Malaria transmission is associated with climatic variability and vector control interventions, and understanding their long-term and lagged associations is critical in regions approaching elimination.This 23-year retrospective study examined associations between climatic factors and malaria incidence in eight base counties of Sistan and Baluchestan Province, southeast Iran.Negative Binomial and Zero-Inflated Poisson regression models were applied to account for overdispersion and excess zeros, incorporating 1-3 month lagged exposures.Seasonal patterns were assessed using linear mixed-effects models, and the impact of indoor residual spraying (IRS) population coverage (2013-2023) was evaluated using a negative binomial generalized linear model.Malaria incidence declined during the elimination phase but resurged in 2022-2023.Across counties analyzed with Negative Binomial models, a 1 C increase in mean temperature (1-3 month lag) was associated with a ~16% increase in incidence (IRR = 1.16), highlighting a consistent positive effect.Relative humidity showed heterogeneous but generally positive associations, whereas precipitation effects were weak and inconsistent.Incidence was higher in spring (4.6-fold), summer (7.9fold), and autumn (6.8-fold) compared with winter.Increased IRS population coverage was positively associated with malaria incidence (IRR = 4.15 per 10% increase; 95% CI: 2.06-8.34),likely reflecting reactive spraying in response to higher transmission.Malaria transmission in southeast Iran is shaped by temperature-driven climatic variability and seasonal dynamics.Programmatic vector control responds to changes in transmission, emphasizing the need for integrated, climate-informed planning.Further research incorporating lagged predictive modeling and human mobility data is warranted to enhance elimination strategies.
Dehghan et al. (Wed,) studied this question.
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