Economic effects of highly pathogenic avian influenza

ABSTRACT

This study aimed to characterize the highly pathogenic avian influenza (HPAI) hemagglutinin type 5 and neuraminidase type 1 (H5N1) clade 2.3.4.4b outbreak in dairy cattle and to estimate the effect of the outbreak on health, productivity, and economics at the herd and individual levels for 130 d from the outbreak. Herd records from a Michigan dairy farm, confirmed as affected based on PCR testing in milk, were used for this cohort study. Records included daily bulk tank information, herd management and feed intake data, and temperature alerts generated from cows’ intraruminal automated sensor devices during the year of the outbreak and the previous year. Health indicators included fever (used to determine the cumulative incidence of HPAI H5N1–affected cows and out- break length), culling, death, SCC, and DMI. Productivity was estimated based on milk yield and composition. The outbreak and postoutbreak periods were compared with the same periods of the previous year using join- point segmented regression analysis. Analyses included 486 daily bulk tank observations and 13,542 fever alerts from 437 Holstein dairy cows. Based on these outcomes, we estimated the economic effect of HPAI H5N1 at the herd and individual level using a stochastic simulation model. Cumulative incidence was 32% of the herd during the outbreak lasting 45 d. The outbreak led to an average milk yield reduction of 5.7%, with a peak in reduction of 22% lower than the preoutbreak average. The total milk drop was 324 kg of milk per cow in the herd, or 1,014 kg per affected cow. A lengthy recovery of milk yield began 19 d after the onset of the outbreak, reaching the previous year’s yield 132 d (4.4 mo) later. The bulk tank SC (BTSCC) peaked at 296,703 cells/mL, marking a 3-fold increase from preoutbreak levels. This tipping point occurred 22 d after the outbreak onset. The BTSCC gradually returned to preoutbreak levels 46 d after the outbreak began, coinciding with the outbreak’s conclusion. During the outbreak, the average DMI consumed by lactating cows was reduced by 1.5 kg/d per cow (3.5%), whereas affected cows reduced DMI on average 4.7 kg/d over the outbreak. The cost of HPAI H5N1 for affected cows based on milk reduction, replacement, treatment costs, and reduced DMI was estimated at $504 (90% range = $422–$597). At the herd level, for a 500-cow herd, the economic effect was estimated at $79,145 (90% range = $56,726–$84,994). The economic effect of the outbreak per cow in the herd averaged $158 (90% range = $132– $184; i.e., averaged over the entire herd). Milk reduction represented 92.3% of the total economic losses, followed by death related costs (4.7%), treatment and labor costs (1.6%), and culling costs (1.5%). Reduced DMI saved an estimated $11,705 in feed expenses for a 500-cow herd. The effect of HPAI H5N1 on health, productivity, and economics was both severe and immediate, challenging the economic sustainability of the dairy farms. These findings emphasize the urgent need for strong biosecurity measures to prevent and control such outbreaks effectively to limit the high burden estimated.

