Ecological divergence of wild birds drives avian influenza spillover and global spread.

The diversity of influenza A viruses (IAV) is primarily hosted by two highly divergent avian orders: Anseriformes (ducks, swans and geese) and Charadriiformes (gulls, terns and shorebirds). Studies of IAV have historically focused on Anseriformes, specifically dabbling ducks, overlooking the diversity of hosts in nature, including gull and goose species that have successfully adapted to human habitats. This study sought to address this imbalance by characterizing spillover dynamics and global transmission patterns of IAV over 10 years at greater taxonomic resolution than previously considered. Furthermore, the circulation of viral subtypes in birds that are either host-adapted (low pathogenic H13, H16) or host-generalist (highly pathogenic avian influenza-HPAI H5) provided a unique opportunity to test and extend models of viral evolution. Using Bayesian phylodynamic modelling we uncovered a complex transmission network that relied on ecologically divergent bird hosts. The generalist subtype, HPAI H5 was driven largely by wild geese and swans that acted as a source for wild ducks, gulls, land birds, and domestic geese. Gulls were responsible for moving HPAI H5 more rapidly than any other host, a finding that may reflect their long-distance, pelagic movements and their immuno-naïve status against this subtype. Wild ducks, long viewed as primary hosts for spillover, occupied an optimal space for viral transmission, contributing to geographic expansion and rapid dispersal of HPAI H5. Evidence of inter-hemispheric dispersal via both the Pacific and Atlantic Rims was detected, supporting surveillance at high latitudes along continental margins to achieve early detection. Both neutral (geographic expansion) and non-neutral (antigenic selection) evolutionary processes were found to shape subtype evolution which manifested as unique geographic hotspots for each subtype at the global scale. This study reveals how a diversity of avian hosts contribute to viral spread and spillover with the potential to improve surveillance in an era of rapid global change.

Global dissemination of influenza A virus is driven by wild bird migration through arctic and subarctic zones.

Influenza A viruses (IAV) circulate endemically among many wild aquatic bird populations that seasonally migrate between wintering grounds in southern latitudes to breeding ranges along the perimeter of the circumpolar arctic. Arctic and subarctic zones are hypothesized to serve as ecologic drivers of the intercontinental movement and reassortment of IAVs due to high densities of disparate populations of long distance migratory and native bird species present during breeding seasons. Iceland is a staging ground that connects the East Atlantic and North Atlantic American flyways, providing a unique study system for characterizing viral flow between eastern and western hemispheres. Using Bayesian phylodynamic analyses, we sought to evaluate the viral connectivity of Iceland to proximal regions and how inter-species transmission and reassortment dynamics in this region influence the geographic spread of low and highly pathogenic IAVs. Findings demonstrate that IAV movement in the arctic and subarctic reflects wild bird migration around the perimeter of the circumpolar north, favouring short-distance flights between proximal regions rather than long distance flights over the polar interior. Iceland connects virus movement between mainland Europe and North America, consistent with the westward migration of wild birds from mainland Europe to Northeastern Canada and Greenland. Though virus diffusion rates were similar among avian taxonomic groups in Iceland, gulls play an outsized role as sinks of IAVs from other avian hosts prior to onward migration. These data identify patterns of virus movement in northern latitudes and inform future surveillance strategies related to seasonal and emergent IAVs with potential public health concern.

A Pilot Study of the Serious Illness Conversation Guide in a Dialysis Clinic.

