Level Of Coverage Research Articles

Sustainability Assessment Tools for Dairy Supply Chains: A Typology

The dairy sector faces increasing pressure to adopt sustainable practices. Various tools have been developed to evaluate sustainability of the dairy supply chain. This paper provides an overview of these tools, highlighting their strengths and limitations regarding sustainability dimensions, indicators, and system boundaries. A systematic literature search identified 27 tools that were then categorized into a typology based on dimensions of sustainability, geographical applicability, and accessibility. In-depth analysis was conducted on six tools: Sustainability Assessment of Food and Agriculture (SAFA), Sustainability Monitoring and Assessment RouTine (SMART), Response-Inducing Sustainability Evaluation (RISE) 3.0 version, Swiss Agricultural Life Cycle Assessment (SALCAsustain), MOnitoring Tool for Integrated Farm Sustainability (MOTIFS), and Technology Impact and Policy Impact CALculations (TIPICAL). Assessment focused on the relevance of covered sustainability dimensions to the dairy sector, level of supply chain coverage, type of indicators, accessibility, and practicability. The review identified tools which integrate multiple sustainability aspects in a comprehensive way (SAFA and SMART) and tools offering accurate quantification of the impact on sustainability dimensions of the production system (SALCAsustain, RISE, MOTIFS, TIPICAL). Only two tools extend assessment past the farm gate (SAFA, SMART). Future users should select tools based on the specific objectives of measuring sustainability in dairy systems. This review contributes to the literature by addressing various aspects of sustainability assessment tools, by addressing the need for an integrated and comprehensive view, and by considering the entire dairy supply chain.

WPŁYW ZRÓZNICOWANEJ ZAWARTO ˙ SCI BIAŁKA I MOCZNIKA W MLEKU, JAKO BIOMERKERÓW ´ ENERGETYCZNO-BIAŁKOWEGO ZBILANSOWANIA DAWEK POKARMOWYCH, NA POZIOM WYBRANYCH CECH UZYTKOWO ˙ SCI MLECZNEJ KRÓW RASY POLSKIEJ ´ HOLSZTYNSKO-FRYZYJSKIEJ

The aim of the study was to assess the impact of varied levels of milk protein and urea content on selected milk production traits of Polish Holstein-Friesian cows. The research included 34,397 data sets related to daily milk production of Polish Holstein-Friesian cows. These animals were kept in 15 cattle herds located in the Mazovian and Podlasie voivodeships. In the first stage of the research, the animals were differentiated based on the level of urea in their milk and the percentage of protein. According to the adopted assumptions, the energy and protein balance level of feed rations was determined based on the concentration of urea and protein in the milk. Due to the level of urea, three cow groups were distinguished: <150, 150–250, and >250 mg · L-1. Depending on the concentration of protein in the milk, the following three groups of animals were determined: <3.2%, 3.2–3.6%, and >3.6%. The assessment of the impact of varied energy and protein balance levels in feed rations on selected milk production traits of cows was conducted in subsequent lactation periods, production level and fat to protein (F/P) groups. Four lactation periods were distinguished, which covered successive months of lactation: 1–3, 4–6, 7–10, and 11–18, three production groups, determined based on the following levels of daily milk yield: <20, 20–30, and >30 kg and as well three groups of cows with different F/P ratio in milk were distinguished: <1.2, 1.2–1.6, >1.6. In the next stage of the study, a detailed assessment was conducted on the impact of varied levels of energy and protein balance in feed rations on the analyzed milk production traits. The analyzed population of cows was divided into 9 groups based on the level of urea content (mg · L-1) and protein concentration (%), with varying levels of coverage of the protein and energy requirements of cows. The interdependencies between milk performance traits of cows fed diets with balanced levels of energy and protein and their peers, for whom the nutritional diets were differentiated based on energy-protein balance, were determined using Pearson correlation coefficients and linear regression. When assessing the energy supply of cows, the study showed that too low energy levels in diets lead to a decrease in the chemical composition of milk, while too high levels lead to a decrease in milk yield compared to peers fed optimally balanced diets. Milk from cows with inadequate energy and protein nutrition contained less fat and protein by 0.54% and 0.59%, respectively, compared to milk from cows fed optimally. On the other hand, excessive energy supply was accompanied by an increase in fat (+0.66%) and protein (+0.57%) concentration with a decrease in daily milk yield (-4,1 kg). When evaluating the level of protein coverage for cows, the study showed that an excess of protein in feed led to an increase in urea levels in milk. The level of urea in milk from cows fed with excess protein in their feed (>250 mg · L-1 and <3.2%; >250 mg · L-1 and >3.6%; >250 mg · L-1 and 3.2–3.6%) contained more urea per liter compared to milk from cows fed a balanced diet, with increases of 127, 107, and 109 mg, respectively.

