comparative immunogenicity of enhanced influenza vaccines ... · the university of hong kong 2 feb...

Comparative Immunogenicity of Enhanced Influenza Vaccines in Older Adults in Hong Kong: A Randomized

Controlled Trial

Ben Cowling

School of Public HealthThe University of Hong Kong

2 Feb 2020

Influenza disease burden in older adults

In Hong Kong, persons ≥ 65y contribute:

• 57% of all influenza-associated hospitalisations

• 96% of all influenza-associated excess P&I deaths

• This despite high influenza vaccination coverage

Wu P et al. 2017 Sci Rep

Waning in vaccine effectiveness within a year

Vaccine effectiveness against H3N2 declines by time since vaccination, I-MOVE study, 2011/12 – 2014/15, persons ≥60y

Kissling et al. 2016 Eurosurveillance3

Vaccination and influenza activity in the US, 2010-18

Shaded blue areas show influenza epidemics, more recent years are plotted in darker shades.

4

Vaccination and influenza activity in Hong Kong, 2010-18

5

Shaded red areas show influenza epidemics, more recent years are plotted in darker shades.

Potent Influenza Vaccination strategies in Older adults –randomized immunogenicity Trial

Inclusion criteria - 62-82 years of age, living in the community in Hong Kong, no cognitive impairment or contraindication to vaccination

Blood draw at days 0, 30 and 182 each round for serology

• 10% of participants provided additional blood for CMI at days 0, 7, 30, 182, and additional blood for serology at day 91 and 273

Cowling et al. 2019 CID

Results – Baseline characteristics (n=1,861)

4 • CID 2019:XX (XX XXXX) • Cowling et!al

Sample Size Justification

For the present comparison of responses to 4 different vaccines in Year 1, we sought to detect small to moderate but meaningful relative differences in immunogenicity. A! sample size of 200 participants per group would permit 80% power to detect in-creases of !14% in the proportion of enhanced vaccine recipi-ents with !4-fold rises in titer, and GMT ratios of 1.4 or higher in the enhanced vaccine groups, compared to a SD vaccine. Overall, we aimed to enroll 2200 participants into our study, anticipating a 10% dropout rate per year and a final sample size of at least 146 participants in each group through to the fourth year of the planned trial (see the Supplementary Appendix).

RESULTS

We screened 3283 older adults, of whom 2695 were eligible and 2039 agreed to participate. We obtained signed informed con-sent from 2008 persons and were able to randomize and vacci-nate 1861 participants from 7 October 2017 through 12 January 2018, of whom 1826 provided Day 30 postvaccination serum samples (Figure 1). About 10% of participants were asked to give additional blood; 168 contributed PBMCs for analyses of cell-mediated immunity.

Participants were balanced by age, sex, underlying medical conditions, and prior vaccination history between the 4 study groups, with no statistically signi"cant di#erences in these key

variables overall or among those contributing to the primary antibody "ndings reported here (Table 1). $e most common underlying conditions were hypertension, osteoarthritis, and diabetes. Most participants (66%) had received an in%uenza vac-cination in the preceding year (2016–2017), and only 22% had not received any in%uenza vaccination in the preceding 5!years. All prior in%uenza vaccinations were with an SD vaccine. We selected 200 participants from each group for a serologic anal-ysis, and the characteristics of this subset were representative of the entire cohort (Table 2). Pre- and post-vaccination GMTs and corresponding MFRs are described in Table 3 for each vac-cine group, and Figure 2 presents comparisons of the MFRs be-tween the enhanced vaccine groups and the SD group. Table 4 shows the proportions of participants achieving speci"c titer thresholds a&er vaccination.

$ere were no statistically signi"cant baseline di#erences between the groups in prevaccination GMTs for each of the antigens tested, except that the baseline GMTs to the B/Victoria antigen were statistically signi"cantly lower in the SD group (Table 3). As shown in Table 3, among SD QIV re-cipients, the HAI GMT to A(H1N1) increased from 17 to 69. MF59-adjuvanted and HD recipients achieved a signi"cantly higher postvaccination GMT to A(H1N1) than SD recipi-ents; recombinant-HA recipients did not. Nonetheless, MFRs for A(H1N1) were statistically signi"cantly higher for all 3

Table 1. Baseline Characteristics of the 1861 Participants, by Vaccination Group!

Characteristics All Participants

Standard-dose quadrivalent vaccine,

n!=!508

MF59-adjuvanted trivalent vaccine,

n!=!508High-dose trivalent vaccine, n!=!510

Recombinant-HA quadrivalent

vaccine, n!=!335

n (%) n (%) n (%) n (%)

Age, years 65–70 269 (53%) 248 (49%) 258 (51%) 171 (51%) 71–76 130 (26%) 149 (29%) 143 (28%) 82 (24%) 77–82 109 (21%) 111 (22%) 109 (21%) 82 (24%)Female sex 301 (59%) 308 (61%) 327 (64%) 195 (58%)Underlying medical conditions Hypertension 230 (45%) 262 (52%) 239 (47%) 161 (48%) Osteoarthritis 110 (22%) 102 (20%) 109 (21%) 70 (21%) Diabetes 98 (19%) 104 (20%) 88 (17%) 61 (18%) Heart diseases 52 (10%) 47 (9%) 52 (10%) 29 (9%) Cancer 46 (9%) 43 (8%) 40 (8%) 22 (7%) Othersa 209 (41%) 221 (44%) 226 (44%) 141 (42%)Received influenza vaccination in 2016–2017 season 328 (65%) 332 (65%) 351 (69%) 226 (67%)Number of times received influenza vaccination in the preceding 5!yearsb

0 126 (25%) 104 (20%) 111 (22%) 71 (21%) 1–2 113 (22%) 120 (24%) 112 (22%) 68 (20%) 3–4 54 (11%) 45 (9%) 61 (12%) 38 (11%) 5–6 195 (38%) 201 (40%) 212 (42%) 144 (43%)

Abbreviation: HA, hemagglutinin.aOther underlying conditions included: stroke, chronic lung disease, kidney disease, liver disease, depression or anxiety disorder, neurologic disorder, autoimmune disease, disease of the digestive system, hypothyroidism, dermatological disease, etc.bThere were 6 possible influenza vaccines, including the 5 Northern hemisphere influenza vaccines from 2012–2013 through 2016–2017 plus the Southern hemisphere 2015 vaccine, which was available in Hong Kong for a special vaccination campaign [20]. The Southern hemisphere formulation is not usually available in Hong Kong.

