# Avian Influenza A(H9N2) Virus Transmission across Chicken Production and Distribution Networks, Vietnam

Mathew Hennessey, Thuy Hoang, Jayna Raghwani, Younjung Kim, Hoa Thi Thanh Pham, Trang Huyen Nguyen, Hung Quoc Nguyen, Joshua G Lynton-Jenkins, Ashley C Banyard, Ian H Brown, et al.

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## To cite this version:

Mathew Hennessey, Thuy Hoang, Jayna Raghwani, Younjung Kim, Hoa Thi Thanh Pham, et al. "Avian Influenza A(H9N2) Virus Transmission across Chicken Production and Distribution Networks, Vietnam. Emerging Infectious Diseases, 2026, 32 (2), pp.259-264. 10.3201/eid3202.251416. hal-05529858

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Submitted on 27 Feb 2026

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# Avian Influenza A(H9N2) Virus Transmission across Chicken Production and Distribution Networks, Vietnam

Mathew Hennessey, Thuy Hoang Thi, Jayna Raghwani, Younjung Kim, Hoa Thi Thanh Pham, Trang Huyen Nguyen, Hung Quoc Nguyen, Joshua G. Lynton-Jenkins, Ashley C. Banyard, Ian H. Brown, Joe James, Tom Lewis, Nicola S. Lewis, Dirk Pfeiffer, Fiona Tomley, Damer Blake, Ngoc Pham Thi, Anne Conan, Vuong Nghia Bui,<fnref n="1" /> Guillaume Fournié<fnref n="1" />

In northern Vietnam, during March 2021–March 2022, prevalence of influenza A(H9N2) in chickens was higher in distribution facilities than on farms and varied between facility types. Phylogenetic analysis indicated extensive viral mixing along networks of chicken production and distribution, highlighting a need for risk mitigation across the entire network.

High-pathogenicity avian influenza A subtype H5N1 viruses of the Goose/Guangdong/1/96 lineage and low pathogenicity avian influenza A subtype H9N2 viruses are endemic in Southeast Asia, including Vietnam. Both subtypes affect poultry production and pose zoonotic risks (1) directly and through their involvement in the generation of novel virus reassortments (2). In Vietnam, the subtypes are frequently detected in live bird markets, and higher prevalence is associated with practices such as mixing poultry from multiple sources (3). However, that finding should be interpreted cautiously because farms and the markets they supply have limited prevalence data, and the focus on markets has diverted attention from larger slaughter facilities despite those facilities

playing a key role in poultry distribution. Together, those gaps constrain understanding of avian influenza virus (AIV) transmission risk along the production and distribution network (PDN) through which poultry are raised, traded, and consumed. We conducted a cross-sectional study in northern Vietnam to assess avian influenza A(H5N1) and A(H9N2) prevalence in chickens, determine how AIV prevalence varied between farms and the different distribution facility types, and examine how viral genetic diversity was structured along the PDN.

## The Study

We selected 50 farms and 52 distribution facilities, including retail and wholesale markets, small-scale slaughter points, and industrial slaughterhouses, across 4 provinces (Bac Giang, Ha Noi, Hai Dung, and Quang Ninh) (Figure 1). We identified distribution facilities trading or processing slow-growing colored broiler chickens (i.e., hybrids of indigenous roosters and fast-growing broiler hens that account for most chicken meat produced in Vietnam [4]) through consultation with provincial

Author affiliations: Royal Veterinary College, London, UK (M. Hennessy, J. Raghwani, N.S. Lewis, D. Pfeiffer, F. Tomley, D. Blake, G. Fournié); National Institute of Veterinary Research, Hanoi, Vietnam (T.H. Thi, T.H. Nguyen, H.Q. Nguyen, N.P. Thi, V.N. Bui); University of Oxford, Oxford, UK (Y. Kim); Université de Montpellier, Montpellier, France (H.T.T. Pham, A. Conan); World Organisation for Animal Health/Food and Agriculture Organization International Reference Laboratory for Avian Influenza Animal and Plant Health Agency, Addlestone, UK (J.G. Lynton-Jenkins, A.C. Banyard, J. James, T. Lewis);

Pirbright Institute, Pirbright, UK (I.H. Brown); World Health Organization Collaborating Centre for Influenza Reference and Research, London (N.S. Lewis); City University, Hong Kong, China (A. Conan); French Agricultural Research Centre for International Development, Harare, Zimbabwe (A. Conan); Université de Lyon, Marcy l'Etoile, France (G. Fournié); Université Clermont Auvergne, Saint Genes Champanelle, France (G. Fournié)

DOI: https://doi.org/10.3201/eid3202.251416

<footnote n="1">¹These authors contributed equally to this article.</footnote>
<figure><img src="image_3.png" /><figcaption>**Figure 1.** Geographic area and sites for study of avian influenza virus A(H9N2) prevalence across chicken production and distribution networks, Bac Giang, Hanoi, Hai Duong, and Quang Ninh Provinces, Vietnam, March 2021–March 2022. The 4 study provinces and the individual sites (farms and distribution facilities) are shown alongside the detection of avian influenza viruses (contaminated defined as ≥1 positive sample; noncontaminated defined as all samples testing negative) and the spatiotemporal cluster of contaminated farms. The 2 other farms that appear located in the cluster were not sampled during the temporal window.</figcaption></figure>

authorities and traders. We randomly selected 4 retail markets and 4–5 slaughter points in the urban area of each province and recruited all wholesale markets and slaughterhouses in the study area. We traced farming areas supplying distribution facilities through interviews and snowball sampling. We randomly selected 1 farm per distribution facility from the list of farms of these supplying areas. During March 2021–March 2022, we collected oropharyngeal and cloacal swab specimens from 15 slow-growing broilers at each site and from fast-growing broilers when present. On farms, we sampled flocks near the end of production cycles. We administered structured questionnaires to capture husbandry, vaccination, and trade practices. Our study was approved by the National Institute of Veterinary

Research (Vietnam) (approval no. 020-480433/DD-YTCC) and the Royal Veterinary College (UK) Ethics and Welfare Committee (approval no. URN: 20204811983-3). Participants were informed about the study and then asked to provide their verbal consent to take part.

