Detection of Hemagglutinin H5 Influenza A Virus RNA and Model of Potential Inputs in an Urban California Sewershed

Abstract

In 2024, highly pathogenic avian influenza A H5N1 caused outbreaks in wild birds, poultry, cows, and other mammals in the United States with 61 human cases also reported by the CDC. Detection of influenza A H5 RNA in wastewater has been previously reported in sewersheds in Texas and North Carolina with nearby impacted dairy herds following the emergence of H5N1 in dairy cows. Here, we conduct retrospective testing of total influenza A and H5 hemagglutinin genes in wastewater as well as present and apply new assays for detection of H1 and H3 genes across a respiratory virus season in an urban California sewershed from September 2023 to May 2024. Total influenza A, H1, and H3 were regularly detected, while H5 was first detected in March. We developed a model that uses Monte Carlo simulations and previously published parameters to estimate the numbers of infected people, poultry, wild birds, or liters of H5-contaminated milk required to result in measured H5 concentrations in wastewater. Our findings demonstrate that in this California sewershed, contaminated milk or infected poultry were the most likely sources of H5 to wastewater. We created a publicly available tool to apply the H5 input model in other sewersheds to estimate the required inputs.

Introduction

Approximately 3–11% of the population in the United States is infected with influenza virus each year, and Influenza A virus (IAV) is responsible for the majority of these infections. In recent years, wastewater monitoring of infectious diseases has emerged as a powerful tool for tracking trends in disease incidence in the community. Previous research has found that concentrations of total IAV genomic RNA in wastewater track closely with occurrence of infections in the contributing community. − IAV has subtypes that are classified by both hemagglutinin (HA) and neuraminidase (NA) proteins. The H1 and H3 subtypes are most common in humans and swine, while many subtypes, including H1, H3, H5, H7, H9, and H10, are common in avian populations. Given that levels of total IAV (measurements that include all H subtypes) in wastewater have been closely correlated with human disease and municipal wastewater primarily consists of anthropogenic inputs, the predominant source of IAV RNA in wastewater has thus far been considered to be human.

The highly pathogenic avian influenza (HPAI) A (H5N1) outbreak in birds began in the United States in February 2022 and has resulted in the deaths of millions of poultry and wild fowls. This outbreak in poultry has prompted concerns about increased spillover into humans and the possibility of future person-to-person transmission, as humans sporadically infected with H5N1 have experienced severe symptoms and high mortality in the past. Other animal influenza strains have jumped from animal populations to humans through mutations, adaptation, or reassortment events with human influenza, resulting in epidemics and pandemics. , This concern has grown as outbreaks of unknown illness in cattle in March 2024 were identified as infections caused by H5N1 later that month. Between March 1 and December 19, 2024, 865 infected dairy cow herds and 61 human cases were reported in 16 states. Human cases of H5N1 were reported mostly among those who worked in close proximity to dairy cows and poultry; human-to-human transmission has not been reported or suspected in any of the known cases. −

Beginning in March 2024 and concurrent with cattle outbreaks, we detected the H5 IAV subtype genomic RNA (hereafter, H5 RNA) in wastewater in multiple sites across the United States. Prior to the H5N1 outbreaks in cattle, contributions to wastewater from animals infected with H5N1 (such as poultry) were expected to be minimal. However, cows infected with H5N1 shed the virus in milk, and IAV RNA has been detected both in raw milk and in pasteurized milk available on store shelves. , Because of the food chain, a substantial amount of milk products enter sewers; it is estimated that 12% of milk available for sale is wasted at retailers and 20% by consumers after purchase. School lunches can also lead to milk waste; studies report that 45% of milk was wasted at kindergarten and prekindergarten lunches, and 13% by high school students. This wasted milk may be disposed of down the drain, entering sewer systems, and contributing detectable viral RNA to wastewater. Food industries are also often permitted to dispose of waste generated while processing dairy products in sewer systems. Contributions to wastewater from birds are less likely because of the lack of connection between wild bird habitats and domestic flocks to municipal sewer systems. However, wastewater sewer systems that accept stormflow (“combined sewers”) are less common but may receive fecal waste from wildfowl and other wild birds that mixes with runoff and enters sewer systems. Both poultry and wildfowl can shed IAV in their feces when infected. , Wastewater treatment plants with open-air settling tanks or that accept waste from industries that generate standing water may be susceptible to inputs of bird feces. Therefore, we conclude that any one of cow’s milk, poultry feces, wildfowl feces, or human contributions are the most likely sources of H5 in wastewater.

In this study, we present findings from retrospective testing of wastewater solids for total IAV and H1, H3, and H5 IAV subtype RNA from September 2023May 2024 in a publicly owned treatment work (POTW) in California. We also present findings from a model developed to estimate the theoretical contributions of humans, cow milk, wildfowl feces, and poultry feces to the wastewater system necessary to result in the observed H5 RNA concentrations. Our objectives were to (1) identify the timing of the first H5 detection in the sewershed during a period with circulating human influenza and (2) develop and implement a model of theoretical sources of H5 into the wastewater system to contextualize our findings.