INTRODUCTION

Since March 24, 2024, highly pathogenic avian influenza (HPAI) hemagglutinin type 5 and neuraminidase type 1 (H5N1) clade 2.3.4.4b has become a new challenge for the dairy industry. Since the index case, the disease has spread steadily across and within states in the United States (Rodriguez et al., 2024b). In an attempt to control the spread of the disease, the USDA issued a federal order to limit interstate movements of infected dairy cattle, requiring a negative testing result for the HPAI H5N1 virus for lactating cows at an approved National Animal Health Laboratory Network laboratory before they can be moved across state lines (USDA-APHIS, 2024a). Meanwhile, alongside state-level animal healthagencies issuing orders to control or prevent the disease’s spread, the USDA’s National Milk Testing Strategy conducts monthly raw milk testing across most US states to monitor H5N1 in dairy herds (USDA-APHIS, 2025). Although the specific role of biosecurity in controlling HPAI H5N1 spread remains unclear, experimental challenges have identified the aerosol respiratory and intra- mammary routes as feasible transmission pathways in cows and calves (Baker et al., 2025; Halwe et al., 2025). According to a USDA-APHIS (2024b) survey of 15 infected dairy herds and 8 poultry premises in Michigan, potential routes for virus introduction into a herd could include various means in addition to the movement of infected animals into naïve herds, such as transmission via contaminated surfaces (e.g., vehicles, people), and potentially infected wildlife and peridomestic species in the area. Thus, strengthening biosecurity protocols remains the most prudent approach, as reducing contact rates and transmission probability is fundamental to infectious disease control (Rodriguez et al., 2024b). The uncertainty surrounding the effect of HPAI H5N1 on dairy farms may lead to a perception that its consequences are minimal and short-lived. This perception can create barriers to the adoption of biosecurity measures for disease prevention. Quantifying the effect of HPAI H5N1 can guide the development of cost-effective preventive and control strategies, serving farmers and advisors to make informed decisions about prevention, treatment, and resource allocation, while assisting policymakers in creating policies, subsidies, or compensation mechanisms to mitigate the economic effects of outbreaks. In this study, we aimed to describe the characteristics of an HPAI H5N1 outbreak in cattle and estimate the effect of the outbreak on health, productivity, and economics at the herd and individual animal levels. We will quantify effect, focusing on milk yield, milk com- ponents, DMI, and clinical treatments. We hypothesized that the HPAI H5N1 outbreak would lead to a significant reduction in milk yield and DMI, an increase in SCC, and a substantial financial burden, all indicating a decline in udder health and overall production efficiency.

MATERIALS AND METHODS

Study Design and Data Source

This is a cohort study with a historical control, designed to evaluate the effect of an HPAI H5N1 confirmed outbreak on a dairy herd in Michigan. Exposure was the HPAI outbreak, and the exposed group was the herd (500 cows) during the 130-d period following the outbreak, whereas the unexposed group (control group) consisted of the same herd during the corresponding period in the previous year, before the outbreak occurred. Daily herd- level data were collected in both periods and statistically compared. Given this study design allows for control for seasonal and management-related variations, observed differences are most likely attributable to the outbreak. The outbreak was confirmed through real-time reverse transcriptase PCR testing in milk samples, initially submitted to the Veterinary Diagnostic Laboratory on May 7, 2024, for screening, followed by confirmation at the National Laboratory Services Network. This dairy herd provided an ideal setting for evaluating the outbreak’s effects on herd performance due to its closed herd management system, stable population resulting from minimal culling during the outbreak, reliable long-term records, and extensive sensor data collected on most cows. Data collection spanned from January 1, 2023 to August 31, 2024, encompassing milk yield, milk composition, DMI, and daily cows inventory (i.e., daily number of lactating cows). Milk yield and milk composition data were sourced from daily bulk tank reports, whereas DMI was recorded using feed management software and obtained at pen-level. The daily cow inventory was obtained from PCDart herd management software. To obtain an estimation of the incidence due to HPAI H5N1, we used health- related fever alerts from smaXtec intraruminal boluses (smaXtec, Graz, Austria), allocated in 87% of the herd (437 cows). Fever-related alerts are triggered when a cow’s body temperature deviates by more than 0.4 °C from its average or baseline temperature. This threshold accounts for natural fluctuations and includes remarks to indicate the nature of the alert. Based on a proprietary algorithm that accounts for factors such as water intake, DIM, and reproductive history, the fever alerts are classified as of reproductive or disease origin. We collected all alerts for the study period and classified them by etiology, selecting for the analysis only those associated with fever due to disease. The incidence of HPAI H5N1 was estimated as the difference between new fever-related alerts during the outbreak period (number of cows with at least 1 fever-related alert over cows at risk) and a baseline estimation using the 45 d before the outbreak. The HPAI H5N1 outbreak exposure period was defined based on observed fever-related alerts. As there is scarce information about the test characteristics of smaXtec for disease detection, we accounted for variability in detection. We reported the the true incidence distribution using the Rogan-Gladen estimation method to correct for the imperfect sensitivity (SE) and specificity (SP). We model 2 scenarios, a SE of 90% and SP of 100% for the upper bound, and 100% SE with 90% SP for the lower bound.