We screened samples for the influenza A virus matrix gene by using real-time reverse transcription PCR (5) and then subtyped positive samples (i.e., those with cycle threshold values <40) for H5 and H9 (Appendix 1, https://wwwnc.cdc.gov/EID/article/32/2/25-1416-App1.pdf). We sequenced samples with cycle threshold values ≤30, compared them with genomes from Vietnam during 2018–2022 for which sequences were available through GISAID (https://www.gisaid.org), and submitted the genomes to

<table><caption>**Table.** Posterior estimates and posterior predictive values of avian influenza virus A(H9N2) prevalence across chicken production and distribution networks, Bac Giang, Ha Noi, Hai Duong, and Quang Ninh Provinces, Vietnam, March 2021–March 2022*</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2">No. sites</th><th rowspan="2">No. chickens</th><th rowspan="2">H9N2-positive chickens, no (%)</th><th colspan="3">H9N2 prevalence, median % (95% HDI)</th></tr><tr><th>Site-level</th><th>Bird-level in contaminated sites</th><th>Overall† bird-level</th></tr></thead><tbody><tr><td>Farms</td><td>50</td><td>750</td><td>31 (4.1)</td><td>0.111 (0.037–0.202)</td><td>0.414 (0.305–0.525)</td><td>0.045 (0.014–0.086)</td></tr><tr><td>Distribution facilities</td><td>52</td><td>932</td><td>168 (18.0)</td><td></td><td></td><td></td></tr><tr><td>Retail market</td><td>16</td><td>240</td><td>38 (15.8)</td><td>0.778 (0.559–0.967)</td><td>0.212 (0.123–0.309)</td><td>0.161 (0.088–0.244)</td></tr><tr><td>Wholesale market</td><td>11</td><td>210</td><td>14 (6.7)</td><td>0.481 (0.163–0.850)</td><td>0.125 (0.033–0.238)</td><td>0.057 (0.014–0.117)</td></tr><tr><td>Slaughter point</td><td>19</td><td>363</td><td>106 (29.2)</td><td>0.725 (0.527–0.898)</td><td>0.413 (0.308–0.515)</td><td>0.295 (0.190–0.402)</td></tr><tr><td>Slaughterhouse</td><td>6</td><td>119</td><td>10 (8.4)</td><td>0.233 (0.014–0.542)</td><td>0.483 (0.158–0.795)</td><td>0.103 (0.002–0.286)</td></tr></tbody></table>

<footnote>*HDI, high density interval.</footnote>

<footnote>†Estimated prevalence across both contaminated and uncontaminated sites.</footnote>
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Time-scaled phylogenies of hemagglutinin sampled avian influenza virus A(H9N2) virus genomes in study of H9N2 virus prevalence across chicken production and distribution networks, Bac Giang, Hanoi, Hai Duong, and Quang Ninh Provinces, Vietnam, March 2021–March 2022. Tree tips are labeled by the unique sampled site identification; red text indicates sequences from 3 farms in the spatiotemporal cluster. Branches are colored by posterior support, and horizontal node bars represent 95% highest posterior density intervals of node ages. Heatmaps indicate province, site type, and chicken type of each sequence. C, chicken type; P, province; S, site type.</figcaption></figure>

GISAID (Appendix 2, https://wwwnc.cdc.gov/EID/article/32/2/25-1416-App2.xlsx). We conducted phylogenetic analyses by using Bayesian methods to infer lineage structure and reassortment patterns (6). We performed separate analysis for distribution facilities and farms by using space-time cluster analysis by using a Bernoulli model (SdTScan, https://www.satscan.org) and Bayesian hierarchical logistic regression models (https://doi.org/10.32614/CRAN.packag.R2jags) to estimate AIV prevalence at site and bird levels.

All farms were independently owned and held 100–15,000 (median 2,000) slow-growing broilers 70–240 days old (mean 116 days) at sampling. Sixty percent of farmers reported AIV vaccination for their flocks.

Among 1,682 sampled chickens (750 from farms and 932 from distribution facilities), a single chicken from a Quang Ninh slaughter point tested positive for

H5, a finding consistent with farm-level H5N1 virus prevalences of 0%–0.1% reported in Egypt and Bangladesh (7,8). Depending on their pathogenicity, some H5N1 virus lineages can circulate in waterfowl without causing overt clinical disease. Spillover into chickens has frequently been associated with close proximity to free-grazing ducks and rice paddy ecosystems (9), and proximity of these species within markets probably facilitates cross-species transmission. In contrast, we detected H9N2 virus in 11.7% (197/1,682) of all sampled chickens. On farms, estimated bird-level prevalence of H9N2 virus was 4.5%, and detection was more frequent in unvaccinated (4/20) than vaccinated (1/30) flocks, although that difference was not significant (p = 0.14 by Fisher exact test). Such high prevalence in farmed chickens is similar to that for Egypt but higher than for previous reports from southern Vietnam and Bangladesh (7,10,11).
The best-fitting model differentiated distribution facilities by type and supplying area (Appendix 1 Table 4), whereas including chicken type or sampling period did not improve the model fit. Overall, bird-level prevalence in distribution facilities was ≈5-fold higher than on farms and was highest in informal slaughter points, followed by retail markets, slaughterhouses, and wholesale markets (Table). Influenza A(H9N2) virus prevalence was nearly as high on farms as in wholesale markets and was estimated to increase by 254% (95% highest density interval 4%–754%) from farms to retail markets and 545% (95% highest density interval 108%–1396%) from farms to slaughter points (Table).

