The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19.
The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19.
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DOI：
10.11604/pamj.2020.36.355.24101
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Okuonzi SA
中科院分区：
文献类型：
--
作者：
Okuonzi SA
COVID-19爆发的速度和影响是前所未有的。预测疾病传播的努力主要是使用全球北方开发的旗舰模型进行的。这些模型没有准确地描述SARS-CoV-2在非洲的真实传播率。这些模型忽视了非洲独特的社会生态构成（人口、社会、环境和生物），而这种构成有助于减缓病毒的传播，减轻病毒的严重程度。本文就传染病建模科学需要如何发展以适应环境因素提出了看法。迫切需要支持国家自主和有针对性的建模。
The outbreak of COVID-19 has been unprecedented in speed and effect. Efforts to predict the disease transmission have mostly been done using flagship models developed by the global north. These models have not accurately depicted the true rate of transmission of SARS-CoV-2 in Africa. The models have ignored Africa’s unique socio-ecological makeup (demographic, social, environmental and biological) that has aided a slower and less severe spread of the virus. This paper opines on how the science of infectious disease modelling needs to evolve to accommodate contextual factors. Country-owned and tailored modelling needs to be urgently supported.
影响因子：
19
作者：
Pearson, Carl A. B.;Van Schalkwyk, Cari;Pulliam, Juliet R. C.
通讯作者：
Pulliam, Juliet R. C.
影响因子：
8.1
作者：
Cabore, Joseph Waogodo;Karamagi, Humphrey Cyprian;Moeti, Matshidiso R.
通讯作者：
Moeti, Matshidiso R.