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.