On the basis of H9 sequences, we assigned all viruses to clade B4.71 (maximum identity >96%). Time-scaled phylogenies of H9N2 virus genomes showed limited genetic diversity (Figure 2, 3; Appendix 1 Figure 5, 6). The estimated time to most

recent common ancestor for all sampled viruses spanned a broad range (95% highest posterior density interval 2008–2018 across all segments), although most sequences shared a more recent time to most recent common ancestor (95% highest posterior density interval ≈2017–2019). Our dataset included sequences from 3 farms forming a spatiotemporal cluster in Hanoi (23.5-fold higher risk than for farms outside; p = 0.045) (Figure 2, 3; Appendix 1 Figure 5, 6). Viruses from 2 farms had high genetic identity, consistent with epidemiologic linkage, whereas virus from a third farm (site 531) clustered separately in all 8 gene segments, suggesting that the spatiotemporal cluster involved ≥2 genetically distinct lineages. Alongside detection of genetically distinct viruses within and between distribution facilities, these findings demonstrate the presence of distinct H9N2 virus lineages at local scales and frequent re-assortment in the region (Figure 2, 3).

<figure><img src="image_5.png" /><figcaption>**Figure 3.** Time-scaled phylogenies of neuraminidase of sampled avian influenza virus A(H9N2) virus genomes in study of H9N2 virus prevalence across chicken production and distribution networks, Bac Giang, Hanoi, Hai Duong, and Quang Ninh Provinces, Vietnam, March 2021–March 2022. Tree tips are labeled by the unique sampled site identification; red text indicates sequences from 3 farms in the spatiotemporal cluster. Branches are colored by posterior support, and horizontal node bars represent 95% highest posterior density intervals of node ages. Heatmaps indicate province, site type, and chicken type of each sequence. C, chicken type; P, province; S, site type.</figcaption></figure>
## Conclusions

Our results indicate that poultry production and distribution network configurations, including the origins of supplying farms, influence H9N2 virus prevalence and thus human exposure risk. The pattern of viral circulation amplification along the PDN is consistent with studies in southern Vietnam and Bangladesh (7,11) and probably reflects trading conditions. For example, birds are mixed from multiple sources and experience lengthy, stressful transportation (i.e., crowding and lack of sustenance), creating opportunities for virus exposure and transmission en route; that finding was supported by the improved model fit when we included supplying areas, suggesting that procurement and distribution practices influence viral prevalence at distribution facilities.

High viral prevalence in slaughter points and retail markets probably reflects sourcing involving multiple suppliers, including wholesale markets, indicating that chickens spent longer in the PDN before sampling. The lack of geographic structure in AIV genetic diversity further points to extensive viral mixing among poultry populations. Control and surveillance efforts should therefore address the entire poultry PDN.

The Vietnam Avian and Human Influenza Preparedness program has prioritized upgrading wholesale markets and industrial slaughterhouses and promoting their use (12). Although low prevalence in such facilities supports this focus, slaughterhouses remain underused, and informal slaughter points are still preferred (13). Surveillance and risk mitigation strategies must also target the numerous distribution facilities in Vietnam that are small and informal but widely used.

## Acknowledgments

We thank Saira Butt for support in the initial development of the Bayesian model, the Food and Agricultural Organization and the Vietnamese Department for Animal Health for sharing information about the locations of markets and slaughter facilities, and the numerous participants for giving up their time to take part in this study.

Financial support for this study was obtained through the United Kingdom Research and Innovation Global Challenge Research Fund One Health Poultry Hub (grant no. BB/S011269/1) awarded to the Royal Veterinary College, 1 of 12 interdisciplinary research hubs funded under the UK government's Global Challenges Research Fund Interdisciplinary Research Hub

initiative. G.F. is supported by the French National Research Agency and the French Ministry of Higher Education and Research. Animal and Plant Health Agency staff were funded by the UK Department for the Environment, Food and Rural Affairs and the devolved Scottish and Welsh governments (grant nos. SE2213, SE2227, and SV3006).

## About the Author

Dr. Hennessey is a postdoctoral researcher at the Royal Veterinary College, London, UK. His primary research interests are the safety and sustainability of food systems and how human-animal-environmental relations influence disease transmission.

## References

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2. Sims LD, Tripodi A, Swayne DE. Spotlight on avian pathology: can we reduce the pandemic threat of H9N2 avian influenza to human and avian health? Avian Pathol. 2020;49:529–31. https://doi.org/10.1080/03079457.2020.1796139

3. Sealy JE, Fournie G, Trang PH, Dang NH, Sadeyen JR, Thanh TL, et al. Poultry trading behaviours in Vietnamese live bird markets as risk factors for avian influenza infection in chickens. Transbound Emerg Dis. 2019;66: 2507–16. https://doi.org/10.1111/tbed.13308

4. Thi Dien N, Thi Minh Khue N, Ebata A, Fournié G, Huyen LTT, Van Dai N, et al. Mapping chicken production and distribution networks in Vietnam: an analysis of socio-economic factors and their epidemiological significances. Prev Vet Med. 2023;214:105906. https://doi.org/10.1016/j.prevetmed.2023.105906

5. Centers for Disease Control and Prevention. CDC real-time RT-PCR (rRT-PCR) protocol for detection and characterization of swine influenza (version 2009). Reference no. I-007-05. 2009 [cited 2025 Jun 4]. https://www.hsdl.org/c/view?docid=778749

6. Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 2018;4:vey016. https://doi.org/10.1093/ve/vey016

