Investigation of risk factors for introduction of highly pathogenic avian influenza H5N1 infection among commercial turkey operations in the United States, 2022: a case-control study

Introduction

The 2022-2023 highly pathogenic avian influenza (HPAI) H5N1 outbreak in the United States (U.S.) is the largest and most costly animal health event in U.S. history. Approximately 70% of commercial farms affected during this outbreak have been turkey farms.

Methods

We conducted a case-control study to identify potential risk factors for introduction of HPAI virus onto commercial meat turkey operations. Data were collected from 66 case farms and 59 control farms in 12 states. Univariate and multivariable analyses were conducted to compare management and biosecurity factors on case and control farms.

Results

Factors associated with increased risk of infection included being in an existing control zone, having both brooders and growers, having toms, seeing wild waterfowl or shorebirds in the closest field, and using rendering for dead bird disposal. Protective factors included having a restroom facility, including portable, available to crews that visit the farm and workers having access and using a shower at least some of the time when entering a specified barn.

Discussion

Study results provide a better understanding of risk factors for HPAI infection and can be used to inform prevention and control measures for HPAI on U.S. turkey farms.

Serological evidence for historical and present-day exposure of North American bison to Mycoplasma bovis

Background

Mycoplasma bovis causes mastitis, otitis, pneumonia and arthritis in cattle and is a major contributor to bovine respiratory disease complex. Around the year 2000, it emerged as a significant threat to the health of North American bison. Whether healthy bison are carriers of M. bovis and when they were first exposed is not known. To investigate these questions we used a commercially available ELISA that detects antibodies to M. bovis to test 3295 sera collected from 1984 through 2019 from bison in the United States and Canada.

Results

We identified moderately to strongly seropositive bison from as long ago as the late 1980s. Average seroprevalence over the past 36 years is similar in the United States and Canada, but country-specific differences are evident when data are sorted by the era of collection. Seroprevalence in the United States during the pre-disease era (1999 and prior) was significantly higher than in Canada, but was significantly lower than in Canada during the years 2000–2019. Considering individual countries, seroprevalence in the United States since the year 2000 dropped significantly as compared to the years 1985–1999. In Canada the trend is reversed, with seroprevalence increasing significantly since the year 2000. ELISA scores for sera collected from free-ranging bison do not differ significantly from scores for sera from more intensively managed animals, regardless of the era in which they were collected. However, seroprevalence among intensively raised Canadian bison has nearly doubled since the year 2000 and average ELISA scores rose significantly.

Conclusions

Our data provide the first evidence that North American bison were exposed to M. bovis many years prior to the emergence of M. bovis-related disease. Patterns of exposure inferred from these results differ in the United States and Canada, depending on the era under consideration. Our data further suggest that M. bovis may colonize healthy bison at a level sufficient to trigger antibody responses but without causing overt disease. These findings provide novel insights as to the history of M. bovis in bison and will be of value in formulating strategies to minimize the impact of mycoplasmosis on bison health and production.

Modelling the domestic poultry population in the United States: A novel approach leveraging remote sensing and synthetic data methods

Comprehensive and spatially accurate poultry population demographic data do not currently exist in the United States; however, these data are critically needed to adequately prepare for, and efficiently respond to and manage disease outbreaks. In response to absence of these data, this study developed a national-level poultry population dataset by using a novel combination of remote sensing and probabilistic modelling methodologies. The Farm Location and Agricultural Production Simulator (FLAPS) (Burdett et al., 2015) was used to provide baseline national-scale data depicting the simulated locations and populations of individual poultry operations. Remote sensing methods (identification using aerial imagery) were used to identify actual locations of buildings having the characteristic size and shape of commercial poultry barns. This approach was applied to 594 U.S. counties with > 100,000 birds in 34 states based on the 2012 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS), Census of Agriculture (CoA). The two methods were integrated in a hybrid approach to develop an automated machine learning process to locate commercial poultry operations and predict the number and type of poultry for each operation across the coterminous United States. Validation illustrated that the hybrid model had higher locational accuracy and more realistic distribution and density patterns when compared to purely simulated data. The resulting national poultry population dataset has significant potential for application in animal disease spread modelling, surveillance, emergency planning and response, economics, and other fields, providing a versatile asset for further agricultural research.

Challenges and Opportunities Developing Mathematical Models of Shared Pathogens of Domestic and Wild Animals

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems, including: (1) the identity of wildlife hosts, their distributions, and movement patterns; (2) the pathogen transmission pathways between wildlife and domestic animals; (3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations; and (4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.

