Understanding Household Dynamics From the Ground Up: A Longitudinal Study From a Rural South African Setting.

Investigations into household structure in low- and middle-income countries (LMICs) provide important insight into how families manage domestic life in response to resource allocation and caregiving needs during periods of rapid sociopolitical and health-related challenges. Recent evidence on household structure in many LMICs contrasts with long-standing viewpoints of worldwide convergence to a Western nuclearized household model. Here, we adopt a household-centered theoretical and methodological framework to investigate longitudinal patterns and dynamics of household structure in a rural South African setting during a period of high AIDS-related mortality and socioeconomic change. Data come from the Agincourt Health and Socio-Demographic Surveillance System (2003-2015). Using latent transition models, we derived six distinct household types by examining conditional interdependency between household heads' characteristics, members' age composition, and migration status. More than half of households were characterized by their complex and multigenerational profiles, with considerable within-typology variation in household size and dependency structure. Transition analyses showed stability of household types under female headship, while higher proportions of nuclearized household types dissolved over time. Household dissolution was closely linked to prior mortality experiences-particularly, following death of a male head. Our findings highlight the need to better conceptualize and contextualize household changes across populations and over time.

Estimating seroprevalence of SARS-CoV-2 in Ohio: A Bayesian multilevel poststratification approach with multiple diagnostic tests.

Globally, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 59 million people and killed more than 1.39 million. Designing and monitoring interventions to slow and stop the spread of the virus require knowledge of how many people have been and are currently infected, where they live, and how they interact. The first step is an accurate assessment of the population prevalence of past infections. There are very few population-representative prevalence studies of SARS-CoV-2 infections, and only two states in the United States-Indiana and Connecticut-have reported probability-based sample surveys that characterize statewide prevalence of SARS-CoV-2. One of the difficulties is the fact that tests to detect and characterize SARS-CoV-2 coronavirus antibodies are new, are not well characterized, and generally function poorly. During July 2020, a survey representing all adults in the state of Ohio in the United States collected serum samples and information on protective behavior related to SARS-CoV-2 and coronavirus disease 2019 (COVID-19). Several features of the survey make it difficult to estimate past prevalence: 1) a low response rate; 2) a very low number of positive cases; and 3) the fact that multiple poor-quality serological tests were used to detect SARS-CoV-2 antibodies. We describe a Bayesian approach for analyzing the biomarker data that simultaneously addresses these challenges and characterizes the potential effect of selective response. The model does not require survey sample weights; accounts for multiple imperfect antibody test results; and characterizes uncertainty related to the sample survey and the multiple imperfect, potentially correlated tests.

A Double-Walled Tetrahedron with AgI 4 Vertices Binds Different Guests in Distinct Sites.

A double-walled tetrahedral metal-organic cage assembled in solution from silver(I), 2-formyl-1,8-naphthyridine, halide, and a threefold-symmetric triamine. The AgI 4 X clusters at its vertices each bring together six naphthyridine-imine moieties, leading to a structure in which eight tritopic ligands bridge four clusters in an (AgI 4 X)4 L8 arrangement. Four ligands form an inner set of tetrahedron walls that are surrounded by the outer four. The cage has significant interior volume, and was observed to bind anionic guests. The structure also possesses external binding clefts, located at the edges of the cage, which bound small aromatic guests. Halide ions bound to the silver clusters were observed to exchange in a well-defined hierarchy, allowing modulation of the cavity volume. The principles uncovered here may allow for increasingly more sophisticated cages with silver-cluster vertex architectures, with post-assembly tuning of the interior cavity volume enabling targeted binding behavior.

The Role of Dynorphin and the Kappa Opioid Receptor in Schizophrenia and Major Depressive Disorder: A Translational Approach.