7. Gupta SD, Hoque MA, Fournié G, Henning J. Patterns of Avian Influenza A (H5) and A (H9) virus infection in backyard, commercial broiler and layer chicken farms in Bangladesh. Transbound Emerg Dis. 2021;68:137–51. https://doi.org/10.1111/tbed.13657

8. El-Zoghby EF, Aly MM, Nasef SA, Hassan MK, Arafa AS, Selim AA, et al. Surveillance on A/H5N1 virus in domestic poultry and wild birds in Egypt. Virol J. 2013;10:203. https://doi.org/10.1186/1743-422X-10-203

9. Minh PQ, Morris RS, Schauer B, Stevenson M, Benschop J, Nam HV, et al. Spatio-temporal epidemiology of highly pathogenic avian influenza outbreaks in the two deltas of Vietnam during 2003-2007. Prev Vet Med. 2009;89:16–24 https://www.sciencedirect.com/science/article/pii/
S0167587709000178. https://doi.org/10.1016/
j.prevetmed.2009.01.004

10. El-Sayed MM, Arafa AS, Abdelmagid M, Youssef AI. Epidemiological surveillance of H9N2 avian influenza virus infection among chickens in farms and backyards in Egypt 2015–2016. Vet World. 2021;14:949–55. https://doi.org/10.14202/vetworld.2021.949-955

11. Le KT, Stevenson MA, Isoda N, Nguyen LT, Chu DH, Nguyen TN, et al. A systematic approach to illuminate a new hot spot of avian influenza virus circulation in South Vietnam, 2016–2017. Transbound Emerg Dis. 2022;69:e831–44. https://doi.org/10.1111/tbed.14380

12. World Bank. Vietnam avian and human influenza control and preparedness. 2015 [cited 2023 Oct 17]. https://www.worldbank.org/en/results/2015/05/12/vietnam-avian-and-human-influenza-control-and-preparedness

13. Le Quyen. Surplus and shortage of centralized animal slaughter network. 2023 [cited 2025 Apr 16]. https://nhachannuoi.vn/thua-va-thieu-mang-luoi-giet-mo-dong-vat-tap-trung

Address for correspondence: Mathew Hennessey, Royal Veterinary College, Hawkshead Lane, Hatfield AL9 7TA, UK; email: mphennessey@rvc.ac.uk

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# Avian Influenza A(H9N2) Virus Transmission across Chicken Production and Distribution Networks, Vietnam

## Appendix 1

## Methods

### Site eligibility criteria

Between March 2021 and March 2022, we visited sites in four provinces of northern Viet Nam (Bac Giang, Ha Noi, Hai Duong, and Quang Ninh) representing areas with dense poultry (i.e., chickens and ducks) and human populations.

Distribution facilities that were active during the study period and traded or processed slow-growing broiler chickens were classified into markets (retail and wholesale) and slaughter facilities (slaughter points and industrial slaughterhouses). A market was an open space with at least two live chicken vendors operating at least once a week and where other goods may also be traded (1). Wholesale markets in Viet Nam are typically large, with over 20 vendors, selling chickens to traders operating in other locations. Retail markets are generally smaller with all chickens directly sold to consumers, restaurateurs, or caterers. Industrial slaughterhouses process large numbers of chickens using semi-automatised systems, while slaughter points handle smaller amounts (tens to hundreds of birds per day) manually. As there was only a small number of wholesale markets and industrial slaughterhouses in the study provinces, all such sites were selected. They were identified through consultation with the Department of Animal Health (DAH) and the Food and Agriculture Organization of the United Nations (FAO), and interviews with poultry traders during field investigations.

Retail markets and slaughter points in urban areas (i.e., wards in cities and towns) of the four provinces were eligible whereas rural sites were excluded. In Ha Noi, where live bird
marketing was prohibited by the Ha Noi People's Committee (Decisions 71/2007/QĐ-UBND) in the urban center wards, surrounding districts were included. Four to five wards were randomly selected per province, with one site for each distribution facility randomly chosen per ward.

For each selected distribution facility, the farming areas supplying them with slow-growing broiler chickens were identified through interviews with vendors and mobile traders, tracing the supply chain back to the production sites at the sub-district (commune) level. For each distribution facility, one commune within the identified supply area was randomly selected, all its eligible farms were listed with the assistance of local DAH, and one was randomly selected. Farms holding $\ge$100 slow-growing broiler chickens at a late production stage (i.e., >70 days-old) were eligible. At each site, cloacal and oropharyngeal swabs were collected from 15 slow-growing broiler chickens to ensure $\ge$95% confidence in detecting AIV at a prevalence of $\ge$20%. If fast-growing broiler chickens were present, up to 15 were also sampled.

Structured questionnaires were administered to owners of farms and distribution facilities to collect data on poultry husbandry, including flock size, vaccination, age at sampling, numbers sold in markets or processed in slaughter facilities. Questionnaires were developed in English by UK and Vietnamese partners, translated into Vietnamese, and piloted before revision. Responses were entered using the Vietnamese version of the survey tool ODK and translated into English for analysis by Vietnamese partners.

## Sample screening

Samples were screened by the National Institute of Veterinary Research (NIVR), Viet Nam, for the influenza A virus matrix gene using real-time reverse transcription polymerase chain reaction (rRT-PCR) (2). Virus RNA (vRNA) was extracted using the QIAamp Viral RNA kit (Qiagen, Germany) following manufacturer's instructions (3). Samples with a cycle threshold ($C_t$) <40 were transferred to the Animal and Plant Health Agency (APHA), UK, for H9 and H5 subtyping by RT-PCR (4,5). A sample was positive if $C_t$ <36 (6), and a bird was positive if either oropharyngeal or cloacal swab was positive. Samples with $C_t$≤30 were considered for sequencing, with two to six randomly selected per site and chicken type, proportional to prevalence.
## Sequencing and bioinformatics

Whole genome sequence (WGS) data was generated at APHA following previously described methods (7). Influenza virus genomes were assembled from raw sequence data with the IRMA pipeline (8), which resulted in between 76–89 sequences with >75% sequence coverage per gene segment. These sequences were combined with publicly available H9N2 virus sequences sampled between 2018 and 2022 from GISAID. HA sequences were classified using the “A/H9 influenza virus lineage and clade assignment” tool (9).

