Research Article
A Remark on Stochastic Climate-Finance SEIR Model for Climate-Induced Infectious Diseases in Southern Nigeria
Imekela Donaldson Ezekiel
,
Sunday Onos Edeki*
Issue:
Volume 11, Issue 2, June 2026
Pages:
24-31
Received:
10 March 2026
Accepted:
27 March 2026
Published:
7 May 2026
Abstract: Climate change has worsened the spread of infectious diseases across the tropics, especially in Southern Nigeria, where fluctuations in temperature, rainfall, and flood aid the spread of vector-borne and waterborne diseases. These environmental disruptions raise levels of morbidity and cost the health and community sectors heavily. The counteractions against these disruptions, hence, demand an inclusive strategy of public health interventions, linked with adaptive climate finance mechanisms. In this study, a stochastic climate–finance SEIR model is developed to investigate the dynamic interaction between infectious disease transmission, climate variability, and financial intervention policies. This work sets the stage for studying the stochastic investment SEIR model intact, which is a representative model to study the complex intrinsic relationship involving climate variability, financial interventions, and the transmission of infectious diseases. A thorough analysis, seasoned with the global existence and uniqueness, ruled positivity and boundedness of the system, and stochastic stability of the disease-free equilibrium were performed using Lyapunov techniques and Itô calculus. Following a careful investigation process made in this study, a stochastic reproduction number was derived, showing how noise affects epidemic thresholds. Numerical simulations were also performed to further show the impact of climate variability and financial responsiveness on epidemic trajectories. The numerical results showed that adaptive management of climate change and climate finance diminished the highest magnitudes of infections while compressing the time needed for epidemics to spiral all out of control in the presence of effectively and tactically employed environmental forcing. The outcome serves as the creation of a structural definition within mathematics, with the sole aim of enabling robust climate-health financing towards the mitigation of infectious disease risks in Southern Nigeria.
Abstract: Climate change has worsened the spread of infectious diseases across the tropics, especially in Southern Nigeria, where fluctuations in temperature, rainfall, and flood aid the spread of vector-borne and waterborne diseases. These environmental disruptions raise levels of morbidity and cost the health and community sectors heavily. The counteractio...
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Research Article
Evaluation of CMIP6 Global Climate Models for Rainfall Simulation Across Agro-Ecological Zones of Ethiopia
Tewodros Solomon*,
Yimer Assefa Yimam
Issue:
Volume 11, Issue 2, June 2026
Pages:
32-52
Received:
30 December 2025
Accepted:
18 May 2026
Published:
4 June 2026
DOI:
10.11648/j.ijssam.20261102.12
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Abstract: Rainfall is one of the most critical climatic variables for investigating the impacts of climate change. Global Climate Models (GCMs) are widely used tools for examining changes in the climate system and projecting future climate scenarios. This study evaluated the performance of Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models in simulating rainfall climatology over Ethiopia. Eight CMIP6 GCMs were assessed at daily, monthly, and annual timescales across five Agro-Ecological Zones (AEZs) of Ethiopia for the period 1995–2014, using station observations as reference data. Model performance was evaluated using Root Mean Square Error (RMSE), Percent Bias (PBIAS), and Pearson’s correlation coefficient (r). Each model was ranked using the Comprehensive Rating Index (CRI). The results showed that model performance varied considerably for daily to annual rainfall totals across the AEZs, with both overestimation and underestimation observed. For daily rainfall, EC-Earth3-Veg performed best in tropical, subtropical, and temperate AEZs; MRI-ESM2-0 performed best in the desert AEZ; and MPI-ESM1-2-LR performed best in the alpine AEZ. BCC-CSM2-MR performed well across tropical, subtropical, temperate, and alpine AEZs, while MRI-ESM2-0 performed better in desert AEZs. For annual rainfall, MRI-ESM2-0 was superior in desert and tropical AEZs, BCC-CSM2-MR performed best in temperate and alpine AEZs, and EC-Earth3-Veg performed best in the subtropical AEZ. EC-Earth3 was the least effective at reproducing mean monthly rainfall. Overall, the models’ performance was inconsistent across timescales and regions. Given the spatial and temporal variability in CMIP6 GCM performance, it is recommended that models be thoroughly evaluated and bias-corrected for specific locations and intended applications, particularly regarding their ability to simulate Ethiopia’s diverse rainfall regimes.
Abstract: Rainfall is one of the most critical climatic variables for investigating the impacts of climate change. Global Climate Models (GCMs) are widely used tools for examining changes in the climate system and projecting future climate scenarios. This study evaluated the performance of Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate ...
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