Related Experiment Video
Updated: Jul 4, 2025
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Modeling the effect of climatic conditions and topography on malaria incidence using Poisson regression: a
Ijaz Ul Haq1, Zafar Mehmood2, Gausal Azam Khan3
1Department of Public Health & Nutrition, The University of Haripur, Haripur, Khyber Pakhtunkhwa, Pakistan.
Background:
Malaria has been identified as a crucial vector-borne disease around the globe. The primary aim of this study was to investigate the incidence of malaria in the district of Bannu and its relationship with climatic conditions such as temperature, rainfall, relative humidity, and topography.
Methods:
Secondary data were obtained from the metrological office and government hospitals across the district for 5 years (2013-2017). A Poisson regression model was applied for the statistical analysis.
Results And Discussion:
The number of reported cases of malaria was 175,198. The regression analysis showed that temperature, relative humidity, and rainfall had a significant association (p < 0.05) with malaria incidence. In addition, the topographic variables were significantly associated (p < 0.05) with malaria incidence in the region. The percent variation in the odds ratio of incidence was 4% for every unit increase in temperature and 2% in humidity. In conclusion, this study indicated that the temperature, humidity, rainfall, and topographic variables were significantly associated with the incidence of malaria. Effective malaria control and interventions integrated with climatic factors must be considered to overcome the disease burden.
More Related Videos
09:02An Experimental Model to Study Tuberculosis-Malaria Coinfection upon Natural Transmission of Mycobacterium tuberculosis and Plasmodium berghei
Published on: February 17, 2014
20:36Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Related Concept Videos
01:18Steps in Outbreak Investigation
01:16What is Climate?
01:11Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
01:25Statistical Methods for Analyzing Epidemiological Data
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
01:25Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...