undergone various changes over time, its symptoms have also varied. The aim of this study is to describe and compare the changes in personal characteristics, symptoms, and underlying conditions of individuals infected with different strains of COVID-19. METHODS This descriptive-analytical study was conducted on 46,747 patients who underwent PCR testing during a two-year period from February 22, 2020 to February 23, 2022, in South Khorasan province, Iran. Patient characteristics and symptoms were extracted based on self-report and the information system. The data were analyzed using logistic regression and artificial neural network approaches. The R software was used for analysis and a significance level of 0.05 was considered for the tests. RESULTS Among the 46,747 cases analyzed, 23,239 (49.7%) were male, and the mean age was 51.48 ± 21.41 years. There was a significant difference in symptoms among different variants of the disease (p < 0.001). The factors with a significant positive association were myalgia (OR: 2.04; 95% CI, 1.76 - 2.36), cough (OR: 1.93; 95% CI, 1.68-2.22), and taste or smell disorder (OR: 2.62; 95% CI, 2.1 - 3.28). Additionally, aging was found to increase the likelihood of testing positive across the six periods. CONCLUSION We found that older age, myalgia, cough and taste/smell disorder are better factors compared to dyspnea or high body temperature, for identifying a COVID-19 patient. As the disease evolved, chills and diarrhea, demonstrated prognostic strength as in Omicron.
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Affiliation(s)
- Seyed Hossein Torabi
- School of Medicine, Birjand University of Medical Sciences, Birjand, South Khorasan Province, Iran
| | - Seyed Mohammad Riahi
- Epidemiology Department of Family and Community Medicine, School of Medicine Cardiovascular Diseases Research Center, Birjand University of Medical Sciences, Birjand, South Khorasan Province, Iran
| | - Azadeh Ebrahimzadeh
- Department of Infectious Diseases, School of Medicine Infectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, South Khorasan Province, Iran
| | - Fatemeh Salmani
- Department of Epidemiology and Biostatistics, School of Health Social Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, South Khorasan Province, Iran.
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Wambua J, Loedy N, Jarvis CI, Wong KLM, Faes C, Grah R, Prasse B, Sandmann F, Niehus R, Johnson H, Edmunds W, Beutels P, Hens N, Coletti P. The influence of COVID-19 risk perception and vaccination status on the number of social contacts across Europe: insights from the CoMix study. BMC Public Health 2023; 23:1350. [PMID: 37442987 PMCID: PMC10347859 DOI: 10.1186/s12889-023-16252-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/06/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND The SARS-CoV-2 transmission dynamics have been greatly modulated by human contact behaviour. To curb the spread of the virus, global efforts focused on implementing both Non-Pharmaceutical Interventions (NPIs) and pharmaceutical interventions such as vaccination. This study was conducted to explore the influence of COVID-19 vaccination status and risk perceptions related to SARS-CoV-2 on the number of social contacts of individuals in 16 European countries. METHODS We used data from longitudinal surveys conducted in the 16 European countries to measure social contact behaviour in the course of the pandemic. The data consisted of representative panels of participants in terms of gender, age and region of residence in each country. The surveys were conducted in several rounds between December 2020 and September 2021 and comprised of 29,292 participants providing a total of 111,103 completed surveys. We employed a multilevel generalized linear mixed effects model to explore the influence of risk perceptions and COVID-19 vaccination status on the number of social contacts of individuals. RESULTS The results indicated that perceived severity played a significant role in social contact behaviour during the pandemic after controlling for other variables (p-value < 0.001). More specifically, participants who had low or neutral levels of perceived severity reported 1.25 (95% Confidence intervals (CI) 1.13 - 1.37) and 1.10 (95% CI 1.00 - 1.21) times more contacts compared to those who perceived COVID-19 to be a serious illness, respectively. Additionally, vaccination status was also a significant predictor of contacts (p-value < 0.001), with vaccinated individuals reporting 1.31 (95% CI 1.23 - 1.39) times higher number of contacts than the non-vaccinated. Furthermore, individual-level factors played a more substantial role in influencing contact behaviour than country-level factors. CONCLUSION Our multi-country study yields significant insights on the importance of risk perceptions and vaccination in behavioral changes during a pandemic emergency. The apparent increase in social contact behaviour following vaccination would require urgent intervention in the event of emergence of an immune escaping variant.
