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R E S E A R C H Open Access
The comparison of epidemiological
characteristics between confirmed and
clinically diagnosed cases with COVID-19
during the early epidemic in Wuhan, China
Fang Shi
1†
, Haoyu Wen
1†
, Rui Liu
2
, Jianjun Bai
1
, Fang Wang
1
, Sumaira Mubarik
1
, Xiaoxue Liu
1
, Yong Yu
3
,
Qiumian Hong
4
, Jinhong Cao
1
and Chuanhua Yu
1,5*
Abstract
Background: To put COVID-19 patients into hospital timely, the clinical diagnosis had been implemented in
Wuhan in the early epidemic. Here we compared the epidemiological characteristics of laboratory-confirmed and
clinically diagnosed cases with COVID-19 in Wuhan.
Methods: Demographics, case severity and outcomes of 29,886 confirmed cases and 21,960 clinically
diagnosed cases reported between December 2019 and February 24, 2020, were compared. The risk
factors were estimated, and the effective reproduction number (Rt) of SARS-CoV-2 was also calculated.
Results: The age and occupation distribution of confirmed cases and clinically diagnosed cases were
consistent, and their sex ratio were 1.0 and 0.9, respectively. The epidemic curve of clinical diagnosis
cases was similar to that of confirmed cases, and the city centers had more cumulative cases and higher
incidence density than suburbs in both of two groups. The proportion of severe and critical cases (21.5 %
vs. 14.0 %, P< 0.0001) and case fatality rates (5.2 % vs. 1.2 %, P< 0.0001) of confirmed cases were all
higher than those of clinically diagnosed cases. Risk factors for death we observed in both of two groups
were older age, male, severe or critical cases. Rt showed the same trend in two groups, it dropped
below 1.0 on February 6 among confirmed cases, and February 8 among clinically diagnosed cases.
Conclusions: The demographic characteristics and spatiotemporal distributions of confirmed and clinically
diagnosed cases are roughly similar, but the disease severity and clinical outcome of clinically diagnosed
cases are better than those of confirmed cases. In cases when detection kits are insufficient during the
early epidemic, the implementation of clinical diagnosis is necessary and effective.
Keywords: COVID-19, Wuhan city, Epidemiology, Clinical diagnosis, Risk factor, Effective reproduction number
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* Correspondence: yuchua@whu.edu.cn
†
Fang Shi and Haoyu Wen contributed equally to this work.
1
Department of Epidemiology and Biostatistics, School of Health Sciences,
Wuhan University, 430071 Wuhan, China
5
Global Health Institute, Wuhan University, 430072 Wuhan, China
Full list of author information is available at the end of the article
Global Healt
h
Research and Polic
y
Shi et al. Global Health Research and Policy (2021) 6:18
https://doi.org/10.1186/s41256-021-00200-8
Introduction
In December 2019, a highly pathogenic coronavirus, se-
vere acute respiratory syndrome coronavirus 2 (SARS-
CoV-2), was recognized in Wuhan, China, and then sus-
tained transmission has been seen throughout and out-
side China. The World Health Organization named the
pneumonia caused by SARS-CoV-2 as Corona Virus
Disease 2019 (COVID-19) [1], and announced that new
coronary pneumonia has developed into a “pandemic”
on 11 March 2020.
Massive measures have been taken by the government
to curb the spread of COVID-19 in Wuhan, including
the lockdown of Wuhan, which helped in limiting
crowd movement to prevent infected cases from
spreading to other areas [2–4]. The viral nucleic acid
test (real-time reverse transcriptase–polymerase chain
reaction [RT-PCR] assay or genome sequencing) is con-
sidered as the diagnostic gold standard of COVID-19
[5,6]. Before February 8, 2020, only patients who had
positive results on virus nucleic acid tests were
regarded as laboratory-confirmed cases across China
(To be consistent with the Chinese government’sre-
ports, the following laboratory-confirmed cases are re-
ferred to as confirmed cases). However, due to a large
number of patients, insufficient testing kits, and bottle-
necks in laboratory testing capacity, the nucleic acid de-
tection failed to meet clinical needs, and patients in
Hubei Province could not be admitted to the hospital
for treatment in time [7]. It is important to admit pa-
tients into hospitals as soon as possible since a deferred
admission may turn patients critical and lead to more
infections. To raise the hospital admission and improve
the efficiency of treatment, the broadened diagnostic
criteria were used and the designation ‘clinically diag-
nosed cases’emerged. According to the revised fifth
version of the guideline over the diagnosis and treat-
ment of COVID-19 issued on Feb 8, 2020, jointly re-
leased by the National Health Commission of China
and the State Administration of Traditional Chinese
Medicine, clinical diagnosis was being used in Hubei
Province only [5]. Without laboratory confirmation,
clinically diagnosed cases were diagnosed by symptoms,
exposures and CT scan only [5,8]. Thanks to the revi-
sion in the diagnostic criteria, the patient admission
rate has surged immediately. In the later period, the de-
tection of COVID-19 had been greatly improved, the
laboratory diagnostic ability could be met needs, and
the suspected cases in Hubei Province could be rapidly
detected. Therefore, the updated guideline known as
the sixth edition issued on Feb 19, 2020, abolished dif-
ferent epidemic-related standards inside and outside
Hubei Province, “clinically diagnosed cases”were no
longer listed [6]. In addition, the number of clinically
diagnosed cases was revised on Feb 24, 2020 [7].