Methods

H1 and H3 Assay Design

IAV H1 and H3 subtype genome sequences were downloaded from the National Center for Biotechnology Information (NCBI) in January 2023 (H1 genomes) and December 2022 (H3 genomes) and supplemented with additional newer sequences available from NCBI and GISAID in April 2024. Sequences were aligned, and primers and probes were designed to target the hemagglutinin (HA) gene using Primer3Plus. Parameters used in assay development (e.g., sequence length and GC content) are provided elsewhere. The primers and probes (Table S1) were found to be specific and sensitive to influenza A containing the H1 and H3 subtypes of the HA gene in silico using NCBI BLAST.

The H1 and H3 assays were tested in vitro against nucleic acids from a large collection of respiratory pathogens including different influenza subtypes (Table S2). Nucleic acids from these panels were extracted and purified as described below for wastewater solids samples and then used as template in droplet digital RT-PCR assays. The panels were run in a single well using the same ddPCR methods described below and elsewhere. ,

IAV M Gene and H5 Assays

The H5 assay used has been described in detail elsewhere, as has the M gene assay. See the Supporting Information for information about primers, probes, and positive control material. The influenza M gene assay detects all IAV subtypes and hereafter, measurements made using the M gene assay will be interpreted as “total IAV RNA”.

Retrospective Analysis of Samples

Biobanked nucleic-acid extracts obtained from wastewater solids samples collected between September 1, 2023, and May 13, 2024, from a POTW (Southeast San Francisco) were retrospectively analyzed for total IAV (M gene), H1, H3, and H5 (n = 110 samples). Nucleic acids were stored between 1 and 10 months at −80 °C before analysis. Samples consisted of grab samples of settled solids from the primary clarifier. Samples were collected by using sterile methods and stored at 4 °C prior to nucleic-acid extraction. The POTW is located in an urban area and serves 750,000 people, and services a geographic area with combined stormwater and sanitary sewer systems meaning that stormwater and urban dry weather runoff (generated via irrigation or car washing, for example) may enter the POTW.

Sample processing methods are described in detail elsewhere. − Briefly, nucleic acids were extracted from the solid fraction of each sample using the Chemagic Viral DNA/RNA 300 Kit H96 (PerkinElmer, Shelton, CT) followed by inhibition removal (Zymo OneStep PCR Inhibitor Removal Kit, Irvine, CA). Nucleic-acid extraction occurred immediately within 24 h of sample collection. Between 0.5 and 1g of the dewatered solids were dried at 110 °C for 19–24 h to determine the dry weight. Concentrations of total IAV (M gene), H1, H3, and H5 RNA were measured in multiplex using droplet digital one-step RT-PCR (dd-RT-PCR) run on an AutoDG Automated Droplet Generator (Bio-Rad, Hercules, CA), Mastercycler Pro (Eppendorf, Enfield, CT) thermocycler, and a QX600 Droplet Reader (Bio-Rad). Ten ddPCR replicates were run for each sample. Only wells with over 10,000 droplets were included; all wells met this criterion. Extraction and PCR positive and negative controls were run on each 96-well plate. Positive controls consisted of Twist synthetic controls (M gene, H1, and H3) and custom gene blocks (H5; IDT); see the SI for full details. Negative controls consisted of no template controls (NTC) containing nuclease-free water. Bovine coronavirus (BCoV) was spiked into samples and measured as an internal control, and pepper mild mottle virus (PMMoV) was measured by using ddPCR as an endogenous internal control. We used QuantaSoft Analysis Pro software (Bio-Rad) to threshold droplets, and a sample had to have 3 or more positive droplets to be considered positive. Three positive droplets correspond to a concentration between 500 and 1000 copies/g. Values were converted to gene copies/dry grams using dimensional analysis. See the SI for the reaction chemistry and cycling parameters.

Model of Theoretical Inputs

We developed a model to estimate the H5 RNA inputs into the system that would be required to obtain the measured H5 RNA concentrations in wastewater solids. We considered inputs from humans, cow milk, poultry feces, and waterfowl feces as each input type had a plausible mechanism for entering wastewater. Using this model, we generated separate estimated inputs for each contribution, as though this was the sole contributor of H5 RNA into the system. We note that these inputs may enter wastewater in a number of ways and from multiple sources, including from household uses, businesses, industrial discharges, and, in some cases, environmental sources (Figure ).

1.

Conceptual image of sources of H5N1 in the POTW.

Mass Balance

We assume that the concentrations measured in wastewater relate to inputs from humans, birds, and cow’s milk according to the following equation

$$F_{\mathrm{wwtp},\mathrm{d}}=F_{\mathrm{human},\mathrm{d}}+F_{\mathrm{poultry},\mathrm{d}}+F_{\mathrm{bird},\mathrm{d}}+F_{\mathrm{milk},\mathrm{d}}$$ 1

where F _wwtp,d indicates the daily flux of H5 RNA (gene copies/day) through the POTW, and F _human,d, F _poultry,d, F _bird,d, and F _milk,d indicate the daily contribution (gene copies/day) of humans, poultry, wild birds, and milk, respectively, to the POTW.

Calculations of Daily H5 Wastewater Fluxes, F _wwtp,d

We assume that both the liquid and solid portions of wastewater contain H5 RNA when detected in solids and calculate the total H5 RNA content across both phases. The concentration in liquids is calculated using the Freundlich isotherm

$$\log C_{\mathrm{s}}=\log K_{\mathrm{f}}+n\log C_{\mathrm{l}}$$ 2

where C _l indicates the H5 RNA concentration in liquids (gene copies/mL), C _s indicates the H5 RNA concentration in solids (gene copies/dry gram), and K _f indicates the Freundlich partitioning coefficient (mL/dry gram).

