Kenyatta University, P.O. Box 43844, Nairobi, Kenya.
Kenya Medical Research Institute, Centre for Global Health Research, Climate and Human Health Research Unit, P.O. Box 1578, Kisumu, Kenya.
Acta Parasitol. 2022 Dec;67(4):1535-1563. doi: 10.1007/s11686-022-00588-4. Epub 2022 Aug 12.
Malaria epidemics are increasing in East Africa since the 1980s, coincident with rising temperature and widening climate variability. A projected 1-3.5 °C rise in average global temperatures by 2100 could exacerbate the epidemics by modifying disease transmission thresholds. Future malaria scenarios for the Lake Victoria Basin (LVB) are quantified for projected climate scenarios spanning 2006-2100.
Regression relationships are established between historical (1995-2010) clinical malaria and anaemia cases and rainfall and temperature for four East African malaria hotspots. The vector autoregressive moving average processes model, VARMAX (p,q,s), is then used to forecast malaria and anaemia responses to rainfall and temperatures projected with an ensemble of eight General Circulation Models (GCMs) for climate change scenarios defined by three Representative Concentration Pathways (RCPs 2.6, 4.5 and 8.5).
Maximum temperatures in the long rainy (March-May) and dry (June-September) seasons will likely increase by over 2.0 °C by 2070, relative to 1971-2000, under RCPs 4.5 and 8.5. Minimum temperatures (June-September) will likely increase by over 1.5-3.0 °C under RCPs 2.6, 4.5 and 8.5. The short rains (OND) will likely increase more than the long rains (MAM) by the 2050s and 2070s under RCPs 4.5 and 8.5. Historical malaria cases are positively and linearly related to the 3-6-month running means of monthly rainfall and maximum temperature. Marked variation characterizes the patterns projected for each of the three scenarios across the eight General Circulation Models, reaffirming the importance of using an ensemble of models for projections.
The short rains (OND), wet season (MAM) temperatures and clinical malaria cases will likely increase in the Lake Victoria Basin. Climate change adaptation and mitigation strategies, including malaria control interventions could reduce the projected epidemics and cases. Interventions should reduce emerging risks, human vulnerability and environmental suitability for malaria transmission.
自 20 世纪 80 年代以来,东非的疟疾疫情不断加剧,这与气温上升和气候变率扩大有关。到 2100 年,预计全球平均气温将上升 1-3.5°C,这可能通过改变疾病传播阈值使疫情恶化。对维多利亚湖流域(LVB)未来疟疾情况进行量化,预测了跨越 2006-2100 年的气候情景。
建立了四个东非疟疾热点地区历史(1995-2010 年)临床疟疾和贫血病例与降雨量和温度之间的回归关系。然后,使用向量自回归移动平均过程模型 VARMAX(p,q,s),根据三个代表性浓度途径(RCPs 2.6、4.5 和 8.5)定义的气候变化情景,对与八个通用环流模型(GCMs)集合预测的降雨量和温度相关的疟疾和贫血反应进行预测。
在 RCPs 4.5 和 8.5 下,长雨季(3 月至 5 月)和旱季(6 月至 9 月)的最高温度可能会比 1971-2000 年增加 2.0°C 以上。RCPs 2.6、4.5 和 8.5 下的最低温度(6 月至 9 月)可能会增加 1.5-3.0°C 以上。在 RCPs 4.5 和 8.5 下,短雨季(OND)的增幅可能超过长雨季(MAM)。在 RCPs 4.5 和 8.5 下,历史疟疾病例与每月降雨量和最高温度的 3-6 个月移动平均值呈正线性关系。在 8 个通用环流模型中,每个模型的三个情景都呈现出明显的变化模式,这再次证实了使用模型集合进行预测的重要性。
维多利亚湖流域的短雨季(OND)、雨季(MAM)温度和临床疟疾病例可能会增加。气候变化适应和缓解战略,包括疟疾控制干预措施,可以减少预测的疫情和病例。干预措施应降低新出现的风险、人类脆弱性和环境对疟疾传播的适宜性。