Research Excellence
Using data science to resolve the enigma of Amazonian cities
Dr He Daihai of the Department of Applied Mathematics has recently published a research paper in one of the world’s most-cited and comprehensive multidisciplinary scientific journals, the Proceedings of the National Academy of Sciences (PNAS). The article title is “Resolving the enigma of Iquitos and Manaus: A modelling analysis of multiple COVID-19 epidemic waves in two Amazonian cities”.
The two nearby Amazonian cities of Iquitos (Peru) and Manaus (Brazil) experienced the world’s highest infection and mortality rates during the first COVID-19 wave in 2020. Key studies suggested that over 70% of the city populations were infected in this wave and thus close to herd immunity and protected. It remains an enigma as to why a deadly second wave followed in Manaus worse than the first. To resolve this, Dr He and his research team have presented a data-driven model of epidemic dynamics in Iquitos which is used to help explain and model events in Manaus. The partially observed Markov process model simultaneously fits a flexible “variable R0”, estimates long-term immunity waning and impulsive immune evasion, and thus provides a comprehensive framework for characterizing and modelling new variants of concern. This work has significantly impacted the mathematical modelling of infectious disease epidemiology.
Learn more: https://www.pnas.org/doi/10.1073/pnas.2211422120
利用數據科學解開亞馬遜城市新冠疫情之謎
應用數學系何岱海博士最近於全球被引用最多的綜合性多學科學術期刊之一的美國國家科學院院刊 (PNAS)，發表了一篇有關新冠病毒的研究報告 。報告標題為《解開伊基托斯和馬瑙斯之謎：針對亞馬遜兩個城市多輪新冠疫情的建模分析》。
兩個鄰近的亞馬遜城市 ── 伊基托斯（秘魯）和馬瑙斯（巴西）在 2020 年的第一波新冠疫情中，錄得全球最高的感染率和死亡率。研究指出，馬瑙斯在這一波疫情中超過七成的人口受到感染，已接近群體免疫，整個群體理應受到保護。然而，為何馬瑙斯的第二波疫情卻比第一波更為嚴重呢？為了解決這個問題，何博士及其研究團隊提出了一個以數據驅動的流行病動態模型。透過分析在伊基托斯收集到的數據，協助解釋和模擬馬瑙斯的疫情。部分可觀察的馬爾可夫過程模型同時加入一個具彈性的“變量 R0”，估算長時間免疫力減弱和突發性免疫逃避反應的幅度，從而建立了一個新的變種病毒株分析及建模框架。這項研究對於傳染病傳播數學建模帶來了深遠的影響。
