Preprint Article Version 1 This version is not peer-reviewed

Mapping Multi-Disease Risk during El Niño: An Ecosyndemic Approach

Version 1 : Received: 26 September 2018 / Approved: 27 September 2018 / Online: 27 September 2018 (06:04:08 CEST)

How to cite: Ramirez, I.J.; Lee, J.; Grady, S.C. Mapping Multi-Disease Risk during El Niño: An Ecosyndemic Approach. Preprints 2018, 2018090534 (doi: 10.20944/preprints201809.0534.v1). Ramirez, I.J.; Lee, J.; Grady, S.C. Mapping Multi-Disease Risk during El Niño: An Ecosyndemic Approach. Preprints 2018, 2018090534 (doi: 10.20944/preprints201809.0534.v1).

Abstract

El Niño is a quasi-periodic pattern of climate variability and extremes often associated with hazards and disease. While El Niño links to individual diseases have been examined, less is known about the cluster of multi-disease risk referred to as an ecosyndemic, which emerges during extreme events. The objective of this study was to explore a mapping approach to represent the spatial distribution of ecosyndemics in Piura, Peru at the district-level during the first few months of 1998. Using geographic information systems and multivariate analysis, two methodologies were employed to map disease overlap of 7 climate-sensitive diseases and construct an ecosyndemic index, which was then mapped and applied to another El Niño period as proof of concept. The main findings showed that many districts across Piura faced multi-disease risk over several weeks in the austral summer of 1998. The distribution of ecosyndemics were spatially clustered in western Piura among 11 districts. Furthermore, the ecosydemic index in 1998 when compared to 1983 showed a strong positive correlation, demonstrating the utility of the index. The study supports PAHO efforts to develop multi-disease based and interprogrammatic approaches to control and prevention, particularly for climate and poverty-related infections in Latin America and the Caribbean.

Subject Areas

syndemic; El Niño; infectious disease; diarrhea; malaria; respiratory; cholera; spatial cluster; GIS

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