Total daily H5 RNA flux through the POTW (gene copies/day) is calculated as the sum of H5 RNA in solids (gene copies/day) and liquids (gene copies/day). We obtained the daily flow rate (in millions of gallons per day) and total suspended solids (TSS; mg/L) from the POTW for each day. The total daily flux of solids through the POTW is calculated as

$$M_{\mathrm{s}}=\frac{F_{\mathrm{L}\mathrm{\_}\mathrm{day}}\times \mathrm{TSS}}{{10}^3}$$ 3

where F _{L_day} is the daily flow rate in terms of L/day, TSS is the total suspended solids (mg/L), and the 10³ factor is to convert from mg/day to g/day. The daily flux of H5 RNA in the solids (gene copies/day) is calculated by

$${\mathrm{H}5}_{\mathrm{s}}=M_{\mathrm{s}}\times C_{\mathrm{s}}$$ 4

The daily flux of H5 RNA in the liquids (gene copies/day) is calculated by

$${\mathrm{H}5}_{\mathrm{l}}=F_{\mathrm{L}\mathrm{\_}\mathrm{day}}\times C_{\mathrm{l}}$$ 5

The total daily flux of H5 RNA through the POTW (gene copies/day) is calculated by

$$F_{\mathrm{wwtp},\mathrm{d}}={\mathrm{H}5}_{\mathrm{s}}+{\mathrm{H}5}_{\mathrm{l}}$$ 6

Human Inputs

We consider human contributions to the POTW from saliva, sputum, and feces, such that

$$F_{\mathrm{human},\mathrm{d}}=N_{\mathrm{human},\mathrm{d}}\times (C_{\mathrm{f}}\times V_{\mathrm{f}}\times {\mathrm{FS}}_{\mathrm{f}}+C_{\mathrm{sp}}\times V_{\mathrm{sp}}\times {\mathrm{FS}}_{\mathrm{sp}}+C_{\mathrm{sal}}\times V_{\mathrm{sal}}\times {\mathrm{FS}}_{\mathrm{sal}})$$ 7

where N indicates the number of infected people contributing to wastewater, C indicates concentration in that excretion type (gene copies per mL or per g), V indicates volume of that excretion type entering the wastewater system per day per person (mL or g), FS indicates the fraction of infected persons shedding influenza by that route (unitless), f refers to feces, sp refers to sputum, and sal refers to saliva.

Assuming no contribution to the POTW from birds or milk, we can simplify eq to

$$F_{\mathrm{wwtp},\mathrm{d}}=F_{\mathrm{human},\mathrm{d}}$$ 8

and, plugging in eq

$$F_{\mathrm{wwtp},\mathrm{d}}=N_{\mathrm{human},\mathrm{d}}\times (C_{\mathrm{f}}\times V_{\mathrm{f}}\times {\mathrm{FS}}_{\mathrm{f}}+C_{\mathrm{sp}}\times V_{\mathrm{sp}}\times {\mathrm{FS}}_{\mathrm{sp}}+C_{\mathrm{sal}}\times V_{\mathrm{sal}}\times {\mathrm{FS}}_{\mathrm{sal}})$$ 9

Rearranging to solve for the number of infected individuals (N)­

$$N_{\mathrm{human},\mathrm{d}}=\frac{F_{\mathrm{wwtp},\mathrm{d}}}{C_{\mathrm{f}}\times V_{\mathrm{f}}\times {\mathrm{FS}}_{\mathrm{f}}+C_{\mathrm{sp}}\times V_{\mathrm{sp}}\times {\mathrm{FS}}_{\mathrm{sp}}+C_{\mathrm{sal}}\times V_{\mathrm{sal}}\times {\mathrm{FS}}_{\mathrm{sal}}}$$ 10

Poultry and Duck Inputs

We separately consider inputs from poultry and ducks to the POTW through feces

$$F_{\mathrm{poultry},\mathrm{d}}=N_{\mathrm{poultry},\mathrm{d}}\times (C_{\mathrm{CS}}\times {\mathrm{CF}}_{\mathrm{SG}}\times V_{\mathrm{f}})$$ 11

where C _CS indicates the concentration of influenza reported in cloacal swabs collected from domestic poultry or ducks (gene copies/swab), CF_SG indicates a conversion factor from concentration/swab to concentration/g (swab/gram), and V _f indicates the volume of feces produced by poultry or ducks per day (grams).

Assuming no contribution to the POTW from humans or milk, we can simplify eq to

$$F_{\mathrm{wwtp},\mathrm{d}}=F_{\mathrm{poultry},\mathrm{d}}$$ 12

and, plugging in eq

$$F_{\mathrm{wwtp},\mathrm{d}}=N_{\mathrm{poultry},\mathrm{d}}\times (C_{\mathrm{CS}}\times {\mathrm{CF}}_{\mathrm{SG}}\times V_{\mathrm{f}})$$ 13

Rearranging to solve for the number of infected birds (N)­

$$N_{\mathrm{poultry},\mathrm{d}}=\frac{F_{\mathrm{wwtp},\mathrm{d}}}{C_{\mathrm{CS}}\times {\mathrm{CF}}_{\mathrm{SG}}\times V_{\mathrm{f}}}$$ 14

Wild Bird Inputs

We consider inputs from wild birds to the POTW through feces

$$F_{\mathrm{bird},\mathrm{d}}=N_{\mathrm{bird},\mathrm{d}}\times (C_{\mathrm{CS}}\times {\mathrm{CF}}_{\mathrm{SG}}\times V_{\mathrm{f}})$$ 15

where C _CS indicates the concentration of influenza reported in cloacal swabs collected from domestic poultry (gene copies/swab), CF_SG indicates a conversion factor from concentration/swab to concentration/g (swab/gram), and V _f indicates the volume of feces produced by birds per day (grams).