Flood vulnerability mapping in an urban area with high levels of impermeable coverage in southern Brazil

Flood vulnerability mapping in an urban area with high levels of impermeable coverage in southern Brazil

Cone and fruit impacts on understory flammability depend on traits and forest floor coverage

BackgroundUnderstory flammability is affected by abscised plant tissue. Extensive research has shown how interspecific differences in leaf litter traits affect flammability; however, leaves represent only one component of the litter layer. Cones and fruit are also common constituents of the forest floor, yet surprisingly little is known about how flammability is affected by their presence. In this study, we ask how flammability is affected by cones and fruit trait differences, coverage differences, and varying species and coverage combinations. To address these questions, we compared cone and fruit morphological and chemical traits among longleaf pine, loblolly pine, shortleaf pine, sweetgum, post oak, and water oak. We also used burn trials to compare fire behavior of single and mixed-species treatments at three coverage levels (10% of plot area (low), 30% (medium), and 50% (high)) integrated within a common mixed-litter layer under field conditions in central Alabama, USA.ResultsLike other plant tissues, cone/fruit dry matter, carbon, and lignin content promote fuel consumption and flame height, while nitrogen suppresses flammability. Single-species treatments produced distinct patterns in fire behavior, with longleaf pine cones consistently showing higher percent fuel consumption, flame height, and maximum smoldering temperature than sweetgum capsular heads. Mixed-species treatment results were less consistent; however, at high coverage, a representative upland three-way mixture (longleaf pine + sweetgum + post oak) showed significantly greater fuel consumption and flame height relative to a bottomland three-way mixture (loblolly pine + sweetgum + water oak) at high coverage. Medium cone/fruit coverage maximized flammability in most single and multi-species treatments and produced non-additive fuel consumption in mixtures containing longleaf pine and sweetgum.ConclusionOur results confirm that individual species’ cone and fruit flammability often parallels that of litter. Fire behavior in mixture is generally driven by the most flammable constituent species, but this result changes with cone and fruit coverage. Collectively, these results indicate that cones/fruit identity and coverage play an important role in understory flammability and should be integrated into fire behavior modeling efforts in monocultures and mixtures.

BbSelect - An Open-Source Tool for Performing a 3D Pharmacophore-Driven Diverse Selection of R-Groups.

The design of compounds during hit-to-lead often seeks to explore a vector from a core scaffold to form additional interactions with the target protein. A rational approach to this is to probe the region of a protein accessed by a vector with a systematic placement of pharmacophore features in 3D, particularly when bound structures are not available. Herein, we present bbSelect, an open-source tool built to map the placements of pharmacophore features in 3D Euclidean space from a library of R-groups, employing partitioning to drive a diverse and systematic selection to a user-defined size. An evaluation of bbSelect against established methods exemplified the superiority of bbSelect in its ability to perform diverse selections, achieving high levels of pharmacophore feature placement coverage with selection sizes of a fraction of the total set and without the introduction of excess complexity. bbSelect also reports visualizations and rationale to enable users to understand and interrogate results. This provides a tool for the drug discovery community to guide their hit-to-lead activities.

