Skip Navigation
Skip to contents

Epidemiol Health : Epidemiology and Health

OPEN ACCESS
SEARCH
Search

Author index

Page Path
HOME > Browse articles > Author index
Search
Priyamvada Roy 1 Article
Empirical model for estimating dengue incidence using temperature, rainfall, and relative humidity: a 19-year retrospective analysis in East Delhi
Vishnampettai G. Ramachandran, Priyamvada Roy, Shukla Das, Narendra Singh Mogha, Ajay Kumar Bansal
Epidemiol Health. 2016;38:e2016052.   Published online November 27, 2016
DOI: https://doi.org/10.4178/epih.e2016052
  • 20,004 View
  • 374 Download
  • 33 Web of Science
  • 21 Crossref
AbstractAbstract PDF
Abstract
OBJECTIVES
Aedes mosquitoes are responsible for transmitting the dengue virus. The mosquito lifecycle is known to be influenced by temperature, rainfall, and relative humidity. This retrospective study was planned to investigate whether climatic factors could be used to predict the occurrence of dengue in East Delhi.
METHODS
The number of monthly dengue cases reported over 19 years was obtained from the laboratory records of our institution. Monthly data of rainfall, temperature, and humidity collected from a local weather station were correlated with the number of monthly reported dengue cases. One-way analysis of variance was used to analyse whether the climatic parameters differed significantly among seasons. Four models were developed using negative binomial generalized linear model analysis. Monthly rainfall, temperature, humidity, were used as independent variables, and the number of dengue cases reported monthly was used as the dependent variable. The first model considered data from the same month, while the other three models involved incorporating data with a lag phase of 1, 2, and 3 months, respectively.
RESULTS
The greatest number of cases was reported during the post-monsoon period each year. Temperature, rainfall, and humidity varied significantly across the pre-monsoon, monsoon, and post-monsoon periods. The best correlation between these three climatic factors and dengue occurrence was at a time lag of 2 months.
CONCLUSIONS
This study found that temperature, rainfall, and relative humidity significantly affected dengue occurrence in East Delhi. This weather-based dengue empirical model can forecast potential outbreaks 2-month in advance, providing an early warning system for intensifying dengue control measures.
Summary

