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atmosphere
Article
Analysis of Symptomology, Infectiveness, and Reinfections
between Male and Female COVID-19 Patients: Evidence from
Japanese Registry Data
Meng-Hao Li 1, Abu Bakkar Siddique 1, Ali Andalibi 2, *,† and Naoru Koizumi 1 ,*, †
Citation: Li, M.-H.; Siddique, A.B.;
Andalibi, A.; Koizumi, N. Analysis of
Symptomology, Infectiveness, and
Reinfections between Male and
Female COVID-19 Patients: Evidence
from Japanese Registry Data.
Atmosphere 2021,12, 1528. https://
doi.org/10.3390/atmos12111528
Academic Editors: Wan-ki Chow,
Kwok Wai Tham and Yanfeng Li
Received: 4 October 2021
Accepted: 15 November 2021
Published: 19 November 2021
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Copyright: © 2021 by the authors.
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This article is an open access article
distributed under the terms and
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Attribution (CC BY) license (https://
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4.0/).
1Schar School of Policy and Government, George Mason University, Arlington, VA 22201, USA;
r2atuic@gmail.com (M.-H.L.); asiddi@gmu.edu (A.B.S.)
2College of Science, George Mason University, Fairfax, VA 22030, USA
*Correspondence: aandalib@gmu.edu (A.A.); nkoizumi@gmu.edu (N.K.)
† These authors contributed equally to this work.
Abstract:
Background: Hokkaido was the first Japanese prefecture to be affected by COVID-19.
Since the beginning of the pandemic, the Japanese government has been publishing the information
of each individual who was tested positive for the virus. Method: The current study analyzed
the 1269 SARS-CoV-2 cases confirmed in Hokkaido in order to examine sex-based differences in
symptomology and infectiveness, as well as the status of reinfections and the viral transmission
networks. Results: The majority of asymptomatic patients were females and older. Females were
1.3-fold more likely to be asymptomatic (p< 0.001) while a decade of difference in age increased the
likelihood of being asymptomatic by 1% (p< 0.001). The data contained information up to quaternary
viral transmission. The transmission network revealed that, although asymptomatic patients are
more likely to transmit the virus, the individuals infected by asymptomatic cases are likely to be
asymptomatic (p< 0.001). Four distinct co-occurrences of symptoms were observed, including (i)
fever/fatigue, (ii) pharyngitis/rhinitis, (iii) ageusia/anosmia, and (iv) nausea/vomiting/diarrhea.
The presences of diarrhea (p= 0.05) as well as nausea/vomiting (p< 0.001) were predictive of develop-
ing dyspnea, i.e., severe disease. About 1% of the patients experienced reinfection. Conclusions: Sex
and symptomatology appear to play important roles in determining the levels of viral transmission
as well as disease severity.
Keywords:
SAR-COV2; COVID-19; viral transmission networks; severity factor;
asymptomatic carriers
1. Introduction
Infection by SARS-CoV-2 results in the development of mild to serious symptoms in
most individuals, with severity being dependent on age and comorbidities [
1
–
3
]. However,
there is mounting evidence that a significant number of infected individuals are asymp-
tomatic [
4
,
5
]. An asymptomatic SARS-CoV-2 infection refers to the situation where no
clinical signs or symptoms, nor imaging abnormalities, are apparent in an individual who is
confirmed to be infected with the virus by reverse transcriptase-polymerase chain reaction
(RT-PCR) [
6
]. Given that asymptomatic patients appear to constitute a significant portion
of infections [
7
], understanding the factors that are associated with being asymptomatic
is important.
Japan has not been spared from the COVID-19 pandemic, and as of 18 January 2021,
there have been 326,208 cases of the disease reported in the country [
8
]. Hokkaido was the
first Japanese prefecture to be affected by COVID-19 with the first reported case being a
tourist from Wuhan, China, a 40-year-old female who had the COVID-19 symptoms (fever,
cough, fatigue, and pneumonia) on 26 January [
8
]. A State of Emergency was declared on
28 February when the number of cumulative confirmed cases reached 65. Issuance of a
stay-at-home order, as well as the implementation of social distancing and active contact
Atmosphere 2021,12, 1528. https://doi.org/10.3390/atmos12111528 https://www.mdpi.com/journal/atmosphere
Atmosphere 2021,12, 1528 2 of 14
tracing measures called “cluster countermeasure” by the local government [
9
], resulted in
a quick reduction in new cases by mid-March. With the disease seemingly under control,
the government lifted the State of Emergency on 17 March. However, soon thereafter new
cases began to surge again, particularly after the 3-day Equinox holiday between 20 and
22 March [
10
]. On 14 April, the government declared a State of Emergency for the second
time. Although the State of Emergency was re-lifted on 25 May and the number of cases
was no longer surging at the same rate, the prefecture remained designated as one “under
special precautions” (Figure 1) [11].