Basis path coverage testing of MPI programs based on multi-task evolutionary optimization

A Message-Passing Interface (MPI) program usually consists of several processes, and a target path of this program is composed of a target sub-path selected in each process. However, there may be coverage conflict between different target sub-paths in the target path, and there is currently no effective approach to avoid this problem. Therefore, this paper proposes an approach of basis path coverage testing of MPI programs based on multi-task evolutionary optimization, which is used to generate a test case set that meets the criteria of branch and sentence coverage. Firstly, the proposed approach samples a certain number of representative test inputs, and calculates the coverage level of each test input for each target sub-path in the target path, which is used to group the target sub-paths with coverage conflict. Then, we construct an optimization model for each group of the target sub-paths, which can guide test case generation with high effectiveness. Finally, each optimization model is solved by an evolutionary algorithm, and the efficiency of solving these optimization models is improved based on a multi-task framework. The proposed approach is applied to basis path coverage testing of seven benchmark MPI programs under test, and compared with several state-of-the-art approaches. Experimental results indicate that the proposed approach has significant advantages in test case generation, as well as performs good scalability.

The influence of health insurance on coverage of a country’s population with medical services

One of the effective ways to increase the level of population coverage with medical services is health insurance. The paper aims to determine what type of health insurance (compulsory, social, or voluntary) has the greatest impact on a country’s ability to provide large-scale and timely medical services to citizens, as measured by the number of unmet needs for medical examination, treatable and preventable mortality. The control variables included a country’s population size, the level of economic well-being, and the scale of the public health system (number of doctors and hospital beds) based on EUROSTAT data for all 27 EU countries in 2012–2021. Modelling (regression models of panel data with fixed and random effects in STATA 18, Wald test, Hausman test, Breusch and Pagan test) proved that only one of three researched types of insurance – voluntary health insurance – positively influences a country’s ability to provide large-scale and timely medical services to citizens: an increase in its volume by 1% leads to a decrease in unmet needs in medical examination on average across all EU countries by 0.26%, treatable mortality rate by 0.08%, preventive mortality rate by 0.27%. The influence of the other two types – compulsory and social – was not confirmed (received regression coefficients for these variables are not statistically significant). This emphasizes the importance of citizens’ conscious attitude to their health (due to the increase in voluntary health insurance) both in strengthening public health and in ensuring faster and better access to medical services.

Coverage, repulsion, and reactivity of hydrogen on High-Entropy alloys

Modeling hydrogen evolution reaction (HER) activity probability on IrPdPtRhRu(111) high-entropy alloys. Determining hydrogen coverages based on ligand effects and generalized hydrogen–hydrogen repulsion.The rate of H2 formation is highly impacted by the level of hydrogen coverage on the catalyst surface. In search of optimal catalytic properties high-entropy alloys (HEA) are promising candidates that utilize the compositional space of multiple elements. Based on simulations of HEA model (111) surfaces with a range of hydrogen coverages, distributions of binding energies are used to construct a framework that approximates the probability that adsorbed hydrogen may lead to the formation of H2 as a function of applied potential. By optimizing the alloy compositions for the highest activity probability at given potentials the best and most efficient catalyst candidates for HER can be identified. Treating hydrogen–hydrogen repulsion effects and binding energy separately, we find that the repulsion is larger for HEAs than for pure metals. Differing isotherm slopes in the mean adsorption and desorption energies demonstrate a possible hysteresis for hydrogen adsorption on HEAs.

Exploring Acute Kidney Injury Following Aortic Dissection: A Comprehensive Review of Machine Learning Models for Predicting Risk, Management Strategies, Complications, and Racial and Gender Disparities.