Dow

nlo

aded fro

m h

ttps://a

cadem

ic.o

up.c

om

/cid

/advance-a

rticle

-abstra

ct/d

oi/1

0.1

093/c

id/c

iz1034/5

673516 b

y U

niv

ers

ity o

f Hong K

ong, B

enja

min

Cow

ling o

n 1

2 D

ecem

ber 2

019


Mean fold rises from pre- to post-vaccination

Values significantly different from SD QIV MFR are shown in bold and underlined

* Note that MF59-adj and HD vaccines were trivalent and did not include B/Yamagata lineage virus

† Cell-grown antigen, MDCK 4 passages, SIAT 1-2 passages

Motivation Methods Results Comments

Mean fold rises from pre- to post-vaccination

Assay Strain Mean fold rise (post/pre)SD Adj HD Rec

HAI A/Michigan/45/2015 (H1N1) 4.32 5.74 6.90 5.86HAI A/Hong Kong/4801/2014 (H3N2) egg 3.81 4.56 6.07 4.44MN A/Hong Kong/4801/2014 (H3N2) cell† 2.60 2.89 3.42 4.47HAI B/Brisbane/60/2008 4.53 3.48 6.03 3.66HAI B/Phuket/3073/2013⇤ 3.76 1.54 1.66 3.25

Values signi�cantly di�erent from SD QIV MFR are shown in bold and underlined

⇤ Note that MF59-adj and HD vaccines were trivalent and did not includeB/Yamagata lineage virus† Cell-grown antigen, MDCK 4 passages, SIAT 1-2 passages

Ben Cowling Slide 19


Day 30 GMT ratio enhanced versus standard dose


Serology test done on 800 randomly selected participants, 200 in each vaccination arm

Does prior vaccination history modify response to 2017/18 vaccination?

Issues with reduced antibody responses after repeat vaccination

Pre

Tite

r

Not affected

Post Pre

Tite

r

Blunted not reduced

Post Pre

Tite

r

Blunted and reduced

Post

- Previously vaccinated- Previously not vaccinated

Vaccination history* Vaccination armSD (n=200) Adj (n=200) HD (n=200) Rec (n=200)

Self-reported influenza vaccination history each year

2016/17 NH 136 (68.0) 130 (65.0) 139 (69.5) 137 (68.5)2015/16 NH 126 (63.0) 117 (58.5) 133 (66.5) 121 (60.5)2015 SH 8 (4.0) 1 (0.5) 5 (2.5) 6 (3.0)2014/15 NH 105 (52.5) 98 (49.0) 118 (59.0) 102 (51.0)2013/14 NH 90 (45.0) 93 (46.5) 101 (50.5) 96 (48.0)2012/13 NH 81 (40.5) 85 (42.5) 96 (48.0) 98 (49.0)No influenza vaccination in the previous 5 years

45 (22.5) 45 (22.5) 46 (23.0) 46 (23.0)

Year of most recent prior vaccination

2016/17 136 (68.0) 130 (65.0) 139 (69.5) 137 (68.5)2015/16 11 (5.5) 10 (5.0) 9 (4.5) 3 (1.5)2015 (SH vaccine) 0 (0) 0 (0) 0 (0) 0 (0)2014/15 1 (0.5) 1 (0.5) 2 (1.0) 1 (0.5)2013/14 0 (0) 1 (0.5) 0 (0) 1 (0.5)2012/13 1 (0.5) 0 (0) 0 (0) 5 (2.5)Not in last 5 years 45 (22.5) 45 (22.5) 46 (23.0) 46 (23.0)* n=30 unknown vaccination history

Vaccination history (n=800)

A/Michigan/45/2015 (H1N1)

● ●●

●

●

● ●●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r

D0 D30 D0 D30 D0 D30 D0 D30SD Adj HD Rec

(A)

● Received 2016/17 vaccinationDid not receive 2016/17 vaccination

A/Hong Kong/4801/2014 (H3N2) egg−propagated antigen

● ● ●●

●●

●●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(B) A/Hong Kong/4801/2014 (H3N2) cell−propagated antigen

●●

●

●●

● ●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

MN

tite

r


(C)

B/Brisbane/60/2008 (Victoria lineage)

●

●●

●

●●

●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(D) B/Phuket/3073/2013 (Yamagata lineage)

● ● ● ●

●

● ●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(E)

14


● ●●

●

●

● ●●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(A)



● ● ●●

●●

●●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r



●●

●

●●

● ●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

MN

tite

r


(C)


●

●●

●

●●

●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r



● ● ● ●

●

● ●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(E)


● ●●

●

●

● ●●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(A)



● ● ●●

●●

●●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r



●●

●

●●

● ●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

MN

tite

r


(C)


●

●●

●

●●

●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r



● ● ● ●

●

● ●

●

<1010204080

160320640

≥ 1280

Geo

met

ric m

ean

HAI

tite

r


(E)

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280

HAI titer pre−vaccination

HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

SD, 2016/17 unvaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n0.0%

5.0%

10.0%

15.0%

20.0%Proportion

Adj, 2016/17 unvaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

HD, 2016/17 unvaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

Rec, 2016/17 unvaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

SD, 2016/17 vaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

Adj, 2016/17 vaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

HD, 2016/17 vaccinated

<10

10−20

20−40

40−80

80−160

160−320

320−640

640−1280

≥ 1280

<10 10−2020−40

40−8080−160

160−320320−640

640−1280

≥ 1280


HAI

tite

r pos

t−va

ccin

atio

n

0.0%

5.0%

10.0%

15.0%

20.0%Proportion

Rec, 2016/17 vaccinated

Distribution of pre- vs. post-vaccination titer by 2016/17 vaccination status – A(H3N2) egg (Similar for other strains)

15

Summary of findings

• Improved anti-HA antibody responses to each of the enhanced vaccines

• Compared to the other two enhanced vaccines, FluBlok provided similar anti-HA responses to egg-adapted H3N2 vaccine strain, and superior responses by MN to the cell-like H3N2 vaccine strain

• We found reduced immune responses in participants with prior vaccinations• Weaker boosts but similar post-vaccination titers for H1N1• Weaker boosts and lower post-vaccination titers for H3N2-egg• Weaker boosts and lower post-vaccination titers for H3N2-cell for FluBlok

PIVOT full design (4 years)

Motivation Methods Results Comments

PIVOT full design (4 years)

Standard dose QIV(n=600)

MF59-adjuvanted TIV(n=600)

High-dose TIV(n=600)

Recombinant HA QIV(n=400)

Year 1 Year 2 Year 3 Year 4

Ben Cowling Slide 29

22

Update on 2019-nCoVWork presented here was done in collaboration with China CDC

Data as reported by 1 February 2020*

Novel Coronavirus(2019-nCoV) Situation Report - 12

SITUATION IN NUMBERS total and new cases in last 24 hours

Globally 11953 confirmed (2128 new) China 11821 confirmed (2102 new) 1795 severe (268 new) 259 deaths (46 new) Outside of China 132 confirmed (26 new) 23 countries (4 new) WHO RISK ASSESSMENT China Very High Regional Level High Global Level High