Since the beginning of the COVID-19 outbreak, the Japanese government has been
publishing the information of each individual who was tested positive for the virus. The
current study leveraged registry data from Hokkaido between mid-February and mid-July
in order to investigate the viral transmission and clinical characteristics of COVID-19. The
registry data published by the government were particularly detailed in the early stage of
the pandemic, including the period covered under the current study. The data contain rich
information about the transmission paths as a result of the government’s intensive contract
tracing effort [9,12,13].
Figure 1.
The cumulative cases of COVID-19 patients in Hokkaido (14 February–22 July 2020). Sources: Author generated
using the information from the following sources: http://www.pref.hokkaido.lg.jp/hf/kth/kak/hasseijoukyou.htm [
8
];
https://time.com/5826918/hokkaido-coronavirus-lockdown/ [
10
]; http://www.pref.hokkaido.lg.jp/ss/tuk/900brr/
index2.htm#5sai-kaikyu [13]. (Accessed on 16 November 2021).
2. Materials and Methods
2.1. Data
We queried government registries for about a 5-month period between 14 February
(the date when the first PCR positive case was identified in Hokkaido, excluding the tourist
from Wuhan, China) and 22 July 2020. All COVID-19 cases confirmed by the local PHCs
must be reported to the Ministry of Health, Labor and Welfare in Japan [
12
]. These PHCs
also collect, record, and publish demographic, symptomatological, and epidemiologic
information, such as transmission paths (likely infectors and infectees) and travel history,
of the confirmed cases with informed consents [
12
]. Of the 1370 PCR-confirmed cases in
Hokkaido during the study period, 1269 cases (93% including 674 females and 595 males)
had comprehensive demographic and symptomatological information including sex; age
(<10, 11–20, 21–30, 31–40, 41–50, 51–60, 61–70, 71–80, 81–90, 91–100, or >100); the city of
residence or the testing site; the dates of PCR and the onset of symptoms; and symptoms
experienced (if any).
Atmosphere 2021,12, 1528 3 of 14
Contract tracing was administered by public health centers (PHCs) across the nation
in order to retrospectively investigate all identifiable individuals who had had in-person
contact with each confirmed case during the prior 14 days [
13
–
15
]. Individuals who were
determined to have been in “close contact” with the confirmed cases were subjected to
an “initial (PCR) screening test”, even when their source case (i.e., the infector) had no
COVID-19 related symptoms [
14
]. The government defined the individuals who were
in “close contact” as follows: (i) cohabitants of the confirmed cases; (ii) individuals who
had spent long hours in an indoor setting (including a car and a flight) with confirmed
cases; (iii) individuals who had provided (medical and nursing) care to the confirmed cases
without adequate personal protective equipment; (iv) individuals who were likely to have
been exposed to droplets or other body fluids of the confirmed cases; or (iv) individuals
who had been within 1 m (6 feet) radius of the confirmed cases for a total of 15 min or more
without protection [ibid]. Other individuals whose in-person contact with the confirmed
cases did not meet the definition of “close contact” were requested to self-quarantine for
14 days
and were guided to receive a test only if any COVID-19 related symptoms appeared
during the monitoring period. Individuals who did not develop any symptoms during the
monitoring period were, in general, not subject to the testing unless (i) they were in the
occupations that involved high in-person interactions with COVID-19 patients or
(ii) they
were linked to a “cluster” [
13
–
15
]. Here, a “cluster” was defined as a group of five or
more confirmed positive cases who were unrelated within themselves (i.e., no identifiable
in-person interactions) but were traced back to a specific event or location [15].
Epidemiologic data, i.e., the viral transmission paths, were available for 371 cases.
Some of these 371 cases were connected to multiple cases, indicating that they had multiple
possibilities of exposure to infectors and/or infectees. For instance, all family members were
more likely to be connected to each other, because, with the exception of the source family
member who infected his/her family members, the specific transmission paths within the
family are generally unknown. This also applied to the cases of “cluster” infections where
a group of infectors/infectees emerged in one location, e.g., a nursing home.
2.2. Analysis
Clinical characteristics observed in female and male patients were compared using
t-tests for continuous variables and chi-squared tests for nominal variables. Depending
on the distribution of a continuous variable and the sample size of a nominal variable,
Wilcoxon–Mann–Whitney and Fisher’s exact tests were used to replace t-square and chi-
square tests, respectively. Sex-adjusted clinical characteristics observed in age groups
were also compared using t-squared/Wilcoxon–Mann–Whitney and Chi-squared/Fisher’s
exact tests.
Our data included PCR-positive COVID-19 patients without overt symptoms at the
time of the laboratory-confirmed infection. While these cases may be pre-symptomatic, we
have defined them as asymptomatic cases as suggested in the registry notes and to conform
to the current guideline by WHO [
16
]. Our data also included a fraction of individuals
who appeared in the registry twice, with notes indicating that these were “reinfection”
cases. While our data did not contain enough evidence to determine whether these are
truly reinfection cases or more likely to be reactivation or false-positive cases, the notes
in the registry indicated that these patients had tested negative by PCR on two separate
occasions before being discharged from the hospital (or hotel for asymptomatic patients)
due to their first infection. In the absence of other evidence, including viral sequence data,
we defined these cases as reinfections.