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Affiliation(s)
- James Wambua
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Neilshan Loedy
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Christopher I. Jarvis
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Kerry L. M. Wong
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Christel Faes
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Rok Grah
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Bastian Prasse
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Frank Sandmann
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Rene Niehus
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Helen Johnson
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
- Current Address: Health Emergency Preparedness and Response Authority (HERA), European Commission, 1049, Brussels, Belgium
| | - W.John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Philippe Beutels
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- The University of New South Wales, School of Public Health and Community Medicine, Sydney, NSW 2033 Australia
| | - Niel Hens
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Pietro Coletti
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
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Loedy N, Coletti P, Wambua J, Hermans L, Willem L, Jarvis CI, Wong KLM, Edmunds W, Robert A, Leclerc QJ, Gimma A, Molenberghs G, Beutels P, Faes C, Hens N. Longitudinal social contact data analysis: insights from 2 years of data collection in Belgium during the COVID-19 pandemic. BMC Public Health 2023; 23:1298. [PMID: 37415096 PMCID: PMC10326964 DOI: 10.1186/s12889-023-16193-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/26/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND During the COVID-19 pandemic, the CoMix study, a longitudinal behavioral survey, was designed to monitor social contacts and public awareness in multiple countries, including Belgium. As a longitudinal survey, it is vulnerable to participants' "survey fatigue", which may impact inferences. METHODS A negative binomial generalized additive model for location, scale, and shape (NBI GAMLSS) was adopted to estimate the number of contacts reported between age groups and to deal with under-reporting due to fatigue within the study. The dropout process was analyzed with first-order auto-regressive logistic regression to identify factors that influence dropout. Using the so-called next generation principle, we calculated the effect of under-reporting due to fatigue on estimating the reproduction number. RESULTS Fewer contacts were reported as people participated longer in the survey, which suggests under-reporting due to survey fatigue. Participant dropout is significantly affected by household size and age categories, but not significantly affected by the number of contacts reported in any of the two latest waves. This indicates covariate-dependent missing completely at random (MCAR) in the dropout pattern, when missing at random (MAR) is the alternative. However, we cannot rule out more complex mechanisms such as missing not at random (MNAR). Moreover, under-reporting due to fatigue is found to be consistent over time and implies a 15-30% reduction in both the number of contacts and the reproduction number ([Formula: see text]) ratio between correcting and not correcting for under-reporting. Lastly, we found that correcting for fatigue did not change the pattern of relative incidence between age groups also when considering age-specific heterogeneity in susceptibility and infectivity. CONCLUSIONS CoMix data highlights the variability of contact patterns across age groups and time, revealing the mechanisms governing the spread/transmission of COVID-19/airborne diseases in the population. Although such longitudinal contact surveys are prone to the under-reporting due to participant fatigue and drop-out, we showed that these factors can be identified and corrected using NBI GAMLSS. This information can be used to improve the design of similar, future surveys.