The kappa opioid receptor (KOR) and its endogenous ligands dynorphins (DYN) have been implicated in the development or symptomatology of a variety of neuropsychiatric disorders. This review covers a brief history of the development of KOR agonists and antagonists, their effects in healthy volunteers, and the potential role of DYN/KOR dysfunction in schizophrenia and major depressive disorder from a translational perspective. The potential role of DYN/KOR dysfunction in schizophrenia is based on several lines of evidence. Selective KOR agonists induce affective states in healthy volunteers with similarities to the symptoms of schizophrenia. Studies have shown increased DYN in patients with schizophrenia, although the data have been mixed. Finally, meta-analytic data have shown that opioid antagonists are associated with reductions in the symptoms of schizophrenia. The potential role of DYN/KOR dysfunction in major depressive disorder is also based on a combination of preclinical and clinical data. Selective KOR agonists have shown pro-depressive effects in human volunteers, while selective KOR antagonists have shown robust efficacy in several preclinical models of antidepressant activity. Small studies have shown that nonselective KOR antagonists may have efficacy in treatment-resistant depression. Additionally, recent clinical data have shown that the KOR may be an effective target for treating anhedonia, a finding relevant to both schizophrenia and depression. Finally, recommendations are provided for translating preclinical models for schizophrenia and major depressive disorder into the clinic.

Twin epidemics: the effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010-2019.

BACKGROUND: Sub-Saharan African settings are experiencing dual epidemics of HIV and hypertension. We investigate effects of each condition on mortality and examine whether HIV and hypertension interact in determining mortality. METHODS: Data come from the 2010 Ha Nakekela population-based survey of individuals ages 40 and older (1,802 women; 1,107 men) nested in the Agincourt Health and socio-Demographic Surveillance System in rural South Africa, which provides mortality follow-up from population surveillance until mid-2019. Using discrete-time event history models stratified by sex, we assessed differential mortality risks according to baseline measures of HIV infection, HIV-1 RNA viral load, and systolic blood pressure. RESULTS: During the 8-year follow-up period, mortality was high (477 deaths). Survey weighted estimates are that 37% of men (mortality rate 987.53/100,000, 95% CI: 986.26 to 988.79) and 25% of women (mortality rate 937.28/100,000, 95% CI: 899.7 to 974.88) died. Over a quarter of participants were living with HIV (PLWH) at baseline, over 50% of whom had unsuppressed viral loads. The share of the population with a systolic blood pressure of 140mm Hg or higher increased from 24% at ages 40-59 to 50% at ages 75-plus and was generally higher for those not living with HIV compared to PLWH. Men and women with unsuppressed viral load had elevated mortality risks (men: adjusted odds ratio (aOR) 3.23, 95% CI: 2.21 to 4.71, women: aOR 2.05, 95% CI: 1.27 to 3.30). There was a weak, non-linear relationship between systolic blood pressure and higher mortality risk. We found no significant interaction between systolic blood pressure and HIV status for either men or women (p>0.05). CONCLUSIONS: Our results indicate that HIV and elevated blood pressure are acting as separate, non-interacting epidemics affecting high proportions of the older adult population. PLWH with unsuppressed viral load were at higher mortality risk compared to those uninfected. Systolic blood pressure was a mortality risk factor independent of HIV status. As antiretroviral therapy becomes more widespread, further longitudinal follow-up is needed to understand how the dynamics of increased longevity and multimorbidity among people living with both HIV and high blood pressure, as well as the emergence of COVID-19, may alter these patterns.

Dynamic Multicontrast X-Ray Imaging Method Applied to Additive Manufacturing.

We present a dynamic implementation of the beam-tracking x-ray imaging method providing absorption, phase, and ultrasmall angle scattering signals with microscopic resolution and high frame rate. We demonstrate the method's ability to capture dynamic processes with 22-ms time resolution by investigating the melting of metals in laser additive manufacturing, which has so far been limited to single-modality synchrotron radiography. The simultaneous availability of three contrast channels enables earlier segmentation of droplets, tracking of powder dynamic, and estimation of unfused powder amounts, demonstrating that the method can provide additional information on melting processes.

Idiopathic pulmonary fibrosis: a more common condition than you may think.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive incurable lung disease that affects a significant amount of people in the UK. Many health professionals have a limited understanding of IPF, which can result in a delayed diagnosis and inadequate care for individuals and their families. This article aims to provide an overview of IPF and help to enhance health professionals' understanding of the disease, thus contributing towards improving the care that IPF sufferers receive. This article provides a definition of IPF and explores its pathophysiology. It discusses the causes and risk factors for developing the condition, examines how IPF is diagnosed and details the treatment options available for IPF patients.

Should the SARS-CoV-2 vaccine be mandatory for nurses? An ethical debate.