In order to identify factors correlated with asymptomatic cases, multivariate logistic
regression was run with the absence of symptoms as the dependent variable. For the
symptomatic cases, a supervised principal component analysis (PCA) was performed to
assess the co-occurrence of symptoms. For each retained factor (i.e., a set of co-occurring
symptoms), we estimated the factor score, which was subsequently used in multivariate
logistic regression to identify the factor score correlated with the severity of COVID-19.
Atmosphere 2021,12, 1528 4 of 14
Here, we defined severe cases by the presence of dyspnea. In order to visually inspect
the patterns of viral transmissions, we constructed viral transmission networks using the
records of the patients whose infectors or infectees were known in the registry. Network
construction and visualization were conducted by using programming language R (R Core
Team) and visualization software Gephi (v 0.9.2). All statistical analyses were performed in
STATA (StataCorp, v14). For all analyses, statistical significance was defined by p
≤
0.05
unless noted otherwise.
3. Results
3.1. Symptoms
No significant difference was observed in the mean age of male and female COVID-19
patients (54 vs. 53; p= 0.24). The most common symptom was fever, affecting 81% of
females and 88% of males (Table 1). Fatigue and the presence of coughs were the next most
common symptoms, each affecting around 40% of both females and males. Surprisingly,
the number of female asymptomatic cases was nearly twice that of males (177 or 26%
vs. 80 or 13%, p< 0.001). Analysis of age-related differences by sex (Table 2) indicated
that headaches were more common in men and women between the ages of 20 and 40
(
p< 0.001
for both men and women), whereas loss of taste was more common in men and
women aged between 10 and 30 (p< 0.001 for both men and women). Body ache was
less common among older patients (>59) (p< 0.001 for males and p= 0.01 for females).
Although the number of patients who reported nausea/vomiting was small (n= 27), there
was a significant statistical correlation between young age (10–19) and the presence of the
symptoms for females (p= 0.05).
Table 1. Demographic and clinical characteristics of the patients.
Patient Characteristics Male (n= 595) Female (n= 674) p-Value
Age 1, mean (SD) 54 (23) 53 (22) 0.24
Asymptomatic cases, n(%) 80 (13%) 177 (26%) <0.001
Symptom, n(%)
Fever 430 (88%) 388 (81%) 0.01
Cough 202 (41%) 193 (40%) 0.77
Pharyngitis 72 (15%) 102 (21%) 0.01
Rhinitis 60 (12%) 97 (20%) 0.01
Fatigue 213 (43%) 195 (41%) 0.38
Diarrhea 44 (9%) 49 (10%) 0.51
Headache 82 (15%) 103 (21%) 0.05
Pneumonia 71 (14%) 54 (11%) 0.14
Dyspnea 70 (14%) 53 (11%) 0.13
Loss of taste 73 (15%) 94 (20%) 0.05
Loss of smell 8 (2%) 9 (2%) 0.77
Reduced appetite 12 (2%) 6 (1%) 0.17
Body aches 73 (15%) 58 (12%) 0.20
Nausea/Vomiting 5 (1%) 22 (5%) 0.001
Phlegm 8 (2%) 13 (3%) 0.24
Chill 2 (<1%) 3 (1%) 0.64
Reinfection cases, n(%) 4 (1%) 4 (1%) 0.79
No. of symptoms 2, mean (SD) 2.91 (1.52) 3.00 (1.62) 0.34
No. of individuals who infected
others, n(%) 122 (21%) 88 (13%) <0.001
Avg. no. of infectees per infector,
mean (SD) 3.48 (5.07) 3.89 (5.90) 0.60
Duration: Onset-PCR, mean # days
(SD) 6.90 (6.55) 6.29 (5.23) 0.09
1Age was treated as a continuous variable. 2Exclude asymptomatic cases.
Atmosphere 2021,12, 1528 5 of 14
Table 2. Symptom by age and sex.