Statistical Analysis

All statistical analyses were performed using R 3.4.4 software (R, RStudio, Inc., Boston, MA). Outcomes, such as milk yield, SCC, fat, protein, lactose, and DMI, were analyzed daily up to 130 d from the outbreak, and were compared against the same timeframe from the previous year. To adjust for fluctuations in the number of lactating cows, milk yield and DMI data were standardized by adjusting daily values to reflect the performance of a hypothetical herd of 500 cows, ensuring valid comparison. We used the 110 d preceding the outbreak (i.e., preoutbreak period) to evaluate consistency assumptions between years. Differences in milk yield and DMI between the outbreak and the previous year were estimated as previously described and averaged by the incidence of disease to obtain estimates for affected cows. A joinpoint segmented regression analysis was conducted to assess trends in milk yield from January to August for both years. Briefly, data are divided into different linear segments (i.e., trends), and significant changes in these trends (joinpoints) are identified capturing shifts in milk production over time (Liu et al., 2023). A linear regression model was fitted for each outcome using period year as the independent variable to estimate differences in daily values between the 2 periods. The “segmented” package in R was used to identify joinpoints, estimating up to 2 joinpoints within each year to determine different linear trends. The model provided estimates for the slope of each segment, indicating whether the outcome (e.g., milk yield) was increasing, decreasing, or remaining constant within each period. In addition, estimated marginal means and mean differences were calculated along with 95% CI. Outcomes were plotted using a locally estimated scatterplot smoothing regression to visualize seasonal patterns and interannual differences. A partial budget was conducted using a stochastic simulation model to estimate the cost of HPAI H5N1 using @Risk 7.6 software (Palisade Corporation, Ithaca, NY). The economic consequences of HPAI included costs as sociated with milk yield (volume and solids), milk quality (premiums and payment SCC adjustment), DMI, culling death, and treatment-related costs (labor and drugs). The price of milk yield was calculated by accounting for daily variations in milk components based on a separate price for milk fat, protein, and other dairy solids, and the SCC financial adjustment by Federal Milk Marketing Orders (USDA-AMS, 2024). These costs were based on the average for the period between April and August 2024. In addition, we included milk price premiums based on milk quality and a discounted marginal profit of 5%. The cost of culling due to HPAI was estimated as the difference between the economic value of a culled cow and its replacement cost, multiplied by the number of culling events attributable to HPAI through the population attributable fraction (AFp). The AFp was calculated based on disease prevalence and the relative risk of culling in the postoutbreak period as compared with the same period in the previous year. The cost of mortality was estimated using the same approach but without accounting for salvage value, as deceased cows had no residual market value. Cost of feed DM was $0.31/kg, obtained from the feed management software. Treatment costs included yeast (i.e., probiotics), vitamin B, and fluid therapy, with treatments having a 3 consecutive day duration, and labor (Table 1). Model simulations were run using 10,000 iterations to generate stable results. We assumed that the incidence of HPAI H5N1 followed a normal distribution with an SD of 5%. The 90% incidence range represents the interval within which 90% of the simulated outcomes (i.e., incidence) fall. This percentile-based range is commonly used to represent the likely variability in costs or outcomes given the uncertainty and probability distribution of input parameters. Model output were reported as: (1) the cost of HPAI H5N1 by affected cow based on incidence, (2) the cost of HPAI H5N1 per average cow in the herd, and (3) cost at the herd level assuming a 500-cow dairy.RESULTS

Descriptive Results

The average milk yield during the preoutbreak period (January 1–April 21, 2024) was 42 kg/d per cow (SD: 0.95 kg). The average bulk tank SCC (BTSCC) was 83,000 cells/mL (SD: 18,000 cells/mL). Inventory remained similar between 2023 (498 cows rolling average; SD 10 cows) and 2024 (491 cows rolling average; SD 12 cows). Culling over 2023 was 39.5% concentrated mostly between October and December. The outbreak period, based on clinical signs, occurred from April 21 to