Citations

Citations to this article as recorded by  
  • Improving dengue fever predictions in Taiwan based on feature selection and random forests
    Chao-Yang Kuo, Wei-Wen Yang, Emily Chia-Yu Su
    BMC Infectious Diseases.2024;[Epub]     CrossRef
  • Intrauterine Transmission of Zika and Vertical Transfer of Neutralizing Antibodies Detected Immediately at Birth in Oaxaca, Mexico: An Analysis in the Context of Microcephaly
    Alfredo Porras-García, Dina Villanueva-García, Rafael Arnaud-Rios, Nadia García-Lemus, Angélica Castillo-Romero, Mariana Mejía-Flores, Luis Erik Contreras, Liliana Hernández-Castillo, Elva Jiménez-Hernández, Juan Manuel Mejía-Aranguré, Sara A. Ochoa, Juan
    Microorganisms.2024; 12(3): 423.     CrossRef
  • Influence of climatic factors on the life stages of Aedes mosquitoes and vectorial transmission: A review
    Pooja Prasad, Sanjeev Kumar Gupta, Kaushal Kumar Mahto, Gaurav Kumar, Alka Rani, Iyyappan Velan, Deepak Kumar Arya, Himmat Singh
    Journal of Vector Borne Diseases.2024; 61(2): 158.     CrossRef
  • Bayesian spatio-temporal analysis of dengue transmission in Lao PDR
    Mick Soukavong, Kavin Thinkhamrop, Khanittha Pratumchart, Chanthavy Soulaphy, Phonepadith Xangsayarath, Mayfong Mayxay, Sysavanh Phommachanh, Matthew Kelly, Kinley Wangdi, Archie C. A. Clements, Apiporn T. Suwannatrai
    Scientific Reports.2024;[Epub]     CrossRef
  • A Systematic Review on the Distribution and Density of Aedes Species in the Hindu-Kush Himalayan Countries
    Punya Ram Sukupayo, Ram Chandra Poudel, Tirth Raj Ghimire
    Indian Journal of Entomology.2024; : 1.     CrossRef
  • Effects of meteorological factors on dengue incidence in Bangkok city: a model for dengue prediction
    Wilawan Kumharn, Wittaya Piwngam, Oradee Pilahome, Waichaya Ninssawan, Yuttapichai Jankondee, Somboon Chaochaikong
    Modeling Earth Systems and Environment.2023; 9(1): 1215.     CrossRef
  • The effect of temperature on dengue virus transmission by Aedes mosquitoes
    Zhuanzhuan Liu, Qingxin Zhang, Liya Li, Junjie He, Jinyang Guo, Zichen Wang, Yige Huang, Zimeng Xi, Fei Yuan, Yiji Li, Tingting Li
    Frontiers in Cellular and Infection Microbiology.2023;[Epub]     CrossRef
  • A retrospective study of environmental predictors of dengue in Delhi from 2015 to 2018 using the generalized linear model
    Poornima Suryanath Singh, Himanshu K. Chaturvedi
    Scientific Reports.2022;[Epub]     CrossRef
  • The application of geographic information system for dengue epidemic in Southeast Asia: A review on trends and opportunity
    Cipta Estri Sekarrini, Sumarmi, Syamsul Bachri, Didik Taryana, Eggy Arya Giofandi
    Journal of Public Health Research.2022; 11(3): 227990362211041.     CrossRef
  • Application of time series methods for dengue cases in North India (Chandigarh)
    Kumar Shashvat, Rikmantra Basu, Amol P. Bhondekar
    Journal of Public Health.2021; 29(2): 433.     CrossRef
  • Learning from panel data of dengue incidence and meteorological factors in Jakarta, Indonesia
    Karunia Putra Wijaya, Dipo Aldila, K. K. W. Hashita Erandi, Muhammad Fakhruddin, Miracle Amadi, Naleen Ganegoda
    Stochastic Environmental Research and Risk Assessment.2021; 35(2): 437.     CrossRef
  • Dengue risk assessment using multicriteria decision analysis: A case study of Bhutan
    Tsheten Tsheten, Archie C. A. Clements, Darren J. Gray, Kinley Wangdi, Elvina Viennet
    PLOS Neglected Tropical Diseases.2021; 15(2): e0009021.     CrossRef
  • Co-Circulation of All Four Dengue Viruses and Zika Virus in Guerrero, Mexico, 2019
    Daniel Nunez-Avellaneda, Chandra Tangudu, Jacqueline Barrios-Palacios, Carlos Machain-Williams, Luz del Carmen Alarcón-Romero, Ma Isabel Zubillaga-Guerrero, Salatiel Nunez-Avellaneda, Lauren A. McKeen, Israel Canche-Aguilar, Laura Loaeza-Díaz, Bradley J.
    Vector-Borne and Zoonotic Diseases.2021; 21(6): 458.     CrossRef
  • Development and Comparison of Dengue Vulnerability Indices Using GIS-Based Multi-Criteria Decision Analysis in Lao PDR and Thailand
    Sumaira Zafar, Oleg Shipin, Richard E. Paul, Joacim Rocklöv, Ubydul Haque, Md. Siddikur Rahman, Mayfong Mayxay, Chamsai Pientong, Sirinart Aromseree, Petchaboon Poolphol, Tiengkham Pongvongsa, Nanthasane Vannavong, Hans J. Overgaard
    International Journal of Environmental Research and Public Health.2021; 18(17): 9421.     CrossRef
  • Spatial and temporal patterns of dengue incidence in Bhutan: a Bayesian analysis
    Tsheten Tsheten, Archie C.A. Clements, Darren J. Gray, Sonam Wangchuk, Kinley Wangdi
    Emerging Microbes & Infections.2020; 9(1): 1360.     CrossRef
  • Real-time dengue forecast for outbreak alerts in Southern Taiwan
    Yu-Chieh Cheng, Fang-Jing Lee, Ya-Ting Hsu, Eric V. Slud, Chao A. Hsiung, Chun-Hong Chen, Ching-Len Liao, Tzai-Hung Wen, Chiu-Wen Chang, Jui-Hun Chang, Hsiao-Yu Wu, Te-Pin Chang, Pei-Sheng Lin, Hui-Pin Ho, Wen-Feng Hung, Jing-Dong Chou, Hsiao-Hui Tsou, Da
    PLOS Neglected Tropical Diseases.2020; 14(7): e0008434.     CrossRef
  • Forecasting Zoonotic Infectious Disease Response to Climate Change: Mosquito Vectors and a Changing Environment
    Andrew W. Bartlow, Carrie Manore, Chonggang Xu, Kimberly A. Kaufeld, Sara Del Valle, Amanda Ziemann, Geoffrey Fairchild, Jeanne M. Fair
    Veterinary Sciences.2019; 6(2): 40.     CrossRef
  • Forest cover and climate as potential drivers for dengue fever in Sumatra and Kalimantan 2006–2016: a spatiotemporal analysis
    Zida Husnina, Archie C. A. Clements, Kinley Wangdi
    Tropical Medicine & International Health.2019; 24(7): 888.     CrossRef
  • Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk
    Bernard Bett, Delia Grace, Hu Suk Lee, Johanna Lindahl, Hung Nguyen-Viet, Pham-Duc Phuc, Nguyen Huu Quyen, Tran Anh Tu, Tran Dac Phu, Dang Quang Tan, Vu Sinh Nam, Tzai-Hung Wen
    PLOS ONE.2019; 14(11): e0224353.     CrossRef
  • Factors determining dengue outbreak in Malaysia
    Rohani Ahmad, Ismail Suzilah, Wan Mohamad Ali Wan Najdah, Omar Topek, Ibrahim Mustafakamal, Han Lim Lee, Jiang-Shiou Hwang
    PLOS ONE.2018; 13(2): e0193326.     CrossRef
  • Developing a dengue forecast model using machine learning: A case study in China
    Pi Guo, Tao Liu, Qin Zhang, Li Wang, Jianpeng Xiao, Qingying Zhang, Ganfeng Luo, Zhihao Li, Jianfeng He, Yonghui Zhang, Wenjun Ma, Benjamin Althouse
    PLOS Neglected Tropical Diseases.2017; 11(10): e0005973.     CrossRef

Epidemiol Health : Epidemiology and Health
TOP