The COVID-19 pandemic has had a devastating impact on the UK, as well as many other countries around the world, affecting all aspects of society. Nurses and other health and care professionals are a group particularly exposed to the virus through their work. Evidence suggests that vaccines form the most promising strategy for fighting this pandemic. Should vaccination against be mandatory for nurses and other health professionals? This article explores this question using an ethical framework.

Non-confirming replication of "Performance of InSilicoVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards," by Flaxman et al.

BACKGROUND: A verbal autopsy (VA) is an interview conducted with the caregivers of someone who has recently died to describe the circumstances of the death. In recent years, several algorithmic methods have been developed to classify cause of death using VA data. The performance of one method-InSilicoVA-was evaluated in a study by Flaxman et al., published in BMC Medicine in 2018. The results of that study are different from those previously published by our group. METHODS: Based on the description of methods in the Flaxman et al. study, we attempt to replicate the analysis to understand why the published results differ from those of our previous work. RESULTS: We failed to reproduce the results published in Flaxman et al. Most of the discrepancies we find likely result from undocumented differences in data pre-processing, and/or values assigned to key parameters governing the behavior of the algorithm. CONCLUSION: This finding highlights the importance of making replication code available along with published results. All code necessary to replicate the work described here is freely available on GitHub.

DALES, Drug Allergy Labels in Elective Surgical patients: a prospective multicentre cross-sectional study of incidence, risks, and attitudes in penicillin de-labelling strategies.

BACKGROUND: Penicillin allergy is associated with a range of poor health outcomes. Allergy testing can be made simpler by using a direct drug provocation test in patients at low risk of genuine allergy. This approach could allow population-level 'de-labelling'. We sought to determine the incidence and nature of penicillin allergy labels in UK surgical patients and define patient and anaesthetist attitudes towards penicillin allergy testing. METHODS: A prospective cross-sectional questionnaire study was performed in 213 UK hospitals. 'Penicillin allergic' patients were interviewed and risk-stratified. Knowledge and attitudes around penicillin allergy were defined in patients and anaesthetists. RESULTS: Of 21 219 patients, 12% (n=2626) self-reported penicillin allergy; 27% reported low-risk histories potentially suitable for a direct drug provocation test; an additional 40% reported symptoms potentially suitable for a direct drug provocation test after more detailed assessment. Of 4798 anaesthetists, 40% claimed to administer penicillin routinely when they judged the label low risk. Only 47% of anaesthetists would be happy to administer penicillin to a patient previously de-labelled by an allergy specialist using a direct drug provocation test; perceived lack of support was the most common reason for not doing so. CONCLUSIONS: At least 27% of patients with a penicillin allergy label may be suitable for a direct drug provocation test. Anaesthetists demonstrated potentially unsafe prescribing in patients with penicillin allergy labels. More than half of anaesthetists lack confidence in the results of a direct drug provocation tests undertaken by a specialist. Our findings highlight significant barriers to the effective implementation of widespread de-labelling in surgical patients.

Clusters of HIV Risk and Protective Sexual Behaviors in Agincourt, Rural South Africa: Findings from the Ha Nakekela Population-Based Study of Ages 15 and Older.

Understanding how sexual behaviors cluster in distinct population subgroups along the life course is critical for effective targeting and tailoring of HIV prevention messaging and intervention activities. We examined interrelatedness of sexual behaviors and variation between men and women across a wide age range in a rural South African setting with a high HIV burden. Data come from the Ha Nakekela population-based survey of people aged 15-85-plus drawn from the Agincourt Health and Socio-Demographic Surveillance System. We used latent class analysis of six sexual behavior indicators to identify distinct subgroup sexual behavior clusters. We then examined associations between class membership and sociodemographic and other behavioral risk factors and assessed the accuracy of a reduced set of sexual behavior indicators to classify individuals into latent classes. We identified three sexual behavior classes: (1) single with consistent protective behaviors; (2) risky behaviors; and (3) in union with lack of protective behaviors. Patterns of sexual behaviors varied by gender. Class membership was also associated with age, HIV status, nationality, and alcohol use. With only two sexual behavior indicators (union status and multiple sexual partners), individuals were accurately assigned to their most likely predicted class. There were distinct multidimensional sexual behavior clusters in population subgroups that varied by sex, age, and HIV status. In this population, only two brief questions were needed to classify individuals into risk classes. Replication in other situations is needed to confirm these findings.

