Centre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, Kharagpur, 721 302, India.
Malar J. 2024 Oct 9;23(1):301. doi: 10.1186/s12936-024-05129-0.
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.
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.
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.
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.
虫媒病，如疟疾，对全球构成重大威胁，气候因素极大地影响其强度。印度等热带国家特别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。
本研究使用了著名的国际理论物理中心（ICTP）在的里雅斯特开发的虫媒病社区模型（Vector-borne Disease Community Model，VECTRI）来估计疟疾的昆虫接种率（Entomological Inoculation Rate，EIR）。未来的气候预测数据集，包括 CMIP 5 和人口数据集，被用作分析的输入。考虑了三种 RCP 情景（代表性浓度路径是气候变化情景，它根据未来温室气体浓度预测到 2100 年的辐射强迫）。预测涵盖了 2020 年 1 月 1 日至 2029 年 12 月 31 日期间。
2020-2029 年期间估计的平均 EIR 范围为 ，并且在所有 RCP 2.6、4.5 和 8.5 情景下，疟疾风险都显著下降。每年观察到 0.3 至 2.6 [最小-最大] EIR/人/天的下降，与降雨量减少 5 至 17 [最小-最大] mm/年和相关的高温减少 0.03 至 0.06 [最小-最大] °C/年有关。在后季风期，8 月至 11 月被确定为疟疾传播的高风险时期。空间分析显示，印度东海岸面临更高的疟疾风险脆弱性，随着 RCP 情景的发展，这种脆弱性不断增加。因此，必须保持警惕，特别是在降雨量较大的地区。
本研究为决策者提供了有价值的见解，强调了实施未来战略以有效减轻疟疾风险的必要性。利用这些发现，可以采取适当措施应对疟疾威胁，保护公众健康。