To inform evidence-based decisions, more information
relevant to the epidemiology of COVID-19 was urgently
needed [9]. There are many studies on the confirmed
cases [10–12], but no description of the epidemiology of
clinically diagnosed cases has been seen. Here is a com-
parison and generalization of epidemiological character-
istics of confirmed and clinically diagnosed cases with
COVID-19 during the early epidemic in Wuhan.
Methods
Data sources
This was a retrospective study. All data from December
8, 2019 (date of the first onset) to 24 February 2020,
were extracted from China’s Infectious Disease Informa-
tion System. Details of data collection are provided else-
where [13]. After excluding duplicate cases and those
who were unable to obtain a unique identifying card, a
total of 29,886 confirmed cases and 21,960 clinically di-
agnosed cases with COVID-19 in Wuhan were eligible
for this study finally.
Variables
COVID-19 was classified into mild type, moderate type,
severe type as well as critical type according to disease
severity, the detailed classification criteria were shown in
Supplementary Table S1. The date of onset was defined
as the day when the symptom was observed. The pro-
portion of severe and critical cases was defined as (se-
vere cases + critical cases) / (mild cases + moderate
cases + severe cases + critical cases). Case fatality rates
were calculated as the number of deaths divided by the
total number of cases. Incidence density was estimated
as the number of cases divided by the number of per-
manent resident population, which was collected from
the Hubei Statistical Yearbook 2020.
Case Definitions
According to the 5th edition of the guideline over the
diagnosis and treatment of COVID-19 [5], confirmed
cases were patients who had positive SARS-CoV-2 re-
sults after conducting RT-PCR assay or high-throughput
sequencing of nasal and pharyngeal swab specimens.
Clinically diagnosed cases were suspected cases with
lung imaging features consistent with coronavirus pneu-
monia. Bilateral distribution of patchy shadows and
ground-glass opacity were typical hallmarks of CT scan
for COVID-19 [8].
Statistical analysis
All data were recorded and sorted in Excel. Continuous
variables were described using median and interquartile
range (IQR) when the data did not obey normal distribu-
tion. Categorical variables were described by frequency,
rate and percentage. The epidemic curve was built and
Shi et al. Global Health Research and Policy (2021) 6:18 Page 2 of 11
maps of Wuhan at the county-level were drawn. Case
severity and clinical outcomes between confirmed
cases and clinically diagnosed cases were compared
using Chi square tests or Kolmogorov-Smirnov Z
tests. Univariable and multivariable logistic-regression
analysis was performed to ascertain the risk factors
for severity or death. The logistic-regression model
did not include variable ‘days from onset to diagnosis’
because there was collinearity between variable ‘date
of onset’and ‘days from onset to diagnosis’.Oddsra-
tio (OR) and its 95 % confidence intervals were calcu-
lated, corresponding forest-plot was drawn. The
effective reproduction number (Rt), which is an indi-
cator to measure the transmission of infectious dis-
eases, is defined as the mean number of secondary
cases generated by a typical primary case at time t in
a population. When Rt is less than 1, the epidemic of
infectious diseases will be gradually controlled; when
Rt is greater than 1, infectious diseases will continue
to spread, suggesting that prevention and control
measures need to be optimized or strengthened. We
appliedthemethoddevelopedbyAnneCori[14]to
estimate Rt and its 95 % credible interval via a weekly
sliding average. Referring to previous epidemiological
surveys of Wuhan in the early stage of the COVID-19
outbreak, the parameters of serial interval distribution
(gamma distribution, mean = 7.5 days, standard devi-
ation = 3.4 days) were cited [15]. SPSS version 26.0
and R version 4.0 were used for statistical analyses
and ArcGIS version 10.7 was used for cartography.
