Titre:	Regionalization of a landscape-based hazard index of malaria transmission : an example of the State of Amapá, Brazil
Auteur(s):	Zhichao, Li Catry, Thibault Dessay, Nadine Gurgel, Helen da Costa Almeida, Cláudio Aparecido de Barcellos, Christovam Roux, Emmanuel
Assunto::	Malária Amazônia
Date de publication:	2017
Editeur:	MDPI
Référence bibliographique:	ZHICHAO, Li et al. Regionalization of a landscape-based hazard index of malaria transmission: an example of the State of Amapá, Brazil. Data, v. 2, n. 4, 37, 2017. DOI: https://doi.org/10.3390/data2040037. Disponível em: https://www.mdpi.com/2306-5729/2/4/37. Acesso em: 11 dez. 2019.
Abstract:	Identifying and assessing the relative effects of the numerous determinants of malaria transmission, at different spatial scales and resolutions, is of primary importance in defining control strategies and reaching the goal of the elimination of malaria. In this context, based on a knowledge-based model, a normalized landscape-based hazard index (NLHI) was established at a local scale, using a 10 m spatial resolution forest vs. non-forest map, landscape metrics and a spatial moving window. Such an index evaluates the contribution of landscape to the probability of human-malaria vector encounters, and thus to malaria transmission risk. Since the knowledge-based model is tailored to the entire Amazon region, such an index might be generalized at large scales for establishing a regional view of the landscape contribution to malaria transmission. Thus, this study uses an open large-scale land use and land cover dataset (i.e., the 30 m TerraClass maps) and proposes an automatic data-processing chain for implementing NLHI at large-scale. First, the impact of coarser spatial resolution (i.e., 30 m) on NLHI values was studied. Second, the data-processing chain was established using R language for customizing the spatial moving window and computing the landscape metrics and NLHI at large scale. This paper presents the results in the State of Amapá, Brazil. It offers the possibility of monitoring a significant determinant of malaria transmission at regional scale.
Licença::	© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
DOI:	https://doi.org/10.3390/data2040037
Collection(s) :	Artigos publicados em periódicos e afins

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