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Affiliation(s)
- Neilshan Loedy
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Pietro Coletti
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - James Wambua
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Lisa Hermans
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Lander Willem
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Christopher I. Jarvis
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Kerry L. M. Wong
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - W. John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Alexis Robert
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Quentin J. Leclerc
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Epidemiology and Modelling of Bacterial Escape to Antimicrobials, Institut Pasteur, Paris, France
| | - Amy Gimma
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Geert Molenberghs
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- L-BioStat, Department of Public Health and Primary Care, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia
| | - Christel Faes
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Niel Hens
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
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10
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Mejdahl CT, Nielsen PB, Nielsen LA, Christensen AF, Nielsen BK. Experiences of being at high-risk during the COVID-19 pandemic and its impact on emotional well-being and daily life in people with chronic conditions: a qualitative study. J Patient Rep Outcomes 2023; 7:62. [PMID: 37405541 DOI: 10.1186/s41687-023-00607-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 06/24/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND With its health risks and extensive disruption to everyday life, the SARS-CoV-2 (COVID-19) pandemic has affected the lives of billions of people. People with chronic conditions are particularly susceptible to severe illness if infected by COVID-19, and they have repeatedly been urged to take stringent steps to 'shield' themselves from the virus. It is argued that the negative impact of isolation and other lockdown-related restrictions on emotional well-being and daily life may be most prominent among people at increased risk for severe illness from COVID-19. This qualitative thematic analysis aimed to explore how individuals with chronic conditions perceived the risk posed by COVID-19 and to understand how being at high risk affected their emotional well-being and everyday life. METHODS The study is a thematic analysis of qualitative data consisting of semi-structured interviews with adults affected by at least one chronic condition supplemented with free text comments from a PRO-based survey. RESULTS Based on 17 semi-structured interviews and 144 free text comments from a PRO-based survey three thematic patterns representing diverse COVID-19-related risk experiences were extracted: (1) Feeling vulnerable and at risk, (2) Uncertainty about being at risk, and (3) Distancing from the high-risk label. CONCLUSIONS The risk of COVID-19 impacted the participants' everyday lives and emotional well-being in various ways. Some participants felt vulnerable and at risk causing them and their families to take on far-reaching precautions with significant consequences for their everyday life and emotional well-being. Some participants expressed uncertainty associated with whether they were at increased risk. Such uncertainty gave rise to dilemmas about how to navigate their everyday life. Other participants did not identify themselves as at higher risk and took no special precautions. Such a lack of perceived risk may undermine their motivation for taking preventive measures, which calls for public attention regarding current or future pandemics.
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Affiliation(s)
| | - Pernille Bjørnholt Nielsen
- DEFACTUM - Public Health Research, Central Denmark Region, Olof Palmes Allé 15, Aarhus N, DK-8200, Denmark
| | - Lise Arnth Nielsen
- DEFACTUM - Public Health Research, Central Denmark Region, Olof Palmes Allé 15, Aarhus N, DK-8200, Denmark
| | | | - Berit Kjærside Nielsen
- DEFACTUM - Public Health Research, Central Denmark Region, Olof Palmes Allé 15, Aarhus N, DK-8200, Denmark
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11
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Lajot A, Wambua J, Coletti P, Franco N, Brondeel R, Faes C, Hens N. How contact patterns during the COVID-19 pandemic are related to pre-pandemic contact patterns and mobility trends. BMC Infect Dis 2023; 23:410. [PMID: 37328811 DOI: 10.1186/s12879-023-08369-8] [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: 02/09/2023] [Accepted: 06/02/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Non-pharmaceutical interventions (NPIs) were adopted in Belgium in order to decrease social interactions between people and as such decrease viral transmission of SARS-CoV-2. With the aim to better evaluate the impact of NPIs on the evolution of the pandemic, an estimation of social contact patterns during the pandemic is needed when social contact patterns are not available yet in real time. METHODS In this paper we use a model-based approach allowing for time varying effects to evaluate whether mobility and pre-pandemic social contact patterns can be used to predict the social contact patterns observed during the COVID-19 pandemic between November 11, 2020 and July 4, 2022. RESULTS We found that location-specific pre-pandemic social contact patterns are good indicators for estimating social contact patterns during the pandemic. However, the relationship between both changes with time. Considering a proxy for mobility, namely the change in the number of visitors to transit stations, in interaction with pre-pandemic contacts does not explain the time-varying nature of this relationship well. CONCLUSION In a situation where data from social contact surveys conducted during the pandemic are not yet available, the use of a linear combination of pre-pandemic social contact patterns could prove valuable. However, translating the NPIs at a given time into appropriate coefficients remains the main challenge of such an approach. In this respect, the assumption that the time variation of the coefficients can somehow be related to aggregated mobility data seems unacceptable during our study period for estimating the number of contacts at a given time.