*The situation report includes information reported to WHO Geneva by 10 AM CET

Figure 1. Countries, territories or areas with reported confirmed cases of 2019-nCoV, 01 February 2020

HIGHLIGHTS

x The main driver of transmission, based on currently available data, is

symptomatic cases. WHO is aware of possible transmission of 2019-nCoV from infected people before they developed symptoms. Detailed exposure histories are being taken to better understand the pre-clinical phase of infection and how transmission may have occurred in these few instances. Asymptomatic infection may be rare, and transmission from an asymptomatic person is very rare with other coronaviruses, as we have seen with Middle East Respiratory Syndrome coronavirus. Thus, transmission from asymptomatic cases is likely not a major driver of transmission. Persons who are symptomatic will spread the virus more readily through coughing and sneezing.

x In China, 60.5% of all cases since the start of the outbreak have been reported from Hubei Province (see further information under Technical Focus).

x Additional instances of human-to-human transmission outside China were reported (see further information under Technical Focus).

First 41 cases detected through PUE system

Articles

www.thelancet.com Published online January 24, 2020 https://doi.org/10.1016/S0140-6736(20)30183-5 3

(methylprednisolone 40–120 mg per day) was given as a combined regimen if severe community-acquired pneumonia was diagnosed by physicians at the designated hospital. Oxygen support (eg, nasal cannula and invasive mechanical ventilation) was administered to patients according to the severity of hypoxaemia. Repeated tests for 2019-nCoV were done in patients confirmed to have 2019-nCoV infection to show viral clearance before hospital discharge or discontinuation of isolation.

Data collectionWe reviewed clinical charts, nursing records, laboratory findings, and chest x-rays for all patients with laboratory-confirmed 2019-nCoV infection who were reported by the local health authority. The admission data of these patients was from Dec 16, 2019, to Jan 2, 2020. Epidemiological, clinical, laboratory, and radiological characteristics and treatment and outcomes data were obtained with standardised data collection forms (modified case record form for severe acute respira-tory infection clinical characterisation shared by the International Severe Acute Respiratory and Emerging Infection Consortium) from electronic medical records. Two researchers also independently reviewed the data collection forms to double check the data collected. To ascertain the epidemiological and symptom data, which were not available from electronic medical records, the researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data.

Cytokine and chemokine measurementTo characterise the e!ect of coronavirus on the production of cytokines or chemokines in the acute phase of the illness, plasma cytokines and chemokines (IL1B, IL1RA, IL2, IL4, IL5, IL6, IL7, IL8 (also known as CXCL8), IL9, IL10, IL12p70, IL13, IL15, IL17A, Eotaxin (also known as CCL11), basic FGF2, GCSF (CSF3), GMCSF (CSF2), IFN", IP10 (CXCL10), MCP1 (CCL2), MIP1A (CCL3), MIP1B (CCL4), PDGFB, RANTES (CCL5), TNF#, and VEGFA were measured using Human Cytokine Standard 27-Plex Assays panel and the Bio-Plex 200 system (Bio-Rad, Hercules, CA, USA) for all patients according to the manufacturer’s instructions. The plasma samples from four healthy adults were used as controls for cross-comparison. The median time from being transferred to a designated hospital to the blood sample collection was 4 days (IQR 2–5).

Detection of coronavirus in plasmaEach 80 µL plasma sample from the patients and contacts was added into 240 µL of Trizol LS (10296028; Thermo Fisher Scientific, Carlsbad, CA, USA) in the Biosafety Level 3 laboratory. Total RNA was extracted by Direct-zol RNA Miniprep kit (R2050; Zymo research, Irvine, CA, USA) according to the manufacturer’s instructions and

50 µL elution was obtained for each sample. 5 µL RNA was used for real-time RT-PCR, which targeted the NP gene using AgPath-ID One-Step RT-PCR Reagent (AM1005; Thermo Fisher Scientific). The final reaction mix concentration of the primers was 500 nM and probe was 200 nM. Real-time RT-PCR was per formed using the following conditions: 50°C for 15 min and 95°C for 3 min, 50 cycles of amplification at 95°C for 10 s and 60°C for 45 s. Since we did not perform tests for detecting infectious virus in blood, we avoided the term viraemia and used RNAaemia instead. RNAaemia was defined as a positive result for real-time RT-PCR in the plasma sample.

DefinitionsAcute respiratory distress syndrome (ARDS) and shock were defined according to the interim guidance of WHO

For more on the International Severe Acute Respiratory and Emerging Infection Consortium see https://isaric.tghn.org/

Figure !: Date of illness onset and age distribution of patients with laboratory-confirmed 2019-nCoV infection(A) Number of hospital admissions by age group. (B) Distribution of symptom onset date for laboratory-confirmed cases. The Wuhan local health authority issued an epidemiological alert on Dec 30, 2019, and closed the Huanan seafood market 2 days later.

0<18 18–24 25–49 50–64 !65

5

10

15

20

Num

ber o

f cas

es

Age (years)

AGeneral wardIntensive care unit

Dec 1, 2019

Dec 10, 2019

Dec 11, 2019

Dec 12, 2019

Dec 13, 2019

Dec 14, 2019

Dec 15, 2019

Dec 16, 2019

Dec 17, 2

019

Dec 18, 2019

Dec 19, 2019

Dec 20, 2019

Dec 21, 2019

Dec 22, 2019

Dec 23, 2019

Dec 24, 2019

Dec 25, 2019

Dec 26, 2019

Dec 27, 2

019

Dec 28, 2019

Dec 29, 2019

Dec 30, 2019

Dec 31, 2019

Jan 1, 2020

Jan 2, 20200

2

4

6

8

Num

ber o

f cas

es

Onset date

B

NoYes

Huanan seafood market exposure

Epidemiological alert

Market closed

Huang et al. 2020 Lancet

Huanan Seafood Wholesale Market

Wu et al. 2020 Eurosurveillance

Start reporting confirmed 2019−nCoV cases

First exported case confirmed

National task force visited Wuhan

31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21Dec Jan

0

80

160

240

320

400

480

Date

Cum

ulat

ive n

o. c

ases

Pneumonia of unknown etiologyConfirmed 2019−nCoV infections in mainland ChinaExported 2019−nCoV infections

4 www.eurosurveillance.org

DiscussionIn this article, we describe a preliminary assessment of the outbreak of infections with the newly identified 2019-nCoV. This assessment is based on the cases of infection reported over time by health authorities in Wuhan and then at the national level, as well as the media in China and other countries. One of the most urgent priorities is to determine the degree of human-to-human transmissibility of the novel pathogen, and accordingly, this is where information is most urgently needed. We outline two possible scenarios in the!Table!and find that the early evidence was most consistent with limited human-to-human transmissibil-ity, however more recent data seem to be increasingly more compatible with scenario 2 in which sustained human-to-human transmission has been occurring. Determining the exposure profile among the recently confirmed cases would directly contribute to this

assessment. Additional information on approaches to case identification and laboratory testing protocols in Wuhan and in other cities in China would also be informative. A separate priority is to identify the ani-mal reservoir of this novel pathogen and any intermedi-ary hosts, including potential supply chains of wild or game meat.