Clinician-led conversations about future care priorities occur infrequently with end-stage renal disease (ESRD) patients on dialysis. This was a pilot study of structured serious illness conversations using the Serious Illness Conversation Guide (SICG) in a single dialysis clinic to assess acceptability of the approach and explore conversation themes and potential outcomes among patients with ESRD. Twelve individuals with ESRD on dialysis from a single outpatient dialysis clinic participated in this study. Participants completed a baseline demographics survey, engaged in a clinician-led structured serious illness conversation, and completed an acceptability questionnaire. Conversations were recorded, transcribed and thematically analyzed. The average age of participants was 68.8 years. The conversations averaged 20:53 in length. Ten participants (83%) felt that the conversation was held at the right time in their clinical course and eleven participants (91%) felt that it was worthwhile. Most participants (73%) reported neutral feelings about clinician use of a printed guide. Eleven participants (91%) reported no change in anxiety about their illness following the conversation, and five participants (42%) reported that the conversation increased their hopefulness about future quality of life. Thematic analysis revealed common perspectives on dialysis including that participants view in-center hemodialysis as temporary, compartmentalize their kidney disease, perceive narrowed life experiences and opportunities, and believe dialysis is their only option. This pilot study suggests that clinician-led structured serious illness conversations may be acceptable to patients with ESRD on dialysis. The themes identified can inform future serious illness conversations with dialysis patients.

Ecogeographic Drivers of the Spatial Spread of Highly Pathogenic Avian Influenza Outbreaks in Europe and the United States, 2016-Early 2022.

H5Nx highly pathogenic avian influenza (HPAI) viruses of clade 2.3.4.4 have caused outbreaks in Europe among wild and domestic birds since 2016 and were introduced to North America via wild migratory birds in December 2021. We examined the spatiotemporal extent of HPAI viruses across continents and characterized ecological and environmental predictors of virus spread between geographic regions by constructing a Bayesian phylodynamic generalized linear model (phylodynamic-GLM). The findings demonstrate localized epidemics of H5Nx throughout Europe in the first several years of the epizootic, followed by a singular branching point where H5N1 viruses were introduced to North America, likely via stopover locations throughout the North Atlantic. Once in the United States (US), H5Nx viruses spread at a greater rate between US-based regions as compared to prior spread in Europe. We established that geographic proximity is a predictor of virus spread between regions, implying that intercontinental transport across the Atlantic Ocean is relatively rare. An increase in mean ambient temperature over time was predictive of reduced H5Nx virus spread, which may reflect the effect of climate change on declines in host species abundance, decreased persistence of the virus in the environment, or changes in migratory patterns due to ecological alterations. Our data provide new knowledge about the spread and directionality of H5Nx virus dispersal in Europe and the US during an actively evolving intercontinental outbreak, including predictors of virus movement between regions, which will contribute to surveillance and mitigation strategies as the outbreak unfolds, and in future instances of uncontained avian spread of HPAI viruses.

Epidemiology and Ecology of Influenza A Viruses among Wildlife in the Arctic.

Arctic regions are ecologically significant for the environmental persistence and geographic dissemination of influenza A viruses (IAVs) by avian hosts and other wildlife species. Data describing the epidemiology and ecology of IAVs among wildlife in the arctic are less frequently published compared to southern temperate regions, where prevalence and subtype diversity are more routinely documented. Following PRISMA guidelines, this systematic review addresses this gap by describing the prevalence, spatiotemporal distribution, and ecological characteristics of IAVs detected among wildlife and the environment in this understudied region of the globe. The literature search was performed in PubMed and Google Scholar using a set of pre-defined search terms to identify publications reporting on IAVs in Arctic regions between 1978 and February 2022. A total of 2125 articles were initially screened, 267 were assessed for eligibility, and 71 articles met inclusion criteria. IAVs have been detected in multiple wildlife species in all Arctic regions, including seabirds, shorebirds, waterfowl, seals, sea lions, whales, and terrestrial mammals, and in the environment. Isolates from wild birds comprise the majority of documented viruses derived from wildlife; however, among all animals and environmental matrices, 26 unique low and highly pathogenic subtypes have been characterized in the scientific literature from Arctic regions. Pooled prevalence across studies indicates 4.23% for wild birds, 3.42% among tested environmental matrices, and seroprevalences of 9.29% and 1.69% among marine and terrestrial mammals, respectively. Surveillance data are geographically biased, with most data from the Alaskan Arctic and many fewer reports from the Russian, Canadian, North Atlantic, and Western European Arctic. We highlight multiple important aspects of wildlife host, pathogen, and environmental ecology of IAVs in Arctic regions, including the role of avian migration and breeding cycles for the global spread of IAVs, evidence of inter-species and inter-continental reassortment at high latitudes, and how climate change-driven ecosystem shifts, including changes in the seasonal availability and distribution of dietary resources, have the potential to alter host-pathogen-environment dynamics in Arctic regions. We conclude by identifying gaps in knowledge and propose priorities for future research.