Symptoms 1–9 10–19 20–29 30–39 40–49 50–59 60–69 70–79 80–89 90–99 Total p-Value
M F M F M F M F M F M F M F M F M F M F M F M F
Fever (n)12 2 5 10 38 43 39 40 59 49 63 56 80 49 75 62 39 39 12 25 422 375
(%) 100.00 100.00 62.50 90.91 84.44 75.44 88.64 83.33 89.39 84.48 91.30 82.35 90.91 76.56 87.21 80.52 81.25 81.25 80.00 92.59 87.73 81.52 0.25 0.54
Cough (n)5 0 2 3 17 30 26 23 36 26 31 24 29 24 37 35 12 14 5 9 200 188
(%) 41.67 0.00 25.00 27.27 37.78 52.63 59.09 47.92 54.55 44.83 44.93 35.29 32.95 37.50 43.02 45.45 25.00 29.17 33.33 33.33 40.87 40.87 0.02 0.21
Pharyngitis (n)0 0 0 3 4 18 10 11 10 11 17 17 16 19 11 13 3 4 0 2 71 98
(%) 0 0 0 27.27 8.89 31.58 22.73 22.92 15.15 18.97 24.64 25.00 18.18 29.69 12.79 16.88 6.25 8.33 0 7.41 14.76 21.3 0.03 0.05
Rhinitis (n)4 0 1 6 9 18 5 21 6 8 8 11 10 11 11 9 2 3 1 2 57 89
(%) 33.33 0 12.50 54.55 20.00 31.58 11.36 43.75 9.09 13.79 11.59 16.18 11.36 17.19 12.79 11.69 4.17 6.25 6.67 7.41 11.85 19.35 0.22 <0.001
Fatigue (n)0 0 4 2 19 28 25 20 35 27 33 34 35 24 38 28 18 16 3 12 210 191
(%) 0 0 50.00 18.18 43.18 49.12 56.82 41.67 53.03 46.55 47.83 50.00 39.77 37.50 44.19 36.36 37.50 33.33 20.00 44.44 43.66 41.52 0.02 0.31
Diarrhea (n)0 0 2 2 4 3 4 8 6 4 9 12 9 9 6 7 3 3 0 1 43 49
(%) 0.00 0.00 25 18.18 8.89 5.26 9.09 16.67 9.09 6.90 13.04 17.65 10.23 14.06 6.98 9.09 5.77 6.25 0 3.70 8.94 10.65 0.51 0.21
Headache (n)0 0 2 3 20 20 12 21 16 14 12 17 13 6 6 13 1 2 0 1 82 97
(%) 0 0 25.00 27.27 44.44 35.09 27.27 43.75 24.24 24.14 17.39 25.00 14.77 9.38 6.98 16.88 2.08 4.17 0 3.70 17.05 21.09 <0.001 <0.001
Pneumonia (n)0 0 0 0 5 4 5 3 9 10 13 13 14 3 17 9 7 5 0 6 70 53
(%) 0.00 0.00 0.00 0.00 11.11 7.02 11.36 6.25 13.64 17.24 18.84 19.12 15.91 4.69 19.77 11.69 14.58 10.42 0.00 22.22 14.55 11.52 0.37 0.07
Dyspnea (n)0 0 1 0 3 10 8 4 10 8 12 9 9 10 13 4 13 5 1 3 70 53
(%) 0.00 0.00 12.50 0.00 6.67 17.54 18.18 8.33 15.15 13.79 17.39 13.24 10.23 15.63 15.12 5.19 27.08 10.42 6.67 11.11 14.55 11.11 0.15 0.45
Loss of Taste (n)1 0 4 5 18 22 13 18 15 13 10 14 6 8 3 2 2 6 0 2 72 90
(%) 8.33 0.00 50.00 45.45 40.00 39.6 29.55 37.50 22.73 22.41 14.49 20.59 6.82 12.50 3.49 2.60 4.17 12.50 0 7.41 14.97 19.57 <0.001 <0.001
Loss of Smell (n)0 0 0 0 5 3 2 1 1 0 0 0 0 2 0 1 0 0 0 0 8 7
(%) 0.00 0.00 0.00 0.00 11.11 5.26 4.55 2.08 1.52 0.00 0.00 0.00 0.00 3.13 0.00 1.30 0.00 0.00 0.00 0.00 1.66 1.47 <0.001 0.36
Reduced
Appetite (n)0 0 0 0 1 0 0 1 2 0 0 0 3 1 4 4 1 0 0 0 11 6
(%) 0.00 0.00 0.00 0.00 2.08 0.00 0.00 2.08 3.03 0.00 0.00 0.00 3.41 1.56 4.65 5.19 2.08 0.00 0.00 0.00 2.29 1.30 0.71 0.17
Body Aches (n)0 0 2 3 6 9 14 8 15 11 11 14 14 5 8 5 1 0 0 1 71 56
(%) 0.00 0.00 25.00 27.27 13.33 15.79 31.82 16.67 22.72 18.97 15.94 20.59 15.91 7.69 9.30 6.02 2.08 0.00 0.00 3.70 14.76 12.17 <0.001 0.01
Nausea/Vomiting
(n)0 0 1 3 0 4 1 1 0 2 0 1 2 5 1 3 0 2 0 1 5 22
(%) 0.00 0.00 12.50 27.27 0.00 7.02 2.27 2.08 0.00 3.45 0.00 1.47 2.27 7.81 1.16 3.90 0.00 4.17 0.00 3.70 1.04 4.78 0.10 0.05
Phlegm (n)0 0 0 1 1 2 4 0 0 3 2 2 0 1 0 1 0 2 1 0 8 12
(%) 0.00 0.00 0.00 9.09 2.22 3.51 9.09 0.00 0.00 5.17 2.90 2.94 0.00 1.56 0.00 1.30 0.00 4.17 6.67 0.00 1.66 2.61 0.01 0.65
Chill (n)0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 2 3
(%) 0.00 0.00 0.00 0.00 2.22 0.00 2.27 0.00 0.00 1.72 0.00 0.00 0.00 1.56 0.00 0.00 0.00 0.00 0.00 3.70 0.42 0.65 0.45 0.56
Atmosphere 2021,12, 1528 6 of 14
3.2. Reinfection
The data contained nine cases of reinfection, including four females ranging in age
from 10 to 70 (one patient was 10 years old, one was 30 years old, one was 50 years old,
and one was 70 years old) and four males ranging from 30 to 90 (one patient was 30, one
patient was 40, one patient was 60, and one was 90) (Table 1). One person who experienced
reinfection did not have complete data and was excluded from further analysis. After