Longitudinal analysis of body weight and average daily feed intake during the feedlot test period in Angus cattle.

The objectives of this study were to compare different models for analysing body weight (BW) and average daily feed intake (ADFI) data collected during a 70-day feedlot test period and to explore whether genetic parameters change over time to evaluate the implications of selection response. (Co)variance components were estimated using repeatability and random regression models in 2,071 Angus steers. Models included fixed effects of contemporary group, defined as herd-year-observation_date-age, with additive genetic and permanent environmental components as random effects. Models were assessed based on the log likelihood, Akaike's information criterion and the Bayesian information criterion. For both traits, random regression models (RRMs) presented a better fit, indicating that genetic parameters change over the test period. Using a two-trait RRM, the heritability from day 1 up to day 70 for BW increased from 0.40 to 0.50, while for ADFI, it decreased from 0.44 to 0.33. The genetic correlation increased from 0.53 at day 1 up to 0.79 at day 70. Selection based on an index assuming no change in genetic parameters would yield a 2.78%-3.13% lower selection response compared to an index using parameters estimated with RRMs and assuming these genetic parameters are correct. Results imply that it may be beneficial to implement RRMs to account for the change of parameters across the feedlot period in feed efficiency traits.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle.

BACKGROUND: Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions. RESULTS: The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15. CONCLUSIONS: Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

An integrated approach to processing WHO-2016 verbal autopsy data: the InterVA-5 model.

BACKGROUND: Verbal autopsy is an increasingly important methodology for assigning causes to otherwise uncertified deaths, which amount to around 50% of global mortality and cause much uncertainty for health planning. The World Health Organization sets international standards for the structure of verbal autopsy interviews and for cause categories that can reasonably be derived from verbal autopsy data. In addition, computer models are needed to efficiently process large quantities of verbal autopsy interviews to assign causes of death in a standardised manner. Here, we present the InterVA-5 model, developed to align with the WHO-2016 verbal autopsy standard. This is a harmonising model that can process input data from WHO-2016, as well as earlier WHO-2012 and Tariff-2 formats, to generate standardised cause-specific mortality profiles for diverse contexts. The software development involved building on the earlier InterVA-4 model, and the expanded knowledge base required for InterVA-5 was informed by analyses from a training dataset drawn from the Population Health Metrics Research Collaboration verbal autopsy reference dataset, as well as expert input. RESULTS: The new model was evaluated against a test dataset of 6130 cases from the Population Health Metrics Research Collaboration and 4009 cases from the Afghanistan National Mortality Survey dataset. Both of these sources contained around three quarters of the input items from the WHO-2016, WHO-2012 and Tariff-2 formats. Cause-specific mortality fractions across all applicable WHO cause categories were compared between causes assigned in participating tertiary hospitals and InterVA-5 in the test dataset, with concordance correlation coefficients of 0.92 for children and 0.86 for adults. The InterVA-5 model's capacity to handle different input formats was evaluated in the Afghanistan dataset, with concordance correlation coefficients of 0.97 and 0.96 between the WHO-2016 and the WHO-2012 format for children and adults respectively, and 0.92 and 0.87 between the WHO-2016 and the Tariff-2 format respectively. CONCLUSIONS: Despite the inherent difficulties of determining "truth" in assigning cause of death, these findings suggest that the InterVA-5 model performs well and succeeds in harmonising across a range of input formats. As more primary data collected under WHO-2016 become available, it is likely that InterVA-5 will undergo minor re-versioning in the light of practical experience. The model is an important resource for measuring and evaluating cause-specific mortality globally.

Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India.