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Affiliation(s)
- Adrien Lajot
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
- Data Science Institute, I-BioStat, University of Hasselt, Hasselt, Belgium.
| | - James Wambua
- Data Science Institute, I-BioStat, University of Hasselt, Hasselt, Belgium
| | - Pietro Coletti
- Data Science Institute, I-BioStat, University of Hasselt, Hasselt, Belgium
| | - Nicolas Franco
- Data Science Institute, I-BioStat, University of Hasselt, Hasselt, Belgium
- Namur Institute for Complex Systems (naXys) and Department of Mathematics, University of Namur, Namur, Belgium
| | - Ruben Brondeel
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - Christel Faes
- Data Science Institute, I-BioStat, University of Hasselt, Hasselt, Belgium
| | - Niel Hens
- Data Science Institute, I-BioStat, University of Hasselt, Hasselt, Belgium
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and infectious disease institute, University of Antwerp, Antwerp, Belgium
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12
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Steinegger B, Granell C, Rapisardi G, Gómez S, Matamalas J, Soriano-Paños D, Gómez-Gardeñes J, Arenas A. Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study. JMIR Public Health Surveill 2023; 9:e40514. [PMID: 37213190 PMCID: PMC10208305 DOI: 10.2196/40514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/02/2022] [Accepted: 04/27/2023] [Indexed: 05/23/2023] Open
Abstract
BACKGROUND The initial wave of the COVID-19 pandemic placed a tremendous strain on health care systems worldwide. To mitigate the spread of the virus, many countries implemented stringent nonpharmaceutical interventions (NPIs), which significantly altered human behavior both before and after their enactment. Despite these efforts, a precise assessment of the impact and efficacy of these NPIs, as well as the extent of human behavioral changes, remained elusive. OBJECTIVE In this study, we conducted a retrospective analysis of the initial wave of COVID-19 in Spain to better comprehend the influence of NPIs and their interaction with human behavior. Such investigations are vital for devising future mitigation strategies to combat COVID-19 and enhance epidemic preparedness more broadly. METHODS We used a combination of national and regional retrospective analyses of pandemic incidence alongside large-scale mobility data to assess the impact and timing of government-implemented NPIs in combating COVID-19. Additionally, we compared these findings with a model-based inference of hospitalizations and fatalities. This model-based approach enabled us to construct counterfactual scenarios that gauged the consequences of delayed initiation of epidemic response measures. RESULTS Our analysis demonstrated that the pre-national lockdown epidemic response, encompassing regional measures and heightened individual awareness, significantly contributed to reducing the disease burden in Spain. The mobility data indicated that people adjusted their behavior in response to the regional epidemiological situation before the nationwide lockdown was implemented. Counterfactual scenarios suggested that without this early epidemic response, there would have been an estimated 45,400 (95% CI 37,400-58,000) fatalities and 182,600 (95% CI 150,400-233,800) hospitalizations compared to the reported figures of 27,800 fatalities and 107,600 hospitalizations, respectively. CONCLUSIONS Our findings underscore the significance of self-implemented prevention measures by the population and regional NPIs before the national lockdown in Spain. The study also emphasizes the necessity for prompt and precise data quantification prior to enacting enforced measures. This highlights the critical interplay between NPIs, epidemic progression, and human behavior. This interdependence presents a challenge in predicting the impact of NPIs before they are implemented.