Assuming no contribution to the POTW from humans or milk, we can simplify eq to

$$F_{\mathrm{wwtp},\mathrm{d}}=F_{\mathrm{bird},\mathrm{d}}$$ 16

and, plugging in eq

$$F_{\mathrm{wwtp},\mathrm{d}}=N_{\mathrm{bird},\mathrm{d}}\times (C_{\mathrm{CS}}\times {\mathrm{CF}}_{\mathrm{SG}}\times V_{\mathrm{f}})$$ 17

Rearranging to solve for the number of infected birds (N)­

$$N_{\mathrm{bird},\mathrm{d}}=\frac{F_{\mathrm{wwtp},\mathrm{d}}}{C_{\mathrm{CS}}\times {\mathrm{CF}}_{\mathrm{SG}}\times V_{\mathrm{f}}}$$ 18

Cow Milk Inputs

We estimate the daily flux of H5 RNA from cow milk (gene copies/day) by

$$F_{\mathrm{milk},\mathrm{d}}=C_{\mathrm{MILK}}\times V_{\mathrm{MILK}}\times {\mathrm{CF}}_{\mathrm{milk}}$$ 19

where C _MILK refers to the H5 concentration in cow’s milk, V _MILK indicates the volume of milk entering the wastewater system per day, and CF_milk is a conversion factor from the EID50/mL units; C _MILK is reported in gene copies/mL units.

Assuming no contribution to the POTW from humans or birds, we can simplify eq to

$$F_{\mathrm{wwtp},\mathrm{d}}=F_{\mathrm{milk},\mathrm{d}}$$ 20

and, plugging in eq

$$F_{\mathrm{wwtp},\mathrm{d}}=C_{\mathrm{MILK}}\times V_{\mathrm{MILK}}\times {\mathrm{CF}}_{\mathrm{milk}}$$ 21

Rearranging to solve for the daily volume of infected milk entering the POTW

$$V_{\mathrm{MILK}}=\frac{F_{\mathrm{wwtp},\mathrm{d}}}{C_{\mathrm{MILK}}\times {\mathrm{CF}}_{\mathrm{milk}}}$$ 22

Data Sources

Using previously published systematic reviews and parameters on daily human waste input into the system, we identified data on human IAV shedding into wastewater per day per infected individual (Table ). , For cow milk, we identified a distribution of H5N1 RNA per gallon of pasteurized milk using published reports on H5N1 EID50 content in pasteurized cow milk , and a conversion from EID50 to RNA gene copies in milk. Distributions of daily H5 RNA shedding in the feces of poultry, ducks, and blue-winged teal were separately estimated from studies reporting IAV shedding in each bird type (Table S4). , Blue-winged teal were used as the model species for waterfowl, per Humphreys et al., and domestic ducks were included to represent larger species of waterfowl. Raw data for empirical distributions are provided in the Stanford Digital Repository (https://purl.stanford.edu/ks454rq5640).

1. Model Parameters for Human Wastewater Inputs.

category	parameter	unit	distribution	parameters	references
Humans
Human Wastewater Inputs
sputum	mL sputum produced to sewer per person	mL/day	uniform	min = 0.1, max = 1
saliva	tooth brushing events/day	tooth brushing events/day	discrete	[(0,0.02),(1,0.29),(2,0.55),(3+,0.14)]
saliva	mL saliva to sewer per tooth brushing event	mL/tooth brushing event	point	1
stool	stool production per day per person	log g/day	truncated log-normal	mean log = 4.763, sd log = 0.471, min = 0, max = 520
urine	urine production per day per person	L/day	γ	α (shape) = 5.315, β(scale) = 0.25, and a (positive) offset Δ of 0.5
Human Shedding
sputum	gene copies of influenza in sputum	gc/mL	empirical
saliva	gene copies of influenza in saliva	gc/mL	empirical		assume equivalent to sputum shedding, per findings by Crank et al. for SARS-CoV-2
stool	gene copies of influenza in stool	gc/g	empirical		−
urine	gene copies of influenza in urine	gc/mL	point	0	assumption
Human Fractional Shedding
sputum	fraction of infected people shedding influenza in sputum	unitless	uniform	min = 0.73, max = 1	calculated from data in Lowry et al.
saliva	fraction of infected people shedding influenza in saliva	unitless	uniform	min = 0.85, max = 1	calculated from data in Lowry et al.
stool	fraction of infected people shedding influenza in stool	unitless	truncated normal	mean = 0.40, sd = 0.21; min = 0, max = 1	calculated from data in Lowry et al.
urine	fraction of infected people shedding influenza in urine	unitless	uniform	min = 0.05, max = 1	assumption based on Lowry et al.
Cow Milk
milk	H5 concentration in commercial (pasteurized) milk	log 10 EID50/mL	truncated log-normal	mean = 5.93, sd = 2.63, min = 0, max = 2.5 × 105	calculated from refs ,
milk	conversion from EID50 to gc	gc/EID50	uniform	min = 25, max = 125
milk	conversion from mL to gallons	mL/gallon	point	3785.41253	constant
Poultry, Ducks, and Waterfowl
poultry	H5 concentration, cloacal swabs	log10 gc/swab	log 10 normal	mean = 4.6, sd = 1.6	extracted from Figure 3 for chickens
blue-winged teal	H5 concentration, cloacal swabs	log10 gc/swab	log 10 normal	mean = 3.68, sd = 1.0
ducks	H5 concentration, cloacal swabs	log10 gc/swab	log 10 normal	mean = 3.84, sd = 1.56	extracted from Figure 3 for ducks
poultry, blue-winged teal, and ducks	mass feces per cloacal swab	g/swab	uniform	min = 0.05, max = 0.2	assumption
poultry, blue-winged teal, and ducks	conversion factor-swab to g	swab/g	point	1/mass_feces_cloacal_swab	Conversion factor
poultry	daily amount of bird poop/bird, g	g/day	uniform	min = 130, max = 184	assumption from values in Tanczuk et al.
blue-winged teal	daily amount of bird poop/bird, g	g/day	uniform	min = 5.7, max = 8.7	Calculated from
ducks	daily amount of bird poop/bird, g	g/day	uniform	min = 279, max = 393
poultry, blue-winged teal, and ducks	fractional shedding	unitless	point	1	assumption

