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Investigating the Relationship Between Climatic Factors and Malaria Cases in the Municipality of Beira Using Flexible Smoothing Regression

Article scientifique 2023 Anglais

Résumé

Abstract Background: Malaria, a prominent health concern globally, exhibits a strong correlation with climatic determinants. With the changing global climate, understanding this relationship becomes imperative in crafting preventive strategies against the disease. Objectives: This research aimed to ascertain the relationships between climatic variables and malaria incidence in Beira City between 2012 and 2020, as well as project the potential implications of climate change on future malaria transmission. Methods: The study deployed the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) with a flexible smoothing function to probe the associations between climate variables and weekly malaria incidence. It further evaluated the potential repercussions of climate change on malaria transmission under different emission trajectories. Results: Significant associations were found between climatic factors and malaria incidence. The findings indicated that recent rainfall (within the last three weeks) and relative humidity (over the past four weeks) had a positive impact on malaria incidence. Conversely, the temperature from the previous week and other time-related variables had a negative effect. Future projections under different emission scenarios (RCP2.6, RCP4.6, and RCP8.5) anticipate a decline in malaria incidence by 2030. Conclusion: Climatic variables play a pivotal role in influencing malaria incidence. As such, they should be at the forefront of considerations for effective malaria prevention and control strategies. Moreover, the study provides invaluable insights that can guide public health decisions, emphasizing the need to address the potential repercussions of climate change on malaria transmission.

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Muleia, R., Karim, M., Maúre, G., Américo, J., Adjei, I., Marrufo, T. (2023). Investigating the Relationship Between Climatic Factors and Malaria Cases in the Municipality of Beira Using Flexible Smoothing Regression. https://doi.org/10.21203/rs.3.rs-3639558/v1

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Auteur(s)

Rachid Muleia Md. Rezaul Karim Genito Maúre José Américo Isaac Adjei Tatiana Marrufo

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