Center for Biomedical Modeling, The Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique, IPLESP, Paris, France.
Nat Commun. 2021 May 14;12(1):2837. doi: 10.1038/s41467-021-23051-w.
Twenty-six million people are living with HIV in sub-Saharan Africa; epidemics are widely dispersed, due to high levels of mobility. However, global elimination strategies do not consider mobility. We use Call Detail Records from 9 billion calls/texts to model mobility in Namibia; we quantify the epidemic-level impact by using a mathematical framework based on spatial networks. We find complex networks of risk flows dispersed risk countrywide: increasing the risk of acquiring HIV in some areas, decreasing it in others. Overall, 40% of risk was mobility-driven. Networks contained multiple risk hubs. All constituencies (administrative units) imported and exported risk, to varying degrees. A few exported very high levels of risk: their residents infected many residents of other constituencies. Notably, prevalence in the constituency exporting the most risk was below average. Large-scale networks of mobility-driven risk flows underlie generalized HIV epidemics in sub-Saharan Africa. In order to eliminate HIV, it is likely to become increasingly important to implement innovative control strategies that focus on disrupting risk flows.
撒哈拉以南非洲地区有 2600 万人感染了艾滋病毒；由于高度的流动性，疫情广泛传播。然而，全球消除战略并未考虑到流动性。我们使用来自 90 亿个通话/短信的通话记录来模拟纳米比亚的流动情况；我们使用基于空间网络的数学框架来量化疫情层面的影响。我们发现，风险流动的复杂网络分散在全国范围内：一些地区感染艾滋病毒的风险增加，另一些地区则降低。总的来说，40%的风险是由流动驱动的。网络中存在多个风险中心。所有选区（行政单位）都以不同程度的输入和输出风险。有几个选区输出的风险非常高：它们的居民感染了其他选区的许多居民。值得注意的是，输出风险最多的选区的患病率低于平均水平。流动驱动的风险流的大规模网络是撒哈拉以南非洲地区普遍存在的艾滋病毒疫情的基础。为了消除艾滋病毒，实施以阻断风险流为重点的创新控制战略可能变得越来越重要。