It is challenging to judge severity from the informa-tion available to date. We estimated the risk of death among hospitalised cases of around 14% (Figure 2). For both SARS-CoV and MERS-CoV infections, the risk of severe disease increases substantially with age and with the presence of underlying conditions [23-25]. One other caveat with estimating severity is that there can be long delays between hospitalisation and death for infections that are ultimately fatal. For SARS in Hong Kong, the average time from illness to death for fatal

T!"#$Evidence on transmission dynamics of human infections with 2019-nCoV, as at 22 January 2020

Observation Date Interpretation Supports Scenario 1?a Supports Scenario 2?b

By 20 January, 198 laboratory-confirmed cases, 3 fatal, 25 recovered [28]

20 Jan 2020

Fatality risk among hospitalised cases is 11%c Yes Yes

No infections among the more than 700 people under medical surveillance, including HCWs [28]

20 Jan 2020

Very low human-to-human transmissibility Yes

No (Note: assuming adequate contact tracing

and surveillance)Only one likely human-to-human cluster among the first 41 cases [18]

20 Jan 2020

Very low human-to-human transmissibility (R0!of 0.02) Yes No (Note: assuming

adequate contact tracing)

Only approximately 70% of the first 41 cases had exposure to Southern China Seafood Wholesale Market [16]

15 Jan 2020

Low human-to-human transmissibility (R0!of 0.3) Yes

No (Note: possible selection bias towards

identifying cases linked to that market)

New cases with a travel history to Wuhan before onset were confirmed in other cities in China [29]

20 Jan 2020

Indicative of many mild to moderate infections (not

requiring hospitalisation) in Wuhan

Yes Yes

Four exported cases to other countries, all with relatively mild illness [30,31]

12–20 Jan

2020

Indicative of many mild to moderate infections not

necessitating hospitalisation or outpatient medical care in

Wuhan

Yes Yes

Four exported cases, at least three of whom had no contact with Southern China Seafood Wholesale Market [30,31]

12–20 Jan

2020

At least some limited human-to-human transmission

(unclear!R0)Yes Yes

Two family clusters in Guangdong, with family members who did not visit Wuhan but were infected after the other family member(s) returning from Wuhan were confirmed with the infection [29]

20 Jan 2020

At least some limited human-to-human transmission

(unclear!R0)Yes Yes

15 HCWs confirmed with infection of 2019-nCoV (not clear whether infections were from one case or multiple cases) [20]

20 Jan 2020

Super-spreading event? Could still be consistent with limited human-to-human transmission

if an isolated incident (unclear!R0)

Yes Yes

Exported cases identified in Taiwan and the United States with illness onset dates on 11 and 19 January [32,33]

22 Jan 2020

Could be because of surveillance bias, but is more consistent with an increase in

incidence of infections over time

No (Note: possible selection bias

because of enhanced surveillance towards

identifying more recent cases)

Yes

HCWs: healthcare workers; nCoV: novel coronavirus; MHC: Municipal Health Commission.a!Most infections are zoonotic with limited human-to-human transmission (R0 < 1).b!Initial zoonotic spillover with efficient human-to-human transmission (R0 > 1).c!Estimated as (fatal cases) / (fatal cases + recovered cases).

Wu et al. 2020 Eurosurveillance

4 travel-related cases by 17 Jan 2020 implies many infections in Wuhan

17 January 2020 Imperial College London

Page 2 of 4

infection risk than residents. Accounting for either factor correctly requires additional data but would increase our estimate of the total number of cases.

2. We estimate the potential number of symptomatic cases with disease severity of a level requiring hospitalisation (both the cases detected in Thailand and Japan were moderately severe). Our estimates do not include cases with mild or no symptoms.

3. The incubation period of 2019-nCov is not known and has been approximated with the estimates obtained for MERS-CoV and SARS [8,9].

4. We assume that international travel is independent of the risk of exposure to 2019n-CoV or of infection status. If zoonotic exposure was biased towards wealthier people, travel frequency may be correlated with exposure. Also, some travel might be causally linked to infection status (to seek healthcare overseas) or the infection status of contacts in Wuhan (this may apply to the case detected in Japan) [10]. Accounting for either association would increase the probability of a case travelling and therefore reduce our estimates of the total number of cases. .

Sensitivity analysis

We explore the sensitivity of estimates of total cases to our assumptions about: i) the duration of the detection window (exploring a lower value of 8 days); ii) the catchment population size of Wuhan airport (assuming it might be 11 million, the population of Wuhan city [12], rather than 19 million, the population of the entire metropolitan area [1]); and iii) true exportations reported internationally (2, 3 and 4 cases). Table 1 summarises the baseline assumptions and alternative scenarios explored. We note that the currently reported number of cases (44) is substantially lower than the lower bound of our most conservative scenario (190 cases, Scenario 3).

Table 1: Estimated case numbers based on the baseline assumptions and alternative scenarios explored.

Baseline Scenario 1 Scenario 2 Scenario 3 Scenario 4 Exported number of confirmed cases*

3 3 3 2 4

Daily international passengers travelling out of Wuhan International airport1

3,301 3,301 3,301 3,301 3,301

Effective catchment population of Wuhan airport

19 million 11 million 19 million 19 million 19 million

Detection window (days) 10 days 10 days 8 days 10 days 10 days Estimated Total number of cases (95% CI)

1,723 (427 ± 4,471)

996 (246 ± 2,586)

2,155 (535 ± 5,590)

1149 (190 ± 3,549)

2,298 (712 ± 5,341)

*reported number of confirmed cases detected internationally. 1calculated from the 3 month totals reported by [11] corrected for the travel surge during Chinese New Year (see Summary).