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Affiliation(s)
| | | | | | | | - Joan Matamalas
- Harvard Medical School, Boston, MA, United States
- Brigham and Women's Hospital, Boston, MA, United States
| | - David Soriano-Paños
- Department of Condensed Matter Physics, University of Zaragoza, Zaragoza, Spain
| | | | - Alex Arenas
- Universitat Rovira i Virgili, Tarragona, Spain
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13
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Tizzani M, De Gaetano A, Jarvis CI, Gimma A, Wong K, Edmunds WJ, Beutels P, Hens N, Coletti P, Paolotti D. Impact of tiered measures on social contact and mixing patterns of in Italy during the second wave of COVID-19. BMC Public Health 2023; 23:906. [PMID: 37202734 PMCID: PMC10195658 DOI: 10.1186/s12889-023-15846-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 05/02/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND Most countries around the world enforced non-pharmaceutical interventions against COVID-19. Italy was one of the first countries to be affected by the pandemic, imposing a hard lockdown, in the first epidemic wave. During the second wave, the country implemented progressively restrictive tiers at the regional level according to weekly epidemiological risk assessments. This paper quantifies the impact of these restrictions on contacts and on the reproduction number. METHODS Representative (with respect to age, sex, and region of residence) longitudinal surveys of the Italian population were undertaken during the second epidemic wave. Epidemiologically relevant contact patterns were measured and compared with pre-pandemic levels and according to the level of interventions experienced by the participants. Contact matrices were used to quantify the reduction in the number of contacts by age group and contact setting. The reproduction number was estimated to evaluate the impact of restrictions on the spread of COVID-19. RESULTS The comparison with the pre-pandemic baseline shows a significant decrease in the number of contacts, independently from the age group or contact settings. This decrease in the number of contacts significantly depends on the strictness of the non-pharmaceutical interventions. For all levels of strictness considered, the reduction in social mixing results in a reproduction number smaller than one. In particular, the impact of the restriction on the number of contacts decreases with the severity of the interventions. CONCLUSIONS The progressive restriction tiers implemented in Italy reduced the reproduction number, with stricter interventions associated with higher reductions. Readily collected contact data can inform the implementation of mitigation measures at the national level in epidemic emergencies to come.
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Affiliation(s)
| | | | | | - Amy Gimma
- London School of Hygiene and Tropical Medicine, London, UK
| | - Kerry Wong
- London School of Hygiene and Tropical Medicine, London, UK
| | - W John Edmunds
- London School of Hygiene and Tropical Medicine, London, UK
| | - Philippe Beutels
- Centre for Health Economic Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Niel Hens
- Centre for Health Economic Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- UHasselt, Data Science Institute and I-BioStat, Hasselt, Belgium
| | - Pietro Coletti
- UHasselt, Data Science Institute and I-BioStat, Hasselt, Belgium
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14
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Wong KLM, Gimma A, Coletti P, Faes C, Beutels P, Hens N, Jaeger VK, Karch A, Johnson H, Edmunds WJ, Jarvis CI. Social contact patterns during the COVID-19 pandemic in 21 European countries - evidence from a two-year study. BMC Infect Dis 2023; 23:268. [PMID: 37101123 PMCID: PMC10132446 DOI: 10.1186/s12879-023-08214-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 03/31/2023] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Most countries have enacted some restrictions to reduce social contacts to slow down disease transmission during the COVID-19 pandemic. For nearly two years, individuals likely also adopted new behaviours to avoid pathogen exposure based on personal circumstances. We aimed to understand the way in which different factors affect social contacts - a critical step to improving future pandemic responses. METHODS The analysis was based on repeated cross-sectional contact survey data collected in a standardized international study from 21 European countries between March 2020 and March 2022. We calculated the mean daily contacts reported using a clustered bootstrap by country and by settings (at home, at work, or in other settings). Where data were available, contact rates during the study period were compared with rates recorded prior to the pandemic. We fitted censored individual-level generalized additive mixed models to examine the effects of various factors on the number of social contacts. RESULTS The survey recorded 463,336 observations from 96,456 participants. In all countries where comparison data were available, contact rates over the previous two years were substantially lower than those seen prior to the pandemic (approximately from over 10 to < 5), predominantly due to fewer contacts outside the home. Government restrictions imposed immediate effect on contacts, and these effects lingered after the restrictions were lifted. Across countries, the relationships between national policy, individual perceptions, or personal circumstances determining contacts varied. CONCLUSIONS Our study, coordinated at the regional level, provides important insights into the understanding of the factors associated with social contacts to support future infectious disease outbreak responses.