Temporal and geographic distribution of weather conditions favorable to airborne spread of foot-and-mouth disease in the coterminous United States

Foot-and-mouth disease (FMD) is a highly infectious viral disease of cloven-hoofed animals. FMD outbreaks have the potential to cause significant economic consequences, and effective control strategies are needed to minimize the damage to livestock systems and the economy. Although not the predominant route of infection, airborne transmission has been implicated in previous outbreaks. Under favorable weather conditions, airborne spread of FMD can make the rapid containment of an outbreak more difficult. Our objective was to identify seasonal and geographic differences in patterns of conditions favorable to airborne FMD spread in the United States. Data from a national network of surface weather stations were examined for three study years (December 2011-November 2012, December 2012-November 2013, December 2014-November 2015). Weather conditions were found to be most frequently favorable to airborne spread during the winter (December, January, February). Geographically, conditions were most frequently favorable to airborne FMD spread in the upper Midwestern United States, a region where swine and cattle populations are common. Across study years, conditions for airborne FMD spread were more frequently favorable when weather conditions were generally mild with few extremes with respect to temperature and precipitation (e.g., 2014-2015). However, national patterns in risk areas for airborne FMD spread were similar across study years even though the degree of risk differed based on variations in weather patterns among study years. Our findings suggest that airborne transmission could contribute to FMD spread between livestock premises in the event of an outbreak in the coterminous United States, and that some geographic areas are at an increased risk particularly in seasons with conducive weather conditions. To our knowledge, this is the first study to characterize the risk of airborne FMD spread on a national scale in the United States. The findings presented here can be used to enhance preparedness and surveillance activities by identifying specific geographic areas in the United States where airborne spread is most likely to be a risk factor for transmission during an outbreak.

A Simulation-Based Evaluation of Premovement Active Surveillance Protocol Options for the Managed Movement of Turkeys to Slaughter During an Outbreak of Highly Pathogenic Avian Influenza in the United States

Risk management decisions associated with live poultry movement during a highly pathogenic avian influenza (HPAI) outbreak should be carefully considered. Live turkey movements may pose a risk for disease spread. On the other hand, interruptions in scheduled movements can disrupt business continuity. The Secure Turkey Supply (STS) Plan was developed through an industry-government-academic collaboration to address business continuity concerns that might arise during a HPAI outbreak. STS stakeholders proposed outbreak response measure options that were evaluated through risk assessment. The developed approach relies on 1) diagnostic testing of two pooled samples of swabs taken from dead turkeys immediately before movement via the influenza A matrix gene real-time reverse transcriptase polymerase chain reaction (rRT-PCR) test; 2) enhanced biosecurity measures in combination with a premovement isolation period (PMIP), restricting movement onto the premises for a few days before movement to slaughter; and 3) incorporation of a distance factor from known infected flocks such that exposure via local area spread is unlikely. Daily exposure likelihood estimates from spatial kernels from past HPAI outbreaks were coupled with simulation models of disease spread and active surveillance to evaluate active surveillance protocol options that differ with respect to the number of swabs per pooled sample and the timing of the tests in relation to movement. Simulation model results indicate that active surveillance testing, in combination with strict biosecurity, substantially increased HPAI virus detection probability. When distance from a known infected flock was considered, the overall combined likelihood of moving an infected, undetected turkey flock to slaughter was predicted to be lower at 3 and 5 km. The analysis of different active surveillance protocol options is designed to incorporate flexibility into HPAI emergency response plans.

"One Health" or Three? Publication Silos Among the One Health Disciplines

The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publications fulfilling our search criteria increased by 14.6% per year, which is faster than growth rates for life sciences as a whole and for most biology subdisciplines. Surveyed publications clustered into three communities: one used by ecologists, one used by veterinarians, and a third diverse-authorship community used by population biologists, mathematicians, epidemiologists, and experts in human health. Overlap between these communities increased through time in terms of author number, diversity of co-author affiliations, and diversity of citations. However, communities continue to differ in the systems studied, questions asked, and methods employed. While the infectious disease research community has made significant progress toward integrating its participating disciplines, some segregation--especially along the veterinary/ecological research interface--remains.

A Review of Infectious Agents in Polar Bears (Ursus maritimus) and Their Long-Term Ecological Relevance

Disease was a listing criterion for the polar bear (Ursus maritimus) as threatened under the Endangered Species Act in 2008; it is therefore important to evaluate the current state of knowledge and identify any information gaps pertaining to diseases in polar bears. We conducted a systematic literature review focused on infectious agents and associated health impacts identified in polar bears. Overall, the majority of reports in free-ranging bears concerned serosurveys or fecal examinations with little to no information on associated health effects. In contrast, most reports documenting illness or pathology referenced captive animals and diseases caused by etiologic agents not representative of exposure opportunities in wild bears. As such, most of the available infectious disease literature has limited utility as a basis for development of future health assessment and management plans. Given that ecological change is a considerable risk facing polar bear populations, future work should focus on cumulative effects of multiple stressors that could impact polar bear population dynamics.