June 5, 2024. Before the outbreak, milk yield standardized to 500 cows was 0.9% higher than during the same period in 2023, indicating no meaningful difference in milk yield between 2023 and 2024 before the outbreak. This supports the assumption of equal milk yield in 2024 to that produced the year before (i.e., 2023). During the follow-up period after the outbreak began, the replacement rate was 12.4%, up from 9.8% in the same period the previous year, representing an increase of 2.6% (13 cows). The death rate rose to 1.8% postoutbreak from 1.2% in 2023, a difference of 0.6% (3 cows).

Health Alerts

There were 32% of cows in the herd with fever-related health alerts during the outbreak, with a range from 24% to 36%. The epidemiological curve showed a peak lasting 45 d and then a potential second wave lasting 21 d, resulting in 77 d from the outbreak onset until end of the second wave (Figure 1). The average number of alerts during the preoutbreak period was 7.1% and 5.4% for the same month-period in 2023. During the outbreak, 291 (58%) cows had at least 1 fever-related alert, whereas only 133 (26%) had the same alerts the preceding month (i.e., increase of 32%). Cumulative number of alerts were 35% at the highest point 2 wk after the outbreak onset, whereas it was 5.8% for the same period in 2023 (Figure 1, Table 1). Milk Yield. Milk yield dropped at the onset of the outbreak and recovered to the previous year’s level 77 d after onset. After this initial recovery in milk yield, a second immediate less-severe drop was observed, persisting until the end of the follow-up period. The average reduction during the initial 77 d compared with the same period in 2023 was 6.7% and 5.6% when accounting for the complete period under study (132 d). This milk yield represented a reduction of 324 kg of milk per average lactating cow as a result of the outbreak or 1,014 kg per affected cow. Assuming a 32% HPAI H5N1 incidence based on fever alerts, affected cows produced 712 kg less milk during the outbreak, or 7.7 kg/d. At its lowest day point, milk yield had dropped by 22% at the herd level compared with the preoutbreak average (Figure 2). The analysis of the milk yield trend using segmented regression shows that whereas March 2023 saw a sharp rise in milk yield of 46 kg/d, the same period in 2024 showed a significant decline of −49 kg/d (Supplemental Figure S3 and Table S1, see Notes). Nineteen days after the onset of the outbreak (early May 2024), a recovery trend began with a slope of 51 kg/d, eventually reaching the previous year’s yield 132 d later.

SCC

During the outbreak, the BTSCC daily average was 125,790 cells/mL (95% CI: 115,36–136,220), representing an average daily difference (mean difference) of 53,880 cells/mL (95% CI: 42,400–65,600) with the same period the year before (71,910 cells/mL in 2023). Twenty-two days after outbreak onset, the BTSCC reached the tipping point at 296,703 cells/mL, a 3-fold increase compared with the preoutbreak period (Supplemental Figure S4 and Table S2, see Notes). The BTSCC returned to previous outbreak levels 46 d after the outbreak onset.

Milk Components

The butterfat content in milk followed similar trends in 2023 and 2024 before the outbreak. However, during the outbreak, butterfat increased in 2024 compared with the same period in 2023, reaching a 0.3% difference. Fat percentage in 2024 aligned with 2023 levels at 78 d after outbreak onset. No significant changes were observed in lactose and protein content during the outbreak, aside from minor fluctuations. Lactose and protein content experienced nonmeaningful variations (Figure 3).

DMI

During the outbreak, lactating cows on average reduced consumed DMI by 0.6 kg/d per cow (95% CI: −0.82 to −0.41 kg), 2.1% lower than the same period of the previous year. This DMI difference in a 500-cow herd with 32% incidence of disease represents 307 kg/d (95% CI: −408 to −206 kg/d). Affected cows reduced DMI by an average 1.9 kg/d (Figure 4).

