Abstract
Background
Avian influenza virus (AIV) H9N2 has a major role in the emergence of influenza pandemic. We assessed the risk of AIV H9N2 to the human population and public health.
Method
The hemagglutination inhibition method was used to screen for hemagglutinin antibodies. Microneutralization tests were performed to confirm neutralizing antibodies against the AIV H9N2 subtype. Real-time polymerase chain reaction was conducted to detect the H9 subtype in environmental samples. GraphPad Prism software was used for mapping, and STATA software was used for statistical analysis.
Results
The nationwide seroprevalence among these populations was 0.76%. Seroprevalence was compared across regions, genders, and occupational exposure sites. The seroprevalence rates for males and females showed no significant difference. Significant differences were found across regions and occupational exposure environments (P < .05). The south and southwest regions had the highest seroprevalence rates at 1.58% and 1.38%, respectively. The highest seroprevalence was observed in individuals exposed to live poultry market (1.51%). Significant regional differences in H9 nucleic acid positive rates (NAPRs) were found (P < .05), with the southwest and central regions showing the highest rates at 25.99% and 24.35%, respectively. H9 NAPR in live poultry markets (LPMs), farms, and slaughterhouses varied significantly by region (P < .05).
Conclusions
Poultry-related environments have become a key factor in AIV H9N2 infection among occupational populations. Exposure to LPM showed the highest seroprevalence among occupational groups. The distribution characteristics of H9N2 across different poultry environments increased the risk of infection in occupationally exposed populations.
Keywords: environment, H9N2, occupational populations, poultry, seroprevalence
The avian influenza virus (AIV) H9N2 subtype was first isolated from turkeys in the United States in 1966 [1]. H9N2 has diverged into Eurasian and American branches. Eurasian H9N2 viruses have formed 3 stable poultry lineages: GQ, BJ94, and Y439 [2]. H9N2 is epidemic in poultry across Asia and Africa. Compared to other subtypes, H9N2 exhibits frequent reassortment and evolutionary changes. Several subtypes, including H5N1, H10N8, and H7N9, have acquired internal gene cassettes from H9N2 and caused human illness and death [3–5]. Additionally, H9N2 has received genes from highly pathogenic AIVs such as H7N3 and H5N1 subtypes [6]. This feature has driven the emergence of future zoonotic influenza viruses. In 1998, H9N2 was first reported to infect humans [7]. Since December 2015, a total of 155 human infections with AIV H9N2, including 2 deaths, have been reported to the World Health Organization (WHO) in the Western Pacific Region. Of these, 152 cases occurred in China [8]. Most infections were linked to poultry contact, with 29 cases involving confirmed exposure and 11 without known exposure. Virus sequencing revealed that all human H9N2 isolates contain HA genes from the G1-W, G1-E, or BJ94 lineages and are closely related to local poultry isolates [9, 10].
Unlike infections caused by highly pathogenic AIVs, H9N2 infection in humans generally results in mild or asymptomatic illness and is often overlooked. Understanding H9N2 seroprevalence in human populations, particularly among occupational groups exposed to poultry, is crucial. Serological evidence of human H9N2 infections has been reported in Asia, Africa, the Middle East, and parts of North America [11]. Previous meta-analyses and reports indicate that seroprevalence rates ranged from 0.4% to 13.28% between 1997 and 2020 [12].
In this study, we focused on AIV H9N2 seroprevalence in occupational populations exposed to poultry and on H9N2 distribution in poultry environments with human exposure. Our findings contribute to H9N2 risk assessment in China and suggest that effective control measures in poultry-related environments can reduce the risk of H9N2 infection in occupational populations.
METHODS
Sera Collected
Between October 2018 and March 2023, a total of 65 622 serum samples were collected nationwide, covering 31 provinces, autonomous regions, and municipalities. Occupationally exposed individuals had direct contact with live poultry markets (LPMs), poultry farms, household, slaughterhouses, and wild bird habitats. Fasting venous blood samples were collected, stored at 4°C overnight, and then centrifuged for 10 minutes at 2000 rpm. The resulting sera were transferred and stored at −20°C.