Conclusions

It is likely that the Wuhan outbreak of a novel coronavirus has caused substantially more cases of moderate or severe respiratory illness than currently reported. The estimates presented here suggest surveillance should be expanded to include all hospitalised cases of pneumonia or severe respiratory disease in the Wuhan area and other well-connected Chinese cities. This analysis does not directly address transmission routes, but past experience with SARS and MERS-CoV outbreaks of similar scale suggests currently self-sustaining human-to-human transmission should not be ruled out.

Imperial College London

n engl j med nejm.org 4

T h e n e w e ngl a nd j o u r na l o f m e dic i n e

cifically, the latter part of the curve does not indicate a decrease in the number of incident cases but is due to delayed case ascertainment at the cutoff date. Care should be taken in inter-preting the speed of growth in cases in January, given an increase in the availability and use of testing kits as time has progressed. The major-ity of the earliest cases included reported expo-sure to the Huanan Seafood Wholesale Market, but there was an exponential increase in the number of nonlinked cases beginning in late December.

The median age of the patients was 59 years (range, 15 to 89), and 240 of the 425 patients (56%) were male. There were no cases in chil-dren below 15 years of age. We examined char-acteristics of cases in three time periods: the

first period was for patients with illness onset before January 1, which was the date the Huan-an Seafood Wholesale Market was closed; the second period was for those with onset between January 1 and January 11, which was the date when RT-PCR reagents were provided to Wuhan; and the third period was those with illness onset on or after January 12 (Table 1). The patients with earlier onset were slightly younger, more likely to be male, and much more likely to report exposure to the Huanan Seafood Wholesale Market. The proportion of cases in health care workers gradually increased across the three periods (Table 1).

We examined data on exposures among 10 confirmed cases, and we estimated the mean incubation period to be 5.2 days (95% confidence

Figure!1.!Onset!of!Illness!among!the!First!425!Confirmed!Cases!of!Novel!Coronavirus!(2019-nCoV)–Infected!Pneumonia!(NCIP)!!in!Wuhan,!China.

The decline in incidence after January 8 is likely to be due to delays in diagnosis and laboratory confirmation. China CDC denotes Chi-nese Center for Disease Control and Prevention, NHC National Health Commission of the People’s Republic of China, PCR polymerase chain reaction, WHC Wuhan Health Commission, and WHO World Health Organization.

No.

!of!C

ases

45

50

35

40

30

25

15

10

20

5

027 30 3 6 9 12 15 18 21 24 27 30 2 5 8 11 14 17 20

Nov.

2019

Dec.

2020

Jan.

A novel coronavirus was officiallyannounced as the causative

pathogen of the outbreakby China CDC

Huanan Seafood WholesaleMarket closed

Outbreak announced by WHC;NHC and China CDC involvedin investigation and response

Case-finding activated

Pneumonia cases linkedto the Huanan Seafood

Wholesale Market

China CDC publicly shared the gene sequenceof the novel coronavirus; completed PCRdiagnostic reagent development and testing

PCR diagnostic reagents provided to Wuhan

First confirmed case from Wuhanreported outside China (in Thailand)

China CDC emergency response levelupgraded to Level 1 (the highest level);national technical protocols for 2019-nCoV released by NHC

NCIP incorporated as a notifiabledisease in the Infectious DiseaseLaw and Health and QuarantineLaw in China

Reagent probes and primersshared with the public by China CDC

Strict exit screening measures activatedin Wuhan, people with body temperature!37.3ºC were restricted from leaving

First confirmed case reported in anotherprovince in China (in a person whohad traveled from Wuhan); China CDCissued test reagent to all provincesin China

China CDC Level 2 emergencyresponse activated

Emergency monitoring, case investigation,close contact management, and market

investigation initiated, technical protocolsfor Wuhan released; NHC notified WHOand relevant countries and regions; gene

sequencing completed by China CDC

Outbreak!Period

Not linked to Huanan marketLinked to Huanan market

The New England Journal of Medicine Downloaded from nejm.org by Elizabeth Laurencot on January 31, 2020. For personal use only. No other uses without permission.

Copyright © 2020 Massachusetts Medical Society. All rights reserved.

Transmission dynamics in Wuhan

• Analysis of first 425 cases

• Based on early exponential growth in non-linked cases (up to 3 January) we estimated doubling time of 7.4 days, and R0 of 2.2

Li et al. 2020 NEJM


Early Tr ansmission Dynamics of NCIP

interval [CI], 4.1 to 7.0); the 95th percentile of the distribution was 12.5 days (95% CI, 9.2 to 18) (Fig. 2A). We obtained information on 5 clusters of cases, shown in Figure 3. On the basis of the dates of illness onset of 6 pairs of cases in these clusters, we estimated that the serial interval distribution had a mean (±SD) of 7.5±3.4 days (95% CI, 5.3 to 19) (Fig. 2B).

In the epidemic curve up to January 4, 2020, the epidemic growth rate was 0.10 per day (95% CI, 0.050 to 0.16) and the doubling time was 7.4 days (95% CI, 4.2 to 14). Using the serial interval distribution above, we estimated that R0 was 2.2 (95% CI, 1.4 to 3.9).

The duration from illness onset to first medical visit for 45 patients with illness onset before January 1 was estimated to have a mean of 5.8 days (95% CI, 4.3 to 7.5), which was similar to that for 207 patients with illness onset between January 1 and January 11, with a mean of 4.6 days (95% CI, 4.1 to 5.1) (Fig. 2C). The mean duration from onset to hospital admission was estimated to be 12.5 days (95% CI, 10.3 to 14.8) among 44 cases with illness onset before January 1, which was longer than that among 189 patients with illness onset between January

1 and 11 (mean, 9.1 days; 95% CI, 8.6 to 9.7) (Fig. 2D). We did not plot these distributions for patients with onset on or after January 12, be-cause those with recent onset and longer dura-tions to presentation would not yet have been detected.

Discussion

Here we provide an initial assessment of the transmission dynamics and epidemiologic char-acteristics of NCIP. Although the majority of the earliest cases were linked to the Huanan Sea-food Wholesale Market and the patients could have been infected through zoonotic or environ-mental exposures, it is now clear that human-to-human transmission has been occurring and that the epidemic has been gradually growing in recent weeks. Our findings provide important parameters for further analyses, including evalu-ations of the impact of control measures and predictions of the future spread of infection.

We estimated an R0 of approximately 2.2, meaning that on average each patient has been spreading infection to 2.2 other people. In gen-eral, an epidemic will increase as long as R0 is

CharacteristicBefore!January!1!

(N!=!47)January!1!–January!11!

(N!=!248)January!12!–January!22!

