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Main Authors: Shivank, Singh, Anurag, Ghanbarnejad, Fakhteh, Sharma, Ajay K
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.08562
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author Shivank
Singh, Anurag
Ghanbarnejad, Fakhteh
Sharma, Ajay K
author_facet Shivank
Singh, Anurag
Ghanbarnejad, Fakhteh
Sharma, Ajay K
contents Climate change is intensifying infectious and chronic diseases like malaria and diabetes, respectively, especially among the vulnerable populations. Global temperatures have risen by approximately $0.6^\circ$C since 1950, extending the window of transmission for mosquito-borne infections and worsening outcomes in diabetes due to metabolic stress caused by heat. People living with diabetes have already weakened immune defenses and, therefore, are at an alarmingly increased risk of contraction of malaria. However, most models rarely include both ways of interaction in changing climate conditions. In the paper, we introduce a new compartmental epidemiological model based on synthetic data fitted to disease patterns of India from 2019 to 2021. The framework captures temperature-dependent transmission parameters, seasonal variability, and different disease dynamics between diabetic and non-diabetic groups within the three-compartment system. Model calibration using Multi-Start optimization combined with Sequential Quadratic Programming allows us to find outstanding differences between populations. The odds of malaria infection in diabetic individuals were found to be 1.8--4.0 times higher, with peak infection levels in 35--36\%, as compared to 20--21\% in the non-diabetic ones. The fitted model was able to capture well the epidemiological patterns observed, while the basic reproduction number averaged around 2.3, ranging from 0.31 to 2.75 in different seasons. Given that India's diabetic population is set to rise to about 157 million people by 2050, these findings point to a pressing need for concerted efforts toward climate-informed health strategies and monitoring systems that address both malaria and diabetes jointly.
format Preprint
id arxiv_https___arxiv_org_abs_2511_08562
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Climate Driven Interactions Between Malaria Transmission and Diabetes Prevalence
Shivank
Singh, Anurag
Ghanbarnejad, Fakhteh
Sharma, Ajay K
Multiagent Systems
Climate change is intensifying infectious and chronic diseases like malaria and diabetes, respectively, especially among the vulnerable populations. Global temperatures have risen by approximately $0.6^\circ$C since 1950, extending the window of transmission for mosquito-borne infections and worsening outcomes in diabetes due to metabolic stress caused by heat. People living with diabetes have already weakened immune defenses and, therefore, are at an alarmingly increased risk of contraction of malaria. However, most models rarely include both ways of interaction in changing climate conditions. In the paper, we introduce a new compartmental epidemiological model based on synthetic data fitted to disease patterns of India from 2019 to 2021. The framework captures temperature-dependent transmission parameters, seasonal variability, and different disease dynamics between diabetic and non-diabetic groups within the three-compartment system. Model calibration using Multi-Start optimization combined with Sequential Quadratic Programming allows us to find outstanding differences between populations. The odds of malaria infection in diabetic individuals were found to be 1.8--4.0 times higher, with peak infection levels in 35--36\%, as compared to 20--21\% in the non-diabetic ones. The fitted model was able to capture well the epidemiological patterns observed, while the basic reproduction number averaged around 2.3, ranging from 0.31 to 2.75 in different seasons. Given that India's diabetic population is set to rise to about 157 million people by 2050, these findings point to a pressing need for concerted efforts toward climate-informed health strategies and monitoring systems that address both malaria and diabetes jointly.
title Climate Driven Interactions Between Malaria Transmission and Diabetes Prevalence
topic Multiagent Systems
url https://arxiv.org/abs/2511.08562