Environmental Sample Collection From the Poultry Environment
Environmental samples were collected from LPMs, farms, households, slaughterhouses, wild bird habitats, and other poultry-related locations. Sample types included feces, cages, drinking water, sewage, and chopping boards. Procedures were performed as previously described [13].
Virus
Three strains of H9N2 subtype virus were selected for HI and MN based on antigenic analysis (see Supplementary 1). A/Anhui-Lujiang/39/2018, A/Guizhou/11 495/2021, and A/Anhui-Tianjian/11 086/2023 were used to test sera collected in 2018–2021, 2022, and 2023, respectively. Ferret antisera raised against these viruses were used as positive controls in the HI and MN assays and were provided by the Chinese National Influenza Center.
Hemagglutination Inhibition Assay
The assay was performed as described in the WHO manual for the laboratory diagnosis and virological surveillance of influenza [14]. Briefly, 3 volumes of receptor-destroying enzyme (RDE; Denka Company Ltd., Tokyo, Japan) were added to 1 volume of serum, incubated overnight in a 37°C water bath, and then heated in a 56°C water bath for 30 minutes to inactivate the RDE. Six volumes of phosphate-buffered saline were added, yielding a final serum dilution of 1:10. Serial 2-fold serum dilutions were titrated. Viruses were inactivated using 0.5‰ (v/v) β-propiolactone (Sigma-Aldrich, St. Louis, MO, USA) and then adjusted to 4 hemagglutinin units and reacted with human sera and 1% (v/v) turkey blood cells. Human sera samples that tested positive by HI titer (≥80) in screening assays were confirmed by MN.
Microneutralization Assay
The assay was performed according to the WHO manual for the laboratory diagnosis and virological surveillance of influenza [14]. Serum samples were heat inactivated at 56°C for 30 minutes, followed by 2-fold serial dilutions starting at an initial 1:10 dilution in 96-well plates. A total of 50 µL of virus containing 100 tissue culture infectious doses (TCID50) was added to each well and incubated at 37°C with 5% CO2 for 1 hour. After incubation, Madin–Darby canine kidney cells (100 µL/well) were added and incubated overnight at 37°C. Anti-influenza A virus nucleoprotein monoclonal antibodies (Sigma-Aldrich, St. Louis, MO, USA; Cat. No. MAB8257 and MAB8258) were used to detect viral protein by enzyme-linked immunosorbent assay. MN titers were defined as the reciprocal of the highest serum dilution yielding at least 50% neutralization. When both MN and HI titers were ≥80, the serum was considered positive.
AIV H9 Subtype Identification
Real-time Polymerase Chain Reaction (qPCR) assays for the H9 subtype were conducted on samples collected from environments associated with AIVs. Reactions were performed using the AgPath-ID™ One-Step RT-PCR Kit (4 387 422; Ambion®) following the manufacturer's instructions. Primer and probe sets targeting the matrix and hemagglutinin genes of the H9 subtype were provided by the Chinese National Influenza Surveillance Guideline [15].
Statistical Analysis
Chi-square tests were conducted using STATA software version 15.0 (Texas, USA). A P-value of <.05 was considered statistically significant.
RESULTS
Characteristics of the Occupational Population Exposed to Poultry-Related Environments
A total of 65 622 human serum samples were collected from populations across 31 provinces, municipalities, and autonomous regions from October to March of the following year. Occupational populations were exposed to environments including LPMs, farms, households, slaughterhouses, wild bird habitats, and other poultry-related settings. Age was categorized into 4 groups: junior (0–17), youth (18–45), adult (46–59), and elderly (≥60). The median age was 49.25 years, with an interquartile range of 28.38–69.62. Adults aged 46–59 accounted for the highest proportion (42.71%). Males comprised 52.39% of the sample sera. The proportions of occupational populations exposed to LPMs and households were highest, at 29.32% and 29.72%, respectively (see Supplementary 2).