## Phylodynamic analysis

Complete H9N2 virus sequences were retrieved for all eight gene segments identified in Viet Nam from 2018 to 2023 via GISAID (Appendix 2, https://wwwnc.cdc.gov/EID/article/32/2/25-1416-App2.xlsx). These sequences were combined with newly generated data from this study for each gene segment and aligned using MAFFT v7.487 (10). The evolutionary history of each gene segment was reconstructed using a Bayesian phylogenetic framework implemented in BEAST v1.10.4 (11). Specifically, we applied a codon-structured substitution model, a Bayesian skyline coalescent prior, and a relaxed log-normal distributed molecular clock. For each gene segment, two independent Markov chain Monte Carlo (MCMC) runs of 50 million steps were performed, with sampling conducted at regular intervals to obtain 10,000 samples per chain. Maximum clade credibility trees were visualized with R packages ‘ggtree’ and ‘treeio’ (12). Subtrees containing virus sequences generated from this study were extracted using the *drop tip* function in ‘treeio’ package.

## Space-time cluster analysis

We assessed whether contaminated distribution facilities and farms clustered over space or both space and time. A contaminated site had ≥1 AIV-positive chicken. A Bernoulli model using 999 permutations was specified using SaTScan (13). Both spatial circular and elliptic windows were used, with a maximum size of 50% of the population at risk. Temporal precision was 1 month, with clusters ranging from 1 month to 50% of the study period. Significance was set at p < 0.05.

## Prevalence estimation

Bayesian zero-inflated logistic regression models were built to estimate H9N2 prevalence at site and bird levels, separately for distribution facilities and farms. For distribution facilities,
site- and bird-level factors that may influence prevalence were considered (1): facility type (2), chicken type (slow-, fast-growing broiler) (3), facility province or (4) supplying area, and (5) sampling period, with January–February (Têt festival) defined as high-risk period (14). Wholesale markets and slaughterhouses being unevenly distributed, distribution facility- and session-related variables were included only in models differentiating distribution facility types, and separately due to limited sample size (Table 2). Parameters were estimated by MCMC in R2JAGS (15) in R (16), and compared using deviance information criterion (DIC), with differences ≥5 indicating better fit [32,33].

## Model specification

### Prevalence estimation

Separate bayesian zero-inflated logistic regression models were constructed for distribution facilities and farms with the following structure. The number $Y_{si}$ of chickens of type i testing positive in site s follows a binomial distribution,

$$Y_{si} \sim \text{Binomial}(\theta_{si}, n_{si})$$

With $n_{si}$ the number of chickens of type i sampled in site s and $\theta_{si}$ the chicken-level prevalence in site s:

$$\theta_{si} = C_s \delta_{si}$$

$$C_s \sim \text{Bernoulli}(\omega_t)$$

With $C_s$ the contamination status of site s. It follows a Bernoulli distribution, with $\omega_t$ the probability of a site of type t being contaminated. Thus, in a contaminated site, $\theta_{si} = \delta_{si}$, the probability of a chicken testing positive. $\delta_{si}$ is formulated as a logistic regression

$$\text{logit}(\delta_{si}) = \alpha_s + \sum_j \beta_j A_{sij}$$

$\beta_j$ is a regression coefficient associated with a chicken- or site-level characteristic j, $A_{sij}$ an indicator variable, equal to 1 if chickens of type i in site s, or the site s, shows this characteristic j, and null otherwise. $\alpha_s$ is a site-specific random intercept, assumed to follow a normal distribution with mean $\mu$ and variance $\sigma^2$:

$$\alpha_s \sim \text{Normal}(\mu, \sigma^2)$$
Under the null model, chickens and sites were not differentiated based on their
characteristics, with $\forall t \omega_t = \omega$ and $\forall i, t \operatorname{logit}(\delta_{si}) = \alpha_s$. Due to the limited number of positive
chickens in farms, only a null model without random effect was considered to estimate the
prevalence of H9N2 in these settings. $\delta_{si}$ could then be reformulated as $\delta_{si} = \mu$. On the other
hand, multiple models with different sets of chicken- or site-level variables were considered
when estimating the prevalence of H9N2 in distribution facilities, as mentioned in the
manuscript. The types of distribution facility were either differentiated as (i) markets and
slaughter facilities, or (ii) retail markets, wholesale markets, slaughter points and
slaughterhouses. The distribution facilities' locations were Ha Noi, Bac Giang or Hai
Duong/Quang Ninh as most sites sampled in Hai Duong and Quang Ninh were near their shared
border, and the distribution facilities' supplying areas were Ha Noi, Bac Giang, Hai
Duong/Quang Ninh or Other provinces.