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Affiliation(s)
- Kerry L M Wong
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
| | - Amy Gimma
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Pietro Coletti
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, 3590, Diepenbeek, Belgium
| | - Christel Faes
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, 3590, Diepenbeek, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia
| | - Niel Hens
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, 3590, Diepenbeek, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
| | - Veronika K Jaeger
- Institute of Epidemiology and Social Medicine, University of Muenster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
| | - Andre Karch
- Institute of Epidemiology and Social Medicine, University of Muenster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
| | - Helen Johnson
- European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - WJohn Edmunds
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Christopher I Jarvis
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
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15
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Backer JA, Bogaardt L, Beutels P, Coletti P, Edmunds WJ, Gimma A, van Hagen CCE, Hens N, Jarvis CI, Vos ERA, Wambua J, Wong D, van Zandvoort K, Wallinga J. Dynamics of non-household contacts during the COVID-19 pandemic in 2020 and 2021 in the Netherlands. Sci Rep 2023; 13:5166. [PMID: 36997550 PMCID: PMC10060924 DOI: 10.1038/s41598-023-32031-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 03/21/2023] [Indexed: 04/04/2023] Open
Abstract
The COVID-19 pandemic was in 2020 and 2021 for a large part mitigated by reducing contacts in the general population. To monitor how these contacts changed over the course of the pandemic in the Netherlands, a longitudinal survey was conducted where participants reported on their at-risk contacts every two weeks, as part of the European CoMix survey. The survey included 1659 participants from April to August 2020 and 2514 participants from December 2020 to September 2021. We categorized the number of unique contacted persons excluding household members, reported per participant per day into six activity levels, defined as 0, 1, 2, 3-4, 5-9 and 10 or more reported contacts. After correcting for age, vaccination status, risk status for severe outcome of infection, and frequency of participation, activity levels increased over time, coinciding with relaxation of COVID-19 control measures.
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Affiliation(s)
- Jantien A Backer
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - Laurens Bogaardt
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | | - Pietro Coletti
- UHasselt, Data Science Institute and I-BioStat, Hasselt, Belgium
| | - W John Edmunds
- London School of Hygiene and Tropical Medicine, London, UK
| | - Amy Gimma
- London School of Hygiene and Tropical Medicine, London, UK
| | | | - Niel Hens
- University of Antwerp, Antwerp, Belgium
- UHasselt, Data Science Institute and I-BioStat, Hasselt, Belgium
| | | | - Eric R A Vos
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - James Wambua
- UHasselt, Data Science Institute and I-BioStat, Hasselt, Belgium
| | - Denise Wong
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | | - Jacco Wallinga
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
- Leiden University Medical Center, Leiden, The Netherlands
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16
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Dyer ML, Sallis HM, Khouja JN, Dryhurst S, Munafò MR. Associations between COVID-19 Risk Perceptions and Mental Health, Wellbeing, and Risk Behaviours. JOURNAL OF RISK RESEARCH 2022; 25:1372-1394. [PMID: 37872962 PMCID: PMC7615237 DOI: 10.1080/13669877.2022.2127849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 06/16/2022] [Accepted: 09/02/2022] [Indexed: 10/25/2023]
Abstract
Background Mental health has worsened, and substance use has increased for some people during the coronavirus (COVID-19) pandemic. Some cross-sectional studies suggest that higher COVID-19 risk perceptions are related to poorer mental health and greater risk behaviours (e.g., substance use). However, longitudinal and genetic data are needed to help to reduce the likelihood of reverse causality. Methods We used cross-sectional, longitudinal, and polygenic risk score (PRS; for anxiety, depression, wellbeing) data from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined cross-sectional and prospective longitudinal associations between COVID-19 risk perceptions (i.e., cognitive, affective, self, other, and a combined 'holistic' measure) and mental health (i.e., anxiety, depression), wellbeing, and risk behaviours. Pandemic (April-July 2020) and pre-pandemic (2003-2017) data (ns = 233-5,115) were included. Results Higher COVID-19 risk perceptions (holistic) were associated with anxiety (OR 2.78, 95% confidence interval [CI] 2.20 to 3.52), depression (OR 1.65, 95% CI 1.24 to 2.18), low wellbeing (OR 1.76, 95% CI 1.45 to 2.13), and increased alcohol use (OR 1.46, 95% CI 1.24 to 1.72). Higher COVID-19 risk perceptions were also associated with self-isolating given a suspected COVID-19 infection (OR 1.74, 95% CI 1.13 to 2.68), and less face-to-face contact (OR 0.83, 95% CI 0.70 to 0.98) and physical contact (OR 0.83, 95% CI 0.68 to 1.00). Pre-pandemic anxiety (OR 1.64, 95% CI 1.29 to 2.09) and low wellbeing (OR 1.41, 95% CI 1.15 to 1.74) were associated with higher COVID-19 risk perceptions. The depression PRS (b 0.21, 95% CI 0.02 to 0.40) and wellbeing PRS (b -0.29, 95% CI -0.48 to -0.09) were associated with higher and lower COVID-19 risk perceptions, respectively. Conclusions Poorer mental health and wellbeing are associated with higher COVID-19 risk perceptions, and longitudinal and genetic data suggest that they may play a causal role in COVID-19 risk perceptions.