Seroprevalence Against Avian Influenza Virus H9N2 Subtype in Nationwide During 2018–2023
From 2018 to 2023, the average H9N2 seroprevalence nationwide was 0.76%. Seroprevalence in 2018 (1.25%), 2020 (1.01%), and 2022 (1.11%) each exceeded 1%. The lowest seroprevalence was 0.16% in 2021, while the rate in 2019 was 0.51%. Seroprevalence differed significantly across poultry-related environments (P < .05). The highest rate, 1.51%, was observed among poultry traders and processors exposed to LPMs followed by individuals in other poultry-contact environments and poultry breeders, with rates of 0.64% and 0.59%, respectively. Seroprevalence among household breeders, slaughterhouse processors, and wild bird habitat practitioners was below 0.4%.
The seroprevalence among male and female occupational populations was 0.73% and 0.78%, respectively. No significant difference was observed between the 2 groups (P > .05) (see Table 1).
Table 1.
Occupations and Gender Distribution of H9N2 Seroprevalence Among Populations Exposed to Poultry, 2018–2023
| Occupations and Gender | Seroprevalence (%) of H9N2 Subtype During 2018–2023 | ||||||
|---|---|---|---|---|---|---|---|
| 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | Total | |
| Occupations | |||||||
| Sellers and processors in LPMs | 2.38 | 0.76 | 1.95 | 0.40 | 2.36 | 1.45 | 1.51 |
| (94/3947) | (29/3799) | (45/2309) | (13/3226) | (61/2582) | (49/3375) | (291/19 328) | |
| Poultry farm breeder | 0.77 | 0.21 | 1.21 | 0.10 | 0.82 | 0.68 | 0.59 |
| (20/2612) | (5/2412) | (14/1159) | (3/2765) | (23/2781) | (24/3481) | (89/15 210) | |
| Household breeder | 0.61 | 0.06 | 0.29 | 0.06 | 0.37 | 0.26 | 0.27 |
| (19/3129) | 0.062(2/3246) | 0.29(7/2417) | (2/3385) | (12/3226) | (11/4106) | (53/19 509) | |
| Poultry slaughterhouse processors | 0.65 | 0.34 | 0.00 | 0.03 | 0.57 | 0.84 | 0.37 |
| (7/1081) | (3/879) | (0/192) | (1/896) | (5/873) | (11/3303) | (27/7224) | |
| Wild bird habitat practitioner | 0.00b | 0.00b | 0.00 | 0.00b | 0.86 | 0.90 | 0.30 |
| 0 | 0 | (0/89) | 0 | (2/232) | (1/110) | (3/933) | |
| Others come into contact with poultrya | 0.19 | 0.00 | 0.69 | 0.00 | 1.50 | 0.59 | 0.64 |
| (1/522) | (0/321) | (6/861) | (0/973) | (19/1264) | (9/1507) | (35/5448) | |
| Gender | |||||||
| Male | 1.13 | 0.36 | 1.03 | 0.18 | 1.04 | 0.74 | 0.73 |
| (67/5927) | (21/5812) | (39/3769) | (11/5870) | (61/5857) | (53/7149) | (252/34 384) | |
| Female | 1.37 | 0.35 | 0.98 | 0.14 | 1.19 | 0.77 | 0.78 |
| (74/5364) | (18/5139) | (32/3258) | (8/5643) | (61/5101) | (52/6733) | (245/31 238) | |
| Total | 1.25 | 0.51 | 1.01 | 0.16 | 1.11 | 0.75 | 0.76 |
| (141/11 291) | (39/10 366) | (71/7027) | (19/11 513) | (122/10 958) | (105/13 882) | (497/65 037) | |
aOthers included the vegetable market and farmers’ market.
bNo sample collected.
China was divided into 7 geographical regions: north, northeast, east, south, central, northwest, and southwest. H9N2 seroprevalence in south, southwest, and northwest China was 1.58%, 1.38%, and 1.04%, respectively, followed by east and central China at 0.81% and 0.78%. Seroprevalence in northeast and north China was 0.51% and 0.24%, respectively. A significant difference was found among the 7 regions (P < .05) (see Table 2).
Table 2.
