Confounding effects of climatic factors temporally contribute to the prevalence of malaria. In this study, we explore a new framework for assessment and identification of hidden ecological factors to the incidence of malaria. A statistical technique, partial least squares path modeling and exploratory factor analysis, is employed to identify hidden ecological factors. Three hidden factors are identified: Factor I is related to minimum temperature and relative humidity, Factor II is related to maximum temperature and solar radiation and Factor III is related to precipitation and wind speed, respectively. Factor I is identified as the most influential hidden ecological factor of malaria incidence in the study area, as evaluated by communality and Dillon-Goldstein’s indices.
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An assessment on the hidden ecological factors of the incidence of malaria
Published: 09 June 2017 by MDPI in DIGITALISATION FOR A SUSTAINABLE SOCIETY session International Forum on Ecology of Information Studies
Keywords: Malaria incidence; Climatic factors; Structural equation modeling; Partial least square model and Hidden factors