Evidence map›Paper›PMID 39668959›Full record

ArticleFrontiers in public health2024

Analysis of effects of meteorological variables on dengue incidence in Bangladesh using VAR and Granger causality approach.

Md Jamal Hossain, Nazia Sultana, Anwesha Das, Fariea Nazim Jui, Md Kamrul Islam, Md Mijanoor Rahman, Mohammad Mafizur Rahman

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Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

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3citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Md Jamal HossainDepartment of Applied Mathematics, Noakhali Science and Technology University, Noakhali, Bangladesh.
Nazia SultanaDepartment of Applied Mathematics, Noakhali Science and Technology University, Noakhali, Bangladesh.
Anwesha DasDepartment of Applied Mathematics, Noakhali Science and Technology University, Noakhali, Bangladesh.
Fariea Nazim JuiDepartment of Applied Mathematics, Noakhali Science and Technology University, Noakhali, Bangladesh.
Md Kamrul IslamDepartment of Applied Mathematics, Noakhali Science and Technology University, Noakhali, Bangladesh.
Md Mijanoor RahmanDepartment of Mathematics, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Mohammad Mafizur RahmanSchool of Business, University of Southern Queensland, Toowoomba, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dengue fever is a serious public health issue in Bangladesh, where its incidence rises with the monsoon. Meteorological variables are believed to be responsible factors among others. Therefore, this study examines the effects of meteorological variables (temperature, rainfall, and humidity) on dengue incidence in Bangladesh. While previous studies have examined the relationship between dengue and meteorological variables using single model approaches, this study employs advanced econometric techniques to capture dynamic interactions. Furthermore, in the case of Bangladesh, this type of analysis is necessary due to the fact that dengue outbreak become one of the major issues. However, the analysis related to this issue is not available. Methods: For estimation purposes, the Augmented Dickey-Fuller (ADF) test, Vector Autoregressive (VAR) model, Granger causality tests, Impulse Response Function (IRF), Variance Decomposition (VDC), and Vector Error Correction Model (VECM) are employed. Results: Rainfall has a significant impact on dengue incidence compared to temperature and humidity. The Granger causality test demonstrates that rainfall and dengue incidence are causally related unidirectionally. Rainfall can potentially have a short-term and long-term effect on the incidence of dengue, as per the estimates of the VECM model. Conclusions: These findings will assist policymakers in Bangladesh in developing a dengue fever early warning system depending on climate change. In order to efficiently avoid the spread of dengue in Bangladesh's dengue-endemic urban areas, this study suggests societal monitoring.

Indexed as

DengueHumidityTemperatureBangladeshCausalityDisease OutbreaksHumansIncidenceMeteorological ConceptsModels, StatisticalRaindengue feverGranger causalityimpulse response functionmeteorological variablesVAR modelVECM model

Identifiers

PMID39668959
PMCPMC11634804

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.