BACKGROUND: Verbal autopsies with physician assignment of cause of death (COD) are commonly used in settings where medical certification of deaths is uncommon. It remains unanswered if automated algorithms can replace physician assignment. METHODS: We randomized verbal autopsy interviews for deaths in 117 villages in rural India to either physician or automated COD assignment. Twenty-four trained lay (non-medical) surveyors applied the allocated method using a laptop-based electronic system. Two of 25 physicians were allocated randomly to independently code the deaths in the physician assignment arm. Six algorithms (Naïve Bayes Classifier (NBC), King-Lu, InSilicoVA, InSilicoVA-NT, InterVA-4, and SmartVA) coded each death in the automated arm. The primary outcome was concordance with the COD distribution in the standard physician-assigned arm. Four thousand six hundred fifty-one (4651) deaths were allocated to physician (standard), and 4723 to automated arms. RESULTS: The two arms were nearly identical in demographics and key symptom patterns. The average concordances of automated algorithms with the standard were 62%, 56%, and 59% for adult, child, and neonatal deaths, respectively. Automated algorithms showed inconsistent results, even for causes that are relatively easy to identify such as road traffic injuries. Automated algorithms underestimated the number of cancer and suicide deaths in adults and overestimated other injuries in adults and children. Across all ages, average weighted concordance with the standard was 62% (range 79-45%) with the best to worst ranking automated algorithms being InterVA-4, InSilicoVA-NT, InSilicoVA, SmartVA, NBC, and King-Lu. Individual-level sensitivity for causes of adult deaths in the automated arm was low between the algorithms but high between two independent physicians in the physician arm. CONCLUSIONS: While desirable, automated algorithms require further development and rigorous evaluation. Lay reporting of deaths paired with physician COD assignment of verbal autopsies, despite some limitations, remains a practicable method to document the patterns of mortality reliably for unattended deaths. TRIAL REGISTRATION: ClinicalTrials.gov , NCT02810366. Submitted on 11 April 2016.

Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations.

BACKGROUND: Whole-genome sequence (WGS) data could contain information on genetic variants at or in high linkage disequilibrium with causative mutations that underlie the genetic variation of polygenic traits. Thus far, genomic prediction accuracy has shown limited increase when using such information in dairy cattle studies, in which one or few breeds with limited diversity predominate. The objective of our study was to evaluate the accuracy of genomic prediction in a multi-breed Australian sheep population of relatively less related target individuals, when using information on imputed WGS genotypes. METHODS: Between 9626 and 26,657 animals with phenotypes were available for nine economically important sheep production traits and all had WGS imputed genotypes. About 30% of the data were used to discover predictive single nucleotide polymorphism (SNPs) based on a genome-wide association study (GWAS) and the remaining data were used for training and validation of genomic prediction. Prediction accuracy using selected variants from imputed sequence data was compared to that using a standard array of 50k SNP genotypes, thereby comparing genomic best linear prediction (GBLUP) and Bayesian methods (BayesR/BayesRC). Accuracy of genomic prediction was evaluated in two independent populations that were each lowly related to the training set, one being purebred Merino and the other crossbred Border Leicester x Merino sheep. RESULTS: A substantial improvement in prediction accuracy was observed when selected sequence variants were fitted alongside 50k genotypes as a separate variance component in GBLUP (2GBLUP) or in Bayesian analysis as a separate category of SNPs (BayesRC). From an average accuracy of 0.27 in both validation sets for the 50k array, the average absolute increase in accuracy across traits with 2GBLUP was 0.083 and 0.073 for purebred and crossbred animals, respectively, whereas with BayesRC it was 0.102 and 0.087. The average gain in accuracy was smaller when selected sequence variants were treated in the same category as 50k SNPs. Very little improvement over 50k prediction was observed when using all WGS variants. CONCLUSIONS: Accuracy of genomic prediction in diverse sheep populations increased substantially by using variants selected from whole-genome sequence data based on an independent multi-breed GWAS, when compared to genomic prediction using standard 50K genotypes.

A General Age-Specific Mortality Model With an Example Indexed by Child Mortality or Both Child and Adult Mortality.

The majority of countries in Africa and nearly one-third of all countries require mortality models to infer the complete age schedules of mortality that are required to conduct population estimates, projections/forecasts, and other tasks in demography and epidemiology. Models that relate child mortality to mortality at other ages are important because almost all countries have measures of child mortality. A general, parameterizable component model (SVD-Comp) of mortality is defined using the singular value decomposition and calibrated to the relationship between child or child/adult mortality and mortality at other ages in the observed mortality schedules of the Human Mortality Database. Cross-validation is used to validate the model, and the predictive performance of the model is compared with that of the log-quadratic (Log-Quad) model, which is designed to do the same thing. Prediction and cross-validation tests indicate that the child mortality-calibrated SVD-Comp is able to accurately represent the observed mortality schedules in the Human Mortality Database, is robust to the selection of mortality schedules used for calibration, and performs better than the Log-Quad model. The child mortality-calibrated SVD-Comp can be used where and when child mortality is available but mortality at other ages is unknown.

