Nowadays, the novel coronavirus (COVID-19) is spreading around the world and has attracted extremely wide public attention. From the beginning of the outbreak to now, there have been many mathematical models proposed to describe the spread of the pandemic, and most of them are established with the assumption that people contact with each other in a homogeneous pattern. However, owing to the difference of individuals in reality, social contact is usually heterogeneous, and the models on homogeneous networks cannot accurately describe the outbreak. Thus, we propose a susceptible-asymptomatic-infected-removed (SAIR) model on social networks to describe the spread of COVID-19 and analyse the outbreak based on the epidemic data of Wuhan from January 24 to March 2. Then, according to the results of the simulations, we discover that the measures that can curb the spread of COVID-19 include increasing the recovery rate and the removed rate, cutting off connections between symptomatically infected individuals and their neighbours, and cutting off connections between hub nodes and their neighbours. The feasible measures proposed in the paper are in fair agreement with the measures that the government took to suppress the outbreak. Furthermore, effective measures should be carried out immediately, otherwise the pandemic would spread more rapidly and last longer. In addition, we use the epidemic data of Wuhan from January 24 to March 2 to analyse the outbreak in the city and explain why the number of the infected rose in the early stage of the outbreak though a total lockdown was implemented. Moreover, besides the above measures, a feasible way to curb the spread of COVID-19 is to reduce the density of social networks, such as restricting mobility and decreasing in-person social contacts. This work provides a series of effective measures, which can facilitate the selection of appropriate approaches for controlling the spread of the COVID-19 pandemic to mitigate its adverse impact on people’s livelihood, societies and economies.

如今，新型冠状病毒（COVID-19）正在世界范围内蔓延，引起了极其广泛的公众关注。从爆发开始到现在，已经提出了许多描述大流行传播的数学模型，其中大多数是建立在人们以同质模式相互接触的假设下建立的。然而，由于现实中个体的差异，社会接触通常是异质的，同质网络上的模型无法准确描述疫情。因此，我们在社交网络上提出了一个易感-无症状-感染-移除（SAIR）模型来描述 COVID-19 的传播，并根据武汉市 1 月 24 日至 3 月 2 日的流行数据分析疫情。然后，根据模拟结果，我们发现，可以遏制 COVID-19 传播的措施包括提高恢复率和清除率，切断有症状感染者与其邻居之间的联系，以及切断枢纽节点与其邻居之间的联系。文件中提出的可行措施与政府为抑制疫情而采取的措施完全一致。此外，应立即采取有效措施，否则大流行会传播得更快，持续时间更长。此外，我们利用武汉市1月24日至3月2日的疫情数据，对武汉市的疫情进行了分析，并解释了为什么在疫情初期虽然实行了全面封城，但感染人数却在上升。此外，除上述措施外，遏制 COVID-19 传播的一种可行方法是降低社交网络的密度，例如限制流动性和减少面对面的社交接触。这项工作提供了一系列有效措施，有助于选择适当的方法来控制 COVID-19 大流行的蔓延，以减轻其对人民生计、社会和经济的不利影响。