Both types of aortic dissection (AD), Stanford type A and type B, can result in complications such as acute kidney injury (AKI) and aortic rupture. Renal complications in AD arise from compromised renal perfusion affecting the renal arteries. Understanding the intricate connection between AD and AKI is crucial for navigating the complexities of tailored treatment and formulating specific management plans. Concerning machine learning models, in patients with type A aortic dissection, factors such as decreased platelet count on admission, increased D-dimer level, longer cardiopulmonary bypass duration, elevated white blood cell levels, the need for blood transfusion, longer aortic clamp time, extended surgery duration, advanced age, and an elevated body mass index were positively associated with the development of AKI. For the risk of AKI after type B aortic dissection, elevated Nt-pro brain natriuretic peptide, prolonged activated partial thromboplastin time, elevated admission systolic blood pressure, and a higher contrast agent requirement during operative repair were found to predict the risk. Male gender was associated with a higher risk of AKI, and nonwhite race was linked to a higher risk of AKI, a greater likelihood of requiring more urgent procedures, and lower levels of insurance coverage. The treatment of AKI following AD requires a multifaceted approach. Identifying and addressing the underlying cause, such as low blood pressure, renal artery involvement, or medication-induced injury, is crucial for effective management and preventing further kidney damage. Maintaining proper fluid balance is essential for improving renal perfusion, but careful monitoring is necessary to avoid complications. The evolving landscape of research, particularly in biomarkers and AI programs, reveals a promising role in predicting the risk for and managing AKI post-AD.

Unwelcomed guests: Impact of deer harvest on corn and soybean wildlife damage

While wildlife damages are a relatively small part of crop insurance claims in the United States, reported damages from wildlife are growing and producers are concerned this issue is getting worse. Wildlife agencies advocate for hunting as a control to wildlife damages to crops but to our knowledge, no study has econometrically explored if hunting could reduce crop damage. Therefore, we analyze if county-level white-tailed deer (Odocoileus virginianus) harvest and other factors like habitat and field fragmentation are associated with corn and soybean acres being indemnified due to wildlife damages in Tennessee. We estimate a fractional probit model using crop insurance data to measure crop damages and a county-level white-tailed deer harvest dataset. We find a higher coverage level of a policy increases the likelihood of both corn and soybean acres being indemnified due to wildlife damage. We also find white-tailed deer harvest during the period post-harvest in the previous crop year (November through January) slightly decreases the likelihood of a claim being made due to wildlife damage for corn but was not found to mitigate losses to soybeans. The whitetail hunting season appears to align better with corn production to reduce crop losses than with soybeans. This study will be useful for wildlife and crop agencies in state and federal governments to develop policies to more effectively utilize hunting to reduce crop insurance claims from wildlife damages.

Modelling the cost of engage & treat and test & treat strategies towards the elimination of lymphatic filariasis in Ghana.

Despite several years of LF-MDA implementation, Ghana still has some districts with mf prevalence >1%, partly due to poor treatment coverage levels resulting from non-participation in MDA. To address the challenges, we implemented an Engage & Treat (E&T) and Test & Treat (T&T) strategies for individuals who miss or refuse MDA respectively, in a hotspot district, enabling us to reach many of those who seldom, or never, take part in MDA. This financial cost study was undertaken to analyse data on the LF-MDA, E&T and T&T implementation in 2021 and the financial cost to inform the rollout of the E&T and T&T as mop-up strategies in future LF-MDAs. This costing study analysed cost data from the 2021 LF-MDA implementation activities carried out by the Neglected Tropical Diseases (NTD) programme of the Ghana Health Service and the SENTINEL study, carried out in Ahanta West district for the two interventions (i.e., E&T and T&T). The 2021 Ghana Population and Housing Census data was used to estimate the LF-MDA-eligible population. The financial cost per person treated was estimated and these costs were applied to the projected population to obtain the financial cost for subsequent years. Implementing MDA mop-up strategies either through the E&T or T&T to improve coverage comes at an additional cost to the elimination goals. For example, in 2024 the projected cost per person treated by the routine LF-MDA is estimated at US$0.83. The cost using the integrated LF-MDA and the E&T, T&T led by the NTD programme or T&T integrated into the health system was estimated at US$1.62, US$2.88, and US$2.33, respectively, for the same year. Despite the increased cost, the proposed combined LF-MDA and mop-up strategies will have a higher estimated population treated for 2024 (i.e., 1,392,211) compared to the routine LF-MDA approach (i.e., 988,470) for the same year. Combining LF-MDA with E&T/T&T mop-up strategies, despite their high costs, may provide NTD Programmes with the options of improving treatment coverage and reaching the LF elimination target sooner, given that the routine LF-MDA alone approach has been implemented for many years with some districts yet to reach the elimination targets.

