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4. Characterizing social contact patterns in rural and urban Mozambique: the GlobalMix study, 2021-2022

Author

Kiti, Moses C., primary, Sacoor, Charfudin, additional, Aguolu, Obianuju G., additional, Zelaya, Alana, additional, Chen, Holin, additional, Kim, Sara S., additional, Cavele, Nilzio, additional, Jamisse, Edgar, additional, Tchavana, Corssino, additional, Jose, Americo, additional, Macicame, Ivalda, additional, Joaquim, Orvalho, additional, Ahmed, Noureen, additional, Liu, Carol Y., additional, Yildirim, Inci, additional, Nelson, Kristin, additional, Jenness, Samuel M., additional, Maldonado, Herberth, additional, Kazi, Momin, additional, Srinivasan, Rajan, additional, Mohan, Venkata R., additional, Melegaro, Alessia, additional, Malik, Fauzia, additional, Bardaji, Azucena, additional, Omer, Saad B., additional, and Lopman, Ben, additional

Published
2024
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6. Comprehensive profiling of social mixing patterns in resource poor countries: A mixed methods research protocol.

Author

Aguolu, Obianuju Genevieve, Kiti, Moses Chapa, Nelson, Kristin, Liu, Carol Y., Sundaram, Maria, Gramacho, Sergio, Jenness, Samuel, Melegaro, Alessia, Sacoor, Charfudin, Bardaji, Azucena, Macicame, Ivalda, Jose, Americo, Cavele, Nilzio, Amosse, Felizarda, Uamba, Migdalia, Jamisse, Edgar, Tchavana, Corssino, Giovanni Maldonado Briones, Herberth, Jarquín, Claudia, and Ajsivinac, María

Subjects
MIXED methods research, RESEARCH protocols, PROXIMITY detectors, COGNITIVE interviewing, COMMUNICABLE diseases
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. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol

Author

Aguolu, Obianuju Genevieve, primary, Kiti, Moses Chapa, additional, Nelson, Kristin, additional, Liu, Carol Y., additional, Sundaram, Maria, additional, Gramacho, Sergio, additional, Jenness, Samuel, additional, Melegaro, Alessia, additional, Sacoor, Charfudin, additional, Bardaji, Azucena, additional, Macicame, Ivalda, additional, Jose, Americo, additional, Cavele, Nilzio, additional, Amosse, Felizarda, additional, Uamba, Migdalia, additional, Jamisse, Edgar, additional, Tchavana, Corssino, additional, Briones, Herberth Giovanni Maldonado, additional, Jarquín, Claudia, additional, Ajsivinac, María, additional, Pischel, Lauren, additional, Ahmed, Noureen, additional, Mohan, Venkata Raghava, additional, Srinivasan, Rajan, additional, Samuel, Prasanna, additional, John, Gifta, additional, Ellington, Kye, additional, Joaquim, Orvalho Augusto, additional, Zelaya, Alana, additional, Kim, Sara, additional, Chen, Holin, additional, Kazi, Momin, additional, Malik, Fauzia, additional, Yildirim, Inci, additional, Lopman, Benjamin, additional, and Omer, Saad B., additional

Published
2023
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8. Can long-term COVID-19 vaccination be improved by serological surveillance?: a modeling study for Mozambique

Author

Liu, Carol Y, primary, Shioda, Kayoko, additional, Kraay, Alicia, additional, Massora, Sergio, additional, de Jesus, Auria, additional, Massinga, Arsenia, additional, Monjane, Celso, additional, Omer, Saad B, additional, Jenness, Samuel M, additional, Nelson, Kristin, additional, Flasche, Stefan Y, additional, Mandomando, Inacio, additional, and Lopman, Benjamin A, additional

Published
2023
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10. Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021

Author

Kiti, Moses C., primary, Aguolu, Obianuju G., additional, Zelaya, Alana, additional, Chen, Holin Y., additional, Ahmed, Noureen, additional, Battross, Jonathan, additional, Liu, Carol Y., additional, Nelson, Kristin N., additional, Jenness, Samuel M., additional, Melegaro, Alessia, additional, Ahmed, Faruque, additional, Malik, Fauzia, additional, Omer, Saad B., additional, and Lopman, Ben A., additional

Published
2022
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11. Factors influencing the decision to receive seasonal influenza vaccination among US corporate non-healthcare workers

Author

Aguolu, Obianuju Genevieve, primary, Willebrand, Kathryn, additional, Elharake, Jad A., additional, Qureshi, Hanya M., additional, Kiti, Moses Chapa, additional, Liu, Carol Y., additional, Restrepo Mesa, Ana, additional, Nelson, Kristin, additional, Jenness, Samuel, additional, Melegaro, Alessia, additional, Ahmed, Faruque, additional, Yildirim, Inci, additional, Malik, Fauzia A., additional, Lopman, Benjamin, additional, and Omer, Saad B., additional

Published
2022
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16. Rapid Review of Social Contact Patterns During the COVID-19 Pandemic

Author

Liu, Carol Y., primary, Berlin, Juliette, additional, Kiti, Moses C., additional, Del Fava, Emanuele, additional, Grow, André, additional, Zagheni, Emilio, additional, Melegaro, Alessia, additional, Jenness, Samuel M., additional, Omer, Saad B., additional, Lopman, Benjamin, additional, and Nelson, Kristin, additional

