Basic characteristics of patients with novel coronavirus pneumonia in Shaanxi Province. Table 1 summaries the frequency and percentage of related variables, which can outline the basic situation of patients. Specifically, there are slightly more male patients and slightly more patients infected in Shaanxi Province. About 59% patients may be infected by strangers, and about 60% may be infected by weak ties such as general colleagues and friends. About 74% patients may be infected by strong ties such as close friends and relatives. 37% patients’ relatives were also infected, which indicates that there are more clustered infections in the province.
Gender
|
Frequ
ency
|
Percenta
ge (%)
|
Infected place
|
Frequ
ency
|
Percenta
ge (%)
|
Female
|
108
|
45.57
|
Inside Shaanxi Province
|
124
|
52.32
|
Male
|
129
|
54.43
|
Outside Shaanxi Province
|
113
|
47.68
|
Total
|
237
|
100
|
Total
|
237
|
100
|
|
|
Is there a possibility of being
infected by a stranger?
|
Frequ
ency
|
Percenta
ge (%)
|
Is there a possibility of being
infected by weak ties?
|
Frequ
ency
|
Percenta
ge (%)
|
Yes
|
140
|
59.07
|
Yes
|
143
|
60.34
|
No
|
97
|
40.93
|
No
|
94
|
39.66
|
Total
|
237
|
100
|
Total
|
237
|
100
|
|
|
|
|
Is there a possibility of being
infected by strong ties?
|
Frequ
ency
|
Percenta
ge (%)
|
Whether any relatives are
infected?
|
Frequ
ency
|
Percenta
ge (%)
|
Yes
|
176
|
74.26
|
Yes
|
87
|
36.71
|
No
|
61
|
25.74
|
No
|
150
|
63.29
|
Total
|
237
|
100
|
Total
|
237
|
100
|
Table 1. Descriptive Statistics of patients with novel coronavirus pneumonia in Shaanxi Province, China.
Figure 1 shows the frequency distribution of patient age. It can be seen that it conforms to normal distribution. Among them, 48-year-olds have the most infections, and young people age 16 to 20 have the least infections. But the number of infections rise sharply above 22.
Figure 2 shows the average age of patients over time. It can be seen that the average age of infected persons increased significantly as time goes. By February 14, it becomes more than 80 years. This also shows that the epidemic control method has good effect. The infected people in later stages are older and weaker people who has weak transmission ability, and infection of those young and middle-aged with strong transmission ability was controlled.
Table 2 and Figure 3 show the average onset time of imported cases after arriving in Shaanxi, and the average interval of taking relevant medical measures after symptoms (such as cough, fever, etc.) in all cases. According to Table 2, the average age of the patients was 46 years old, the youngest was 3 years old, and the oldest was 89 ( this case died in March; the only died case in Shaanxi). For imported cases from other regions in China, they developed symptoms on average 3 days after arriving in Shaanxi. The symptoms appeared as early as 5 days before arriving in Shaanxi. One case did not appear any symptoms until 19 days after arrived. After imported cases arrived in Shaanxi, they went to the clinic or were quarantined after an average of 5.4 days. The patients with the shortest interval had a history of visit doctors one day before arrive. The patient with the longest interval did not go to hospital or be quarantined until 17 days after he arrive. After the onset of symptoms, the average time to take relevant treatment was 1.6 days, indicating that the prevention and control measures in Shaanxi Province were timely and effective. The patient with the shortest time was quarantined 8 days before the onset of symptoms, and the patient with the longest time did not go to hospital until 14 days after the symptoms. No doubt the latter case has a higher risk of virus transmission.
Variables
|
Case
number
|
Mean
|
S.E.
|
Minimum
value
|
Maximum
value
|
Age
|
237
|
45.90
|
16.58
|
3
|
89
|
Symptom onset date minus arriving
in Shaanxi date (days)
|
94
|
3.489
|
4.560
|
-5
|
19
|
Diagnosis/quarantined date minus
arriving in Shaanxi date (days)
|
86
|
5.488
|
3.846
|
-1
|
17
|
Diagnosis/quarantined date minus
Symptom onset date (days)
|
178
|
1.607
|
2.973
|
-8
|
14
|
Table 2. Statistics related to the onset time of novel coronavirus patients in Shaanxi Province, China.
It shows in figure 3 that with time goes, the average onset time of symptoms has a tendency to increase, which means that the later imported cases are often patients with a longer incubation period. Therefore, they were not detected in the early stage. At the beginning of the epidemic, Shaanxi Province has adopted measures such as quarantine for patients with short incubation periods. It can be seen that with the change of time, the average diagnosis time has a decrease trend, which means that the later prevention and control measures are taken in a timely manner. Many patients develop the disease during the quarantine period, which reduces the risk of spread caused by the virus incubation period.
