Influence of future climate scenarios using CMIP 5 data on malaria transmission in India.

IF 2.4 3区 医学 Q3 INFECTIOUS DISEASES
Subrahmanya Hari Prasad Peri
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引用次数: 0

Abstract

Background: Vector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial.

Methods: This study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria's Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. Three RCP scenarios are considered (Representative Concentration Pathways are climate change scenarios that project radiative forcing to 2100 due to future greenhouse gas concentrations). The projections covered the period from 1 Jan, 2020, to 31 Dec, 2029.

Results: The estimated mean EIR for the years 2020-2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each year 0.3 to 2.6 [min-max] EIR/person/day decline is observed with a strong decline in man rainfall ranging from 5 to 17 [min-max] mm/year and associated high temperatures ranging from 0.03 to 0.06 [min-max] °C/year. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk, which kept increasing through RCP scenarios. Thus, it is essential to exercise caution, especially in areas with heavy rainfall.

Conclusion: This research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health.

使用 CMIP 5 数据的未来气候情景对印度疟疾传播的影响。
背景:疟疾等病媒传染的疾病对全球构成严重威胁,而气候因素在很大程度上影响着这些疾病的强度。印度等热带国家尤其容易受到此类疾病的影响,因此准确估计疟疾风险至关重要:这项研究采用了著名的病媒传染病群落模型 VECTRI,该模型由位于的里雅斯特的国际理论物理中心开发。该模型用于估算疟疾的昆虫接种率(EIR)。未来气候预测数据集(包括 CMIP 5 和人口数据集)被用作分析输入。考虑了三种 RCP 情景(代表性浓度路径是一种气候变化情景,预测未来温室气体浓度对 2100 年的辐射强迫)。预测期为 2020 年 1 月 1 日至 2029 年 12 月 31 日:2020-2029 年的估计平均 EIR 值不等,在所有 RCP 2.6、4.5 和 8.5 情景下,都观察到疟疾风险显著下降。随着降雨量的急剧下降(5 至 17 [最小-最大] 毫米/年)和相关高温(0.03 至 0.06 [最小-最大] °C/年),每年的 EIR/人/天下降了 0.3 至 2.6 [最小-最大]。季风过后的 8 月至 11 月是疟疾传播的高发期。空间分析表明,印度东海岸更容易受到疟疾风险的影响,而且随着 RCP 情景的出现,这种影响在不断增加。因此,必须谨慎行事,尤其是在降雨量大的地区:这项研究为政策制定者提供了宝贵的见解,强调了实施未来战略以有效降低疟疾风险的必要性。利用这些研究结果,可以采取适当的措施来应对疟疾带来的威胁,保护公众健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Malaria Journal
Malaria Journal 医学-寄生虫学
CiteScore
5.10
自引率
23.30%
发文量
334
审稿时长
2-4 weeks
期刊介绍: Malaria Journal is aimed at the scientific community interested in malaria in its broadest sense. It is the only journal that publishes exclusively articles on malaria and, as such, it aims to bring together knowledge from the different specialities involved in this very broad discipline, from the bench to the bedside and to the field.
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