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Aguolu OG, Kiti MC, Nelson K, Liu CY, Sundaram M, Gramacho S, Jenness S, Melegaro A, Sacoor C, Bardaji A, Macicame I, Jose A, Cavele N, Amosse F, Uamba M, Jamisse E, Tchavana C, Briones HGM, Jarquín C, Ajsivinac M, Pischel L, Ahmed N, Mohan VR, Srinivasan R, Samuel P, John G, Ellington K, Joaquim OA, Zelaya A, Kim S, Chen H, Kazi M, Malik F, Yildirim I, Lopman B, Omer SB. Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol. medRxiv 2023:2023.12.05.23299472. [PMID: 38105989 PMCID: PMC10723497 DOI: 10.1101/2023.12.05.23299472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Background Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. Methods To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures.We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. Discussion Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.
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Affiliation(s)
| | | | - Kristin Nelson
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Carol Y. Liu
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Maria Sundaram
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Sergio Gramacho
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Samuel Jenness
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Alessia Melegaro
- DONDENA Centre for Research in Social Dynamics and Public Policy, Bocconi University, Italy
| | | | - Azucena Bardaji
- Manhiça Health Research Centre, Manhica, Mozambique
- ISGlobal, Hospital Clinic – Universitat de Barcelona, Barcelona, Spain
- Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Ivalda Macicame
- Polana Caniço Health Research and Training Centre, CISPOC, Mozambique
| | - Americo Jose
- Polana Caniço Health Research and Training Centre, CISPOC, Mozambique
| | - Nilzio Cavele
- Polana Caniço Health Research and Training Centre, CISPOC, Mozambique
| | | | - Migdalia Uamba
- Polana Caniço Health Research and Training Centre, CISPOC, Mozambique
| | | | | | | | - Claudia Jarquín
- Centro de Estudios en Salud (CES), Universidad del Valle de Guatemala
| | - María Ajsivinac
- Centro de Estudios en Salud (CES), Universidad del Valle de Guatemala
| | - Lauren Pischel
- Yale School of Medicine, Yale University, Connecticut, USA
| | - Noureen Ahmed
- Peter O’Donnell Jr. School of Public Health at UT Southwestern Medical Center, Dallas, Texas
| | | | | | | | - Gifta John
- Christian Medical College Vellore, India
| | - Kye Ellington
- Rollins School of Public Health, Emory University, Georgia, USA
| | | | - Alana Zelaya
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Sara Kim
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Holin Chen
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Momin Kazi
- The Aga Khan University, Karachi, Pakistán
| | - Fauzia Malik
- Peter O’Donnell Jr. School of Public Health at UT Southwestern Medical Center, Dallas, Texas
| | - Inci Yildirim
- Yale School of Medicine, Yale University, Connecticut, USA
| | - Benjamin Lopman
- Rollins School of Public Health, Emory University, Georgia, USA
| | - Saad B. Omer
- Peter O’Donnell Jr. School of Public Health at UT Southwestern Medical Center, Dallas, Texas
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Aguolu OG, Willebrand K, Elharake JA, Qureshi HM, Kiti MC, Liu CY, Restrepo Mesa A, Nelson K, Jenness S, Melegaro A, Ahmed F, Yildirim I, Malik FA, Lopman B, Omer SB. Factors influencing the decision to receive seasonal influenza vaccination among US corporate non-healthcare workers. Hum Vaccin Immunother 2022; 18:2122379. [PMID: 36136345 PMCID: PMC9746537 DOI: 10.1080/21645515.2022.2122379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Influenza causes significant mortality and morbidity in the United States (US). Employees are exposed to influenza at work and can spread it to others. The influenza vaccine is safe, effective, and prevents severe outcomes; however, coverage among US adults (50.2%) is below Healthy People 2030 target of 70%. These highlights need for more effective vaccination promotion interventions. Understanding predictors of vaccination acceptance could inform vaccine promotion messages, improve coverage, and reduce illness-related work absences. We aimed to identify factors influencing influenza vaccination among US non-healthcare workers. Using mixed-methods approach, we evaluated factors influencing influenza vaccination among employees in three US companies during April-June 2020. Survey questions were adapted from the WHO seasonal influenza survey. Most respondents (n = 454) were women (272, 59.9%), 20-39 years old (n = 250, 55.1%); white (n = 254, 56.0%); had a college degree (n = 431, 95.0%); and reported receiving influenza vaccine in preceding influenza season (n = 297, 65.4%). Logistic regression model was statistically significant, X (16, N = 450) = 31.6, p = .01. Education [(OR) = 0.3, 95%CI = 0.1-0.6)] and race (OR = 0.4, 95%CI = 0.2-0.8) were significant predictors of influenza vaccine acceptance among participants. The majority had favorable attitudes toward influenza vaccination and reported that physician recommendation would influence their vaccination decisions. Seven themes were identified in qualitative analysis: "Protecting others" (109, 24.0%), "Protecting self" (105, 23.1%), "Vaccine accessibility" (94, 20.7%), "Education/messaging" (71, 15.6%), "Policies/requirements" (15, 3.3%), "Reminders" (9, 2.0%), and "Incentives" (3, 0.7%). Our findings could facilitate the development of effective influenza vaccination promotion messages and programs for employers, and workplace vaccination programs for other diseases such as COVID-19, by public health authorities.