Economic Cost

The cost of HPAI H5N1 for affected cows during the study period was estimated at $504 (90% range = $422– $597), with variation depending on multiple parameters included in the analysis (Figure 5, Table 1). At the herd level, for a 500-cow herd, the economic effect based on milk reduction, culling, death, treatment, and DMI was estimated at $79,145 (90% range = $56,726–$84,994). Therefore, across the entire herd, each cow contributed $158 (90% range = $132–$184) on average to the overall economic effect of the outbreak (i.e., cost of HPAI H5N1 per average cow in the herd). Milk reduction accounted for the majority of HPAI-related costs (92.3%), followed by death-related costs (4.7%), treatment and labor costs (1.6%), and culling costs (1.5%). Reduced DMI saved an estimated $11,705 in feed expenses for a 500-cow herd.

DISCUSSION

In this study, we estimated the health, productive, and economic effect of HPAI H5N1 in cattle based on a confirmed outbreak in a dairy herd. We observed an incidence, based on clinical signs of fever, estimated at 32% which shows the widespread reach of the virus within the herd. The outbreak led to a significant drop in milk yield characterized by 2 distinct periods of decline denoting
a longer-lasting effect on herd health and productivity than expected. During the outbreak, DMI per cow was noticeably reduced. Whereas the reduced DMI mitigated some of the overall economic burden by lowering feed costs, it is likely one of the reasons correlated with the drop in milk production. Ultimately, the financial toll of HPAI H5N1 on the herd was substantial, similar to major production diseases such as mastitis with clinical presentations. The fever alerts generated during the outbreak lasted ~45 d, capturing the progression of the infection within the herd. There was a smaller second wave of alerts that could suggest a propagated source of disease transmission rather than a point-source epidemiological curve. Out of the cows with alerts during the second wave, most of them (58%) had fever alerts during the 45 d of the outbreak. Although the smaller secondary wave may be related to the spread of infection of a few additional susceptible cows, it is likely to be mostly caused by an increase in the temperature-humidity index (THI) occurring closer to that period (Supplemental Figure S2), as a similar but less pronounced peak of alerts was observed in June 2023 after an increase in THI. Nevertheless, the pattern observed indicates an original source exposure followed by rapid spread. The high incidence of cows infected with HPAI H5N1 further highlights the wide spread reach of the virus and underscores the potential for rapid transmission in dairy operations where animals are housed in close proximity. Whereas the incidence of HPAI H5N1 has not been thoroughly documented in the literature, cows with clinical signs reported by farm workers have been reported to range from 4.5% (over a 2-d period; Oguzie et al., 2024) to 10% to 15% (over an unspecified timeframe; Burrough et al., 2024). However, as these figures focus only on cows with visible clinical signs, overlooking cows with mid signs of disease, the true number of infected animals is expected to be underestimated. Clinical signs depend heavily on farm workers’ skills for assessment, which can vary based on whether active or passive surveillance is employed, the consistency of case definitions among workers, and the observation period. Because HPAI H5N1 is an infectious disease frequently associated with fever, automated sensor devices that can track body temperature fluctuations with high frequency and accuracy are well suited to identify infected animals across a broader range of infectious related diseases. Farmers who already have these types of sensors in place could potentially use them