To estimate the total daily H5 RNA for the POTW, we calculated total solids and total liquids at the POTW per day using the flow rate and total suspended solids (TSS) reported by the POTW. We assumed homogeneity in both solids and liquids, meaning that the quantity of H5 RNA measured in the solids sample is the same throughout all solids passing through the system. The H5 RNA concentration in liquids was estimated from the solids using the partitioning coefficient of IAV RNA in wastewater and the adsorption intensity (Table ). We summed the total H5 RNA in solids and the total H5 RNA in liquids to calculate the total H5 RNA at the POTW per day.

2. Wastewater Model Input Parameters.

category	parameter	unit	distribution	parameters	references
wastewater	solid–liquid partitioning coefficient	mL/g	empirical
wastewater	adsorption intensity	unitless	uniform	min = 0.7, max = 1.9

Raw data were fit to distributions using the fitdistrplus package in R. For each parameter, we first used the descdist function to create a Cullen-Fraser graph, which plots the square of skewness against kurtosis. The value from the observed data is plotted, as are the locations of theoretical distributions. Whichever theoretical distribution the observation is plotted nearest is selected as the distribution type, with the β distribution being the lowest priority (meaning if the observation is near normal, uniform, exponential, or logistic, while still being located within the β region, the other non-beta distribution is selected). After selecting a distribution type, data were fitted to the distribution using the fitdist function, and distribution parameters were extracted.

Model Approach

In the models, we assumed that the measured H5 RNA in wastewater originated entirely from one of the four input types and then independently calculated (1) the number of infected humans in the sewershed, (2) the number of liters of milk input into the sewer, (3) the number of poultry contributing feces to the sewer, and (4) the number of waterfowl contributing feces to the sewer that would be required to result in the measured H5 concentration. By looking at each source independently, we can estimate an upper bound on the number of infected individuals or IAV-impacted liters of milk that could contribute to the system. To assess variability in our parameter estimates, we conducted Monte Carlo simulations using n = 10,000 iterations. For each iteration, we randomly selected a value from each parameter’s distribution and conducted the calculations. For the empirical distributions, data were randomly drawn. Presented throughout are the median and interquartile range (25th–75th percentile) from these simulations. Due to the limited data available for our assumptions, we are reporting order of magnitude results.

Sensitivity Analysis

We use a previously published method to conduct a sensitivity analysis to determine which parameters the model is most sensitive to. , The model is run with the parameter first set to its 25th percentile (p25) and then set to the 75th percentile (p75) while all other parameters are set to their median value. We calculate the ratio between the model outputs for p75/p25. A p75:p25 ratio of 1 indicates that the model is not sensitive to the parameter, while a ratio above or below indicates that the model is sensitive to that parameter. For ratios below 1, we calculated the inverse (1/p75:p25) so that all ratios are presented on a comparable scale.

Shiny Application

We developed an application using the R Shiny package to make the model available for public use. Users can input the H5 wastewater concentration in solids (gene copies/dry g), the flow rate (in millions of gallons [MGD] per day), and total suspended solids (TSS; mg/L) at the treatment plant. The model will conduct n = 50,000 iterations and provide estimates of the required inputs. The Shiny app is available at https://abharv52.shinyapps.io/h5_input_estimates/.

Identifying Food and/or Agricultural Industries within the Sewershed

We used multiple online sources to search for potential industrial contributors of dairy products to sewershed wastewater. We searched Google Maps for dairy, cheese, or butter processing facilities and cross-checked locations with the sewershed boundaries to see whether they fell within the sewershed. The boundary shapefile was provided by the POTW. We also searched the Enforcement and Compliance History Online (ECHO) database for facilities with Clean Water Act permits with a Standardized Industry Code (SIC) indicating dairy processing (Table S5).

Results

H1 and H3 Assay Performance and QA/QC

Both in silico and in vitro testing indicated that the H1 and H3 assays are 100% specific. In vitro tests returned nondetects for all nontarget pathogens, including other influenza subtypes.