Establishing a definition of polar bear (Ursus maritimus) health: a guide to research and management activities

The meaning of health for wildlife and perspectives on how to assess and measure health, are not well characterized. For wildlife at risk, such as some polar bear (Ursus maritimus) subpopulations, establishing comprehensive monitoring programs that include health status is an emerging need. Environmental changes, especially loss of sea ice habitat, have raised concern about polar bear health. Effective and consistent monitoring of polar bear health requires an unambiguous definition of health. We used the Delphi method of soliciting and interpreting expert knowledge to propose a working definition of polar bear health and to identify current concerns regarding health, challenges in measuring health, and important metrics for monitoring health. The expert opinion elicited through the exercise agreed that polar bear health is defined by characteristics and knowledge at the individual, population, and ecosystem level. The most important threats identified were in decreasing order: climate change, increased nutritional stress, chronic physiological stress, harvest management, increased exposure to contaminants, increased frequency of human interaction, diseases and parasites, and increased exposure to competitors. Fifteen metrics were identified to monitor polar bear health. Of these, indicators of body condition, disease and parasite exposure, contaminant exposure, and reproductive success were ranked as most important. We suggest that a cumulative effects approach to research and monitoring will improve the ability to assess the biological, ecological, and social determinants of polar bear health and provide measurable objectives for conservation goals and priorities and to evaluate progress.

An approach for de-identification of point locations of livestock premises for further use in disease spread modeling

We describe a method for de-identifying point location data used for disease spread modeling to allow data custodians to share data with modeling experts without disclosing individual farm identities. The approach is implemented in an open-source software program that is described and evaluated here. The program allows a data custodian to select a level of de-identification based on the K-anonymity statistic. The program converts a file of true farm locations and attributes into a file appropriate for use in disease spread modeling with the locations randomly modified to prevent re-identification based on location. Important epidemiological relationships such as clustering are preserved to as much as possible to allow modeling similar to those using true identifiable data. The software implementation was verified by visual inspection and basic descriptive spatial analysis of the output. Performance is sufficient to allow de-identification of even large data sets on desktop computers available to any data custodian.

Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America

Wild birds are the primary source of genetic diversity for influenza A viruses that eventually emerge in poultry and humans. Much progress has been made in the descriptive ecology of avian influenza viruses (AIVs), but contributions are less evident from quantitative studies (e.g., those including disease dynamic models). Transmission between host species, individuals and flocks has not been measured with sufficient accuracy to allow robust quantitative evaluation of alternate control protocols. We focused on the United States of America (USA) as a case study for determining the state of our quantitative knowledge of potential AIV emergence processes from wild hosts to poultry. We identified priorities for quantitative research that would build on existing tools for responding to AIV in poultry and concluded that the following knowledge gaps can be addressed with current empirical data: (1) quantification of the spatio-temporal relationships between AIV prevalence in wild hosts and poultry populations, (2) understanding how the structure of different poultry sectors impacts within-flock transmission, (3) determining mechanisms and rates of between-farm spread, and (4) validating current policy-decision tools with data. The modeling studies we recommend will improve our mechanistic understanding of potential AIV transmission patterns in USA poultry, leading to improved measures of accuracy and reduced uncertainty when evaluating alternative control strategies.

An epidemiologic simulation model of the spread and control of highly pathogenic avian influenza (H5N1) among commercial and backyard poultry flocks in South Carolina, United States

Epidemiologic simulation modeling of highly pathogenic avian influenza (HPAI) outbreaks provides a useful conceptual framework with which to estimate the consequences of HPAI outbreaks and to evaluate disease control strategies. The purposes of this study were to establish detailed and informed input parameters for an epidemiologic simulation model of the H5N1 strain of HPAI among commercial and backyard poultry in the state of South Carolina in the United States using a highly realistic representation of this poultry population; to estimate the consequences of an outbreak of HPAI in this population with a model constructed from these parameters; and to briefly evaluate the sensitivity of model outcomes to several parameters. Parameters describing disease state durations; disease transmission via direct contact, indirect contact, and local-area spread; and disease detection, surveillance, and control were established through consultation with subject matter experts, a review of the current literature, and the use of several computational tools. The stochastic model constructed from these parameters produced simulated outbreaks ranging from 2 to 111 days in duration (median 25 days), during which 1 to 514 flocks were infected (median 28 flocks). Model results were particularly sensitive to the rate of indirect contact that occurs among flocks. The baseline model established in this study can be used in the future to evaluate various control strategies, as a tool for emergency preparedness and response planning, and to assess the costs associated with disease control and the economic consequences of a disease outbreak.

Coxiella burnetii in northern fur seal (Callorhinus ursinus) placentas from St. Paul Island, Alaska

The decline in the number of northern fur seal (NFS; Callorhinus ursinus) pups on St. Paul Island, Alaska, has led to multidisciplinary research, including investigation into issues of reproductive health and success. Given the recent identification of Coxiella burnetii in the placenta of two other marine mammal species, NFS placentas were collected from Reef rookery on St. Paul Island, Alaska, during the 2010 pupping season, examined histologically, and tested for C. burnetii using polymerase chain reaction (PCR). Of 146 placentas examined, gram-negative intratrophoblastic bacteria that were positive for C. burnetii on immunohistochemistry were observed in 5 (3%) placentas. Placental infection was usually devoid of associated inflammation or significant ancillary pathology. One hundred nine (75%) of the placentas were positive for C. burnetii on PCR. C. burnetii is globally distributed and persists for long periods in the environment, providing ample opportunity for exposure of many species. The significance of this finding for the declining fur seal population, potential human exposure and infection, and impact on other sympatric marine mammal or terrestrial species is unclear; further investigation into the epidemiology of Coxiella in the marine ecosystem is warranted.