Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Antigenic Characterization and Pandemic Risk Assessment of North American H1 Influenza A Viruses Circulating in Swine.

The first pandemic of the 21st century was caused by an H1N1 influenza A virus (IAV) introduced from pigs into humans, highlighting the importance of swine as reservoirs for pandemic viruses. Two major lineages of swine H1 circulate in North America: the 1A classical swine lineage (including that of the 2009 H1N1 pandemic) and the 1B human seasonal-like lineage. Here, we investigated the evolution of these H1 IAV lineages in North American swine and their potential pandemic risk. We assessed the antigenic distance between the HA of representative swine H1 and human seasonal vaccine strains (1978 to 2015) in hemagglutination inhibition (HI) assays using a panel of monovalent antisera raised in pigs. Antigenic cross-reactivity varied by strain but was associated with genetic distance. Generally, the swine 1A lineage viruses that seeded the 2009 H1 pandemic were antigenically most similar to the H1 pandemic vaccine strains, with the exception of viruses in the genetic clade 1A.1.1.3, which had a two-amino acid deletion mutation near the receptor-binding site, which dramatically reduced antibody recognition. The swine 1B lineage strains, which arose from previously circulating (pre-2009 pandemic) human seasonal viruses, were more antigenically similar to pre-2009 human seasonal H1 vaccine viruses than post-2009 strains. Human population immunity was measured by cross-reactivity in HI assays to representative swine H1 strains. There was a broad range of titers against each swine strain that was not associated with age, sex, or location. However, there was almost no cross-reactivity in human sera to the 1A.1.1.3 and 1B.2.1 genetic clades of swine viruses, and the 1A.1.1.3 and 1B.2.1 clades were also the most antigenically distant to the human vaccine strains. Our data demonstrate that the antigenic distances of representative swine strains from human vaccine strains represent an important part of the rational assessment of swine IAV for zoonotic risk research and pandemic preparedness prioritization. IMPORTANCE Human H1 influenza A viruses (IAV) spread to pigs in North America, resulting in a sustained circulation of two major groups of H1 viruses in swine. We quantified the genetic diversity of H1 in swine and measured antigenic phenotypes. We demonstrated that the swine H1 lineages were significantly different from the human vaccine strains and that this antigenic dissimilarity increased over time as the viruses evolved in swine. Pandemic preparedness vaccine strains for human vaccines also demonstrated a loss in similarity with contemporary swine strains. Human sera revealed a range of responses to swine IAV, including two groups of viruses with little to no immunity. The surveillance and risk assessment of IAV diversity in pig populations are essential to detect strains with reduced immunity in humans and provide critical information for pandemic preparedness.

Cost-Effectiveness of Juluca for Human Immunodeficiency Virus Infection Treatment in Virologically Suppressed Adults in Taiwan.

OBJECTIVES: Although the efficacy of traditional 3-drug regimens for the treatment of HIV is well established, tolerability and toxicity concerns remain. New 2-drug regimens such as Juluca (dolutegravir [DTG]/rilpivirine [RPV]) offer noninferior efficacy versus 3-drug regimens (SWORD-1 and SWORD-2 studies), while reducing cumulative drug exposure and potentially long-term toxicities and drug-drug interactions. Here, we assess the cost-effectiveness of DTG/RPV for the treatment of HIV-1 for virologically suppressed adults in Taiwan. METHODS: A hybrid decision tree and Markov cohort state transition model was used to evaluate the expected economic costs and clinical outcomes associated with DTG/RPV and comparators. Model health states were defined by viral load and CD4 cell count. Efficacy and safety data were informed from SWORD-1 and SWORD-2 studies and the literature. The risk of long-term toxicities (cardiovascular disease, bone fractures, and chronic kidney disease) were included. Current branded drug acquisition prices were included, and healthcare costs informed by a bespoke costing study using National Health Insurance Research Database data. Incremental cost-effectiveness ratios were calculated and compared with a willingness-to-pay threshold of 2 times Taiwan's gross domestic product (NT$1 550 000). RESULTS: DTG/RPV was found to be a cost-saving regimen compared to 3 comparators (rilpivirine [RPV]/emtricitabine [FTC]/tenofovir disoproxil fumarate [TDF], dolutegravir [DTG]/abacavir [ABC]/lamivudine [3TC], and elvitegravir [EVG]/cobicistat [c]/emtricitabine [FTC]/tenofovir alafenamide [TAF]) and fell in the southwest quadrant of the cost-effectiveness plane where it is generating significant savings with a small decrement in lifetime quality-adjusted life-years (-0.005). It was, however, more expensive than efavirenz [EFV]/emtricitabine [FTC]/ tenofovir disoproxil fumarate [TDF]. CONCLUSIONS: DTG/RPV is cost-saving compared to RPV/FTC/TDF, DTG/ABC/3TC, and EVG/c/FTC/TAF, and provides comparable efficacy with reduced cumulative drug exposure.