Weakly informative priors were specified, *Normal*(0,100) for the regression coefficients
and the mean of the random intercept, *InverseGamma*(1,1) for the variance of the random
intercept, *Beta*(1,1) for the probability of a site being contaminated and the probability of a
chicken testing positive in the farm model. After a burn-in of 10,000 iterations, models were
considered to have achieved convergence based on the visual inspection of traceplots and if
Gelman statistics were <1.001 and effective sample size was >10,000 for each parameter (17).
As a posterior predictive check, the contamination status of each site and the infection status of
each sampled chicken in contaminated site were simulated, and summary statistics were
compared to the observations. The median and highest density interval (HDI) of each
parameter's marginal posterior distribution were computed as well as odds ratios where
appropriate. For models with distribution facilities differentiated according to their type and
location or supplying area, the overall viral prevalence for each distribution facility type was
averaged as follows. First, parameter values were sampled from the joint posterior distribution.
The posterior predicted prevalence in each sampled distribution facility was obtained by
multiplying the corresponding estimated site-level and chicken-level prevalence. These posterior
predicted prevalence estimates were then averaged with respect to the distribution facility type
and province. This was repeated for 10,000 iterations, and medians and HDI computed for the
resulting distributions.
Model script

model

{

for(i in 1:no_site_by_type) {

positive[i] ~ dbin(p_bird.1[i], total[i])

p_bird.1[i] <- i_endpoint[site_id[i]]*p_bird[i]

p_bird[i] <- ilogit(intercept_bird +

p_bird_bird_type[i] +

p_bird_type[site_id[i]] +

p_bird prov[site_id[i]] +

random_site[site_id[i]]

p_bird_bird_type[i] <- 0

}

for(j in 1: no_site) {

i_endpoint[j] ~ dbern(p_endpoint[site_type[j]]) # uses 'endpoint', 'site_type', or 'sales'

p_bird_type[j] <- β_T1*retail[j] + β_T2*wholesale[j] + β_T3*shouse[j]

p_bird prov[j] <- β_P1*cHN[j] + β_P2*cBG[j] + β_P3*cHD_QN[j] + β_P4*cOT[j]

random_site[j] ~ dnorm(0, 1/sigma_1^2)

}

# β priors for endpoint

p_endpoint[1] <- p_endpoint_1

p_endpoint[2] <- p_endpoint_2

p_endpoint[3] <- p_endpoint_3

p_endpoint[4] <- p_endpoint_4
p_endpoint_1 ~ dbeta (1,1)

p_endpoint_2 ~ dbeta (1,1)

p_endpoint_3 ~ dbeta (1,1)

p_endpoint_4 ~ dbeta (1,1)

intercept_bird ~ dnorm(0, 1/SD^2)

β_T1 ~ dnorm(0, 1/SD^2)

β_T2 ~ dnorm(0, 1/SD^2)

β_T3 ~ dnorm(0, 1/SD^2)

β_P1 ~ dnorm(0, 1/SD^2)

β_P2 ~ dnorm(0, 1/SD^2)

β_P3 ~ dnorm(0, 1/SD^2)

β_P4 ~ dnorm(0, 1/SD^2)

sigma_1 <- 1 / sqrt(tau)

tau ~ dgamma (1,1)

}

# Additional results

## Farm practices

Of the 52 tested farms, all but two raised only chickens; two farms also raised ducks and were negative for AIV.

Most farmers (30/50, 60%) reported AIV vaccination, but only three specified the subtype, all H5N1. Vaccination occurred at a median age of 28 days (range 10–50) with a median 87 days (40–165) between vaccination and sampling.

## Chickens sold through distribution facilities

Wholesale markets sold far more chickens daily (median: 2906, range: 239–115,050) than retail markets (93, 11–759), and slaughterhouses (550, 143–2250) processed more than
slaughter points (25, 4–125). Overall, fast-growing broiler chickens were sampled in seven (36.8%) slaughter points, three (50%) slaughterhouses, three (27.3%) wholesale markets and no retail markets.

Farms supplying distribution facilities were located across the four study provinces and others in northern Viet Nam. Most distribution facilities (46/52, 88.5%) were supplied, at least partially, by farms in their own province (Appendix 1 Table 1). About half (27/52, 51.9%) were supplied by one province, this was highest for slaughter points (63.2%) and lowest for wholesale markets (33.3%), the latter also most often supplied by non-study provinces (72.7%).

Across farms and distribution facilities, 213 chickens (12.6%) were M gene-positive, 197 (11.7%) H9-positive, and one H5-positive – a slow-growing broiler from a Quang Ninh slaughter point. All but one H9-positive chickens had oropharyngeal positivity, 6 had cloacal positivity (Appendix 1 Table 2). Subsequent WGS confirmed all H9- and H5-positive samples as H9N2 and H5N1, respectively.

A total of 750 slow-growing broilers were sampled from 50 farms. Across 52 distribution facilities, 932 chickens were sampled (748 slow-growing, 184 fast-growing), from four provinces (Appendix 1 Table 3).

## AIV modeling

All models converged (Appendix 1 Figure 1,2).

For distribution facilities, the best-fitting model differentiated sites by facility type (retail market, wholesale market, slaughter point, slaughterhouse) and by the location of the supplying farms (Ha Noi, Bac Giang, Hai Duong/Quang Ninh) and had a DIC 20.2 units lower than the null model (Appendix 1 Table 4). This model also outperformed a comparable model which used facility location instead of supplying farm location, with a DIC difference of 5.3 units. One additional model within 5 DIC units of the best-fitting model included chicken type (Slow-growing broiler, fast-growing broiler); however, estimates of shared coefficients were similar across models.

Simulations from the best-fitting model reproduced positive chicken counts, overall and by distribution facility type, though prevalence was overestimated in Bac Giang, Ha Noi and Quang Ninh (Appendix 1 Figure 3).
Marginal posterior distributions for the best fitting distribution facility model are shown
in Appendix 1 Table 5, Figure 4.

Phylodynamic and spatiotemporal cluster analysis

Sequences from the three farms (sites 522, 531, 550) in the Ha Noi spatiotemporal cluster highlighted contrasted patterns: viruses from two farms (522, 550) located around 4km from each other (Appendix 1 Table 6) clustered together, while another (531) located further away in the cluster consistently grouped separately across all segments (Appendix 1 Figure 5,6).