The Environmental Microbiology Minimal Information (EMMI) and McClary-Gutierrez et al. guidelines were used for reporting results (both checklists available at https://purl.stanford.edu/ks454rq5640). Positive and negative controls performed as expected. Nucleic-acid extraction efficiency in samples exceeded the quality control threshold of 0.1 for bovine coronavirus (median = 1.8, interquartile range (IQR) = 1.2–2.4); recoveries greater than one are likely a result of errors associated with the measurement of bovine coronavirus seeded into the sample. PMMoV was detected at high concentrations in all samples (median of 6.1 × 10⁸, IQR = 4.8 × 10⁸–7.9 × 10⁸ cp/g) providing further support for efficient nucleic-acid extraction.

H5 RNA Detection in Wastewater Samples

H5 RNA was first detected at the POTW on March 18, 2024 (Figure ). Between March 18 and May 13 (the final sample of this study), 13 of 25 (52%) samples tested positive for H5 RNA. The median concentration detected was 2410 gc/dry g, with the peak concentration detected on May 3 (19,000 gc/dry g). H5 RNA detections were not related to rainfall patterns in the region (Figure S1).

2.

Concentrations of influenza A M gene (all IAV), H5, H1, and H3 RNA in wastewater solids. Concentrations measured are indicated by filled circles, with the 68% confidence interval represented by bars. Samples with no detection are indicated by open circles. The lines represent the 5-adjacent sample trimmed average. Line colors are visual aid only.

Both total IAV (M gene) and H1 RNA were regularly detected throughout the sampling period, and concentrations of both peaked in late December 2023 (Figure ). H3 RNA was regularly detected from December 2023 onward. H1 and H3 RNA concentrations remained low during H5 RNA detections from March through May. Of clinical influenza cases reported in CA during the 2023–2024 season, over 70% of cases were H1N1 (Figure S2).

Modeled Sources of H5 RNA

We calculated the total gene copies of H5 theoretically contributed to wastewater per infected human, 1 L of milk, and daily fecal production in poultry and wild birds (Table ). The estimated required inputs per source varied with the measured H5 RNA concentrations (Figure ). Overall, the lower bound (25th percentile) of contributions required to result in the median measured H5 RNA concentration was 10³ liters of milk, 10⁴ infected humans, 10³ infected poultry, 10³ infected ducks, or 10⁵ infected blue-winged teal.

3. Median Gene Copies of H5 RNA Contributed to Wastewater Per Day Per Infected Individual (Person, Poultry, Waterfowl) or Per Liter (IAV RNA Containing Milk).

	percentile
source	25	50 (median)	75
person	2 × 106	8 × 106	3 × 107
liters of milk	4 × 106	3 × 107	1 × 108
poultry	4 × 106	5 × 107	6 × 108
ducks	2 × 106	2 × 107	2 × 108
blue-winged teal	9 × 104	3 × 105	1 × 106

3.

Median and IQR (25th–75th quantile) of number of infected individuals required (humans, poultry, waterfowl) or liters of milk required to result in the lowest nonzero, median, and maximum H5 concentration measured at the POTW.

The peak H5 RNA concentration was detected on May 3, 2024; for this concentration (19,000 gc/dry g), the lower bound (25th percentile) required contributions were 10⁴ liters of milk, 10⁵ infected humans, 10³ infected poultry, 10⁴ infected ducks, or 10⁶ infected blue-winged teal.

When considering the extreme lower bound of the 10th percentile, the required contributions for the median H5 concentration were 10² liters of milk, 10³ infected humans, 10² infected poultry, 10² infected ducks, or 10⁵ infected blue-winged teal (Table S4).

Sensitivity Analysis

The H5 input model is very sensitive to the concentrations of IAV in poultry and waterfowl cloacal swabs, the concentration of influenza RNA in cow milk, and the concentration of influenza in human saliva (Figure ).

4.

Sensitivity analysis results. Presented are the ratios of model output between the 75th and 25th percentiles for each parameter, while all other parameters are set to their median value.

Possible Sources of Animal Inputs into the Wastewater System

We identified two dairy processing facilities in the sewershed: a cheese-making business and a butter creamery. We were not able to determine the volume of waste output from these businesses or whether their waste entered the sewer system. We expect that POTW staff have knowledge of discharge from these facilities, but this information is not public. Given that an estimated 20% of milk is wasted in residential settings, an estimated daily milk consumption per capita of 118 mL, and a sewershed population of 750,000, we estimate that approximately 22,000 L of milk are wasted per day in households in the sewershed. This is a conservative estimate, not accounting for waste in pasteurization, dairy products, food service, or at retail stores (of which an estimated 15% is wasted).

We also located one live bird market in the sewershed, where poultry are kept alive and where poultry feces enter the sewershed via drains in the establishment. The market operates on select dates, and birds are typically housed at the market for a maximum of 24 h before being sold; thousands of birds can be present at any one time.

