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Janko MM, Araujo AL, Ascencio EJ, Guedes GR, Vasco LE, Santos RO, Damasceno CP, Medrano PG, Chacón-Uscamaita PR, Gunderson AK, O'Malley S, Kansara PH, Narvaez MB, Coombes C, Pizzitutti F, Salmon-Mulanovich G, Zaitchik BF, Mena CF, Lescano AG, Barbieri AF, Pan WK. Study protocol: improving response to malaria in the Amazon through identification of inter-community networks and human mobility in border regions of Ecuador, Peru and Brazil. BMJ Open 2024; 14:e078911. [PMID: 38626977 PMCID: PMC11029361 DOI: 10.1136/bmjopen-2023-078911] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 02/29/2024] [Indexed: 04/19/2024] Open
Abstract
INTRODUCTION Understanding human mobility's role in malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission. METHODS We measure community connectivity across the study area using a respondent driven sampling design among key informants who are at least 18 years of age. 45 initial communities will be selected: 10 in Brazil, 10 in Ecuador and 25 in Peru. Participants will be recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses will be ranked and the 2-3 most connected communities will then be selected and surveyed. This process will be repeated for a third round of data collection. Community network matrices will be linked with each country's malaria surveillance system to test the effects of mobility on disease risk. ETHICS AND DISSEMINATION This study protocol has been approved by the institutional review boards of Duke University (USA), Universidad San Francisco de Quito (Ecuador), Universidad Peruana Cayetano Heredia (Peru) and Universidade Federal Minas Gerais (Brazil). Results will be disseminated in communities by the end of the study.
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Affiliation(s)
- Mark M Janko
- Duke Global Health Institute, Durham, North Carolina, USA
| | - Andrea L Araujo
- Instituto de Geografia, Universidad San Francisco de Quito, Quito, Ecuador
| | - Edson J Ascencio
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Gilvan R Guedes
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Luis E Vasco
- Instituto de Geografia, Universidad San Francisco de Quito, Quito, Ecuador
| | - Reinaldo O Santos
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Camila P Damasceno
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | | | - Pamela R Chacón-Uscamaita
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Annika K Gunderson
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Sara O'Malley
- Duke University Nicholas School of the Environment, Durham, North Carolina, USA
| | - Prakrut H Kansara
- Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Manuel B Narvaez
- Instituto de Geografia, Universidad San Francisco de Quito, Quito, Ecuador
| | - Carolina Coombes
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | | | - Benjamin F Zaitchik
- Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Carlos F Mena
- Instituto de Geografia, Universidad San Francisco de Quito, Quito, Ecuador
| | - Andres G Lescano
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Alisson F Barbieri
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - William K Pan
- Duke Global Health Institute, Durham, North Carolina, USA
- Duke University Nicholas School of the Environment, Durham, North Carolina, USA
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Janko MM, Araujo AL, Ascencio EJ, Guedes GR, Vasco LE, Santos RA, Damasceno CP, Medrano PG, Chacón-Uscamaita PR, Gunderson AK, O’Malley S, Kansara PH, Narvaez MB, Coombes CS, Pizzitutti F, Salmon-Mulanovich G, Zaitchik BF, Mena CF, Lescano AG, Barbieri AF, Pan WK. Network Profile: Improving Response to Malaria in the Amazon through Identification of Inter-Community Networks and Human Mobility in Border Regions of Ecuador, Peru, and Brazil. medRxiv 2023:2023.11.29.23299202. [PMID: 38076857 PMCID: PMC10705622 DOI: 10.1101/2023.11.29.23299202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Objectives Understanding human mobility's role on malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission. Design A community-level network survey. Setting We collect data on community connectivity along three river systems in the Amazon basin: the Pastaza river corridor spanning the Ecuador-Peru border; and the Amazon and Javari river corridors spanning the Brazil-Peru border. Participants We interviewed key informants in Brazil, Ecuador, and Peru, including from indigenous communities: Shuar, Achuar, Shiwiar, Kichwa, Ticuna, and Yagua. Key informants are at least 18 years of age and are considered community leaders. Primary outcome Weekly, community-level malaria incidence during the study period. Methods We measure community connectivity across the study area using a respondent driven sampling design. Forty-five communities were initially selected: 10 in Brazil, 10 in Ecuador, and 25 in Peru. Participants were recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses were ranked and the 2-3 most connected communities were then selected and surveyed. This process was repeated for a third round of data collection. Community network matrices will be linked with eadch country's malaria surveillance system to test the effects of mobility on disease risk. Findings To date, 586 key informants were surveyed from 126 communities along the Pastaza river corridor. Data collection along the Amazon and Javari river corridors is ongoing. Initial results indicate that network sampling is a superior method to delineate migration flows between communities. Conclusions Our study provides measures of mobility and connectivity in rural settings where traditional approaches are insufficient, and will allow us to understand mobility's effect on malaria transmission.
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Affiliation(s)
- Mark M. Janko
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Andrea L. Araujo
- Instituto de Geografía, Universidad San Francisco de Quito, Quito, Ecuador
| | - Edson J. Ascencio
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Gilvan R. Guedes
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Luis E. Vasco
- Instituto de Geografía, Universidad San Francisco de Quito, Quito, Ecuador
| | - Reinaldo A. Santos
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Camila P. Damasceno
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Perla G. Medrano
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Pamela R. Chacón-Uscamaita
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Annika K. Gunderson
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Sara O’Malley
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Prakrut H. Kansara
- Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Manuel B. Narvaez
- Instituto de Geografía, Universidad San Francisco de Quito, Quito, Ecuador
| | - Carolina S. Coombes
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | | | - Benjamin F. Zaitchik
- Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Carlos F. Mena
- Instituto de Geografía, Universidad San Francisco de Quito, Quito, Ecuador
| | - Andres G. Lescano
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Alisson F. Barbieri
- Center for Regional Development and Planning (Cedeplar), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - William K. Pan
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
- Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
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