Results
Baseline epidemiological characteristics
As of 24 February 2020, a total of 29,886 confirmed
cases and 21,960 clinically diagnosed cases with COVID-
19 were included in this study. The epidemiological
curves of clinically diagnosed cases were similar to that
of confirmed cases, the peak of COVID-19 onset oc-
curred between the Wuhan lockdown and February 8
(Fig. 1). The baseline characteristics of cases were shown
in Table 1. The sex ratio of confirmed cases and clinic-
ally diagnosed cases were 1.0 and 0.9, and the age distri-
bution and occupation distribution of the two groups
were similar (Supplementary Fig. S1). The median inter-
vals between onset and diagnosis of confirmed cases and
clinically diagnosed cases were 9.0 (5.0–13.0) and 11.0
(5.0–18.0) days, respectively. As time goes on, the inter-
val between onset and diagnosis had decreased signifi-
cantly (Supplementary Fig. S2). The city centers have
more cumulative cases and higher incidence density than
suburbs in both of the two groups (Fig. 2and Supple-
mentary Table S2).
Severity of illness
The proportion of severe and critical types in confirmed
cases was higher than that in clinically diagnosed cases
(21.5 % vs. 14.0 %, P< 0.0001). As given in Supplemen-
tary Table S3, the epidemiological characteristics of
COVID-19 varied by the classification of severity. The
median ages of the severe and critical cases were higher
than mild and moderate cases, and the proportion of
Fig. 1 The epidemiological curves of confirmed cases and clinically diagnosed cases with COVID-19 in Wuhan from January 1 to February
24, 2020
Shi et al. Global Health Research and Policy (2021) 6:18 Page 3 of 11
severe and critical cases increased with age (Supplemen-
tary Fig. S3). The proportion of severe and critical cases
in males was higher than that in females (53.6 % vs.
43.7 % in confirmed cases, and 60.6 % vs. 36.4 % in clin-
ically diagnosed cases), and a later date of onset was as-
sociated with the milder disease. The proportion of
severe and critical cases in confirmed and clinically diag-
nosed cases all decreased over time (Supplementary Fig.
S4). Univariable and multivariable logistic-regression
model showed that age greater than 60 years, males, spe-
cial occupations (such as housework or unemployed, re-
tirees, and healthcare worker) and earlier date of onset
were risk factors for severity in both confirmed cases
and clinically diagnosed cases (Supplementary Table S4
and Fig. S5).
Analysis of Deaths
The case fatality rates of confirmed cases and clinically
diagnosed cases with COVID-19 were 5.2 and 1.5 %, re-
spectively (Table 2). The median age and sex ratio of
deaths were significantly higher than those who did not
die both in confirmed cases and clinically diagnosed
cases. The case fatality rates of severe and critical cases
were higher than those of mild and moderate cases, re-
spectively. The deaths of confirmed cases were concen-
trated in city centers, while the deaths of clinically
diagnosed cases were mainly concentrated in the sub-
urbs (Supplementary Fig. S6). The percentage of deaths
decreased over time during the early epidemic (Supple-
mentary Fig. S4). Univariable and multivariable logistic-
Table 1 Baseline Epidemiological Characteristics of Confirmed
Cases and Clinically Diagnosed Cases in Wuhan
Baseline Characteristics No. Confirmed
Cases (%)
No. Clinically
Diagnosed Cases (%)
Total 29886 21960
Age, median (IQR
a
), years 57.0(44.0–67.0) 54.0(41.0–65.0)
Age group, years
0~ 186(0.6) 220(1.0)
10~ 226(0.8) 173(0.8)
20~ 1371(4.6) 1412(6.4)
30~ 3720(12.4) 3280(14.9)
40~ 4435(14.8) 3736(17.0)