excluding this individual, reinfection cases made up approximately 1% of the total number
of cases in both males and females. The duration between the confirmation of the first and
second episodes of COVID-19 (both by PCR) ranged between 16 days and 42 days, with a
mean of 29 (
±
9.6) days. One of the individuals, who was asymptomatic at the first PCR,
was shown to be PCR positive again 41 days later, with fever as the only symptom of the
disease. This individual had had two negative PCR tests in the period between the first
PCR and the one 41 days later. As such, although it is possible that he had not completely
cleared the virus and had a sub-PCR detectible viral load that spiked some 5 weeks later, it
is also possible that he became reinfected by the virus. In the seven remaining cases, the
symptoms of the first infection were generally similar to those of the second infection, as
was the number of symptoms experienced.
3.3. Asymptomatic Patients
Table 3summarizes the number of asymptomatic patients by age and sex. The majority
of asymptomatic patients were females and older. Out of the 10 decadal age groups into
which the patients were classified, there was a statistically significant difference in six of
them between the number of asymptomatic males versus females (0 or 0% vs. 3 or 60%,
p= 0.003
, in ages 1–9; 4 or 8% vs. 19 or 25%, p= 0.002, in ages 20–29; 5 or 10% vs. 16 or 25%,
p= 0.005
, in ages 30–39; 4 or 5% vs. 16 or 18%, p= 0.001, in ages 50–59; 13 or 20% vs. 39 or
44%, p= 0.002, in ages 80–89; 5 or 22% vs. 25 or 48%, p= 0.003, in ages 90–99). Although
the difference between asymptomatic females and males was not significant for every age
group, the pattern was present in all of the groups, strongly suggesting that the observed
differences are highly likely.
Table 3. Asymptomatic patients by age and sex.
Asymptomatic 1–9 10–19 20–29 30–39 40–49 50–59 60–69 70–79 80–89 90–99 Total
M F M F M F M F M F M F M F M F M F M F M F
No (n) 12 2 8 11
46 58 44
48 68 59
71 72 91 65 91
83
52 50 18 27 515 497
(%)
100
40
57
85
92 75 90
75 84 82
95 82 89 81 84
81
80 56 78 52 87
74
Yes (n) 0 3 6 2 4
19
5 16 13 13 4
16 11 15 17
20
13 39
5
25 80 177
(%) 0 60
43
15 8
25 10
25 16 18 5
18 11 19 16
19
20 44 22 48 13
26
Total (n) 12 5
14
13
50 77 49
64 81 72
75 88 102 80 108 103 65 89 23 52 595 674
(%)
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
p-value 0.003 0.118 0.020 0.045 0.740 0.010 0.130 0.480 0.002 0.030 <0.001
A subsequent logistic regression validated this observation. Females were 1.3-fold
more likely to be asymptomatic than compared to males (Table 4, OR = 2.31, p< 0.001),
while a decade of difference in age increased the likelihood of being asymptomatic by 1%
(OR = 1.01, p< 0.001). Separately, we tested whether older females were more likely to be
asymptomatic than older males by including the interaction term between female and age
in the regression below, but this was statistically insignificant (p= 0.31).
Table 4. Multivariate logistic regression for asymptomatic patients.
Characteristics Odds Ratio p-Value (95% C.I.)
Age 1.01 <0.001 1.01 1.02
Female 2.31 <0.001 1.72 3.11
Atmosphere 2021,12, 1528 7 of 14
3.4. Viral Transmission
In our data, males were more likely to transmit the virus to at least one individual (122
or 21% vs. 88 or 13%, p< 0.001). There was no significant difference in the sex of the infectees
(3.48 vs. 3.89, p= 0.60) (Table 1). In total, 371 cases were connected to at least one case in
the registry. Of those, 210 patients infected at least one person, while the other 161 cases
did not infect anyone else but were themselves infected by one of the
210 patients.
Figure 2
depicts the networks of viral transmission. In the diagram, each patient is represented by a
circle. The size of each circle represents the number of infections generated by the patient.