(N!=!130)

Median age (range) — yr 56 (26–82) 60 (21–89) 61 (15–89)

Age group — no./total no. (%)

<15 yr 0/47 0/248 0/130

15–44 yr 12/47 (26) 39/248 (16) 33/130 (25)

45–64 yr 24/47 (51) 106/248 (43) 49/130 (38)

!65 yr 11/47 (23) 103/248 (42) 48/130 (37)

Male sex — no./total no. (%) 31/47 (66) 147/248 (59) 62/130 (48)

Exposure history — no./total no. (%)

Wet market exposure 30/47 (64) 32/196 (16) 5/81 (6)

Huanan Seafood Wholesale Market 26/47 (55) 19/196 (10) 5/81 (6)

Other wet market but not Huanan Seafood Wholesale Market

4/47 (9) 13/196 (7) 0/81

Contact with another person with respiratory symptoms

14/47 (30) 30/196 (15) 21/83 (25)

No exposure to either market or person with respiratory symptoms

12/47 (26) 141/196 (72) 59/81 (73)

Health care worker — no./total no. (%) 0/47 7/248 (3) 8/122 (7)

* Reduced denominators indicate missing data. Percentages may not total 100 because of rounding.

Table!1.!Characteristics!of!Patients!with!Novel!Coronavirus–Infected!Pneumonia!in!Wuhan!as!of!January!22,!2020.*



Li et al. 2020 NEJM


T h e n e w e ngl a nd j o u r na l o f m e dic i n e

greater than 1, and control measures aim to re-duce the reproductive number to less than 1. The R0 of SARS was estimated to be around 3,12 and SARS outbreaks were successfully controlled by isolation of patients and careful infection con-trol.13 In the case of NCIP, challenges to control include the apparent presence of many mild in-fections14 and limited resources for isolation of cases and quarantine of their close contacts. Our estimate of R0 was limited to the period up to January 4 because increases in awareness of the outbreak and greater availability and use of tests in more recent weeks will have increased the proportions of infections ascertained. It is pos-sible that subsequent control measures in Wu-han, and more recently elsewhere in the country as well as overseas, have reduced transmissibil-ity, but the detection of an increasing number of

cases in other domestic locations and around the world suggest that the epidemic has contin-ued to increase in size. Although the population quarantine of Wuhan and neighboring cities since January 23 should reduce the exportation of cases to the rest of the country and overseas, it is now a priority to determine whether local transmission at a similar intensity is occurring in other locations.

It is notable that few of the early cases oc-curred in children, and almost half the 425 cases were in adults 60 years of age or older, although our case definition specified severe enough ill-ness to require medical attention, which may vary according to the presence of coexisting condi-tions. Furthermore, children might be less likely to become infected or, if infected, may show milder symptoms, and either of these situations

Figure!2.!Key!Time-to-Event!Distributions.

The estimated incubation period distribution (i.e., the time from infection to illness onset) is shown in Panel A. The estimated serial interval distribution (i.e., the time from illness onset in successive cases in a transmission chain) is shown in Panel B. The estimated distributions of times from illness onset to first medical visit are shown in Panel C. The estimated distributions of times from illness onset to hospital admission are shown in Panel D.

A

0 7 14 210.00

0.05

0.10

0.25

0.20

0.15

Days!from!Infection!to!Symptom!Onset

B

0 7 14 210.00

0.05

0.10

0.20

0.15

Serial!Interval!(days)

0 3 6 9 120.00

0.05

0.10

0.15

0.20

0.25

Days!from!Illness!Onset!to!First!Medical!Visit

Onset before January 1Onset during January 1!11

C

0 10 20 300.00

0.05

0.10

0.15

Days!from!Illness!Onset!to!Hospitalization

Rela

tive!

Freq

uenc

y

Rela

tive!

Freq

uenc

y

Rela

tive!

Freq

uenc

y

Rela

tive!

Freq

uenc

y

D

Onset before January 1Onset during January 1!11



• Incubation period mean 6 days, upper limit around 14 days

• Serial interval mean 7 days (but we now think it could be shorter)

• Mean delay from onset to hospitalization around 10 days (proxy for delay from onset to laboratory confirmation)

Li et al. 2020 NEJM

Severity

• Severity appears low initially, but increases as time progresses and cases begin to resolve

• Our early estimate of (fatality risk among hospitalised cases) = 14% based on:

(4 deaths)/(4 deaths + 25 recoveries)

Articles

www.thelancet.com Vol 382 July 13, 2013 141

younger individuals (p=0·0019; fi gure 1, table 2). For the 37 individuals who died, median time to death was 11 days (IQR 6–23). For the 65 individuals who recovered, median time to recovery was 18 days (14–29).

71 (66%) of 108 patients for whom detailed clinical information was available required mechanical ventil-ation, and 83 (75%) of 110 were admitted to ICU. We used multiple imputation to account for missing data for dates of ICU admission for one patient and for mechanical ventilation for 23 patients, and censored in 17 patients who were still in hospital as of May 28. We estimated that risks of ICU admission (p=0·08) and mechanical ventilation (p=0·0067) were higher for patients aged 60 years or older than for younger patients (fi gure 2, table 2). We recorded some evidence that disease progressed or resolved faster in patients younger than 60 years than in older individuals (fi gures 1, 2), but the small sample size meant that we did not have su! cient statistical power to warrant further investigation.

When we estimated the fatality risk of patients admitted to hospital on the basis of information available on di" erent dates, we noted that the estimated risk gradually decreased (fi gure 3). Uncertainty was initially substantial, but decreased with time (fi gure 3), because of the increasing number of cases and follow-up of individuals admitted to hospital.

We estimated that 23 (95% credible interval [CrI] seven to 58) symptomatic individuals infected with avian infl uenza A H7N9 sought medical care at ILI sentinels in Shanghai up to May 28, on the basis that two cases were identifi ed there by ILI surveillance. Additionally, we estimated that 40 (seven to 129) sought medical care at ILI sentinels in Nanjing on the basis that one case was identifi ed by ILI surveillance. With method 1, we estimated that about 0·75% of individuals with symptomatic 2009 infl uenza A H1N1 pandemic virus infection sought medical care. With the assump-tion that a similar proportion of symptomatic individuals infected with avian infl uenza A H7N9 would have

0 7 14 21 28 35 420

10

20

30

40

50

60

70

80

90

100A B C

Fata

lity r

isk (%

)

Time from hospital admission (days)0 7 14 21 28 35 42


Time from hospital admission (days)Recovery Death Estimated fatality risk when all patients have died or recovered

Figure !: Fatality risk for patients with laboratory-confi rmed infection with avian infl uenza A H7N9 virus who were admitted to hospital(A) 123 patients of all ages, (B) 52 patients younger than 60 years, and (C) 71 patients aged at least 60 years. As of May 28, 2013, 17 patients were still in hospital; the solid lines will converge when these cases resolve.