50~ 6347(21.2) 4851(22.1)
60~ 7678(25.7) 5007(22.8)
70~ 3979(13.3) 2285(10.4)
80~ 1671(5.6) 839(3.8)
≥90 217(0.7) 121(0.6)
Missing 56(0.2) 36(0.2)
Sex
Male 15059(50.4) 10165(46.3)
Female 14827(49.6) 11795(53.7)
Occupation
Child and student 439(1.5) 482(2.2)
Cadre 1489(5.0) 1119(5.1)
Freelancer 203(0.7) 194(0.9)
Physical labor 712(2.4) 641(2.9)
Public service staff 1816(6.1) 1477(6.7)
Housework or
unemployed
5684(19.0) 5401(24.6)
Retirees 10012(33.5) 6114(27.8)
Farmer or pastoral worker 1390(4.7) 1002(4.6)
Healthcare worker 1188(4.0) 1211(5.5)
Missing 6953(23.3) 4319(19.7)
Case severity
Mild 18192(60.9) 11326(51.6)
Moderate 4148(13.9) 7446(33.9)
Severe 5278(17.7) 2749(12.5)
Critical 823(2.8) 315(1.4)
Missing 1445(4.8) 124(0.6)
Death or not
Not 28322(94.8) 21703(98.8)
Yes 1564(5.2) 257(1.2)
Date of onset
Before Dec 31, 2019 135(0.5) 92(0.4)
Jan 1–10, 2020 591(2.0) 388(1.8)
Jan 11–20, 2020 2921(9.8) 1981(9.0)
Jan 21–31, 2020 13502(45.2) 7741(35.3)
Table 1 Baseline Epidemiological Characteristics of Confirmed
Cases and Clinically Diagnosed Cases in Wuhan (Continued)
Baseline Characteristics No. Confirmed
Cases (%)
No. Clinically
Diagnosed Cases (%)
Feb 1–10, 2020 9600(32.1) 8583(39.1)
Feb 11–20, 2020 2758(9.2) 3172(14.4)
Feb 21–24, 2020 355(1.2) ——
Missing 24(0.1) 3(0.0)
Days from onset to
diagnosis, median (IQR)
9.0 (5.0–13.0) 11.0 (5.0–18.0)
District of residence
City centre 23768(79.5) 17003(77.4)
Suburb 5577(18.7) 4755(21.7)
Outside Wuhan 339(1.1) 173(0.8)
Missing 202(0.7) 29(0.1)
Level of hospital
Tertiary hospital 21622(72.3) 18598(84.7)
Primary and secondary
hospital
8166(27.3) 3362(15.3)
Missing 98(0.3) ——
a
IQR interquartile range
Shi et al. Global Health Research and Policy (2021) 6:18 Page 4 of 11
regression was developed to predict the risk factors for
death from COVID-19. Age greater than 60 years, males,
and more serious case severity were found to be related
to an increased risk of death in both of two groups (Fig. 3
and Supplementary Table S5).
Rt of confirmed and clinically diagnosed cases
Rt curves showed the same trend in the two groups. For
confirmed (or clinically diagnosed) cases, Rt fluctuated
above 2.0 before January 30, reached a peak of 3.64
(3.54) on January 23 (January 22), and further declined
after Wuhan city lockdown, finally decreased to below
1.0 after February 6 (February 8). The trend of Rt was
shown in Fig. 4.
Discussion
Wuhan bore the brunt during the epidemic. To put pa-
tients into hospital and under treatment timely, the
clinically diagnosed cases had been identified from Feb-
ruary 8 to February 18. Besides, the number of clinically
diagnosed cases was revised on February 24 [7]. The
study is a comparison of the 29,886 confirmed cases and
21,960 clinically diagnosed cases with COVID-19 in the
early stage of the epidemic in Wuhan. To the best of our
knowledge, no other papers discussed these two types of
patients and how similar or dissimilar they are in de-
scribing the epidemic.
This study showed that the demographic characteris-
tics of confirmed and clinically diagnosed cases were
similar, suggesting that clinical diagnosis was effective
which could accurately detect the vast majority of
COVID-19 patients. The age and occupational distribu-
tion of clinically diagnosed cases were coincident with
those of confirmed cases. This study showed that people
of all ages were susceptible to the virus, but most pa-
tients were middle-aged and old people. Patients aged
Fig. 2 The cumulative numbers and incidence density of confirmed cases and clinically diagnosed cases with COVID-19 in 13 districts of Wuhan.
