Malaria Transmission and Spillover across the Peru–Ecuador Border: A Spatiotemporal Analysis

Annika K. Gunderson, Rani E. Kumar, Cristina Recalde-Coronel, Luis E. Vasco, Andree Valle-Campos, Carlos F. Mena, Benjamin F. Zaitchik, Andres G. Lescano, William K. Pan and Mark M. Janko
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Annika K. Gunderson: Duke Global Health Institute, Duke University, Durham, NC 27710, USA
Rani E. Kumar: Nicholas School of the Environment, Duke University, Durham, NC 27710, USA
Cristina Recalde-Coronel: Department of Earth and Planetary Sciences, Johns Hopkins University, 327 Olin Hall, 3400 N. Charles Street, Baltimore, MD 21218, USA
Luis E. Vasco: Instituto de Geografía, Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, Quito 170104, Ecuador
Andree Valle-Campos: Emerge, Emerging Diseases and Climate Change Research Unit, Universidad Cayetano Peruana Heredia, San Martín de Porres 15102, Peru
Carlos F. Mena: Instituto de Geografía, Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, Quito 170104, Ecuador
Benjamin F. Zaitchik: Department of Earth and Planetary Sciences, Johns Hopkins University, 327 Olin Hall, 3400 N. Charles Street, Baltimore, MD 21218, USA
Andres G. Lescano: Emerge, Emerging Diseases and Climate Change Research Unit, Universidad Cayetano Peruana Heredia, San Martín de Porres 15102, Peru
William K. Pan: Duke Global Health Institute, Duke University, Durham, NC 27710, USA
Mark M. Janko: Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA

IJERPH, 2020, vol. 17, issue 20, 1-9

Abstract: Border regions have been implicated as important hot spots of malaria transmission, particularly in Latin America, where free movement rights mean that residents can cross borders using just a national ID. Additionally, rural livelihoods largely depend on short-term migrants traveling across borders via the Amazon’s river networks to work in extractive industries, such as logging. As a result, there is likely considerable spillover across country borders, particularly along the border between Peru and Ecuador. This border region exhibits a steep gradient of transmission intensity, with Peru having a much higher incidence of malaria than Ecuador. In this paper, we integrate 13 years of weekly malaria surveillance data collected at the district level in Peru and the canton level in Ecuador, and leverage hierarchical Bayesian spatiotemporal regression models to identify the degree to which malaria transmission in Ecuador is influenced by transmission in Peru. We find that increased case incidence in Peruvian districts that border the Ecuadorian Amazon is associated with increased incidence in Ecuador. Our results highlight the importance of coordinated malaria control across borders.

Keywords: malaria; human mobility; spillover; spatiotemporal modeling; Bayesian methods (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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