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Affiliation(s)
- Obianuju Genevieve Aguolu
- Yale Institute of Global Health, Yale University, New Haven, CT, USA
- Yale School of Medicine, Yale University, New Haven, CT, USA
- CONTACT Obianuju Genevieve Aguolu Yale Institute of Global Health, Yale University, 1 Church Street, Room 345, New Haven, CT06510, USA
| | | | - Jad A. Elharake
- Yale Institute of Global Health, Yale University, New Haven, CT, USA
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Hanya M. Qureshi
- Yale Institute of Global Health, Yale University, New Haven, CT, USA
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Moses Chapa Kiti
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Carol Y. Liu
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | | | - Kristin Nelson
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Samuel Jenness
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Alessia Melegaro
- DONDENA Centre for Research in Social Dynamics and Public Policy, Bocconi University, Milan, Italy
| | - Faruque Ahmed
- Division of Global Migration and Quarantine, Centers for Disease Control and Prevention, Atlanta, GA, Georgia
| | - Inci Yildirim
- Yale Institute of Global Health, Yale University, New Haven, CT, USA
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Fauzia A. Malik
- Yale Institute of Global Health, Yale University, New Haven, CT, USA
| | - Benjamin Lopman
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Saad B. Omer
- Yale Institute of Global Health, Yale University, New Haven, CT, USA
- Yale School of Medicine, Yale University, New Haven, CT, USA
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Akpan IJ, Aguolu OG, Kobara YM, Razavi R, Akpan AA, Shanker M. Association Between What People Learned About COVID-19 Using Web Searches and Their Behavior Toward Public Health Guidelines: Empirical Infodemiology Study. J Med Internet Res 2021; 23:e28975. [PMID: 34280117 PMCID: PMC8415385 DOI: 10.2196/28975] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 07/09/2021] [Accepted: 07/09/2021] [Indexed: 12/18/2022] Open
Abstract
Background The use of the internet and web-based platforms to obtain public health information and manage health-related issues has become widespread in this digital age. The practice is so pervasive that the first reaction to obtaining health information is to “Google it.” As SARS-CoV-2 broke out in Wuhan, China, in December 2019 and quickly spread worldwide, people flocked to the internet to learn about the novel coronavirus and the disease, COVID-19. Lagging responses by governments and public health agencies to prioritize the dissemination of information about the coronavirus outbreak through the internet and the World Wide Web and to build trust gave room for others to quickly populate social media, online blogs, news outlets, and websites with misinformation and conspiracy theories about the COVID-19 pandemic, resulting in people’s deviant behaviors toward public health safety measures. Objective The goals of this study were to determine what people learned about the COVID-19 pandemic through web searches, examine any association between what people learned about COVID-19 and behavior toward public health guidelines, and analyze the impact of misinformation and conspiracy theories about the COVID-19 pandemic on people’s behavior toward public health measures. Methods This infodemiology study used Google Trends’ worldwide search index, covering the first 6 months after the SARS-CoV-2 outbreak (January 1 to June 30, 2020) when the public scrambled for information about the pandemic. Data analysis employed statistical trends, correlation and regression, principal component analysis (PCA), and predictive models. Results The PCA identified two latent variables comprising past coronavirus epidemics (pastCoVepidemics: keywords that address previous epidemics) and the ongoing COVID-19 pandemic (presCoVpandemic: keywords that explain the ongoing pandemic). Both principal components were used significantly to learn about SARS-CoV-2 and COVID-19 and explained 88.78% of the variability. Three principal components fuelled misinformation about COVID-19: misinformation (keywords “biological weapon,” “virus hoax,” “common cold,” “COVID-19 hoax,” and “China virus”), conspiracy theory 1 (ConspTheory1; keyword “5G” or “@5G”), and conspiracy theory 2 (ConspTheory2; keyword “ingest bleach”). These principal components explained 84.85% of the variability. The principal components represent two measurements of public health safety guidelines—public health measures 1 (PubHealthMes1; keywords “social distancing,” “wash hands,” “isolation,” and “quarantine”) and public health measures 2 (PubHealthMes2; keyword “wear mask”)—which explained 84.7% of the variability. Based on the PCA results and the log-linear and predictive models, ConspTheory1 (keyword “@5G”) was identified as a predictor of people’s behavior toward public health measures (PubHealthMes2). Although correlations of misinformation (keywords “COVID-19,” “hoax,” “virus hoax,” “common cold,” and more) and ConspTheory2 (keyword “ingest bleach”) with PubHealthMes1 (keywords “social distancing,” “hand wash,” “isolation,” and more) were r=0.83 and r=–0.11, respectively, neither was statistically significant (P=.27 and P=.13, respectively). Conclusions Several studies focused on the impacts of social media and related platforms on the spreading of misinformation and conspiracy theories. This study provides the first empirical evidence to the mainly anecdotal discourse on the use of web searches to learn about SARS-CoV-2 and COVID-19.