(a) rose diagram of cumulative confirmed cases, (b) rose diagram of cumulative clinically diagnosed cases. The 7 districts with blue series belong
to the city centers, and the 6 districts with orange series belong to the suburbs in Wuhan. (c) map of incidence density of confirmed cases, (d)
map of incidence density of clinically diagnosed cases
Shi et al. Global Health Research and Policy (2021) 6:18 Page 5 of 11
Table 2 Epidemiological Characteristics of Death Cases and Cases not Dead in Wuhan
Characteristics Confirmed Cases Clinically Diagnosed Cases P
Death (%) Not Dead
(%)
Case Fatality Rate
(%)
Death (%) Not Dead
(%)
Case Fatality Rate
(%)
Total 1564 28322 5.2 257 21703 1.2 <
0.001
Age, median (IQR
a
), years 70.0(63.0–
79.0)
56.0(53.0–
66.0)
—— 70.0(62.0–
78.0)
54.0(40.0–
65.0)
—— ——
Age group, years
0~ 0(0.0) 186(0.7) 0.0 0(0.0) 220(1.0) 0.0 ——
10~ 1(0.1) 225(0.8) 0.4 1(0.4) 172(0.8) 0.6 1.000
20~ 6(0.4) 1365(4.8) 0.4 1(0.4) 1411(6.5) 0.1 0.120
30~ 20(1.3) 3700(13.1) 0.5 3(1.2) 3277(15.1) 0.1 0.001
40~ 49(3.1) 4386(15.5) 1.1 9(3.5) 3727(17.2) 0.2 <
0.001
50~ 175(11.2) 6172(21.8) 2.8 34(13.2) 4817(22.2) 0.7 <
0.001
60~ 455(29.1) 7223(25.5) 5.9 77(30.0) 4930(22.7) 1.5 <
0.001
70~ 473(30.2) 3506(12.4) 11.9 80(31.1) 2205(10.2) 3.5 <
0.001
80~ 300(19.2) 1371(4.8) 18.0 45(17.5) 794(3.7) 5.4 <
0.001
≥90 52(3.3) 165(0.6) 24.0 6(2.3) 115(0.5) 5.0 <
0.001
Missing 33(2.1) 23(0.1) 58.9 1(0.4) 35(0.2) 2.8 <
0.001
Sex
Male 1026(65.6) 14033(49.5) 6.8 177(68.9) 9988(46.0) 1.7 <
0.001
Female 538(34.4) 14289(50.5) 3.6 80(31.1) 11715(54.0) 0.7 <
0.001
Occupation
Child and student 2(0.1) 437(1.5) 0.5 0(0.0) 482(2.2) 0.0 0.227
Cadre 31(2.0) 1458(5.1) 2.1 4(1.6) 1115(5.1) 0.4 <
0.001
Freelancer 6(0.4) 197(0.7) 3.0 1(0.4) 193(0.9) 0.5 0.143
Physical labor 19(1.2) 693(2.4) 2.7 4(1.6) 637(2.9) 0.6 0.004
Public service staff 23(1.5) 1793(6.3) 1.3 2(0.8) 1475(6.8) 0.1 <
0.001
Housework or unemployed 267(17.1) 5417(19.1) 4.7 57(22.2) 5344(24.6) 1.1 <
0.001
Retirees 753(48.1) 9259(32.7) 7.5 104(40.5) 6010(27.7) 1.7 <
0.001
Farmer or pastoral worker 51(3.3) 1339(4.7) 3.7 15(5.8) 987(4.5) 1.5 0.001
Healthcare worker 12(0.8) 1176(4.2) 1.0 2(0.8) 1209(5.6) 0.2 0.007
Missing 400(25.6) 6553(23.1) 5.8 68(26.5) 4251(19.6) 1.6 <
0.001
Case severity
Mild 603(38.6) 17589(62.1) 3.3 79(30.7) 11247(51.8) 0.7 <
0.001
Moderate 69(4.4) 4079(14.4) 1.7 31(12.1) 7415(34.2) 0.4 <
0.001
Shi et al. Global Health Research and Policy (2021) 6:18 Page 6 of 11
over 60 years accounted for 41·0 % of confirmed cases
and 36·6 % of clinically diagnosed cases. Age-related de-
cline and dysregulation of immune function give rise to
the heightened vulnerability to COVID-19 in the elderly
[16]. Retirees accounted for the largest proportion of pa-
tient’s occupations, which may be due to the fact that re-
tirees are usually older adults. The median (IQR)
interval between onset and diagnosis in confirmed cases
was 9 (5–13) days, which were slightly shorter than that
in clinically diagnosed cases [11 (5–17) days]. Patients
with early-onset received the nucleic acid diagnosis pref-
erentially, while the patients with late-onset could not
receive RT-PCR or genome sequencing of SARS-COV-2
in time when the detection kits were insufficient. Be-
sides, Wuhan experienced the peak of the COVID-19
outbreak between the Wuhan lockdown and February 8,
which accelerated the consumption of detection reagents
and the backlog of patients. At this time, it was neces-
sary to carry out a clinical diagnosis for patients who
had already developed symptoms but could not be con-
