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Statistical modelling of the effects of weather factors on malaria occurrence in Abuja, Nigeria


Citation

Segun, Oguntade Emmanuel and Shohaimi, Shamarina and Nallappan, Meenakshii and Ajibola, Lamidi-Sarumoh Alaba and Salari, Nader (2020) Statistical modelling of the effects of weather factors on malaria occurrence in Abuja, Nigeria. International Journal of Environmental Research and Public Health, 17 (10). art. no. 3474. pp. 1-12. ISSN 1661-7827; ESSN: 1660-4601

Abstract

Background: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria incidence in Abuja, Nigeria. Methodology/Principal Findings: monthly data on malaria incidence and weather variables were collected in Abuja from the year 2000 to 2013. The analysis of count outcomes was based on generalized linear models, while Pearson correlation analysis was undertaken at the bivariate level. The results showed more malaria incidence in the months with the highest rainfall recorded (June–August). Based on the negative binomial model, every unit increase in humidity corresponds to about 1.010 (95% confidence interval (CI), 1.005–1.015) times increase in malaria cases while the odds of having malaria decreases by 5.8% for every extra unit increase in temperature: 0.942 (95% CI, 0.928–0.956). At lag 1 month, there was a significant positive effect of rainfall on malaria incidence while at lag 4, temperature and humidity had significant influences. Conclusions: malaria remains a widespread infectious disease among the local subjects in the study area. Relative humidity was identified as one of the factors that influence a malaria epidemic at lag 0 while the biggest significant influence of temperature was observed at lag 4. Therefore, emphasis should be given to vector control activities and to create public health awareness on the proper usage of intervention measures such as indoor residual sprays to reduce the epidemic especially during peak periods with suitable weather conditions.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
DOI Number: https://doi.org/10.3390/ijerph17103474
Publisher: MDPI
Keywords: Negative binomial models; Weather variables; Malaria; Nigeria
Depositing User: Nabilah Mustapa
Date Deposited: 16 Jun 2020 06:39
Last Modified: 16 Jun 2020 06:39
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/ijerph17103474
URI: http://psasir.upm.edu.my/id/eprint/36968
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