Discussion

We first detected H5 RNA in San Francisco wastewater in mid-March 2024 after H5N1 outbreaks in cows had been identified in the United States, but before any outbreaks had been reported in California. Samples from September 2023 to mid-March 2024 were all nondetect for H5 RNA, despite regular detection of the influenza A M gene and known outbreaks of H5N1 in domestic poultry and wild birds in the region. The timing of the initial H5 RNA detections generally aligned with detections of H5 RNA in wastewater from Amarillo, TX (with detections late February to late April in the South plant and detections from mid-March to late April in the North plant) and Dallas, TX (detections mid-March to mid-April). However, while dairy cow herds were identified with H5N1 illness in Texas during this time, none were identified in California until late August 2024. High concentrations of H5 RNA were detected in wastewater from dairy industries discharging to the wastewater system in Amarillo, TX, while no major dairy operations of similar scale were identified in the San Francisco sewershed. H5N1 outbreaks in poultry flocks were reported in San Francisco (May 9, 2024) within the time period of wastewater H5 RNA detections. As such, the source of H5 RNA in wastewater in San Francisco is unclear based on circumstantial evidence, and we implemented a modeling approach to determine the feasibility of different H5 influenza sources to the sewer system producing these results. We found the model helpful to estimate the order of magnitude contributions that may be required from different pathways; however, data on shedding and other assumptions mean that the ability of the model to make precise estimates is limited.

Waterfowl

Based on the model results, blue-winged teal and similar small waterfowl species are unlikely to be a major source of H5 RNA to wastewater from the SF sewershed, while domestic ducks could be a feasible source in some situations. Feces from at least 10 000 blue-winged teal would be required to result in the minimum H5 RNA concentration measured, and there is unlikely to be a feasible way for the required mass of bird feces to enter the system despite it being a combined system in which some contribution is likely. On the other hand, feces from a minimum of 100 domestic ducks would be required to result in the minimum H5 concentration measured and 10,000 for the maximum H5 concentration detected. For lower H5 concentrations, domestic duck feces may be a feasible source in the system when there is a route for feces to enter wastewater.

This analysis was limited by a lack of data on wild bird fecal shedding of influenza, which we find that the model is extremely sensitive to. In California in 2024, waterfowl such as geese as well as owls, gull, falcons, and other types of wild birds have all tested positive for H5N1. Our shedding data was based on a study in blue-winged teals, which are considered representative of waterfowl, and domestic ducks. Influenza shedding in other types of birds with confirmed H5N1 in California is sparse. It is possible that other species of wildfowl could shed greater quantities of IAV in feces or produce much greater quantities of feces. However, the mechanisms through which wild bird feces enter the wastewater system are limited, and the model assumes that all feces produced are entering the system. Stormwater or urban runoff entering the combined system could wash bird feces into the system, yet there were no precipitation events recorded in San Francisco during the period of H5 RNA detections. Bird feces could enter the system through bodies of standing water that drain to the system, yet none were identified within the sewershed.

Poultry

Poultry is a feasible contributor of H5 to the SF sewer system, especially given the live bird market located within the sewershed where chicken feces can be washed into the sanitary sewer system. Notably, poultry at the live bird market infected with H5N1 were identified on May 9, 2024, during the study period and coinciding with an H5 RNA wastewater detection. The USDA describes that the outbreak involved 700 birds; this number is within the IQR of the modeled number of poultry required for both the minimum and median H5 RNA concentrations measured in wastewater. Based on the author’s observation, we estimate that the bird market may house as many as 3000 birds at one time, which is within the lower IQR (25th percentile) for the number of infected poultry required to result in the maximum H5 concentration measured. However, there were additional H5 detections after the May 2024 outbreak, and it is unlikely that such a large number of H5N1-infected birds could go undetected. Outbreaks of highly pathogenic avian influenza (HPAI), which includes H5N1, result in severe morbidity and mortality in affected flocks. An early sign of HPAI is often unexpected chicken deaths, and common symptoms in chickens are severe and would be difficult to miss. On Dutch poultry farms, the time between virus introduction and final mortality within individual chicken flocks ranged from 5 to 12 days, signifying rapid spread through flocks. We saw sustained detection of H5 RNA in wastewater across 5 weeks in the POTW, which would require that chickens at the live bird market be consistently infected with H5N1 during this time period if the market were the sole or primary H5 RNA wastewater source.

We found that the poultry model is very sensitive to poultry fecal shedding. Our model uses fecal shedding estimates for HPAI from a meta-analysis that incorporates data from 71 studies, including 25 studies specific to H5N1. The presentation of H5N1 in poultry in the U.S. since the beginning of the outbreak in 2022 has been similar to H5N1 outbreaks in poultry in other regions; as such, we feel that we are using the best available estimates of poultry fecal shedding.

Milk

We find that milk is feasible as a primary or sole H5 RNA source to the POTW, but only if the milk supply is widely contaminated. Pasteurization of milk inactivates IAV, but does not reduce the IAV RNA concentration in milk which is still detectable by PCR. − Residential milk waste could drive H5 RNA detections; even for the maximum H5 RNA wastewater concentration, the lower bound model output (25th percentile) requires 10,000 L of contaminated milk to enter the sewer system. This is within our conservative estimate of the amount of milk wasted residentially each day in the sewershed (22,000 L) not including the contribution of small dairies, retailers, and food service, and so it is possible that dumping of contaminated milk could result in the detected H5 RNA if there was widespread contamination of milk at retailers within SF.

This analysis was limited by the availability of data on the H5 and IAV concentrations in milk. No H5 or IAV containing milk was reported in milk processed in California during the time of this study, , although testing was limited (Tarbuck et al.: n = 3, Suarez et al., n = 6), and no infected dairy cows were reported in California during the time period of this study. However, it is possible that contaminated milk may enter the supply chain in San Francisco through either unidentified local cattle outbreaks or milk processed in other locations with H5N1 outbreaks in dairy cattle. The model is sensitive to the H5 concentration in milk, and thus, our input estimates would be affected by an over- or underestimation of the H5 concentration in milk.