firmed by the laboratory, since the condition will worsen
if they could not be isolated or admitted promptly. The
interval between onset and diagnosis had seen a con-
tinuous decrease as time went by, meaning the
Table 2 Epidemiological Characteristics of Death Cases and Cases not Dead in Wuhan (Continued)
Characteristics Confirmed Cases Clinically Diagnosed Cases P
Death (%) Not Dead
(%)
Case Fatality Rate
(%)
Death (%) Not Dead
(%)
Case Fatality Rate
(%)
Severe 477(30.5) 4801(17.0) 9.0 73(28.4) 2676(12.3) 2.7 <
0.001
Critical 210(13.4) 613(2.2) 25.5 39(15.2) 276(1.3) 12.4 <
0.001
Missing 205(13.1) 1240(4.4) 14.2 35(13.6) 89(0.4) 28.2 <
0.001
Date of onset
Before Dec 31, 2019 29(1.9) 106(0.4) 21.5 4(1.6) 88(0.4) 4.3 <
0.001
Jan 1–10, 2020 132(8.4) 459(1.6) 22.3 9(3.5) 379(1.7) 2.3 <
0.001
Jan 11–20, 2020 392(25.1) 2529(8.9) 13.4 30(11.7) 1951(9.0) 1.5 <
0.001
Jan 21–31, 2020 769(49.2) 12733(45.0) 5.7 95(37.0) 7646(35.2) 1.2 <
0.001
Feb 1–10, 2020 215(13.7) 9385(33.1) 2.2 84(32.7) 8499(39.2) 1.0 <
0.001
Feb 11–20, 2020 26(1.7) 2732(9.6) 0.9 32(12.5) 3140(14.5) 1.0 0.796
Feb 21–24, 2020 0(0.0) 355(1.3) 0.0 0(0.0) 0(0.0) —— ——
Missing 1(0.1) 23(0.1) 4.2 3(1.2) —— 0.0 ——
Days from onset to diagnosis, median
(IQR)
10.0(7.0–
14.0)
9.0(4.0–13.0) —— 8.0(3.0–15.0) 11.0(5.0–
18.0)
—— ——
District of residence
City centre 1208(77.2) 22560(79.6) 5.1 169(65.8) 16834(77.6) 1.0 <
0.001
Suburb 227(14.5) 5350(18.9) 4.1 58(22.6) 4697(21.6) 1.2 <
0.001
Outside Wuhan 33(2.1) 306(1.1) 9.7 1(0.4) 172(0.8) 0.6 <
0.001
Missing 96(6.1) 106(0.4) 47.5 29(11.3) —— —— ——
Level of hospital
Tertiary hospital 1254(80.2) 20368(71.9) 5.8 205(79.8) 18393(84.7) 1.1 <
0.001
Primary / secondary hospital 310(19.8) 7856(27.8) 3.8 52(20.2) 3310(15.3) 1.5 <
0.001
Missing —— 98(0.3) —— —— —— —— ——
a
IQR interquartile range
Shi et al. Global Health Research and Policy (2021) 6:18 Page 7 of 11
implementation of clinical diagnosis effectively short-
ened the duration before diagnosis in the early stage of
the epidemic. When the median interval between onset
and diagnosis was shortened to 2 days, the clinical diag-
nosis was canceled on February 19, 2020.
There are 13 districts in Wuhan: Jiang’an, Jianghan,
Qiaokou, Hanyang, Wuchang, Qingshan, Hongshan,
Dongxihu, Hannan, Caidian, Jiangxia, Huangpi and
Xinzhou, the first seven of which are city centers. The
cumulative number of patients in the city centers was
4.7 and 3.6 times those in the suburbs among confirmed
cases and clinically diagnosed cases, respectively. The
city centers have a large number of permanent residents
and floating populations, which is prone to the spread of
Fig. 3 Risk factors for death in COVID-19 patients from multivariable logistic-regression analysis
Fig. 4 Estimated Rt of confirmed cases and clinically diagnosed cases with COVID-19 in Wuhan, China. The 95 % confidence intervals are
presented as red or blue shading. The gray horizontal line indicates Rt = 1, below which suggests that the outbreak is gradually controlled
Shi et al. Global Health Research and Policy (2021) 6:18 Page 8 of 11
the virus. Besides, the city centers have abundant and
concentrated medical resources, for example, there are
more tertiary hospitals (Supplementary Fig. S7), which
makes it easier for the infected people there to be diag-
nosed than suburbanites. The geographical distribution
of incidence density in confirmed and clinically diag-
nosed cases was similar, the incidence density in city
centers was 2.8 times that in suburbs among confirmed
cases, and 2.4 times among clinically diagnosed cases.