A standardized instrument quantifying risk factors associated with bi-directional transmission of SARS-CoV-2 and other zoonotic pathogens: The COVID-19 human-animal interactions survey (CHAIS).

Similar to many zoonotic pathogens which transmit from animals to humans, SARS-CoV-2 (CoV-2), the virus responsible for the COVID-19 pandemic, most likely originated in Rhinolophus bats before spreading among humans globally. Early into the pandemic, reports of CoV-2 diagnoses in animals from various countries emerged. While most CoV-2 positive animals were confirmed to have been in close contact with CoV-2 positive humans, there has been a paucity of published evidence to-date describing risk factors associated with CoV-2 transmission among humans and animals. The COVID-19 Human-Animal Interactions Survey (CHAIS) was developed to provide a standardized instrument describing human-animal interactions during the pandemic and to evaluate behavioral, spatiotemporal, and biological risk factors associated with bi-directional zoonotic transmission of CoV-2 within shared environments, predominantly households with limited information about human-wildlife or human-livestock interactions. CHAIS measures four broad domains of transmission risk: 1) risk and intensity of infection in human hosts, 2) spatial characteristics of shared environments, 3) behaviors and human-animal interactions, and 4) susceptible animal subpopulations. Following the development of CHAIS, with a One Health approach, a multidisciplinary group of experts (n = 20) was invited to review and provide feedback on the survey for content validity. Expert feedback was incorporated into two final survey formats-an extended version and an abridged version for which specific core questions addressing zoonotic and reverse zoonotic transmission were identified. Both versions are modularized, with each section having the capacity to serve as independent instruments, allowing researchers to customize the survey based on context and research-specific needs. Further adaptations for studies seeking to investigate other zoonotic pathogens with similar routes of transmission (i.e. respiratory, direct contact) are also possible. The CHAIS instrument is a standardized human-animal interaction survey developed to provide important data on risk factors that guide transmission of CoV-2, and other similar pathogens, among humans and animals.

Evaluation of a call center to assess post-discharge maternal and early neonatal outcomes of facility-based childbirth in Uttar Pradesh, India.

BACKGROUND: Maternal and neonatal outcomes in the immediate post-delivery period are critical indicators of quality of care. Data on childbirth outcomes in low-income settings usually require home visits, which can be constrained by cost and access. We report on the use of a call center to measure post-discharge outcomes within a multi-site improvement study of facility-based childbirth in Uttar Pradesh, India. METHODS: Of women delivering at study sites eligible for inclusion, 97.9% (n = 157,689) consented to follow-up. All consenting women delivering at study facilities were eligible to receive a phone call between days eight and 42 post-partum to obtain outcomes for the seven-day period after birth. Women unable to be contacted via phone were visited at home. Outcomes, including maternal and early neonatal mortality and maternal morbidity, were ascertained using a standardized script developed from validated survey questions. Data Quality Assurance (DQA) included accuracy (double coding of calls) and validity (consistency between two calls to the same household). Regression models were used to identify factors associated with inconsistency. FINDINGS: Over 23 months, outcomes were obtained by the call center for 98.0% (154,494/157,689) consenting women and their neonates. 87.9% of call center-obtained outcomes were captured by phone call alone and 12.1% required the assistance of a field worker. An additional 1.7% were obtained only by a field worker, 0.3% were lost-to-follow-up, and only 0.1% retracted consent. The call center captured outcomes with a median of 1 call (IQR 1-2). DQA found 98.0% accuracy; data validation demonstrated 93.7% consistency between the first and second call. In a regression model, significant predictors of inconsistency included cases with adverse outcomes (p<0.001), and different respondents on the first and validation call (p<0.001). CONCLUSIONS: In areas with widespread mobile cell phone access and coverage, a call center is a viable and efficient approach for measurement of post-discharge childbirth outcomes.