H9N2 Seroprevalence Distribution Among Occupational Populations Exposed to Poultry-Related Environments in 7 Geographical Regions During 2018–2023
| Region | H9N2 Seroconversion (%) During 2018–2023 | ||||||
|---|---|---|---|---|---|---|---|
| 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | average | |
| Northeast | 0.80 | 0.21 | 0.49 | 0.35 | 0.56 | 0.69 | 0.52 |
| North China | 0.61 | 0.00 | 0.00 | 0.00 | 0.49 | 0.34 | 0.24 |
| East China | 1.19 | 0.90 | 0.74 | 0.00 | 1.07 | 0.96 | 0.81 |
| South China | 1.89 | 0.19 | 1.45 | 0.27 | 4.29 | 1.40 | 1.58 |
| Central China | 1.42 | 0.00 | 1.74 | 0.43 | 0.71 | 0.40 | 0.78 |
| Northwest | 2.47 | 0.59 | 0.69 | 0.49 | 1.07 | 0.95 | 1.04 |
| Southwest | 2.53 | 0.60 | 1.36 | 0.25 | 1.70 | 1.84 | 1.38 |
From 2018 to 2023, Guangxi and Fujian provinces had the highest H9N2 seroprevalence rates at 2.15% and 1.74%, respectively, followed by Guizhou at 1.38%. Six provinces reported seroprevalence between 0.9% and 1.3%, while 5 provinces had rates between 0.5% and 0.9%. Nine provinces recorded seroprevalence below 0.5% (see Supplementary 3).
Distribution of Avian Influenza Virus H9N2 Subtype in the Poultry Environments Exposed to the Occupational Population
The environments to which occupational populations were exposed included LPMs, farms, households, slaughterhouses, wild bird habitats, and other poultry-contact settings. Samples were collected from these environments across 7 geographic regions nationwide. H9 nucleic acid positive rates (NAPRs) were detected, showing significant variation among regions (P < .05). H9 NAPR in the southwest, central, and south regions was significantly higher than in other regions, at 25.99%, 24.35%, and 22.73%, respectively.
In LPMs, H9 NAPR varied significantly by region (P < .05), with the highest rate in the central region (33.37%), followed by southwest China and south China at 30.82% and 27.56%, respectively. The lowest rate was observed in northeast China (9.81%).
In farming environments, H9 NAPR also showed significant regional differences (P < .05), with the southwest and south regions recording the highest rates at 5.45% and 5.16%, respectively. In slaughterhouses, H9 NAPR varied significantly across regions (P < .05), with the highest rate in southwest China (26.25%) and the lowest in north China (2.63%). Rates in 5 other regions ranged from 10.12% to 16.47%. In households, the highest H9 NAPR was recorded in the south (8.17%). No significant differences were observed in wild bird habitats or other poultry-contact environments (see Table 3).
Table 3.
H9 NAPR in Poultry Environments Exposed to Occupational Populations
| Region | The H9 Subtype NAPR (%) | ||||||
|---|---|---|---|---|---|---|---|
| LPM | Farming | Household | Slaughterhouses | Other Places Contacted the Poultry | Wild Bird Habitat | Total | |
| Northeast China | 9.81 (284/2894) |
0.22 (8/3687) |
0.19 (3/1620) |
10.12 (43/425) |
0.00 (0/30) |
0.00 (0/26) |
3.89 (338/8682) |
| South China | 27.56 (4644/16 849) |
5.16 (37/717) |
8.17 (38/465) |
14.19 (22/155) |
18.2 (482/2648) |
0.00 (0/619) |
24.35 (5223/21 453) |
| Central China | 33.37 (3351/10 041) |
2.56 (68/2652) |
2.48 (38/1535) |
16.47 (137/832) |
5.44 (8/147) |
1.32 (9/681) |
22.73 (3611/15 888) |
| Southwest China | 30.82 (7008/22 738) |
5.45 (157/2880) |
1.25 (21/1686) |
26.25 (982/3741) |
18.20 (121/665) |
0.53 (1/188) |
25.99 (8290/31 898) |
| North China | 19.51 (452/2317) |
0.51 (33/6534) |
0.88 (48/5439) |
2.63 (26/989) |
7.79 (6/77) |
0.03 (1/3543) |
2.99 (566/18 899) |
| Northwest China | 18.95 (2328/12 283) |
2.09 (215/10 303) |
2.21 (73/3301) |
12.62 (197/1561) |
23.67 (116/490) |
0.27 (4/1470) |
9.97 (2933/29 408) |
| East China | 24.02 (5251/21 858) |
2.28 (193/8452) |
1.14 (104/9137) |
14.64 (270/1844) |