0 7 14 21 28 35 420

10

20

30

40

50

60

70

80

90

100A B C

Risk

of a

dver

se o

utco

mes

(%)



Time from hospital admission (days)Admission to intensive care unit, mechanical ventilation, or death DeathMechanical ventilation or death

Figure ": Risks of adverse outcomes for patients with laboratory-confi rmed infection with avian infl uenza A H7N9 virus who were admitted to hospital(A) 123 patients of all ages, (B) 52 patients younger than 60 years, and (C) 71 patients aged at least 60 years.

Yu, Cowling et al. 2013 LancetWu et al. 2020 Eurosurveillance

Articles


patients were clustered and had a history of exposure to the Huanan seafood market. Among them, there were 47 patients with long-term exposure history, most of whom were salesmen or market managers, and two patients with short-term exposure history, who were shoppers. None of the patients were medical sta!. Most patients were men, with a mean age of 55·5 years (SD 13·1; table 1). 50 (51%) patients had chronic diseases, including cardiovascular and cerebro vascular diseases, endocrine system disease, digestive system disease, respiratory system disease, malignant tumour, and nervous system disease (table 1).

On admission, most patients had fever or cough and a third of patients had shortness of breath (table 2). Other symptoms included muscle ache, headache,

confu sion, chest pain, and diarrhoea (table 2). Many patients presented with organ function damage, including 17 (17%) with ARDS, eight (8%) with acute respiratory injury, three (3%) with acute renal injury, four (4%) with septic shock, and one (1%) with venti-lator-associated pneumonia (table 2).

On admission, leucocytes were below the normal range in nine (9%) patients and above the normal range in 24 (24%) patients (table 3). 38 (38%) patients had neutrophils above the normal range. Lymphocytes and haemoglobin were below the normal range in many

Patients (n=99)

Age, years

Mean (SD) 55·5 (13·1)

Range 21–82

!39 10 (10%)

40–49 22 (22%)

50–59 30 (30%)

60–69 22 (22%)

"70 15 (15%)

Sex

Female 32 (32%)

Male 67 (68%)

Occupation

Agricultural worker 2 (2%)

Self-employed 63 (64%)

Employee 15 (15%)

Retired 19 (19%)

Exposure to Huanan seafood market* 49 (49%)

Long-term exposure history 47 (47%)

Short-term exposure history 2 (2%)

Chronic medical illness 50 (51%)

Cardiovascular and cerebrovascular diseases 40 (40%)

Digestive system disease 11 (11%)

Endocrine system disease† 13 (13%)

Malignant tumour 1 (1%)

Nervous system disease 1 (1%)

Respiratory system disease 1 (1%)

Admission to intensive care unit 23 (23%)

Clinical outcome

Remained in hospital 57 (58%)

Discharged 31 (31%)

Died 11 (11%)

Data are n (%) unless specified otherwise. 2019-nCoV=2019 novel coronavirus. *Long-term exposure is having worked at or lived in or around Huanan seafood market, whereas short-term exposure is having been to Huanan seafood market occasionally. †12 were diabetic.

Table !: Demographics, baseline characteristics, and clinical outcomes of 99 patients admitted to Wuhan Jinyintan Hospital (Jan 1–20, 2020) with 2019-nCoV pneumonia

Patients (n=99)

Signs and symptoms at admission

Fever 82 (83%)

Cough 81 (82%)

Shortness of breath 31 (31%)

Muscle ache 11 (11%)

Confusion 9 (9%)

Headache 8 (8%)

Sore throat 5 (5%)

Rhinorrhoea 4 (4%)

Chest pain 2 (2%)

Diarrhoea 2 (2%)

Nausea and vomiting 1 (1%)

More than one sign or symptom 89 (90%)

Fever, cough, and shortness of breath 15 (15%)

Comorbid conditions

Any 33 (33%)

ARDS 17 (17%)

Acute renal injury 3 (3%)

Acute respiratory injury 8 (8%)

Septic shock 4 (4%)

Ventilator-associated pneumonia 1 (1%)

Chest x-ray and CT findings

Unilateral pneumonia 25 (25%)

Bilateral pneumonia 74 (75%)

Multiple mottling and ground-glass opacity 14 (14%)

Treatment

Oxygen therapy 75 (76%)

Mechanical ventilation

Non-invasive (ie, face mask) 13 (13%)

Invasive 4 (4%)

CRRT 9 (9%)

ECMO 3 (3%)

Antibiotic treatment 70 (71%)

Antifungal treatment 15 (15%)

Antiviral treatment 75 (76%)

Glucocorticoids 19 (19%)

Intravenous immunoglobulin therapy 27 (27%)

2019-nCoV=2019 novel coronavirus. ARDS=acute respiratory distress syndrome. ECMO=extracorporeal membrane oxygenation. CRRT=continuous renal replacement therapy.

Table ": Clinical characteristics and treatment of patients with 2019-nCoV pneumonia

Articles


patients were clustered and had a history of exposure to the Huanan seafood market. Among them, there were 47 patients with long-term exposure history, most of whom were salesmen or market managers, and two patients with short-term exposure history, who were shoppers. None of the patients were medical sta!. Most patients were men, with a mean age of 55·5 years (SD 13·1; table 1). 50 (51%) patients had chronic diseases, including cardiovascular and cerebro vascular diseases, endocrine system disease, digestive system disease, respiratory system disease, malignant tumour, and nervous system disease (table 1).

On admission, most patients had fever or cough and a third of patients had shortness of breath (table 2). Other symptoms included muscle ache, headache,

confu sion, chest pain, and diarrhoea (table 2). Many patients presented with organ function damage, including 17 (17%) with ARDS, eight (8%) with acute respiratory injury, three (3%) with acute renal injury, four (4%) with septic shock, and one (1%) with venti-lator-associated pneumonia (table 2).

On admission, leucocytes were below the normal range in nine (9%) patients and above the normal range in 24 (24%) patients (table 3). 38 (38%) patients had neutrophils above the normal range. Lymphocytes and haemoglobin were below the normal range in many

Patients (n=99)

Age, years

Mean (SD) 55·5 (13·1)

Range 21–82

!39 10 (10%)

40–49 22 (22%)

50–59 30 (30%)

60–69 22 (22%)

"70 15 (15%)

Sex

Female 32 (32%)

Male 67 (68%)

Occupation

Agricultural worker 2 (2%)

Self-employed 63 (64%)

Employee 15 (15%)

Retired 19 (19%)

Exposure to Huanan seafood market* 49 (49%)

Long-term exposure history 47 (47%)

Short-term exposure history 2 (2%)

Chronic medical illness 50 (51%)

Cardiovascular and cerebrovascular diseases 40 (40%)

Digestive system disease 11 (11%)

Endocrine system disease† 13 (13%)

Malignant tumour 1 (1%)

Nervous system disease 1 (1%)

Respiratory system disease 1 (1%)

Admission to intensive care unit 23 (23%)

Clinical outcome

Remained in hospital 57 (58%)

Discharged 31 (31%)

Died 11 (11%)

Data are n (%) unless specified otherwise. 2019-nCoV=2019 novel coronavirus. *Long-term exposure is having worked at or lived in or around Huanan seafood market, whereas short-term exposure is having been to Huanan seafood market occasionally. †12 were diabetic.