Implementation and results of an integrated data quality assurance protocol in a randomized controlled trial in Uttar Pradesh, India.

BACKGROUND: There are few published standards or methodological guidelines for integrating Data Quality Assurance (DQA) protocols into large-scale health systems research trials, especially in resource-limited settings. The BetterBirth Trial is a matched-pair, cluster-randomized controlled trial (RCT) of the BetterBirth Program, which seeks to improve quality of facility-based deliveries and reduce 7-day maternal and neonatal mortality and maternal morbidity in Uttar Pradesh, India. In the trial, over 6300 deliveries were observed and over 153,000 mother-baby pairs across 120 study sites were followed to assess health outcomes. We designed and implemented a robust and integrated DQA system to sustain high-quality data throughout the trial. METHODS: We designed the Data Quality Monitoring and Improvement System (DQMIS) to reinforce six dimensions of data quality: accuracy, reliability, timeliness, completeness, precision, and integrity. The DQMIS was comprised of five functional components: 1) a monitoring and evaluation team to support the system; 2) a DQA protocol, including data collection audits and targets, rapid data feedback, and supportive supervision; 3) training; 4) standard operating procedures for data collection; and 5) an electronic data collection and reporting system. Routine audits by supervisors included double data entry, simultaneous delivery observations, and review of recorded calls to patients. Data feedback reports identified errors automatically, facilitating supportive supervision through a continuous quality improvement model. RESULTS: The five functional components of the DQMIS successfully reinforced data reliability, timeliness, completeness, precision, and integrity. The DQMIS also resulted in 98.33% accuracy across all data collection activities in the trial. All data collection activities demonstrated improvement in accuracy throughout implementation. Data collectors demonstrated a statistically significant (p = 0.0004) increase in accuracy throughout consecutive audits. The DQMIS was successful, despite an increase from 20 to 130 data collectors. CONCLUSIONS: In the absence of widely disseminated data quality methods and standards for large RCT interventions in limited-resource settings, we developed an integrated DQA system, combining auditing, rapid data feedback, and supportive supervision, which ensured high-quality data and could serve as a model for future health systems research trials. Future efforts should focus on standardization of DQA processes for health systems research. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02148952 . Registered on 13 February 2014.

Surgeons' Perspectives on Avoiding Nonbeneficial Treatments in Seriously Ill Older Patients with Surgical Emergencies: A Qualitative Study.

BACKGROUND: Clinical decisions for seriously ill older patients with surgical emergencies are highly complex. Measuring the benefits of burdensome treatments in this context is fraught with uncertainty. Little is known about how surgeons formulate treatment decisions to avoid nonbeneficial surgery, or engage in preoperative conversations about end-of-life (EOL) care. OBJECTIVE: We sought to describe how surgeons approach such discussions, and to identify modifiable factors to reduce nonbeneficial surgery near the EOL. DESIGN: Purposive and snowball sampling were used to recruit a national sample of emergency general surgeons. Semistructured interviews were conducted between February and May 2014. MEASUREMENTS: Three independent coders performed qualitative coding using NVivo software (NVivo version 10.0, QSR International). Content analysis was used to identify factors important to surgical decision making and EOL communication. RESULTS: Twenty-four surgeons were interviewed. Participants felt responsible for conducting EOL conversations with seriously ill older patients and their families before surgery to prevent nonbeneficial treatments. However, wide differences in prognostic estimates among surgeons, inadequate data about postoperative quality of life (QOL), patients and surrogates who were unprepared for EOL conversations, variation in perceptions about the role of palliative care, and time constraints are contributors to surgeons providing nonbeneficial operations. Surgeons reported performing operations they knew would not benefit the patient to give the family time to come to terms with the patient's demise. CONCLUSIONS: Emergency general surgeons feel responsible for having preoperative discussions about EOL care with seriously ill older patients to avoid nonbenefical surgery. However, surgeons identified multiple factors that undermine adequate communication and lead to nonbeneficial surgery.