Dengue is one of major public health problems in Indonesia. However, health surveillance as one of important activies for controlling this disease still needs improvement, particularly in predicting the excessing incidence amongst population. Since many factors are associated with the spreading of dengue, it is important to incorporate those factors in the existing dengue surveillance to enhance its predictability.

This literature review was aimed to provide scientific consideration whether any dengue model developed in other countries is applicable for strengthening dengue surveillance. The review was conducted by searching related scientific articles in health journal databases available from University of Melbourne’s electronic library. The criteria to critically appraise the models were: the adequacy of sample size; the appropriateness and adequacy of both the measurements and the sources of dengue outcomes and predictors data; model’s validation; and potential bias.

 Nineteen models were identified of which each model has heir own limitation and potential bias. Therefore, no model could be directly implemented to improve the existing dengue surveillance in Indonesia. Nevertheless, aspects and methods in constructing some models, such as the importance of incorporating various predictors; the importance of determining area or community risk level; and the usefulness of employing Geographical Information System (GIS) technology could be considered. Subsequently, this review recommends that further studies for developing region-based prediction models should be proposed and conducted in the future.