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Affiliation(s)
- Ikpe Justice Akpan
- Department of Management & Information Systems, Kent State University, New Philadelphia, OH, United States
| | - Obianuju Genevieve Aguolu
- Infectious Disease Internal Medicine Department, Yale School of Medicine, Yale University, New Haven, CT, United States
| | - Yawo Mamoua Kobara
- Statistical and Actuarial Sciences, Western University, London, ON, Canada
| | - Rouzbeh Razavi
- Department of Management & Information Systems, Kent State University, Kent, OH, United States
| | - Asuama A Akpan
- Research and Development, Ibom International Center for Research and Scholarship, Windsor, ON, Canada
| | - Murali Shanker
- Department of Management & Information Systems, Kent State University, Kent, OH, United States
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Akpan IJ, Aguolu OG, Ezeume IC. Overcoming the Challenge of Communicating the Concept and Science of SARS-CoV-2 and COVID-19 to Non-Experts. ACTA ACUST UNITED AC 2021. [DOI: 10.1080/05775132.2021.1912984] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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Shafiq M, Elharake JA, Malik AA, McFadden SM, Aguolu OG, Omer SB. COVID-19 Sources of Information, Knowledge, and Preventive Behaviors Among the US Adult Population. J Public Health Manag Pract 2021; 27:278-284. [PMID: 33762543 DOI: 10.1097/phh.0000000000001348] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
CONTEXT The COVID-19 pandemic has resulted in more than 20 million cases and 350 000 deaths in the United States. With the ongoing media coverage and spread of misinformation, public health authorities need to identify effective strategies and create culturally appropriate and evidence-based messaging that best encourage preventive health behaviors to control the spread of COVID-19. OBJECTIVE The purpose of this study was to understand the relationship between COVID-19 sources of information and knowledge, and how US adults' knowledge may be associated with preventive health behaviors to help mitigate COVID-19 cases and deaths. DESIGN AND SETTING For this cross-sectional study, survey data pertaining to COVID-19 were collected via online platform, Qualtrics, in February and May 2020. PARTICIPANTS Data responses included 718 US adults from the February survey and 672 US adults from the May survey-both representative of the US adult population. MAIN OUTCOME MEASURES Sociodemographic characteristics, COVID-19 knowledge score, COVID-19 reliable sources of information, and adherence to COVID-19 preventive health behaviors. RESULTS AND CONCLUSIONS The main findings showed that disseminating COVID-19 information across various sources, particularly television, health care providers, and health officials, to increase people's COVID-19 knowledge contributes to greater adherence to infection prevention behaviors. Across February and May 2020 survey data, participants 55 years and older and those with higher educational background reported a higher average COVID-19 knowledge score. In addition, among the racial and ethnic categories, Black/African American and Native American/Alaska Native participants reported a lower average COVID-19 knowledge score than white participants-signaling the need to establish COVID-19 communication that is culturally-tailored and community-based. Overall, health care authorities must deliver clear and concise messaging about the importance of adhering to preventive health behaviors, even as COVID-19 vaccines become widely available to the general public. Health officials must also focus on increasing COVID-19 knowledge and dispelling misinformation.
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Affiliation(s)
- Mehr Shafiq
- Yale Institute for Global Health, New Haven, Connecticut (Ms Shafiq, Mr Elharake, and Drs Malik, McFadden, Aguolu, and Omer); Columbia University Mailman School of Public Health, New York City, New York (Ms Shafiq); Yale School of Public Health, New Haven, Connecticut (Mr Elharake and Dr Omer); Yale School of Medicine, New Haven, Connecticut (Drs Malik, McFadden, Aguolu, and Omer); and Yale School of Nursing, Orange, Connecticut (Dr Omer)
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