The color of the circle represents the order (primary, secondary, tertiary, or quaternary)
of the infections. The networks containing up to quaternary viral transmission. Of the
371 cases
, 115 cases (31%) were primary, 212 cases (57%) were secondary, 40 cases (11%)
were tertiary, and 4 cases (1%) were quaternary cases. There were 108 separate viral
transmission networks. Most of these networks consisted of two patients (67 networks or
64%) while there was one network that involved 36 patients. The average network size
was 3.44. Figure 3represents the histogram of the network sizes.
Figure 2. Viral transmission networks and the order of infections.
Figure 3. Histogram: network size of viral transmission.
Atmosphere 2021,12, 1528 8 of 14
Figures 4and 5present the age and the sex group that each case belongs to in the
networks. The diagrams show no discernable patterns in terms of age and sex distributions
in the networks, indicating that viral transmission occurred across age and sex groups
regardless of the presence or absence of symptoms.
Figure 4. Viral transmission networks by sex.
Figure 5. Viral transmission networks by age.
Figure 6present the asymptomatic status that each case belongs to in the networks. In
the diagram, red circles correspond to asymptomatic cases, and blue circles correspond to
symptomatic cases. The diagram suggests that although asymptomatic patients transmit
the virus to others at a higher level, the infected individuals are also likely to be asymp-
tomatic. This finding was confirmed by using descriptive statistics, which indicated that
only 13% (n= 39) of the individuals who were infected by symptomatic patients ended
up being asymptomatic, whereas 53% (n= 41) of the individuals who were infected by
asymptomatic patients ended up being asymptomatic (p< 0.001).
Atmosphere 2021,12, 1528 9 of 14
Figure 6. Viral transmission networks by asymptomatic status.
Table 5summarizes the results of a multivariate logistic regression that identifies the
determinants of viral transmission. Male patients were 82% more likely to transmit the virus
regardless of being symptomatic and asymptomatic (OR = 1.82, p< 0.001). Asymptomatic
patients were 81% more likely to transmit the virus (OR = 1.81, p= 0.02). Patients with
pneumonia were 54% less likely to transmit the virus (OR = 0.46, p= 0.02), possibly due
to being in the hospital. Additionally, the time between PCR and the onset of symptoms
was positively associated with the likelihood of viral transmission (5% greater likelihood,
OR = 1.05, p< 0.001).
Table 5. Multivariate logistic regression for viral transmission.
Characteristics Odds Ratio p-Value (95% C.I.)
Duration: PCR-onset 1.05 <0.001 1.03 1.08
Male 1.82 <0.001 1.31 2.55
Asymptomatic 1.81 0.018 1.11 2.97
Pneumonia 0.46 0.019 0.24 0.88
3.5. Severity
Principal component analysis identified six unique factors with an eigenvalue that
is equal to or larger than one. Among those, we observed four distinct viral transmis-
sion networks of co-occurring symptoms. Specifically, we observed the co-occurrence
of fever and fatigue (F1); pharyngitis and rhinitis (F2); loss of taste and smell (F3); and
diarrhea/nausea/vomiting (F4). The factor scores estimated for these four factors were
then used to identify the determinants of severity in multivariate logistic regression. Inter-
estingly, the presence of diarrhea/nausea/vomiting was predictive of developing dyspnea,
i.e., severe disease (OR = 1.58, p< 0.001). Severe disease, as defined by dyspnea, was
also more prevalent in males (OR = 1.84, p< 0.005). To confirm this result, we performed
concomitant logistic regression with dyspnea as the outcome dependent variable and male,
diarrhea, and nausea/vomiting as explanatory variables. Two separate regressions were
run to avoid multicollinearity, one with diarrhea and male, another with nausea/vomiting,
and male as explanatory variables (Table 6). Here, being a male was a risk factor for having
dyspnea with similar coefficients in the two regressions (OR = 1.59, p= 0.02; OR = 1.71,
p= 0.01).
Experiencing diarrhea increased the likelihood of developing dyspnea by 82%
(OR = 1.82, p= 0.05) while experiencing nausea/vomiting increased the likelihood of
Atmosphere 2021,12, 1528 10 of 14
developing dyspnea by 373% (OR = 4.73, p< 0.001). From the notes provided with the data,
diarrhea and nausea/vomiting tended to be symptoms experienced in the early stage of
the disease while dyspnea was observed at the later stage, indicating that early stage GI
infections may result in a severe case of the disease.
Table 6. Multivariate logistic regression for severity determinants.
Characteristics Odds Ratio p-Value (95% C.I.)