Humans

Infected humans are unlikely to be a major contributor of H5 RNA to San Francisco wastewater. As of December 19, 2024, only 61 people in the United States have been identified with H5N1 infections, and these cases were mostly in people who worked closely with infected cows or poultry. Human-to-human transmission of H5N1 is not suspected at this time. While it is possible that asymptomatic or undiagnosed cases exist and the true number of infections is higher, there is no evidence to support the likelihood of widespread infection in humans at this timeespecially 10³ cases as the model estimates would be required to produce the minimum H5 concentration. Note that while we find that humans are unlikely to be the major source of H5 RNA to wastewater, we cannot rule out the presence of human cases. Our estimates provide the range of people, birds, or milk required to result in the H5 concentrations if just that source is contributing to the wastewater; it is possible for multiple of these sources to be responsible for the H5 in wastewater, at numbers smaller than our model outputs.

Our estimates of the required H5 human cases are constrained by available human IAV shedding data and do not necessarily align with previous observations of influenza A in wastewater during outbreaks in humans. The shedding data are based on human shedding of influenza A overall (no subtyping conducted), H1N1, H3N2, or H7N9, and data on H5N1 shedding in humans are not available. No information is available on human IAV shedding of any subtype in urine. Recent H5N1 infections have presented differently than seasonal influenza, , and shedding profiles of H5N1 may differ from those of other influenza types. We also noted that our estimate that 10³ to 10⁴ infected humans would be required to result in the minimum H5 concentration observed is 3–4 orders of magnitude larger than the number of infected individuals that were empirically observed to produce a similar concentration of total IAV in Ann Arbor, Michigan and at Stanford University, as determined through case reporting and in depth outbreak investigation. Future work is needed to better quantify human shedding of influenza in wastewater-relevant excretions.

Research is also needed into the possibility of human dietary shedding of H5 following the consumption of H5N1-containing dairy products. Other single-stranded RNA viruses, such as PMMoV, brown rugose tomato virus, and porcine circoviruses, have been detected in human stool following consumption of foods containing these viruses. − If H5 IAV present in milk or other dairy products is able to be shed in human stool, then uninfected humans who consume dairy products could contribute to H5 wastewater detections.

Limitations

We note that a major limitation of the study is the uncertainty in the data underlying many parameters, especially because the model was found to be sensitive to several of these parameters related to shedding. These shedding parameters are particularly influential in the model and, in many cases, are poorly understood. Concerns about this limitation are exacerbated by the observation that modeled estimates for human infections are substantially higher than would be expected based on observations from previous influenza A outbreaks of other subtypes. Despite these limitations, we feel that the model provides a helpful framework for discussing the order of magnitude estimated contributions from different sources to wastewater. More data on shedding in animals, and wild birds in particular, and humans will continue to improve estimates in the future.

Another limitation of this study is that inputs from humans, poultry, ducks, blue-winged teal, and milk were estimated separately. Multiple sources could contribute to H5 RNA wastewater detections, yet there is no information available to constrain the fraction of input that may come from each source; thus, each source was modeled separately. If multiple sources contribute H5 to the wastewater system, the number of required infected individuals or liters of milk could be lower than the lower bounds estimated by our models. Our H5 assay will detect all IAV in the H5 subtype, and this could include strains other than the currently circulating H5N1 (e.g., H5N8); however, no other H5 strains are currently expected to be circulating in wastewater-relevant species. It should also be noted that the IAV genome, particularly the HA gene, has a high rate of mutation. Although the H1, H3, and H5 assays used herein are highly sensitive and specific for the dominant IAV H1, H3, and H5 subtypes circulating at the time of the study, they may not be highly sensitive and specific in different time periods during which different subtypes are in circulation. For example, we confirmed that the H1 assay is no longer sensitive for the H1N1 clade circulating in the 2024–2025 flu season.

The model developed could be applied to other sites with H5 detections in wastewater to help constrain potential sources, and we developed a Shiny app tool to allow the model to be easily deployed at other sites. For other sites using the model, however, the feasibility and appropriateness of each pathway included in the model would need to be determined based on the specifics of the wastewater system.

In this study, we show that H5 was detected in an urban watershed months before H5N1 cases in California dairy cattle were reported. Given the lack of dairy industry in the sewershed or surrounding area, the source of H5 RNA in the wastewater system was unclear. Here, we employ modeling to estimate the theoretical H5 contributions from infected humans, poultry, and wildfowl and from H5-contaminated milk. We demonstrate that humans and waterfowl are unlikely to be major contributors of H5 to the system, while poultry and milk are both feasible sources of H5 in this system.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c14792.

• Additional details on ddPCR methods, modeling approach and parameters, and additional results (PDF)

Paulos, A. P.; Hilton, S. P.; Shelden, B.; Duong, D.; Boehm, A. B.; Wolfe, M. K. Detection of Hemagglutinin H5 Influenza A Virus RNA and Model of Potential Inputs in an Urban California Sewershed. medRxiv January1, 2025, p 2024.12.31.24319823. https://doi.org/10.1101/2024.12.31.24319823.

The authors declare the following competing financial interest(s): BS and DD are employees of Verily Life Sciences, LLC.