City centers were hardest-hit regions of the COVID-19
epidemic, it is necessary to carry out key monitoring,
prevention and control of the epidemic in city centers.
The proportion of severe and critical types in confirmed
cases was significantly higher than that in clinically diag-
nosed cases (21.5 % vs. 14.0 %, P<0.05). Therefore, the
case fatality rate of confirmed cases was considerably sig-
nificantly above that of clinically diagnosed patients (5.2 %
vs. 1.5 %, P< 0.05). In the case of limited detection re-
agents, severe and critical cases received the nucleic acid
diagnosis preferentially. Approximately 67 % of severe and
critical patients were laboratory-confirmed, while only
54 % of mild and moderate patients obtained the virus nu-
cleic acid tests. Some critical patients who progressed to
acute respiratory distress syndrome (ARDS) after mild
symptoms for 7–8 days had been observed [17], implying
the early recognition of infected cases is extremely import-
ant and mild patients should also receive early treatment
to avoid becoming critically ill [15]. Therefore, it was ne-
cessary to carry out clinical diagnosis under the condition
of a large backlog of suspected cases in Wuhan in the
early stage of the COVID-19 epidemic. Besides, the geo-
graphical distributions of dead confirmed cases and dead
clinically diagnosed cases were diverse. The dead con-
firmed cases were concentrated in city centers, while the
deaths of clinically diagnosed cases were mainly concen-
trated in the suburbs. Suburban residents might not get
laboratory-confirmation promptly due to relatively defi-
cient health resources here. For example, there are less
than 5 tertiary-A hospitals in suburbs, but more than 20
tertiary-A hospitals in city centers. In regions with insuffi-
cient medical resources, clinical diagnosis is an important
supplement to laboratory-diagnostic methods. Many
COVID-19 patients who lived in the suburbs had bene-
fited from clinical diagnosis and received timely treatment.
Thanks to the health public measures including the imple-
mentation of clinical diagnosis, the proportion of severe
and critical cases as well as case-fatality rate had a con-
tinuous decrease, meaning those measures is helpful to
control the growth of severe and critical cases and death.
The common risk factors for severity and death of the
two groups were evaluated. This study found that aging
was a prominent risk factor for severe disease and death
from COVID-19, which was consistent with early reports
[11,13,18]. The immune function and organ reserve
capacity of the elderly are receded, and they tend to have
serious underlying illnesses, the older the age is, the
more severe the disease is [19]. Infectious disease, espe-
cially acute infection will bring adverse prognosis and
death risk to the elderly. The elderly should be regarded
as the key population for epidemic prevention and con-
trol [20,21]. Sex was also closely related to the severity
and death. Research from Johns Hopkins University
found that the average case fatality rate of males across
38 countries was 1.7 times higher than that of females
[22]. In our study, case fatality rate of males was 1.9
times higher than that of females among confirmed
cases, and 2.4 times among clinically diagnosed cases.
The male bias in severity and mortality of COVID-19
stems from the pathogenesis of SARS-CoV-2 infection.
X chromosome and estrogen protect females from lethal
infection [21,23]; besides, numerous studies indicted
ACE2, which used by SARS-CoV-2 to enter into the
host cells [24,25], generally has a higher expression in
males than in females; moreover, females and males vary
in their susceptibility and response to viral infections,
the number and activity of innate immune cells, and im-
mune responses are higher in females than in males
[26]. There were some influencing factors that had op-
posite effects on the clinical outcomes in the two groups.
Later date of onset was associated with a better chance
of survival for confirmed cases, with no association
found for clinically diagnosed cases. Besides, the tertiary
hospitals with better medical level were associated with
better clinical outcomes in confirmed cases, but were as-
sociated with worse outcomes in clinically diagnosed
cases. We speculated that was because mild clinically di-
agnosed cases often went to primary hospitals, while
clinically diagnosed cases with more serious illnesses
were diagnosed and treated in big hospitals. The reason-
able shunt of clinically diagnosed cases eased the med-
ical pressure of tertiary-A hospitals.