Regression 1
Diarrhea 1.82 0.05 1.01 3.29
Male 1.59 0.02 1.09 2.32
Regression 2
Nausea/Vomiting 4.73 <0.001 1.99 11.21
Male 1.71 0.01 1.17 2.51
4. Discussion
The current study analyzed data from 1269 (674 females and 595 males) individuals
who were PCR-positive for SARS-CoV-2. Some of our findings confirmed the observations
of previous studies: Fever was the most prevalent symptom, with 81% females and 88%
of male subjects showing it. Fatigue and cough were the next most prevalent symptoms
with approximately 40% of female and male patients possessing them. These findings
are reported in prior studies including the one by Larsen and colleagues [
17
]. Our study
additionally identified the four sets of co-occurring symptoms including (i) fever and
fatigue; (ii) pharyngitis and rhinitis; (iii) ageusia (loss of taste) and anosmia (loss of smell);
and (iv) nausea, vomiting, and diarrhea. With dyspnea as an indicator of severity, our
results suggested that severe disease was more frequently observed in patients who had
nausea, vomiting, and diarrhea. This interesting correlation may be due to the higher level
of viremia and subsequent multi-organ infection, including the gastrointestinal (GI) tract.
The presence of nausea and vomiting suggests that upper GI involvement and that of
diarrhea, lower GI infection, both are consistent with a disseminated disease as a result of
viremia. Moreover, males were more susceptible to developing severe disease, although
it is unknown whether or not this sex difference is hormonally driven. One study from
China reports a similar finding. Tian et al. reviewed data from 15 clinical studies and
case reports to investigate the GI features of COVID-19 in adult and pediatric patients [
18
].
They report that the proportion of patients with GI symptoms was higher among severe
patients than in non-severe patients. Another single-hospital study from Wuhan, China,
analyzed data from 206 patients with mild disease and GI symptoms. The study reports
that these patients are more likely to have a positive test result for viral RNA in stool
and to have a longer duration before viral clearance. The results of both these studies
are consistent with our findings and suggest that GI symptoms may be suggestive of
more disseminated diseases, although treatments, including antibiotics, and corticosteroids
could also have an impact on the gastrointestinal mucosa and result in GI symptoms. The
presence of GI symptoms in younger individuals has been observed previously [
19
–
21
],
and it is speculated that a weaker respiratory immune response in this age group may
be the reason for their mild respiratory symptoms when compared to adults [
18
]. The
presence of anosmia and ageusia suggests that the virus affects the olfactory epithelium, as
well as taste buds, both of which have cilia that act as the receptors for specific molecules
that we taste and smell, respectively.
Moreove, consistent with prior findings [
4
,
22
], a significant number (~20%) of infected
patients were found to be asymptomatic carriers in our study. Interestingly, however,
there were significantly more female asymptomatic patients than males in our study.
There are a handful of prior studies suggesting this. Williamson and colleagues analyzed
COVID-19 death records in the UK and reported that men had a significantly higher risk of
mortality with an HR of 1.59 [
23
]. Yang et al. studied 78 patients in Wuhan, China, and
Atmosphere 2021,12, 1528 11 of 14
reported that being female and younger increased the likelihood of being asymptomatic [
24
].
Additionally, a meta-analysis by Kronbichler et al. demonstrated that while abnormal
radiological findings could be observed in a large proportion of asymptomatic patients,
asymptomatic patients with normal radiological findings were more likely to be female
and younger [
25
]. Although it is currently unclear why females are more likely to be
asymptomatic, a hormonal effect on T-cells may be involved. This possibility is supported
by Wu et al., who reported that pregnant women are more likely to be asymptomatic [
26
].
In this study, four out of eight pregnant women were asymptomatic before delivery but
became symptomatic after delivery, suggesting that the change in hormones and immune
system during the pregnancy may play a role in the onsets of symptoms.
In contrast to Yang et al. and Kronbichler et al., our data did not suggest that younger
(female) patients were more likely to be asymptomatic. Rather, our data demonstrated that
the likelihood of being asymptomatic increased with age in the Hokkaido population. In
relation to this, in a study of 98 PCR-positive COVID-19 patients, Takahashi and colleagues
observed differences in T cell responses and innate immune cytokine levels in male and
female patients, respectively, that correlated with progression to more severe disease. Their
patient population, however, did not have a broad age distribution, nor was an assessment
of initial symptoms included in their analysis [
27
]. As such, no conclusions about age and
the presence or absence of symptoms could be reached.
The observations by Wu et al., and Takahashi et al., potentially suggest that sex
hormones may be involved in the differences between disease manifestation in male and
female COVID-19 patients. A recent hypothesis by Roche and Roche [
28
] and Garvin
et al. [
29
], suggesting a role for the interconnected bradykinin and renin-angiotensin
system (RAS), offers a plausible explanation for the observed sex-dependent differences.
Estrogen is known to downregulate angiotensin-converting enzyme (ACE), which not
only catalyzes the conversion of angiotensin I to the vasoconstrictor angiotensin II but
also breaks down bradykinin [
30
]. Thus, a decrease in estrogen levels after menopause
could result in higher levels of ACE and lower levels of bradykinin in tissues, resulting
in a less intense inflammatory response and a reduction in the risk of a “bradykinin
storm” triggered by SARS-CoV2. As bradykinin is pro-inflammatory, the lower levels may
explain our observations. Moreover, enhanced angiotensin-converting enzyme 2 (ACE2)
immunostaining activity during pregnancy has been reported in animal studies [
31
,
32
].
