Cécile Chauvel, Philippe Vanhems, Marie-Charlotte Quemin, Marianne Abifadel, Shally Awasthi, Sayera Banu, Silvia Figueiredo Costa, Sara Eyangoh, Monzer Hamze, Zakir Hossain, Bourema Kouriba, Daniel Mukadi-Bamuleka, Francine Ntoumi, Abdoul-Salam Ouedraogo, Phimpha Paboriboune, Jean William Pape, Chan Leakhena Phoeung, Firdausi Qadri, Ana Tereza Ribeiro Vasconcelos, Graciela Russomando, Luc Samison, Marilda Agudo Mendonça Siqueira, Nestani Tukvadze, Jianwei Wang, Florence Komurian Pradel
{"title":"传染病领域GABRIEL网络专业知识的聚类和可视化。","authors":"Cécile Chauvel, Philippe Vanhems, Marie-Charlotte Quemin, Marianne Abifadel, Shally Awasthi, Sayera Banu, Silvia Figueiredo Costa, Sara Eyangoh, Monzer Hamze, Zakir Hossain, Bourema Kouriba, Daniel Mukadi-Bamuleka, Francine Ntoumi, Abdoul-Salam Ouedraogo, Phimpha Paboriboune, Jean William Pape, Chan Leakhena Phoeung, Firdausi Qadri, Ana Tereza Ribeiro Vasconcelos, Graciela Russomando, Luc Samison, Marilda Agudo Mendonça Siqueira, Nestani Tukvadze, Jianwei Wang, Florence Komurian Pradel","doi":"10.1136/bmjgh-2024-017595","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The Global Approach to Biology Research, Infectious diseases and Epidemics in Low-income countries (GABRIEL) network is an international scientific network of 21 centres coordinated by the Merieux Foundation (Lyon, France). Mapping and characterising the similarities and differences in expertise and activities across four major infectious diseases (tuberculosis, antimicrobial-resistant infections, acute respiratory infections and emerging pathogens) among these centres would help to provide a better understanding of the network's capacity. It will also highlight how the applied methodology can enhance information sharing within research networks.</p><p><strong>Methods: </strong>Each centre responded to a questionnaire on their core activities and research themes. An advanced multivariate analysis was performed to relate all items together and highlight new synergies among members of the GABRIEL network. Similarities were found using a clustering algorithm and data were visualised using alluvial plots.</p><p><strong>Results: </strong>This strategy enabled to find new patterns in the GABRIEL network for the implementation of new projects on global health, regardless of geographical proximity or historical connections. Five clusters based on core activities, consisting of 6, 1, 3, 9 and 2 research units, respectively, have been identified, with clusters 1 and 4, including the majority of the units. Four clusters have been defined based on the four major infectious diseases, comprising 7, 3, 5 and 6 research units, respectively.</p><p><strong>Conclusions: </strong>The same methodology could also be applied to identify proximities on other networks of experts or between members of different networks for more efficient research or surveillance global programmes.</p>","PeriodicalId":9137,"journal":{"name":"BMJ Global Health","volume":"10 5","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12086879/pdf/","citationCount":"0","resultStr":"{\"title\":\"Clustering and visualisation of the GABRIEL network expertise in the field of infectious diseases.\",\"authors\":\"Cécile Chauvel, Philippe Vanhems, Marie-Charlotte Quemin, Marianne Abifadel, Shally Awasthi, Sayera Banu, Silvia Figueiredo Costa, Sara Eyangoh, Monzer Hamze, Zakir Hossain, Bourema Kouriba, Daniel Mukadi-Bamuleka, Francine Ntoumi, Abdoul-Salam Ouedraogo, Phimpha Paboriboune, Jean William Pape, Chan Leakhena Phoeung, Firdausi Qadri, Ana Tereza Ribeiro Vasconcelos, Graciela Russomando, Luc Samison, Marilda Agudo Mendonça Siqueira, Nestani Tukvadze, Jianwei Wang, Florence Komurian Pradel\",\"doi\":\"10.1136/bmjgh-2024-017595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>The Global Approach to Biology Research, Infectious diseases and Epidemics in Low-income countries (GABRIEL) network is an international scientific network of 21 centres coordinated by the Merieux Foundation (Lyon, France). Mapping and characterising the similarities and differences in expertise and activities across four major infectious diseases (tuberculosis, antimicrobial-resistant infections, acute respiratory infections and emerging pathogens) among these centres would help to provide a better understanding of the network's capacity. It will also highlight how the applied methodology can enhance information sharing within research networks.</p><p><strong>Methods: </strong>Each centre responded to a questionnaire on their core activities and research themes. An advanced multivariate analysis was performed to relate all items together and highlight new synergies among members of the GABRIEL network. Similarities were found using a clustering algorithm and data were visualised using alluvial plots.</p><p><strong>Results: </strong>This strategy enabled to find new patterns in the GABRIEL network for the implementation of new projects on global health, regardless of geographical proximity or historical connections. Five clusters based on core activities, consisting of 6, 1, 3, 9 and 2 research units, respectively, have been identified, with clusters 1 and 4, including the majority of the units. Four clusters have been defined based on the four major infectious diseases, comprising 7, 3, 5 and 6 research units, respectively.</p><p><strong>Conclusions: </strong>The same methodology could also be applied to identify proximities on other networks of experts or between members of different networks for more efficient research or surveillance global programmes.</p>\",\"PeriodicalId\":9137,\"journal\":{\"name\":\"BMJ Global Health\",\"volume\":\"10 5\",\"pages\":\"\"},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2025-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12086879/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Global Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjgh-2024-017595\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Global Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/bmjgh-2024-017595","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Clustering and visualisation of the GABRIEL network expertise in the field of infectious diseases.
Introduction: The Global Approach to Biology Research, Infectious diseases and Epidemics in Low-income countries (GABRIEL) network is an international scientific network of 21 centres coordinated by the Merieux Foundation (Lyon, France). Mapping and characterising the similarities and differences in expertise and activities across four major infectious diseases (tuberculosis, antimicrobial-resistant infections, acute respiratory infections and emerging pathogens) among these centres would help to provide a better understanding of the network's capacity. It will also highlight how the applied methodology can enhance information sharing within research networks.
Methods: Each centre responded to a questionnaire on their core activities and research themes. An advanced multivariate analysis was performed to relate all items together and highlight new synergies among members of the GABRIEL network. Similarities were found using a clustering algorithm and data were visualised using alluvial plots.
Results: This strategy enabled to find new patterns in the GABRIEL network for the implementation of new projects on global health, regardless of geographical proximity or historical connections. Five clusters based on core activities, consisting of 6, 1, 3, 9 and 2 research units, respectively, have been identified, with clusters 1 and 4, including the majority of the units. Four clusters have been defined based on the four major infectious diseases, comprising 7, 3, 5 and 6 research units, respectively.
Conclusions: The same methodology could also be applied to identify proximities on other networks of experts or between members of different networks for more efficient research or surveillance global programmes.
期刊介绍:
BMJ Global Health is an online Open Access journal from BMJ that focuses on publishing high-quality peer-reviewed content pertinent to individuals engaged in global health, including policy makers, funders, researchers, clinicians, and frontline healthcare workers. The journal encompasses all facets of global health, with a special emphasis on submissions addressing underfunded areas such as non-communicable diseases (NCDs). It welcomes research across all study phases and designs, from study protocols to phase I trials to meta-analyses, including small or specialized studies. The journal also encourages opinionated discussions on controversial topics.