Association of climate factors with dengue incidence in Bangladesh, Dhaka City: A count regression approach

Sorif Hossain; Md Momin Islam; Md Abid Hasan; Promit Barua Chowdhury; Imtiaj Ahmed Easty; Md Kamruzzaman Tusar; Md Bazlur Rashid; Kabirul Bashar

doi:10.1016/j.heliyon.2023.e16053

Association of climate factors with dengue incidence in Bangladesh, Dhaka City: A count regression approach

Heliyon. 2023 May 5;9(5):e16053. doi: 10.1016/j.heliyon.2023.e16053. eCollection 2023 May.

Authors

Sorif Hossain¹, Md Momin Islam², Md Abid Hasan³, Promit Barua Chowdhury⁴, Imtiaj Ahmed Easty³, Md Kamruzzaman Tusar⁵, Md Bazlur Rashid⁶, Kabirul Bashar⁷

Affiliations

¹ Department of Statistics, Noakhali Science and Technology University, Bangladesh.
² Department of Meteorology, University of Dhaka, Dhaka, 1000, Bangladesh.
³ Department of Oceanography, Noakhali Science and Technology University, Bangladesh.
⁴ Institute of Statistical Research and Training, Bangladesh.
⁵ Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Bangladesh.
⁶ Bangladesh Meteorological Department, Bangladesh.
⁷ Department of Zoology, Jahangirnagar University, Bangladesh.

Abstract

Background: In Bangladesh, particularly in Dhaka city, dengue fever is a major factor in serious sickness and hospitalization. The weather influences the temporal and geographical spread of the vector-borne disease dengue in Dhaka. As a result, rainfall and ambient temperature are considered macro factors influencing dengue since they have a direct impact on Aedes aegypti population density, which changes seasonally dependent on these critical variables. This study aimed to clarify the relationship between climatic variables and the incidence of dengue disease.

Methods: A total of 2253 dengue and climate data were used for this study. Maximum and minimum temperature (°C), humidity (grams of water vapor per kilogram of air g.kg^-1), rainfall (mm), sunshine hour (in (average) hours per day), and wind speed (knots (kt)) in Dhaka were considered as the independent variables for this study which trigger the dengue incidence in Dhaka city, Bangladesh. Missing values were imputed using multiple imputation techniques. Descriptive and correlation analyses were performed for each variable and stationary tests were observed using Dicky Fuller test. However, initially, the Poisson model, zero-inflated regression model, and negative binomial model were fitted for this problem. Finally, the negative binomial model is considered the final model for this study based on minimum AIC values.

Results: The mean of maximum and minimum temperature, wind speed, sunshine hour, and rainfall showed some fluctuations over the years. However, a mean number of dengue cases reported a higher incidence in recent years. Maximum and minimum temperature, humidity, and wind speed were positively correlated with dengue cases. However, rainfall and sunshine hours were negatively associated with dengue cases. The findings showed that factors such as maximum temperature, minimum temperature, humidity, and windspeed are crucial in the transmission cycles of dengue disease. On the other hand, dengue cases decreased with higher levels of rainfall.

Conclusion: The findings of this study will be helpful for policymakers to develop a climate-based warning system in Bangladesh.

Keywords: Bangladesh; Climate factors; Count regression; Dengue incidence.