Toward granular search-based automatic unit test case generation

Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of random or search-based algorithms. Despite their effectiveness, these approaches aim at creating tests by solely optimizing metrics like code coverage, without ensuring that the resulting tests have granularities that would allow them to verify both the behavior of individual production methods and the interaction between methods of the class under test. To address this limitation, we propose a two-step systematic approach to the generation of unit tests: we first force search-based algorithms to create tests that cover individual methods of the production code, hence implementing the so-called intra-method tests; then, we relax the constraints to enable the creation of intra-class tests that target the interactions among production code methods. The assessment of our approach is conducted through a mixed-method research design that combines statistical analyses with a user study. The key results report that our approach is able to keep the same level of code and mutation coverage while providing test suites that are more structured, more understandable and aligned to the design principles of unit testing.

Impact of Yoga Awareness on Transmission Dynamics of Communicable Diseases: SIR Model Analysis

Communicable diseases are major health problems that affect the whole economy of the na-tion. So it becomes the prime agenda of developed and developing countries to educate peo-ple about disease dynamics and control strategies. Due to changes in people’s living styles, disease treatment modality has been changed. So, we have introduced Yoga awareness as control strategy which includes Ahar, Vihar, Achar and Vichar. They are means for achiev-ing the physical, mental, social and spiritual well-being. Our main aim is to model the role of Yoga awareness in controlling the disease dynamics. It maintains the physical fitness of practitioners and improve the whole metabolism system of the human body. In this work, the previous SIR model is modified by incorporating a new awareness transmission rate β 1 to the existing model. Real life situation data of Yoga aware and aware infected individuals were col-lected from different Yoga centers of Sudurpashchim province, Nepal and analyzed by using mathematical techniques. Stability analysis of governing by ordinary differential equations showed that model is stable. Yoga awareness reproduction number Ra was calculated by next-generation matrix method. Sensitivity analysis of Ra and concerning parameters indicate that Ra decreases with an increase in Yoga awareness coverage level. Also, the recovery rate has the opposite relation with Ra which indicates that the recovery period also decreases with an increase in awareness coverage. Local and global stability analysis showed that disease-free equilibrium exists when Ra < 1 and endemic equilibrium exists when Ra > 1. Numerical simulations also support the analytical results and suggest that Yoga awareness has a positive influence on controlling disease d ynamics. The increase in the coverage of awareness leads to reduced susceptibility and infectivity. So propagation of disease can be controlled by Yoga awareness.

Herbicide runoff from a soil with different levels of sugarcane straw coverage in Brazil

This study evaluates the effects of different levels of sugarcane straw on the soil surface on the transport by runoff water of four herbicides: ametryn, diuron, hexazinone, and sulfentrazone. Two runoff experiments were conducted in a set of nine experimental plots. In the first experiment, sugarcane was cultivated and no straw was applied to the soil. In the second experiment, sugarcane was cultivated with straw levels of 0, 9, or 18 Mg ha-1 on the soil surface. The runoff water from natural rainfall was collected in reservoirs at the lower end of each plot on different occasions following the application of the herbicides to the plots. The total volume of runoff water collected from the plots was dependent on the coverage of the soil by straw, in the sequence: 0 > 9 > 18 Mg ha-1. For the herbicides hexazinone and sulfentrazone, which are molecules of high solubility in water, increasing the amount of straw on the soil produced an increase in the fraction of the applied dose appearing in the collected runoff water. However, for diuron and ametryn, which have low solubility in water, the presence of straw did not influence the amount found in the collected runoff water.