Published
2021
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17. Social contact patterns among employees in 3 U.S. companies during early phases of the COVID-19 pandemic, April to June 2020

Author

Kiti, Moses C., primary, Aguolu, Obianuju G., additional, Liu, Carol Y., additional, Mesa, Ana R., additional, Regina, Rachel, additional, Willebrand, Kathryn, additional, Couzens, Chandra, additional, Bartelsmeyer, Tilman, additional, Nelson, Kristin, additional, Jenness, Samuel, additional, Riley, Steven, additional, Melegaro, Alessia, additional, Ahmed, Faruque, additional, Malik, Fauzia, additional, Lopman, Ben, additional, and Omer, Saad B., additional

Published
2020
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20. Effectiveness of Direct-acting Antivirals for the Treatment of Chronic Hepatitis C in Rwanda: A Retrospective Study.

Author

Nsanzimana, Sabin, Penkunas, Michael J, Liu, Carol Y, Sebuhoro, Dieudonne, Ngwije, Alida, Remera, Eric, Umutesi, Justine, Ntirenganya, Cyprien, Mugeni, Soline D, and Serumondo, Janvier

Subjects
DRUG efficacy, CHRONIC hepatitis C, HEALTH services accessibility, TRAVEL, ANTIVIRAL agents, RETROSPECTIVE studies, RNA, POPULATION geography, COMPARATIVE studies, DESCRIPTIVE statistics, LOGISTIC regression analysis, LONGITUDINAL method, EVALUATION
Abstract

Background Direct-acting antivirals (DAAs) are becoming accessible in sub-Saharan Africa. This study examined the effectiveness of DAAs in patients treated through the Rwandan national health system and identified factors associated with treatment outcomes. Methods This retrospective study used data from the national hepatitis C virus (HCV) program for patients who initiated DAAs between November 2015 and March 2017. Sustained virological response at 12 weeks after treatment (SVR12) was the primary outcome. Logistic regression models were fit to estimate the relationship between patients' clinical and demographic characteristics and treatment outcome. Results 894 patients started treatment during the study period; 590 completed treatment and had SVR12 results. Among the 304 patients without SVR12 results, 48 were lost to follow-up and 256 had no SVR12 results but clinical data indicated they likely completed treatment; these patients were classified as nonvirological failure because viral clearance could not be determined. In a per-protocol analysis of 590 patients with SVR12 results, SVR12 was achieved in 540 (92%), and virological failure occurred in 50 (8%). Pretreatment HCV RNA above the median split was associated with virological failure. Intention-to-treat analyses including all patients showed that SVR12 was achieved in 540 (60%), with nonvirological failure in 304 (34%) and virological failure in 50 (6%). Patients in Western Province were more likely to experience nonvirological failure than patients in Kigali, likely owing to the 5–7-hour travel required to access testing and treatment. Conclusions DAAs were effective when implemented through the Rwandan national health system. Decentralization and enhanced financing are underway in Rwanda, which could improve access to treatment and follow-up as the country prepares for HCV elimination. [ABSTRACT FROM AUTHOR]

Published
2021
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21. Risk factors for viral hepatitis C infection in Rwanda: Results from a Nationwide Screening Program

Author

Makuza, Jean Damascene, primary, Liu, Carol Y, additional, Ntihabose, Corneille Killy, additional, Dushimiyimana, Donatha, additional, Umuraza, Sabine, additional, Nisingizwe, Marie Paul, additional, Umutesi, Justine, additional, Serumondo, Janvier, additional, Mugeni, Soline Dusabeyesu, additional, Semakula, Muhamed, additional, Gupta, Neil, additional, Hellard, Margaret, additional, and Nsanzimana, Sabin, additional

Published
2019
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25. Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol.

Author

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, and Omer SB

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., Competing Interests: Competing interests No competing interests were disclosed.

Published
2023
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26. Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.

Author

Kiti MC, Aguolu OG, Zelaya A, Chen HY, Ahmed N, Battross J, Liu CY, Nelson KN, Jenness SM, Melegaro A, Ahmed F, Malik F, Omer SB, and Lopman BA

Abstract

Non-pharmaceutical interventions minimize social contacts, hence the spread of SARS-CoV-2. We quantified two-day contact patterns among USA employees from 2020-2021 during the COVID-19 pandemic. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic diaries. Mean (standard deviation) contacts reported by 1,456 participants were 2.5 (2.5), 8.2 (7.1), 9.2 (7.1) and 10.1 (9.5) across round 1 (April-June 2020), 2 (November 2020-January 2021), 3 (June-August 2021), and 4 (November-December 2021), respectively. Between round 1 and 2, we report a 3-fold increase in the mean number of contacts reported per participant with no major increases from round 2-4. We modeled SARS-CoV-2 transmission at home, work, and community. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained very low in work settings. Contact data are important to parameterize models of infection transmission and control., Teaser: Changes in social contact patterns shape disease dynamics at workplaces in the USA., Competing Interests: Competing interests: None

Published
2022
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