Bradykinin (BK-1-9 or BK) and its active metabolite [des-Arg
9
]-BK (BK-1-8 or DABK) bind
to two different G protein-coupled receptors: the B1 receptor (BKB1R), for which its main
ligand is DABK, and the B2 receptor (BKB2R), for which its ligand is BK. ACE2 has been
shown to inactivate DABK by cleaving a single terminal amino acid from the peptide [
33
].
Inhibition of BKB1R activity decreases pulmonary neutrophil infiltration following LPS
exposure and decreases the influx of neutrophils in response to endotoxin [
33
]. The elevated
levels of ACE2 during pregnancy [
34
] may result in lower DABK levels and, thus, explain
why pregnant women are more likely to be asymptomatic [20] or show mild symptoms.
As expected, asymptomatic patients in our study were more likely to transmit the virus
in our study. Interestingly, however, these patients who became infected by asymptomatic
patients were also likely to be asymptomatic. This may be the result of a lower viral load
in asymptomatic individuals. Luo and colleagues also observed that transmission risk
increased with the severity of the disease, suggesting a higher viral load in patients with
more severe symptoms [
35
]. Other studies, however, have found similar viral loads in
symptomatic and asymptomatic patients, although the number of patients analyzed was
small [
23
]. Unfortunately, in our study, no viral samples were available; therefore, it was
impossible to determine the possible effect of viral load or the presence of variants in
explaining asymptomatic to asymptomatic transmissions. The length of time between PCR
testing and the onset of symptoms was also positively associated with the transmission
in our study, presumably due to the maintenance of social contacts during this period.
Furthermore, male patients were 82% more likely to transmit the virus, regardless of
being symptomatic or asymptomatic. This may be either due to a higher viral load in
Atmosphere 2021,12, 1528 12 of 14
males or more likely due to behavioral or physical differences in the anatomy of the upper
respiratory tract, including the mouth, which may result in a greater release of the virus in
droplets or aerosol.
Of significant interest is the presence of nine cases of COVID-19 reinfection in the
study population. Earlier evidence in smaller-scale retrospective clinical studies suggested
that reinfection by the coronavirus is possible. Ye and colleagues studied 55 COVID-19
patients with pneumonia, out of which 9% had a second episode of COVID-19 [
36
]. Case
reports from China (n= 2) [
37
] and Italy (n= 1) [
38
] also confirmed this. In our study, the
prevalence of the virus reinfection was 1%, significantly smaller than that reported in Ye
et al. Due to the aforementioned limitation regarding the availability of viral samples, it is
unclear whether these cases of reinfection were caused by the same variant of SARS-CoV-2
or a different one. The data, however, suggest that in most reinfection cases in the current
study, the symptoms of the first infection were similar to those of the second, raising the
possibility that the first and second infection episodes were caused by different variants of
the virus.
Finally, the current study is a retrospective secondary data analysis; thus, some of the
relevant information, particularly the patients’ data on comorbidities, were not available
in a consistently analyzable fashion. The authors were also unable to ensure either the
accuracy or the completeness of the data. In this sense, some of the results, especially the
findings concerning viral transmission networks, are subject to systematic bias if contact
tracing was performed disproportionately in specific cases or cohorts. While the most up-to-
date guideline published by the Japanese government still requests that all individuals who
were in “close contact” with the confirmed cases be subject to an “initial (PCR) screening
test” [
14
], the level of compliance with such a guideline is unknown, especially in light
of the recent resurge in COVID-19 cases in the country. That being said, we believe that
the guideline was adhered to in Hokkaido in the period between February and July and
that further investigations on the patterns of viral transmissions and symptomology in the
networks are warranted. Such investigations are deemed particularly valid as new variants
of the virus continue to emerge.
5. Conclusions
The likelihood of being asymptomatic increases with age and sex (women and older
individuals are more likely to be asymptomatic). Asymptomatic patients are more likely
to transmit the virus and also to generate asymptomatic cases. Reinfection by the virus
is likely.
Author Contributions:
M.-H.L.—cleaned and co-organized the data and performed network analysis.
A.B.S.—cleaned and co-organized the data and performed network analysis. A.A.—co-designed the
study, contextualized the results, and analyzed the medical aspects of the data. N.K.—co-designed
the study, accessed and organized the prefecture data, and performed the statistical analysis. All
authors have read and agreed to the published version of the manuscript.
Funding:
This study was partially funded by National Science Foundation, USA (EAGER: ISN:/1838306).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Data are available by emailing nkoizumi@gmu.edu.
Conflicts of Interest: The authors declare no conflict of interest.
Atmosphere 2021,12, 1528 13 of 14
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