A Novel Approach Towards Prediction of Mosquito-Borne Diseases
Communicable diseases, particularly vector-borne diseases, are a leading cause of morbidity and mortality worldwide. In the age of big data, answering broad-scale, basic issues regarding the nuanced nature of these diseases would increasingly necessitate the synthesis of diverse datasets to produce new biological information. Data mining and deep learning have the potential to make important advances in understanding fundamental aspects of vector-host-pathogen interactions, and their use in this area should be welcomed. Data mining and machine learning approaches such as deep learning lag in this area and should be used in conjunction with existing methods to speed hypothesis and information generation. Deep learning is used in this research to forecast mosquito-borne diseases based on environmental factors.
 Katrin Kuhn, Diarmid Campbell-Lendrum, Andy Haines, Jonathan Cox ‘Using Climate to Predict Infectious Disease Outbreaks: A Review’ (WHO/SDE/OEH/04.01) https://www.who.int/globalchange/publications/en/oeh0401.pdf
 Vector Borne Diseases
 Müller R., Reuss F., Kendrovski V., Montag D. (2019) Vector-Borne Diseases. In: Marselle M., Stadler J., Korn H., Irvine K., Bonn A. (eds) Biodiversity and Health in the Face of Climate Change. Springer, Cham. https://doi.org/10.1007/978-3-030-02318-8_4
 Ahmed, T., Hyder, M. Z., Liaqat, I., & Scholz, M. (2019). Climatic Conditions: Conventional and Nanotechnology-Based Methods for the Control of Mosquito Vectors Causing Human Health Issues. International journal of environmental research and public health, 16(17), 3165. https://doi.org/10.3390/ijerph16173165
 Fouque, F., Reeder, J.C. Impact of past and on-going changes on climate and weather on vector-borne diseases transmission: a look at the evidence. Infect Dis Poverty 8, 51 (2019). https://doi.org/10.1186/s40249-019-0565-1
 Peter Bull, Isaac Slavitt, Greg Lipstein. (2016). Harnessing the Power of the Crowd to Increase Capacity for Data Science in the Social Sector; arXiv:1606.07781v1 [cs.HC]
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