The transmission route of novel coronavirus is mainly respiratory droplets and contact transmission. From the perspective of social network, infection occurs in three kinds of connection: strangers, weak ties (such as ordinary friends, colleagues, etc.), strong ties (such as couples, family members, relatives, etc.). Figure 4 shows the types of contacts that patients may be infected with over time. In addition to the three main contacts, it also shows whether there is a relative infection of the patient. The change in type of ties was mainly related to the number of people infected. Our main concern is the proportion of each infection route. It can be seen that the strong ties infection route has always been relatively higher proportion than other routes, which shows that the spread of novel coronavirus in Shaanxi is mainly cluster infection. This also shows that the epidemic situation in Shaanxi has been effectively controlled, and has not caused a large number of stranger infections that are most likely to cause panic. However, there was a relatively high outbreak of stranger infections on February 7, mainly because of the cluster infection in Xi’an Duocai Shopping Center, where customers and businesses were infected, and many of them did not know each other. Correspondingly, it also shows that the clustered strong ties infection is the way that needs to be controlled in the epidemic prevention and control, which is basically consistent with the conclusions of various previous studies.
Dynamic Contact Network of Novel Coronavirus Pneumonia Patients Figure 5 is the dynamic contact network of patients with novel coronavirus pneumonia in Shaanxi Province. We intercepted three time points to present the network structure: early network (January 25), intermediate network (February 1), and later network (February 16).
The early contact network was relatively sparse, and most patients could not be identified the infection source. At this time, the largest cluster (component) was composed of three patients, number 9, 10, and 11, and their infection places were all in Wuhan. In the middle period, cluster- shaped infections have appeared, and several major clusters of infection formed. Case 26’s cluster would expand into the largest cluster in later stage. The later network was divided into multiple clusters, the largest of one was a cluster of number 25 and 26 illustrated in the middle of the picture. They were a couple, natives of Shaanxi, who had symptoms after return from Wuhan by driving. They went to local hospitals 5 days after they had symptoms. The source of infection for case 160 at a later stage could also be traced to this cluster. However, there are fewer new clusters in the later period, which indicates that the control of virus transmission is better. In the later period, only cases 234–237 formed a fully-connected component. They belong to one family. There are still many unconnected cases in the network, most of which are imported cases. It is no longer possible to track their infection source outside the province.
Table 3 reports four centrality measurement of the contact network. Degree centrality expresses that, on average, how many other patients the focal patient has contact with, which is slightly larger than the basic regeneration number. Table 3 shows that the average degree of centrality is less than 1. The smallest degree is 0. The largest is 11, indicating that the patient (case 26 in figure 5) has contacted 11 other patients. According to the degree of centrality, it can be speculated that the basic regeneration number of novel coronavirus in Shaanxi Province is less than 1, which means that the spread of the virus is well controlled. Closeness centrality indicates the closeness of the patient with other patients. Higher values indicate faster transmission between patients and fewer intermediate patients. The average value is 0.452, which is a slightly higher closeness centrality, indicating that the infection is mostly cluster infection. It can be seen from Figure 5 that over time, many aggregated sub-networks are formed, but the network is not fully connected under the action of prevention and control measures. Betweenness centrality indicates >the level the patient as an intermediary in spread of the virus. The average value is 0, which is very low, indicating that there are few chain transmissions. According to Figure 5, we can see the transmission mode is mostly one-to-many, that is, A-B, A-C transmission. The PageRank index measures the centrality of the patient’s position in whole contact network. The average value is 0.0042, which is very low. But the maximum value is 0.0228, which indicates that the degree of connection is unevenly distributed among patients. Highly infectious persons can cause a major outbreak of the disease. The spread of Ebola virus is being associated with these super disseminators 23. From Figure 6, we know that a small number of people have a higher degree of centrality. But only three patients have a degree of centrality greater than 5. Most patients’ degree centrality is zero. This shows that although the degree distribution of patients in Shaanxi Province is uneven, the highest number of contacts is low, and there is no super disseminator.
Variables
|
Case No.
|
Mean
|
S.D.
|
Minimum Value
|
Maximus Value
|
Degree Centrality
|
237
|
0.987
|
1.351
|
0
|
11
|
Closeness Centrality
|
237
|
0.452
|
0.440
|
0
|
1
|
Betweenness Centrality
|
237
|
0
|
0.0001
|
0
|
0.0012
|
PageRank
|
237
|
0.0042
|
0.0035
|
0.001
|
0.023
|
Table 3. Statistics of the contact network of novel coronavirus pneumonia patients in Shaanxi Province. The value of closeness centrality and betweenness centrality is in normalized form.