For context, in HA, this corresponded to four amino acid and eight nucleotide differences
between farm 531 and the two others; in PB2, five amino acid and 16 nt differences. Therefore,
the spatiotemporal farm cluster comprised at least two distinct viral lineages. Additionally,
TMRCA of these sites varied across segments, from 0.77 years in NA to 2.18 years in HA. These
observations together with frequent detection of genetic diversity within and between
distribution facilities support co-circulation of divergent lineages at local scales and frequent
reassortment in the region.

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<table><caption>**Appendix 1 Table 1.** The distribution of distribution facilities according to their location, type and supplying areas</caption><thead><tr><th rowspan="2">Distribution facilities</th><th rowspan="2">n</th><th colspan="4">Supplying areas</th><th colspan="4">Location</th></tr><tr><th>Ha Noi</th><th>Bac Giang</th><th>Hai Duong/ Quang Ninh</th><th>Non-study provinces</th><th>Ha Noi</th><th>Bac Giang</th><th>Hai Duong</th><th>Quang Ninh</th></tr></thead><tbody><tr><td>Type</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Retail market</td><td>16</td><td>6</td><td>7</td><td>7</td><td>4</td><td>4</td><td>4</td><td>4</td><td>4</td></tr><tr><td>Wholesale market</td><td>11</td><td>9</td><td>5</td><td>2</td><td>8</td><td>7</td><td>3</td><td>1</td><td>0</td></tr><tr><td>Slaughter point</td><td>19</td><td>8</td><td>7</td><td>8</td><td>5</td><td>5</td><td>5</td><td>5</td><td>4</td></tr><tr><td>Slaughterhouse</td><td>6</td><td>3</td><td>2</td><td>0</td><td>4</td><td>3</td><td>3</td><td>0</td><td>0</td></tr><tr><td>Location</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ha Noi</td><td>19</td><td>19</td><td>2</td><td>1</td><td>12</td><td></td><td></td><td></td><td></td></tr><tr><td>Bac Giang</td><td>15</td><td>1</td><td>14</td><td>0</td><td>4</td><td></td><td></td><td></td><td></td></tr><tr><td>Hai Duong</td><td>10</td><td>3</td><td>1</td><td>9</td><td>5</td><td></td><td></td><td></td><td></td></tr><tr><td>Quang Ninh</td><td>8</td><td>3</td><td>4</td><td>7</td><td>0</td><td></td><td></td><td></td><td></td></tr></tbody></table>

<table><caption>**Appendix 1 Table 2.** Details of AIV screening</caption><thead><tr><th rowspan="2">Gene</th><th colspan="3">H9N2</th><th rowspan="2">Total</th></tr><tr><th>Positive</th><th>Negative</th><th>Total</th></tr></thead><tbody><tr><td>M gene</td><td>Positive</td><td>195</td><td>16*</td><td>211</td></tr><tr><td></td><td>Negative</td><td>2</td><td>0</td><td>2</td></tr><tr><td></td><td>Total</td><td>197</td><td>16</td><td>213</td></tr></tbody></table>

<table><caption>**Appendix 1 Table 3.** Recruited sites and H9N2 prevalence. H9N2+ (%): number and proportion of sites with ≥1 positive chicken or proportion of positive chickens</caption><thead><tr><th rowspan="2">Site</th><th colspan="2">Sites</th><th colspan="2">All chickens</th><th colspan="2">Slow-growing</th><th colspan="2">Fast-growing</th></tr><tr><th>n</th><th>H9N2+ (%)</th><th>n</th><th>H9N2+ (%)</th><th>n</th><th>H9N2+ (%)</th><th>n</th><th>H9N2+ (%)</th></tr></thead><tbody><tr><td>Farms</td><td>50</td><td>5 (10%)</td><td>750</td><td>31 (4.1%)</td><td>750</td><td>31 (4.1%)</td><td>-</td><td>-</td></tr><tr><td>Distribution facilities</td><td>52</td><td>31 (59.6%)</td><td>932</td><td>168 (18.0%)</td><td>748</td><td>130 (17.4%)</td><td>184</td><td>38 (20.7%)</td></tr><tr><td>Retail market</td><td>16</td><td>12 (75.0%)</td><td>240</td><td>38 (15.8%)</td><td>240</td><td>38 (15.8%)</td><td>-</td><td>-</td></tr><tr><td>Wholesale market</td><td>11</td><td>4 (36.4%)</td><td>210</td><td>14 (6.7%)</td><td>165</td><td>6 (3.6%)</td><td>45</td><td>8 (17.8%)</td></tr><tr><td>Slaughter points</td><td>19</td><td>14 (73.7%)</td><td>363</td><td>106 (29.2%)</td><td>269</td><td>76 (28.3%)</td><td>94</td><td>30 (31.9%)</td></tr><tr><td>Slaughterhouse</td><td>6</td><td>1 (16.7%)</td><td>119</td><td>10 (8.4%)</td><td>74</td><td>10 (13.5%)</td><td>45</td><td>0 (0%)</td></tr></tbody></table>