17.16 (87/507) |
0.03 (1/3669) |
12.99 (5906/45 467) |
| χ2 | 229.81 | 59.81 | 41.22 | 65.27 | 7.15 | 14.73 | 14.27 |
| P | .000 | .001 | .000 | .000 | .307 | .22 | .000 |
Sample types associated with occupational exposure included feces, cages, drinking water, sewage, and chopping boards. H9 NAPR exceeded 20% in sewage and chopping boards, at 21.73% and 21.06%, respectively. Rates in sewage and boards were significantly higher than those in other sample types (P < .05). H9 NAPRs in cages and drinking water were 15.35% and 11.44%, respectively. The lowest rate was observed in feces, at only 8.69% (see Table 4).
Table 4.
H9 NAPR in Environmental Samples Exposed to Occupational Populations, 2018–2023
| Year | H9 NAPR(%) in Different Sample Types | ||||
|---|---|---|---|---|---|
| Feces | Cages | Drinking Water | Sewage | Chopping Board | |
| 2018 | 8.91 | 14.85 | 14.50 | 23.45 | 21.93 |
| 2019 | 6.92 | 13.58 | 10.30 | 22.73 | 17.73 |
| 2020 | 10.07 | 13.67 | 6.18 | 19.68 | 24.15 |
| 2021 | 9.65 | 16.83 | 13.65 | 23.69 | 21.87 |
| 2022 | 8.47 | 17.16 | 11.43 | 19.48 | 19.89 |
| 2023 | 8.11 | 16.05 | 12.57 | 21.36 | 20.81 |
| Average | 8.69 | 15.35 | 11.44 | 21.73 | 21.06 |
DISCUSSION
In our study, we selected three strains of the H9N2 subtype to detect antibodies from 2018 to 2023 due to the virus's continuous evolution in poultry and the environment. Although inactivated vaccines have been used to control H9N2 infection in poultry in China since 1998 [16], vaccination does not prevent reinfection or viral shedding in immunized flocks, and vaccine strains cannot be updated in a timely manner. These factors have contributed to the persistent prevalence of H9N2 in poultry. Under immune pressure, H9N2 immune-escape variants have emerged that evade antibody recognition. Between 1994 and 2008, H9N2 evolved into 5 antigenic groups (A–E) [17]. Studies have shown that HA immune-escape mutations such as N193G, R164Q, N166D, I220T, and receptor-binding site deletions enhance viral replication [18, 19], escape antiserum binding, and increase transmission in poultry. Pu et al reported that H9N2 viruses in China have evolved into new antigenic groups F and G [20]. Although anti-H9N2 antibodies can react with both homologous and heterologous viruses from different antigenic groups, heterologous viruses do not respond well to antibody binding [21]. For these reasons, we updated the H9N2 virus strains used to detect anti-H9N2 antibodies in occupational populations in our study.
Our results indicated a significant difference in H9N2 seroprevalence among occupational populations exposed to different environments. Seroprevalence was significantly higher among individuals involved in poultry sales and processing in LPMs. Live poultry markets house multiple poultry species (chickens, ducks, and geese) and wild birds (eg, quail), which carry various subtypes of AIVs, including both highly and low pathogenic strains. Mixed-species farming in these settings accelerates viral recombination, including strains such as H5N1 and H7N9 [22]. Studies have shown that the proportion of H9N2 AIVs in LPMs in China is high—up to 84.89%, particularly in chickens and ducks, with rates of 76.23% and 21.46% [23], respectively Environmental surveillance in China indicated that the AIV-positive rate in LPM-related environments reached 17.78%, with the H9 subtype being the most prevalent [13]. Our study also revealed that the H9 NAPR in sewage samples from LPM environments was 78.43% [24]. Live poultry markets have become a primary site for occupational H9N2 infection. Closing LPMs can significantly reduce the risk of human infection with AIVs. Enhancing management, disinfection, and surveillance in LPMs can lower the risk of H9N2 transmission to humans.
