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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Faculty Publications</text>
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    <name>Article</name>
    <description>Faculty Publications -Articles</description>
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          <name>Creator</name>
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            <elementText elementTextId="210457">
              <text>Bal, Prasanta Kumar; Kumar, Divya Subash; Parihar, Ruchi Singh; Saini, Atul</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>Changing climate and its impacts on the dynamics of future malaria transmission over certain endemic regions in India</text>
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          <name>Date</name>
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              <text>01-01-2025</text>
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          <name>Source</name>
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            <elementText elementTextId="210460">
              <text>Scientific Reports;Volume;15;Issue;1;Article No.;35412;</text>
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          <name>Identifier</name>
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              <text>&lt;a href="https://doi.org/10.1038/s41598-025-07971-x" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1038/s41598-025-07971-x&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105018398010?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105018398010?origin=resultslist&lt;/a&gt;</text>
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              <text>Bal P.K., Qatar Meteorology Department, Civil Aviation Authority, Doha, Qatar; Kumar D.S., Centre for Climate Change and Disaster Management, Anna University, Chennai, India; Parihar R.S., Department of Statistics and Data Science, CHRIST (Deemed to be University), Bangalore, India; Saini A., Department of Geography, Hemavati Nandan Bahuguna Garhwal University, Uttarakhand, Pauri Garhwal, India</text>
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              <text>As climate change plays a major role in evaluating the malaria disease over India, it is highly relevant to assess the spatio-temporal variability of malaria transmission dynamics over different climatic zones in India using modelling studies. In this study, VECTRI (vector-borne disease community model of the International Centre for Theoretical Physics, Trieste) model is simulated to predict the future malaria transmission dynamics over four major climatological zones of India, forced with the different climatic parameters such as temperature and rainfall and non-climatic parameter such as population density. The climate data is obtained from multi model mean of different CMIP6 global climate models under the SSP5-8.5 scenario. Results indicate that there is an overall decrease in EIR (Entomological Inoculation Rate) values of 10 to 30% are seen over most of the Indian regions with an increase in temperature about 4 to 5C and rainfall about 10 to 40%, by end of the century (2080s) when compared with the baseline period (19852014). However, few exceptions are seen over few parts of western and peninsular region where increase in EIR values are seen. This decrease (increase) in EIR values which describes the intensity of malaria transmission is predominantly controlled by temperature and rainfall during summer (winter) monsoon seasons. Such results from the VECTRI model may be useful for policymakers towards various malaria disease control programs in India and this may provide a basis for climate change impact assessments on malaria risk at a regional scale.  The Author(s) 2025.</text>
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          <name>Subject</name>
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              <text>Climate change; Global climate model; Malaria transmission; VECTRI</text>
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              <text>Nature Research</text>
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              <text>ISSN: 20452322;</text>
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              <text>English</text>
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              <text>All Open Access; Gold Open Access; Green Open Access</text>
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              <text>online</text>
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