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Kakarla SG, Kondeti PK, Vavilala HP, Boddeda GSB, Mopuri R, Kumaraswamy S, Kadiri MR, Mutheneni SR. Weather integrated multiple machine learning models for prediction of dengue prevalence in India. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2023; 67:285-297. [PMID: 36380258 PMCID: PMC9666965 DOI: 10.1007/s00484-022-02405-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 07/21/2022] [Accepted: 11/04/2022] [Indexed: 05/11/2023]
Abstract
Dengue is a rapidly spreading viral disease transmitted to humans by Aedes mosquitoes. Due to global urbanization and climate change, the number of dengue cases are gradually increasing in recent decades. Hence, an early prediction of dengue continues to be a major concern for public health in countries with high prevalence of dengue. Creating a robust forecast model for the accurate prediction of dengue is a complex task and can be done through various data modelling approaches. In the present study, we have applied vector auto regression, generalized boosted models, support vector regression, and long short-term memory (LSTM) to predict the dengue prevalence in Kerala state of the Indian subcontinent. We consider the number of dengue cases as the target variable and weather variables viz., relative humidity, soil moisture, mean temperature, precipitation, and NINO3.4 as independent variables. Various analytical models have been applied on both datasets and predicted the dengue cases. Among all the models, the LSTM model was outperformed with superior prediction capability (RMSE: 0.345 and R2:0.86) than the other models. However, other models are able to capture the trend of dengue cases but failed in predicting the outbreak periods when compared to LSTM. The findings of this study will be helpful for public health agencies and policymakers to draw appropriate control measures before the onset of dengue. The proposed LSTM model for dengue prediction can be followed by other states of India as well.
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Affiliation(s)
- Satya Ganesh Kakarla
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Phani Krishna Kondeti
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
| | - Hari Prasad Vavilala
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
| | - Gopi Sumanth Bhaskar Boddeda
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
| | - Rajasekhar Mopuri
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
| | - Sriram Kumaraswamy
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Madhusudhan Rao Kadiri
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Srinivasa Rao Mutheneni
- ENVIS Resource Partner On Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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