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Affiliation(s)
- Maddy L. Dyer
- School of Psychological Science, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Hannah M. Sallis
- School of Psychological Science, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jasmine N. Khouja
- School of Psychological Science, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Sarah Dryhurst
- Winton Centre for Risk and Evidence Communication, University of Cambridge, Cambridge, UK
| | - Marcus R. Munafò
- School of Psychological Science, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
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17
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Adu PA, Binka M, Mahmood B, Jeong D, Buller-Taylor T, Damascene MJ, Iyaniwura S, Ringa N, Velásquez García HA, Wong S, Yu A, Bartlett S, Wilton J, Irvine MA, Otterstatter M, Janjua NZ. Cohort profile: the British Columbia COVID-19 Population Mixing Patterns Survey (BC-Mix). BMJ Open 2022; 12:e056615. [PMID: 36002217 PMCID: PMC9412046 DOI: 10.1136/bmjopen-2021-056615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
PURPOSE Several non-pharmaceutical interventions, such as physical distancing, handwashing, self-isolation, and school and business closures, were implemented in British Columbia (BC) following the first laboratory-confirmed case of COVID-19 on 26 January 2020, to minimise in-person contacts that could spread infections. The BC COVID-19 Population Mixing Patterns Survey (BC-Mix) was established as a surveillance system to measure behaviour and contact patterns in BC over time to inform the timing of the easing/re-imposition of control measures. In this paper, we describe the BC-Mix survey design and the demographic characteristics of respondents. PARTICIPANTS The ongoing repeated online survey was launched in September 2020. Participants are mainly recruited through social media platforms (including Instagram, Facebook, YouTube, WhatsApp). A follow-up survey is sent to participants 2-4 weeks after completing the baseline survey. Survey responses are weighted to BC's population by age, sex, geography and ethnicity to obtain generalisable estimates. Additional indices such as the Material and Social Deprivation Index, residential instability, economic dependency, and others are generated using census and location data. FINDINGS TO DATE As of 26 July 2021, over 61 000 baseline survey responses were received of which 41 375 were eligible for analysis. Of the eligible participants, about 60% consented to follow-up and about 27% provided their personal health numbers for linkage with healthcare databases. Approximately 83.5% of respondents were female, 58.7% were 55 years or older, 87.5% identified as white and 45.9% had at least a university degree. After weighting, approximately 50% were female, 39% were 55 years or older, 65% identified as white and 50% had at least a university degree. FUTURE PLANS Multiple papers describing contact patterns, physical distancing measures, regular handwashing and facemask wearing, modelling looking at impact of physical distancing measures and vaccine acceptance, hesitancy and uptake are either in progress or have been published.