for early disease detection and track progression. A limitation, however, of these sensors is that infections that do not result in a minimal detectable fluctuation would potentially lead to an underdetection of cases. Other sensors that monitor parameters related to clinical signs of HPAI such as milk meters to detect sharp decreases in milk yield could potentially also be used for the same purpose. The increase in fever-related alerts is well correlated with the decline in milk yield, perfectly aligning during the last week of April. Notably, visible clinical signs were only observed at least 1 wk later than fever alerts as reported by the farm owner. The peak of alerts also aligns with the lowest point in milk yield. These observations highlight the value of automated sensor devices for early disease detection and preparedness, allowing for timely interventions that potentially can minimize production losses and improve herd health management during out-
breaks. Whereas automated sensor devices are most commonly adopted as part of reproductive programs, their use for disease control purposes including monitoring and prediction has various degrees of success. In particular, intraruminal automated devices have been evaluated for their ability to detect disease in dairy cattle, showing relatively good accuracy depending on the specific disease and purpose. For example, intraruminal devices achieved over 78% in predicting clinical mastitis (Rodriguez et al., 2023) and 70% in predicting pneumonia (Adams et al., 2013), both based on body temperature changes. These devices offer a significant advantage in identifying infectious diseases by continuously monitoring body temperature in a process-controlled manner, accounting for daily and seasonal fluctuations. Whereas other disease-related factors could have triggered alerts, the alerts remained mostly consistent with minimal variation throughout 2023 and the early months of 2024 before the outbreak. This stability suggests that the sharp increase in cases was primarily driven by HPAI-related infections. Milk yield remained stable before the outbreak, as shown both within and between years. However, during the outbreak, milk yield was meaningfully effected, with an average reduction of 7% and a peak decline of up to 22%. Unlike other infectious diseases in the dairy industry, such as salmonella, bovine leukemia virus, or mastitis, which often have chronic stages and generally low transmission rates (Down et al., 2013; Lu et al., 2013; Kuczewski et al., 2021), the point-source nature of the HPAI H5N1 outbreak led to a more concentrated and severe effect on health and productivity. In this regard, HPAI H5N1 behaves similarly to foot-and-mouth disease (FMD) outbreaks, where rapid transmission and acute effect cause immediate declines in herd health and productivity (Yadav et al., 2022). In FMD, the most transmissible and costly viral disease for cattle (Knight-Jones and Rushton, 2013; Paton et al., 2018), following the primary infection, animals often have weakened immune responses, making them more susceptible to secondary infections and prolonged recovery periods (Hayama et al., 2019). The recovery period on affected cows with HPAI H5N1 was prolonged, with the time between the final cases and full recovery suggesting that the effect on affected cows may last up to 102 d, indicating that the outbreak’s effect was both immediate and sustained, suggesting a longer-lasting effect on herd health and productivity, with potential effects on affected cows persisting for over 4 mo. During the outbreak, a significant spike in BTSCC was observed 1 wk after the peak in health alerts, indicating a delay between the rise in body temperature in cows and the subsequent decline in milk quality. The BTSCC returned to preoutbreak level alongside the resolution of health alerts, indicating a minor effect from the SCC in the small number of newly infected cows toward the end of the outbreak. Thus, BTSCC can serve as a surrogate indicator for determining the end of the outbreak. Two primary factors likely contributed to this increase in BTSCC. First, there was a concentration effect, as the SCC spike was aligned with the lowest milk yield, making the SCC levels appear elevated. Second, the tropism of HPAI H5N1 for epithelial cells in the mammary gland led to neutrophilic inflammation (Nelli et al., 2024). Although SCC returned to preoutbreak levels 2 wk after the epidemic curve ended, milk yield took longer to normalize, suggesting that whereas the virus was no longer active in the mammary gland, damage to the epithelial cells persisted. Similar to SCC, the increase in fat content was likely driven by both a concentration effect, peaking at the same time as the largest drop in milk yield, and damage to the mammary epithelial cells, as inflammatory events in the mammary gland have been observed to alter milk composition by impairing the gland’s ability to process nutrients (Zigo et al., 2021). Milk fat returned to normal at the same time as milk yield and did not seem to be affected by the second drop in milk yield. The decline in DMI began at the same time as the onset of fever alerts and did not return to the preoutbreak level by the end of the follow-up (132 d later). The lowest DMI occurred at 10 d after the peak in fever alerts, showing a progression of clinical signs leading to the drop in milk yield. Whereas the initial decline in DMI was unrelated to elevated THI levels, 2 additional declines coincided with high THI. Notably, the THI trend in 2024 was similar to that of 2023. Thus, although these events may have contributed to the negative effect of THI on DMI and milk yield (Chang-Fung-Martel et al., 2021; Chen et al., 2024), the response of affected cows to heat stress may have differed. Cows affected by HPAI H5N1 with weakened immune systems might have experienced an even greater sensitivity to these environmental stressors, leading to further reductions in intake and productivity. Therefore, whereas the reduced DMI mitigated some of the overall economic burden by lowering feed costs, this change in feeding behavior is likely associated with lower feeding efficiency, which in turn, exacerbates reduction in milk yield. Even considering the cost mitigated with DMI, the cost of HPAI H5N1 in a herd is large and concentrated, which makes it particularly burdensome for producers. A herd with 500 cows can lose between $56,726 and $84,994 in milk revenue, replacement, and treatment-related costs, varying by incidence of HPAI H5N1 cases within the farm, milk prices, weather conditions, and length of the outbreak. A direct causal link between HPAI H5N1 and mortality has not been established. Discussions with producers and veterinarians on affected farms indicate that deaths directly attributed to HPAI H5N1 are rare, as cases are often identified based on clinical signs, whereas the presence of comorbidities is not fully evaluated, indicating a generally positive prognosis for most infected cows. Culling, furthermore, is highly dependent on a farm’s management, and the economic effect will greatly vary depending on the stage of lactation, parity, reproductive stage, and milk yield, among others. Whereas the closed herd status and minimal culling during the outbreak reduce model assumptions and enhance parsimony, management practices are expected to vary widely among herds. The average cost of HPAI H5N1 per cow in the herd (i.e., not only affected cows) is comparable to the costs reported for clinical mastitis, which range from $89 to $142 (adjusted for inflation; Hogeveen et al., 2011). In mastitis cost estimations, reproductive losses typically account for 5% to 10% of the overall cost, primarily driven by milk-related losses, making a similar level of underestimation plausible (Heikkilä et al., 2012; Aghamohammadi et al., 2018; Rodriguez et al., 2024a). Whereas this study provides valuable insights into the effect of the disease, a key limitation is that it focuses on a single herd. This herd is located in the Midwest, where climatic and management conditions might differ from other regions of the United States. The outbreak occurred during spring and early summer, its effect may vary from outbreaks occurring in the South during the peak of summer. We addressed this limitation by modeling economic costs with added variability to input parameters. However, obtaining individual-level data from multiple farms with diverse management systems is essential for a more comprehensive understanding of the disease’s effect, Rodriguez et al.: QUANTIFYING CATTLE H5N1 AVIAN INFLUENZA EFFECT Journal of Dairy Science Vol. TBC No. TBC, TBC greater representativity of results, and the development of more tailored recommendations.