Genotyping strategies of selection candidates in livestock breeding programmes.

Benefits of genomic selection (GS) in livestock breeding operations are well known particularly where traits are sex-limited, hard to measure, have a low heritability and/or measured later in life. Sheep and beef breeders have a higher cost:benefit ratio for GS compared to dairy. Therefore, strategies for genotyping selection candidates should be explored to maximize the economic benefit of GS. The aim of the paper was to investigate, via simulation, the additional genetic gain achieved by selecting proportions of male selection candidates to be genotyped via truncation selection. A two-trait selection index was used that contained an easy and early-in-life measurement (such as post-weaning weight) as well as a hard-to-measure trait (such as intra-muscular fat). We also evaluated the optimal proportion of female selection candidates to be genotyped in breeding programmes using natural mating and/or artificial insemination (NatAI), multiple ovulation and embryo transfer (MOET) or juvenile in vitro fertilization and embryo transfer (JIVET). The final aim of the project was to investigate the total dollars spent to increase the genetic merit by one genetic standard deviation (SD) using GS and/or reproductive technologies. For NatAI and MOET breeding programmes, females were selected to have progeny by 2 years of age, while 1-month-old females were required for JIVET. Genomic testing the top 20% of male selection candidates achieved 80% of the maximum benefit from GS when selection of male candidates prior to genomic testing had an accuracy of 0.36, while 54% needed to be tested to get the same benefit when the prior selection accuracy was 0.11. To achieve 80% of the maximum benefit in female, selection required 66%, 47% and 56% of female selection candidates to be genotyped in NatAI, MOET and JIVET breeding programmes, respectively. While JIVET and MOET breeding programmes achieved the highest annual genetic gain, genotyping male selection candidates provides the most economical way to increase rates of genetic gain facilitated by genomic testing.

Optimizing female allocation to reproductive technologies considering merit, inbreeding and cost in nucleus breeding programmes with genomic selection.

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilization and embryo transfer (JIVET) have been shown to accelerate genetic gain by increasing selection intensity and decreasing generation interval. Genomic selection (GS) increases the accuracy of selection of young candidates which can further accelerate genetic gain. Optimal contribution selection (OCS) is an effective method of keeping the rate of inbreeding at a sustainable level while increasing genetic merit. OCS could also be used to selectively and optimally allocate reproductive technologies in mate selection while accounting for their cost. This study uses stochastic simulation to simulate breeding programmes that use a combination of artificial insemination (AI) or natural mating (N), MOET and JIVET with GS. OCS was used to restrict inbreeding to 1.0% increase per generation and also to optimize use of reproductive technologies, considering their effect on genetic gain as well as their cost. Two Australian sheep breeding objectives were used as an example to illustrate the methodology-a terminal sire breeding objective (A) and a dual-purpose self-replacing breeding objective (B). The objective function used for optimization considered genetic merit, constrained inbreeding and cost of technologies where costs were offset by a premium paid to the seedstock breeder investing in female reproductive technologies. The premium was based on the cumulative discounted expression of genetic merit in the progeny of a commercial tier in the breeding programme multiplied by the proportion of that benefit received by the breeder. With breeding objective B, the highest premium of 64% paid to the breeder resulted in the highest allocation of reproductive technologies (4%-10% for MOET and 19%-54% for JIVET) and hence the highest annual genetic gain. Conversely, breeding objective A, which had a lower dollar value of the breeding objective and a maximum of 5% mating types for JIVET and zero for MOET were optimal, even when highest premiums were paid. This study highlights that the level of investment in breeding technologies to accelerate genetic gain depends on the investment of genetic improvement returned to the breeder per index point gain achieved. It also demonstrates that breeding programmes can be optimized including allocation of reproductive technologies at the individual animal level. Accounting for revenue to the breeder and cost of the technologies can facilitate more practical decision support for beef and sheep breeders.