Our study showed that south and southwest China had the highest seroprevalence among employees, at 1.58% and 1.38%, respectively. South China, including the provinces of Guangdong, Guangxi, and Hainan, is a major region for poultry breeding, live poultry trading, and consumption. The climate is warm and humid, live poultry trading is frequent, and the population is dense. It is also one of the highest-risk areas for H9N2 AIV transmission. South China faces considerable challenges in the prevention and control of H9N2. The region borders Southeast Asian countries, and cross-border live poultry trade may increase the risk of virus importation. Southwest China is a critical node on the East Asia–Australia migratory bird route. Live poultry trade and border commerce are active, and the risk of illegal trade in live poultry and related products remains high, potentially introducing foreign virus strains.
Results also showed that the H9 seroprevalence in different regions exhibited a downward trend from 2019 to 2021 compared with the other years. The possible reasons for this decline included the following two aspects. Firstly, the emergence of the Coronavirus Disease 2019 (COVID-19) pandemic and the implementation of prevention and control measures at the end of 2019 led to the temporary closure of LPMs, resulting in a 30%–50% decrease in the positivity rate in southern China [25]. Secondly, during the COVID-19 pandemic, the occupational populations strengthened personal protection including wearing masks and gloves. Moreover, the modes of poultry breeding and sales underwent changes. The market for on-site poultry slaughter shrank, shifting to closed breeding and centralized slaughter, which greatly reduced the risk of human exposure to avian influenza. For these reasons, the risk of human infection with H9N2 was reduced, leading to a decline in seroprevalence among occupational populations.
Our results indicated that LPM and sewage showed higher H9N2 NAPR compared with the other locations and sample types. These H9N2 viruses posed a potential risk of human infection through reassortment and evolution. Previous studies have shown that the H9N2 evolution can interact with human antibodies. H9N2 evolution caused the mutations at the key sites D201G and A168N of the HA protein [26], as well as at its receptor-binding sites [27], leading to the mutations responsible for the antigenic drift of the H9N2 virus. These mutations directly mediate antibody recognition escape, which impairs the ability of human antibodies to recognize the virus and thus increased the risks of cross-species transmission and human infection. In the future, it is necessary to strengthen the joint surveillance of molecular epidemiology and serology, accurately identify key evolutionary loci and high-risk variants, develop broad-spectrum and long-acting prevention and control technologies, and curb their potential evolution into pandemic strains.
In China, a serological and virological surveillance network for occupational populations and related environments has been established. Based on this system, seroprevalence trends among occupational populations can be monitored in a timely manner. Preventive and control measures against H9N2 have been implemented to reduce the risk of infection.
Supplementary Material
Notes
Data availability statement. The data underlying this article are available in the article and in its online supplementary material.
Financial support. This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFF0802404).
Ethical approval. The study falls under the scope of state-mandated monitoring. State-mandated monitoring (eg, statutory infectious disease reporting, public health surveillance, and environmental/occupational health monitoring), in principle, falls within the scope of “life science and medical research involving human subjects” and may be exempted from ethical review in accordance with the law (based on the 2023 Measures for Ethical Review of Life Science and Medical Research Involving Human Subjects adopted by the National Science and Technology Ethics Commission.).The study was conducted in strict accordance with the Declaration of Helsinki (2013).
Contributor Information
Hong Bo, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Ye Zhang, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Jie Dong, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Xiyan Li, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Weijuan Huang, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Yanhui Cheng, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Zi Li, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Hejiang Wei, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Ning Xiao, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Dayan Wang, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Reference and Research on Influenza, Beijing, China.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
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