CONCLUSIONS

Our results indicate a meaningful effect by HPAI H5N1, with an incidence reaching 32% of the herd within an outbreak lasting 45 d. The outbreak led to a pronounced 7% decline in milk yield during a period larger than the period associated with the outbreak. Also, BTSCC took over 2 mo from the outbreak onset to return to the previous outbreak level, both indicating a lasting prolonged adverse effect on herd health and productivity. Dry matter intake per cow dropped during this time and did not return to normal even 4 mo later. Although this mitigated
feed costs, it likely contributed to the reduction in milk production. Overall, the financial toll of HPAI H5N1 on the herd was substantial, comparable to the economic burden of major production diseases such as mastitis. However, unlike mastitis, HPAI H5N1 manifested as a point-source outbreak on the herd, intensifying its economic effect by concentrating losses into a relatively shorter period. This made the financial strain particularly pronounced for farmers, as the effects were severe and immediate. These results highlight the critical need for robust biosecurity measures to prevent and mitigate such outbreaks effectively.

NOTES

This article was supported by USDA Animal and Plant Health Inspection Service (APHIS; Riverdale Park, MD) . The funder did not participate in the preparation or approval of the manuscript. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the USDA. The authors thank the farm owner and nutritionist for facilitating access to data. Supplemental material for this article is available at [URL]. All procedures were approved by the Institutional Animal Care and Use Committee at Michigan State University (PROTO202400089). The authors have not stated any conflicts of interest.

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