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Affiliation(s)
- Prince A Adu
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Mawuena Binka
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Bushra Mahmood
- Department of Medicine, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Dahn Jeong
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Makuza Jean Damascene
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Sarafa Iyaniwura
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- Department of Mathematics, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Notice Ringa
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Héctor A Velásquez García
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Stanley Wong
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Amanda Yu
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Sofia Bartlett
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, British Columbia, Canada
| | - James Wilton
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Mike A Irvine
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Michael Otterstatter
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Naveed Zafar Janjua
- BC Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
- Centre for Health Evaluation & Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada
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18
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Godbout A, Drolet M, Mondor M, Simard M, Sauvageau C, De Serres G, Brisson M. Time trends in social contacts of individuals according to comorbidity and vaccination status, before and during the COVID-19 pandemic. BMC Med 2022; 20:199. [PMID: 35606803 PMCID: PMC9126104 DOI: 10.1186/s12916-022-02398-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 05/09/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND As we are confronted with more transmissible/severe variants with immune escape and the waning of vaccine efficacy, it is particularly relevant to understand how the social contacts of individuals at greater risk of COVID-19 complications evolved over time. We described time trends in social contacts of individuals according to comorbidity and vaccination status before and during the first three waves of the COVID-19 pandemic in Quebec, Canada. METHODS We used data from CONNECT, a repeated cross-sectional population-based survey of social contacts conducted before (2018/2019) and during the pandemic (April 2020 to July 2021). We recruited non-institutionalized adults from Quebec, Canada, by random digit dialling. We used a self-administered web-based questionnaire to measure the number of social contacts of participants (two-way conversation at a distance ≤2 m or a physical contact, irrespective of masking). We compared the mean number of contacts/day according to the comorbidity status of participants (pre-existing medical conditions with symptoms/medication in the past 12 months) and 1-dose vaccination status during the third wave. All analyses were performed using weighted generalized linear models with a Poisson distribution and robust variance. RESULTS A total of 1441 and 5185 participants with and without comorbidities, respectively, were included in the analyses. Contacts significantly decreased from a mean of 6.1 (95%CI 4.9-7.3) before the pandemic to 3.2 (95%CI 2.5-3.9) during the first wave among individuals with comorbidities and from 8.1 (95%CI 7.3-9.0) to 2.7 (95%CI 2.2-3.2) among individuals without comorbidities. Individuals with comorbidities maintained fewer contacts than those without comorbidities in the second wave, with a significant difference before the Christmas 2020/2021 holidays (2.9 (95%CI 2.5-3.2) vs 3.9 (95%CI 3.5-4.3); P<0.001). During the third wave, contacts were similar for individuals with (4.1, 95%CI 3.4-4.7) and without comorbidities (4.5, 95%CI 4.1-4.9; P=0.27). This could be partly explained by individuals with comorbidities vaccinated with their first dose who increased their contacts to the level of those without comorbidities. CONCLUSIONS It will be important to closely monitor COVID-19-related outcomes and social contacts by comorbidity and vaccination status to inform targeted or population-based interventions (e.g., booster doses of the vaccine).
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Affiliation(s)
- Aurélie Godbout
- Centre de recherche du CHU de Québec-Université Laval, 1050 Chemin Sainte-Foy, Québec, G1S 4L8, Canada.,Laval University, Québec, Canada
| | - Mélanie Drolet
- Centre de recherche du CHU de Québec-Université Laval, 1050 Chemin Sainte-Foy, Québec, G1S 4L8, Canada
| | - Myrto Mondor
- Centre de recherche du CHU de Québec-Université Laval, 1050 Chemin Sainte-Foy, Québec, G1S 4L8, Canada
| | - Marc Simard
- Institut National de Santé Publique du Québec, Québec, Canada
| | - Chantal Sauvageau
- Centre de recherche du CHU de Québec-Université Laval, 1050 Chemin Sainte-Foy, Québec, G1S 4L8, Canada.,Laval University, Québec, Canada.,Institut National de Santé Publique du Québec, Québec, Canada
| | - Gaston De Serres
- Centre de recherche du CHU de Québec-Université Laval, 1050 Chemin Sainte-Foy, Québec, G1S 4L8, Canada.,Laval University, Québec, Canada.,Institut National de Santé Publique du Québec, Québec, Canada
| | - Marc Brisson
- Centre de recherche du CHU de Québec-Université Laval, 1050 Chemin Sainte-Foy, Québec, G1S 4L8, Canada. .,Laval University, Québec, Canada. .,MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
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