Table !: Demographics, baseline characteristics, and clinical outcomes of 99 patients admitted to Wuhan Jinyintan Hospital (Jan 1–20, 2020) with 2019-nCoV pneumonia

Patients (n=99)

Signs and symptoms at admission

Fever 82 (83%)

Cough 81 (82%)

Shortness of breath 31 (31%)

Muscle ache 11 (11%)

Confusion 9 (9%)

Headache 8 (8%)

Sore throat 5 (5%)

Rhinorrhoea 4 (4%)

Chest pain 2 (2%)

Diarrhoea 2 (2%)

Nausea and vomiting 1 (1%)

More than one sign or symptom 89 (90%)

Fever, cough, and shortness of breath 15 (15%)

Comorbid conditions

Any 33 (33%)

ARDS 17 (17%)

Acute renal injury 3 (3%)

Acute respiratory injury 8 (8%)

Septic shock 4 (4%)

Ventilator-associated pneumonia 1 (1%)

Chest x-ray and CT findings

Unilateral pneumonia 25 (25%)

Bilateral pneumonia 74 (75%)

Multiple mottling and ground-glass opacity 14 (14%)

Treatment

Oxygen therapy 75 (76%)

Mechanical ventilation

Non-invasive (ie, face mask) 13 (13%)

Invasive 4 (4%)

CRRT 9 (9%)

ECMO 3 (3%)

Antibiotic treatment 70 (71%)

Antifungal treatment 15 (15%)

Antiviral treatment 75 (76%)

Glucocorticoids 19 (19%)

Intravenous immunoglobulin therapy 27 (27%)

2019-nCoV=2019 novel coronavirus. ARDS=acute respiratory distress syndrome. ECMO=extracorporeal membrane oxygenation. CRRT=continuous renal replacement therapy.

Table ": Clinical characteristics and treatment of patients with 2019-nCoV pneumonia

Chen et al. 2020 Lancet

Articles


Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive studyNanshan Chen*, Min Zhou*, Xuan Dong*, Jieming Qu*, Fengyun Gong, Yang Han, Yang Qiu, Jingli Wang, Ying Liu, Yuan Wei, Jia’an Xia, Ting Yu, Xinxin Zhang, Li Zhang

SummaryBackground In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia.

Methods In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020.

Findings Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneu mothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure.

Interpretation The 2019-nCoV infection was of clustering onset, is more likely to a!ect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection.

Funding National Key R&D Program of China.

Copyright © 2020 Elsevier Ltd. All rights reserved.

IntroductionSince Dec 8, 2019, several cases of pneumonia of unknown aetiology have been reported in Wuhan, Hubei province, China.1–3 Most patients worked at or lived around the local Huanan seafood wholesale market, where live animals were also on sale. In the early stages of this pneumonia, severe acute respiratory infection symptoms occurred, with some patients rapidly dev-eloping acute respiratory distress syndrome (ARDS), acute respiratory failure, and other serious complications. On Jan 7, a novel coronavirus was identified by the Chinese Center for Disease Control and Prevention (CDC) from the throat swab sample of a patient, and was subsequently named 2019-nCoV by WHO.4

Coronaviruses can cause multiple system infections in various animals and mainly respiratory tract infections in humans, such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS).5–7 Most patients have mild symptoms and good prognosis.

So far, a few patients with 2019-nCoV have developed severe pneumonia, pulmonary oedema, ARDS, or mul-tiple organ failure and have died. All costs of 2019-nCoV treatment are covered by medical insurance in China.

At present, information regarding the epidemiology and clinical features of pneumonia caused by 2019-nCoV is scarce.1–3 In this study, we did a comprehensive exploration of the epidemiology and clinical features of 99 patients with confirmed 2019-nCoV pneumonia admitted to Jinyintan Hospital, Wuhan, which admitted the first patients with 2019-nCoV to be reported on.

MethodsStudy design and participantsFor this retrospective, single-centre study, we recruited patients from Jan 1 to Jan 20, 2020, at Jinyintan Hospital in Wuhan, China. Jinyintan Hospital is a hospital for adults (ie, aged !14 years) specialising in infectious diseases. Accord ing to the arrangements put in place by

Published Online January 29, 2020 https://doi.org/10.1016/ S0140-6736(20)30211-7

*Contributed equally.

Tuberculosis and Respiratory Department (Prof N Chen MD, X Dong PhD, Y Wei MD, J Xia MD, T Yu MD, Prof L Zhang MD), Infection Disease Department (F Gong MD, J Wang MD), Science and Education Department (Y Han PhD), and The Office of Drug Clinical Trial Institution (Y Liu MD), Wuhan Jinyintan Hospital, Wuhan, China; Department of Respiratory and Critical Care Medicine, Ruijin Hospital (Prof M Zhou MD, Prof J Qu MD), Institute of Respiratory Diseases (Prof M Zhou, Prof J Qu), Research Laboratory of Clinical Virology, Ruijin Hospital and Ruijin Hospital North (Prof X Zhang MD), and Clinical Research Center, Ruijin Hospital North (Prof X Zhang), Shanghai Jiaotong University School of Medicine, Shanghai, China; State Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China (Prof Y Qiu PhD, Y Han)

Correspondence to: Prof Li Zhang, Tuberculosis and Respiratory Department, Wuhan Jinyintan Hospital, Dongxihu District, Wuhan 430023, China [email protected]

or

Prof Xinxin Zhang, Research Laboratory of Clinical Virology, Ruijin Hospital and Ruijin Hospital North, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China [email protected]

Key unanswered questions to guide control

• Severity – how many mild cases for every severe (hospitalized) case, is it 10:1, 100:1, 1000:1 ?

• Worrying anecdotes about pre-symptomatic transmission including German cases reported in NEJM – is this common?

• Modes of transmission – large droplets?? Many family clusters but low R0 suggests perhaps prolonged close contact is important?

• Effect of interventions applied to date – travel restrictions, border screening, face mask use and massive social distancing

comparative immunogenicity of enhanced influenza vaccines ... · the university of hong kong 2 feb...

Documents