The transmission dynamics of COVID-19 were identical
in confirmed and clinically diagnosed cases. Their Rt both
declined rapidly from the peak after the lockdown of Wu-
han, and further decreased to below 1 after clinical diagno-
sis. It proves that rapid public health responses including
the Wuhan lockdown and the implementation of clinical
diagnosis, have successfully contained the spread of SARS-
CoV-2 and mitigated the development of the epidemic.
Our study has several limitations. Firstly, there were a
few missing values that might slightly affect the result.
Secondly, the clinical outcomes of COVID-19 cases in
our study were followed up to February 24, 2020, when
many patients had not been discharged, so the ultimate
case fatality rate could not be calculated [27]. According
to the National Health Commission of China, a total of
50,333 cases were confirmed with COVID-19 in Wuhan
and 3869 died as of April 30, 2020, the case fatality rate
Shi et al. Global Health Research and Policy (2021) 6:18 Page 9 of 11
was 7.7 %. It speculates that many patients died later.
Thirdly, data reliability of the interval between onset and
diagnosis depended on the patients, which might cause
some recall bias. Finally, we once again reiterated that
the results were based on the data of Wuhan where was
the worst-hit region in China, so it should be prudent to
extrapolate those data to areas with less epidemic.
Conclusion
In summary, the demographic characteristics and spatiotem-
poral distributions of confirmed and clinically diagnosed
cases were roughly similar, but the disease severity as well as
clinical outcome of clinically diagnosed cases were better
than those of confirmed cases. The proportion of severe and
critical cases, case-fatality rate as well as Rt of the two
groups both decreased over time, suggesting that the swift
measures China took, including the Wuhan lockdown and
the implementation of clinical diagnosis, have successfully
mitigated the development of the epidemic. In cases when
medical resources are insufficient to cover the viral nucleic
acid test of all COVID-19 cases, clinical diagnosis is effective
and necessary. Clinical diagnosis is helpful to shorten the
interval between onset and diagnosis, quarantine or treat pa-
tients as soon as possible, and improve the cure rate.
Abbreviations
SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; COVID-
19: Corona Virus Disease 2019; RT-PCR: Real-time reverse transcriptase–
polymerase chain reaction; IQR: Interquartile range; OR: Odds ratio;
Rt: Effective reproduction number
Supplementary information
The online version contains supplementary material available at https://doi.
org/10.1186/s41256-021-00200-8.
Additional file 1.
Authors’contributions
CY supervised the study. CY, FS and HW designed the study. CY, FS, HW and
JB collected and organized the data. FS, HW and RL analyzed the data. FS,
FW, SM, XL, YY, QH and JC interpreted the results. FS wrote the first draft. All
authors read and approved the final manuscript.
Funding
This work was supported by the National Key Research and Development
Program of China (grant numbers 2017YFC1200502, 2018YFC1315302); the
National Natural Science Foundation of China (grant number 81773552); and
the Special Foundation for Basic Scientific Research of Central Universities
(grant number 2020YJ066). The funder of the study had no role in study
design, data collection, data analysis, data interpretation, or writing of the
report. The corresponding author had full access to all the data in the study
and had final responsibility for the decision to submit it for publication.
Availability of data and materials
The data that support the findings of this study are available from the
National Health Commission of the People’s Republic of China, but
restrictions apply to the availability of these data, which were used under
license for the current study, and so are not publicly available. Data are
however available from the authors upon reasonable request and with
permission of the National Health Commission of the People’s Republic of
China.
Declarations
Ethics approval and consent to participate
Data collection, which was determined by the National Health Commission
of the People’s Republic of China, was exempt from institutional review
board approval because it was part of an outbreak investigation. Study
design and data analysis have been reviewed and approved by the Medical
Ethical Committees of Wuhan University (WHU2020-2020YF0031).
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Department of Epidemiology and Biostatistics, School of Health Sciences,
Wuhan University, 430071 Wuhan, China.
2
NHC Key lab of Radiation Biology,
Jilin University, 130021 Changchun, China.
3
School of Public Health and
Management, Hubei University of Medicine, 442000 Shiyan, China.
4
Department of Global Health, School of Health Sciences, Wuhan University,
430071 Wuhan, China.
5
Global Health Institute, Wuhan University, 430072
Wuhan, China.
Received: 17 December 2020 Accepted: 10 May 2021
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