Variability Effects of Meteorological Factors on Reported Malaria Cases in Kano and Lagos States of Nigeria
Article Sidebar
Main Article Content
Abstract: Malaria is one of life’s threatening disease that contributed significantly to morbidity and mortality in Nigeria. The variability effects of meteorological factors between the Northern and Southern region of Nigeria on malaria transmission remain unclear and not well researched. This research was aimed at comparing the non-linear effects of seasonal, trend and meteorological variables on monthly malaria cases in Kano and Lagos State of Nigeria. The monthly malaria cases for age group above 5-year for Kano and Lagos State were obtained from DHIS for the period of January, 2016 to December, 2022. Also, the predictors/meteorological variables (Rainfall, Relative Humidity, Minimum Temperature and Maximum Temperature) were obtained from Nigeria Meteorological Agent. Generalized Additive Model was fitted using Negative Binomial to apply smooth function to estimate and compare the effects of the selected predictors on the malaria transmission in Kano and Lagos States. Rainfall and Maximum temperature were found not significant in explaining the effect of malaria transmission. Malaria transmission was found to be seasonal and varying in Kano State with highest transmission between September and October while the seasonal effect was reduced to linear in Lagos State. The long term trend had a significant increasing effect on malaria transmission in Kano Sate compared to non-significant effect in Lagos State. The effect of Relative Humidity was reduced to linear and increasing in the both State. Paying attention to the variability in the influence of season, trend and meteorological variables on malaria transmission will enhance respective State Government to develop an early warning and awareness that will help in controlling the malaria outbreak in their State.
Downloads
Downloads
References
Dabaro, D., Birhanu, Z., Negash, A. (2021). Effects of rainfall, temperature and topography on malaria incidence in elimination targeted district of Ethiopia. Malar J 20, 104 https://doi.org/10.1186/s12936-021-03641-1. DOI: https://doi.org/10.1186/s12936-021-03641-1
Carrasco-escobar, G., Qquellon, J., Villa, D., & Cava, R. (2021). Time-Varying Effects of Meteorological Variables on Malaria Epidemiology in the Context of Interrupted Control Efforts in the Amazon Rainforest, 2000 – 2017. 8(September). frontiers in Medicine, 1–13. https://doi.org/10.3389/fmed.2021.721515 DOI: https://doi.org/10.3389/fmed.2021.721515
Craig, M. H., et al. (2019). Climate change and malaria: a systematic review. Malaria Journal, 18(1), 1-15
Eunice, A., Wanjoya, A., & Luboobi, L. (2017). Statistical Modeling of Malaria Incidences in Apac District, Uganda. Scientific Research Publishing,901–919. https://doi.org/10.4236/ojs.2017.76063 DOI: https://doi.org/10.4236/ojs.2017.76063
Measure DHS/ICF International. (2013). Demographic and Health Surveys Methodology Standard Recode Manual for DHS6 Version1.0, 145. Retrieved from https://dhsprogram.com/pubs/pdf/ DHSG4/Recode7 DHS 10Sep2018DHSG4.pdf
Olayemi, I. K., Ande, A. T., Chita, S., Ibemesi, G., Ayanwale, V. A., & Odeyemi, O. M. (2011). Insecticide susceptibility profile of the principal malaria vector, anopheles gambiae s.l. (diptera: Culicidae), in north-central nigeria. Journal of Vector Borne Diseases, 48(2), 109–112. DOI: https://doi.org/10.3923/jp.2011.109.115
Paaijmans, K. P., et al. (2010). Temperature-dependent development of Anopheles gambiae (Diptera: Culicidae) and its impact on malaria transmission. Journal of Medical entomology, 47(5), 937-944.
Samdi, L. M., Ajayi, J. A., Oguche, S., & Ayanlade, A. (2012). Seasonal variation of malaria parasite density in paediatric population of Northeastern Nigeria. Global Journal of Health Science, 4(2), 103–109. https://doi.org/10.5539/gjhs.v4n2p103 DOI: https://doi.org/10.5539/gjhs.v4n2p103
Salako, L. A., Ajayi, F. O., Sowunmi, A., & Walker, O. (1990). Malaria in Nigeria: A revisit. Annals of Tropical Medicine and Parasitology, 84(5),435–445. https://doi.org/10.1080/00034983.1990.11812493 DOI: https://doi.org/10.1080/00034983.1990.11812493
WHO (2020). World Malaria Report 2020. World Health Organization
Xia, Y., Morrison-beedy, D., Ma, J., Feng, C., Cross, W., & Tu, X. (2012). Modeling Count Outcomes from HIV Risk Reduction Interventions : A Comparison of Competing Statistical Models for Count Responses. Hindawi Publishing Corporation, AIDS Research and Treatment, Volume 2012, Article ID 593569. https://doi.org/10.1155/2012/593569 DOI: https://doi.org/10.1155/2012/593569
Zerihun, T., Zewotir, T. T., & Kebede, E. (2023). Heliyon Seasonal and spatial variations of malaria transmissions in northwest Ethiopia : Evaluating climate and environmental effects using generalized additive model. Heliyon, 9(4), e15252. https://doi.org/10.1016/j.heliyon.2023.e15252 DOI: https://doi.org/10.1016/j.heliyon.2023.e15252
All articles published in our journal are licensed under CC-BY 4.0, which permits authors to retain copyright of their work. This license allows for unrestricted use, sharing, and reproduction of the articles, provided that proper credit is given to the original authors and the source.