title: Anopheles atroparvus density modeling using MODIS NDVI in a former malarious area in Portugal.
abstract: Malaria is dependent on environmental factors and considered as potentially re-emerging in temperate regions. Remote sensing data have been used successfully for monitoring environmental conditions that influence the patterns of such arthropod vector-borne diseases. Anopheles atroparvus density data were collected from 2002 to 2005, on a bimonthly basis, at three sites in a former malarial area in Southern Portugal. The development of the Remote Vector Model (RVM) was based upon two main variables: temperature and the Normalized Differential Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite. Temperature influences the mosquito life cycle and affects its intra-annual prevalence, and MODIS NDVI was used as a proxy for suitable habitat conditions. Mosquito data were used for calibration and validation of the model. For areas with high mosquito density, the model validation demonstrated a Pearson correlation of 0.68 (p<0.05) and a modelling efficiency/Nash-Sutcliffe of 0.44 representing the model's ability to predict intra- and inter-annual vector density trends. RVM estimates the density of the former malarial vector An. atroparvus as a function of temperature and of MODIS NDVI. RVM is a satellite data-based assimilation algorithm that uses temperature fields to predict the intra- and inter-annual densities of this mosquito species using MODIS NDVI. RVM is a relevant tool for vector density estimation, contributing to the risk assessment of transmission of mosquito-borne diseases and can be part of the early warning system and contingency plans providing support to the decision making process of relevant authorities.
authors: Departmento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Campus da Caparica 2829-516 Monte de Caparica, Portugal.
authors: Pedro M
authors: PM
authors: Lourenço
authors: Carla A
authors: CA
authors: Sousa
authors: Júlia
authors: J
authors: Seixas
authors: Pedro
authors: P
authors: Lopes
authors: Maria T
authors: MT
authors: Novo
authors: A Paulo G
authors: AP
authors: Almeida
mesh_terms: D000465:Algorithms; D000818:Animals; D000852:Anopheles / Q000502:physiology*; D004784:Environmental Monitoring / Q000379:methods; D007303:Insect Vectors; D008018:Life Cycle Stages; D008288:Malaria / Q000635:transmission*; D008962:Models, Theoretical; D011156:Population Density; D011158:Population Growth; D011174:Portugal; D058998:Remote Sensing Technology; D018531:Spacecraft; D013696:Temperature