Estimating HIV Management and Comorbidity Costs Among Aging HIV Patients in the United States: A Systematic Review.

BACKGROUND: As life expectancy of patients infected with human immunodeficiency virus (HIV) approaches that of the general population, the composition of HIV management costs is likely to change. OBJECTIVES: To (a) review treatment and disease management costs in HIV, including costs of adverse events (AEs) related to antiretroviral therapy (ART) and long-term toxicities, and (b) explore the evolving cost drivers. METHODS: A targeted literature review between January 2012 and November 2017 was conducted using PubMed and major conferences. Articles reporting U.S. costs of HIV management, acquired immunodeficiency syndrome (AIDS)-defining events, end of life care, and ART-associated comorbidities such as cardiovascular disease (CVD), chronic kidney disease (CKD), and osteoporosis were included. All costs were inflated to 2017 U.S. dollars. A Markov model-based analysis was conducted to estimate the effect of increased life expectancy on costs associated with HIV treatment and management. RESULTS: 22 studies describing HIV costs in the United States were identified, comprising 16 cost-effectiveness analysis studies, 5 retrospective analyses of health care utilization, and 1 cost analysis in a resource-limited setting. Management costs per patient per month, including routine care costs (on/off ART), non-HIV medication, opportunistic infection prophylaxis, inpatient utilization, outpatient utilization, and emergency department utilization were reported as CD4+ cell-based health state costs ranging from $1,192 for patients with CD4 > 500 cells/mm3 to $2,873 for patients with CD4 < 50 cells/mm3. Event costs for AEs ranged from $0 for headache, pain, vomiting, and lipodystrophy to $31,545 for myocardial infarction. The mean monthly per-patient costs for CVD management, CKD management, and osteoporosis were $5,898, $6,108, and $4,365, respectively. Improvements in life expectancy, approaching that of the general population in 2018, are projected to increase ART-related and AE costs by 35.4% and comorbidity costs by 175.8% compared with estimated costs with HIV life expectancy observed in 1996. CONCLUSIONS: This study identified and summarized holistic cost estimates appropriate for use within U.S. HIV cost-effectiveness analyses and demonstrates an increasing contribution of comorbidity outcomes, primarily associated with aging in addition to long-term treatment with ART, not typically evaluated in contemporary HIV cost-effectiveness analyses. DISCLOSURES: This analysis was sponsored by ViiV Healthcare, which had no role in the analyses and interpretation of study results. Ward, Sugrue, Hayward, and McEwan are employees of HEOR Ltd, which received funding from ViiV Healthcare to conduct this study. Anderson is an employee of GlaxoSmithKline and holds shares in the company. Punekar and Oglesby are employees of ViiV Healthcare and hold shares in GlaxoSmithKline. Lopes was employed by ViiV Healthcare at the time of the study and holds shares in GlaxoSmithKline.