<table><caption>**Appendix 1 Table 4.** Distribution facility models*</caption><thead><tr><th>Distribution facility type</th><th>Bird type</th><th>Location</th><th>Supplying area</th><th>Season</th><th>DIC</th><th>ΔDIC</th></tr></thead><tbody><tr><td></td><td></td><td>null model</td><td></td><td></td><td>220.4</td><td>20.2</td></tr><tr><td></td><td>C</td><td></td><td></td><td></td><td>222.1</td><td>21.9</td></tr><tr><td>A</td><td>C</td><td></td><td></td><td></td><td>221.5</td><td>21.3</td></tr><tr><td>A</td><td>C</td><td></td><td></td><td></td><td>223.3</td><td>23.1</td></tr><tr><td>B</td><td></td><td></td><td></td><td></td><td>215.8</td><td>15.6</td></tr><tr><td>B</td><td>C</td><td></td><td></td><td></td><td>217.2</td><td>17.0</td></tr><tr><td>B</td><td></td><td>D</td><td></td><td></td><td>205.5</td><td>5.3</td></tr><tr><td>B</td><td>C</td><td>D</td><td></td><td></td><td>207.8</td><td>7.6</td></tr><tr><td>B</td><td></td><td></td><td>E</td><td></td><td>200.2</td><td>0</td></tr><tr><td>B</td><td>C</td><td></td><td>E</td><td></td><td>202.1</td><td>1.9</td></tr><tr><td>B</td><td></td><td></td><td></td><td>F</td><td>215.7</td><td>15.5</td></tr><tr><td>B</td><td>C</td><td></td><td></td><td>F</td><td>217.6</td><td>17.4</td></tr></tbody></table>

<footnote>*One sample from a slow-growing broiler from a slaughter point in Quang Ninh was positive for H5N1.</footnote>

<footnote>*Best-fitting model in bold type. A- Market, slaughter facilities. B- Retail market, wholesale market, slaughter point, slaughterhouse. C- Slow-growing broiler, fast-growing broiler. D- Ha Noi, Bag Giang, Hai Duong/Quang Ninh (most Hai Duong/Quang Ninh sites were near their shared border). E- Ha Noi, Bag Giang, Hai Duong/Quang Ninh, Other provinces. F- High-risk season, low-risk season</footnote>
<table><caption>**Appendix 1 Table 5.** Model estimations. H9N2 distribution facility model posterior estimates</caption><thead><tr><th>Parameter</th><th>Posterior values</th><th>Odds Ratio (95% HDI)</th></tr></thead><tbody><tr><td><strong>Site-level</strong></td><td></td><td></td></tr><tr><td>Distribution facility type</td><td></td><td></td></tr><tr><td>Retail market</td><td>0.778 (0.559,0.967)</td><td></td></tr><tr><td>Wholesale market</td><td>0.481 (0.163,0.850)</td><td></td></tr><tr><td>Slaughter point</td><td>0.725 (0.527,0.898)</td><td></td></tr><tr><td>Slaughterhouse</td><td>0.233 (0.014,0.542)</td><td></td></tr><tr><td><strong>Bird-level</strong></td><td></td><td></td></tr><tr><td>Intercept</td><td>0.511 (-0.428,1.446)</td><td></td></tr><tr><td><strong>Distribution facility type</strong></td><td></td><td></td></tr><tr><td>Slaughter point</td><td>Reference</td><td>1</td></tr><tr><td>Retail market</td><td>-1.122 (-1.893,-0.362)</td><td>0.33 (0.12,0.62)</td></tr><tr><td>Wholesale market</td><td>-1.544 (-2.792,-0.38)</td><td>0.21 (0.03,0.56)</td></tr><tr><td>Slaughterhouse</td><td>-0.059 (-1.851,1.705)</td><td>0.94 (0.01,3.94)</td></tr><tr><td><strong>Supplying area</strong></td><td></td><td></td></tr><tr><td>Ha Noi</td><td>-1.661 (-2.546,-0.764)</td><td>0.19 (0.06,0.41)</td></tr><tr><td>Bac Giang</td><td>-0.006 (-0.876,0.867)</td><td>0.99 (0.3,2.09)</td></tr><tr><td>Hai Duong/Quang Ninh</td><td>-0.787 (-1.614,0.043)</td><td>0.46 (0.15,0.93)</td></tr><tr><td>Other provinces</td><td>0.460 (-0.332,1.237)</td><td>1.58 (0.58,3.13)</td></tr></tbody></table>

<table><caption>**Appendix 1 Table 6.** Summary of approximate distances in kilometers between the A(H9N2) positive farms in the spatiotemporal cluster</caption><thead><tr><th>Farm</th><th>522</th><th>531</th><th>550</th></tr></thead><tbody><tr><td>522</td><td>-</td><td>22km</td><td>4km</td></tr><tr><td>531</td><td>22km</td><td>-</td><td>19km</td></tr><tr><td>550</td><td>4km</td><td>19km</td><td>-</td></tr></tbody></table>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /><figcaption>**Appendix 1 Figure 1.** Traceplots for farm model.</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Appendix 1 Figure 2. Traceplots for best fitting distribution facility model.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Appendix 1 Figure 3.** Post-predictive checks for the best fitting distribution facility model. Distribution of the number of market (A) and slaughter (B) distribution facilities according to the number of birds that tested positive for H9N2 in the site. Simulated data represented in black; median number of sites (black dot), 95% HDI (black line) and empirical data from study (red cross). Proportion of birds that tested positive for H9N2 (C); overall, in each province, and in each site type; simulated median prevalence (black dot), 95% HDI (black line) and empirical data from study (red cross).</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**Appendix 1 Figure 4.** Density plots of marginal posterior distributions of the best fitting distribution facility model parameters.</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>**Appendix 1 Figure 5.** Time-scaled phylogenies of PB2 (A), PB1 (B), and PA (C) of sampled H9N2 virus genomes. Tips are labeled by the unique sampled site ID. Province, site type, and chicken type of each sequence are indicated by three heatmaps. Sequences from three farms in the spatiotemporal cluster are highlighted in red.</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>**Appendix 1 Figure 6.** Time-scaled phylogenies of NP (A), MP (B), and NS (C) of H9N2 virus genomes sampled from this study. Tips are labeled by the unique ID of each sampled site. Province, site type, and chicken type of each virus sequence are indicated by three heatmaps. Sites highlighted in red corresponds to virus sequences from three farms associated with spatiotemporal cluster.</figcaption></figure>