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

Author:

Janko Mark M.,Araujo Andrea L.,Ascencio Edson J.,Guedes Gilvan R.,Vasco Luis E.,Santos Reinaldo A.,Damasceno Camila P.,Medrano Perla G.,Chacón-Uscamaita Pamela R.,Gunderson Annika K.,O’Malley Sara,Kansara Prakrut H.,Narvaez Manuel B.,Coombes Carolina S.,Pizzitutti Francesco,Salmon-Mulanovich Gabriela,Zaitchik Benjamin F.,Mena Carlos F.,Lescano Andres G.,Barbieri Alisson F.,Pan William K.

Abstract

AbstractObjectivesUnderstanding 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.DesignA community-level network surveySettingWe 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.ParticipantsWe 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 outcomeWeekly, community-level malaria incidence during the study period.MethodsWe 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.FindingsTo 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.ConclusionsOur 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.Strengths and LimitationsStrength: Community networks are unmeasured in rural areas of the Amazon, but have been shown to capture human mobility in other regions of the world.Strength: Our design captures social, economic, and human wellbeing connectivity and migration in key indigenous communities along the Peru-Ecuador border as well as in the most important confluence for the Amazon River located in the Brazil-Peru-Colombia tri-country intersection.Strength: Our design quantifies cross-border human mobility between communities, as well as the magnitude, timing, duration, and reason for mobility, which provides actionable information for malaria control and elimination programs in the regionLimitation: Migration decisions occur at individual and household levels that are coupled with environmental change and seasonality, meaning that our measures of community mobility may not be stable over time and we may be subject to ecological fallacy by inferring individual risk from community networks.Limitation: Our study relies on passive surveillance to test the community network/human mobility link with malaria. However, there exist cases that are asymptomatic, unreported (i.e., treated with traditional medicines), or that occur in our community network but are reported elsewhere. The extent of these cases can significantly increase uncertainty.FundingThis work was supported by the US National Institutes of Health (R01 AI51056; William K. Pan, PI) and by a grant from the Duke Climate and Health Initiative (William Pan, PI). PRC-U was supported by CONCYTEC through the PROCIENCIA program under the call entitled “Science, Technology and Innovation Thesis and Internships” according to the contract PE501081617-2022. AGL, CSC, EJA and PRC-U were sponsored by Emerge, the Emerging Diseases Epidemiology Research Training grant D43 TW007393 awarded by the Fogarty International Center of the US National Institutes of Health.Competing InterestsWe declare no conflicts

Publisher

Cold Spring Harbor Laboratory

Reference45 articles.

1. World malaria report 2022 [Internet]. [cited 2022 Dec 13]. Available from: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2022

2. PAHO. Pan American Health Organization / World Health Organization. 2019. PAHO’s ‘Municipalities for Zero Malaria’ initiative to tackle malaria at the local level.

3. The Hitchhiking Parasite: Why Human Movement Matters to Malaria Transmission and What We Can Do About It

4. Modeling asymptomatic infections and workrelated human circulation as drivers of unstable malaria transmission in low-prevalence areas: A study in the Northern Peruvian Amazon;Acta Trop,2019

5. A Large Proportion of P. falciparum Isolates in the Amazon Region of Peru Lack pfhrp2 and pfhrp3: Implications for Malaria Rapid Diagnostic Tests

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3