Test Coverage in Microservice Systems: An Automated Approach to E2E and API Test Coverage Metrics

Test coverage is a critical aspect of the software development process, aiming for overall confidence in the product. When considering cloud-native systems, testing becomes complex, as it becomes necessary to deal with multiple distributed microservices that are developed by different teams and may change quite rapidly. In such a dynamic environment, it is important to track test coverage. This is especially relevant for end-to-end (E2E) and API testing, as these might be developed by teams distinct from microservice developers. Moreover, indirection exists in E2E, where the testers may see the user interface but not know how comprehensive the test suits are. To ensure confidence in health checks in the system, mechanisms and instruments are needed to indicate the test coverage level. Unfortunately, there is a lack of such mechanisms for cloud-native systems. This manuscript introduces test coverage metrics for evaluating the extent of E2E and API test suite coverage for microservice endpoints. It elaborates on automating the calculation of these metrics with access to microservice codebases and system testing traces, delves into the process, and offers feedback with a visual perspective, emphasizing test coverage across microservices. To demonstrate the viability of the proposed approach, we implement a proof-of-concept tool and perform a case study on a well-established system benchmark assessing existing E2E and API test suites with regard to test coverage using the proposed endpoint metrics. The results of endpoint coverage reflect the diverse perspectives of both testing approaches. API testing achieved 91.98% coverage in the benchmark, whereas E2E testing achieved 45.42%. Combining both coverage results yielded a slight increase to approximately 92.36%, attributed to a few endpoints tested exclusively through one testing approach, not covered by the other.

Density functional theory studies on dehydrogenation of methanol to formaldehyde on Pt(1 1 1) surface at different coverage

Platinum metal exhibits excellent catalytic activity and selectivity in many important chemical reactions. In this paper, density functional theory is used to study the adsorption configurations of oxygen in methanol on Pt(111) surface and dehydrogenation reaction (CH3OH → CH2O) at different coverage. It is found that methanol molecules prefer to adsorb at the top position of Pt(111) at various coverage levels. With the coverage increases, the adsorption capacity of methanol decreases rapidly, and then tends to flatten until the coverage reaches 1/6. The product of CH2O is formed by two-step dehydrogenation process. The energy barrier for both dehydrogenations increase first and then decreases with increasing coverage. The lowest energy barrier for both dehydrogenations occurs on the Pt(111) surface with coverage of 1/6 (Ea, OH = 0.66 eV, Ea, CH = 0.16 eV). Therefore, coverage of 1/6 is the optimal coverage for CH3OH generating CH2O on the Pt(111) surface.

Current Status of Birth Registration Practice in Nepal

Birth registration is an essential element of civil registration and vital statistics which provide a legal identity and recognize the rights of an individual. In Nepal, birth registration has a long history starting from the Village Panchayat Act 1962 which was the first act with a provision for a birth certificate. Despite the over half-century experience of birth registration efforts, challenges to universal birth certificate coverage remain present, especially among the rural population. This research will investigate the current practices of birth registration in Nepal based on the findings of the National Population and Housing Census 2021. The analysis will show respective rates of birth certificate issuance across the regions, provinces, and development districts. Some areas show remarkable success in birth registration, while others struggle to reach significant coverage levels. The experience shows the critical role of government responsiveness to the development of birth registration which is especially important for rural areas and districts with significant rural populations. In this light, targeted efforts and outreach campaigns are necessary to eliminate barriers, thus guaranteeing equal access to birth registration for all children in Nepal.

High SARS-CoV-2 incidence and asymptomatic fraction during Delta and Omicron BA.1 waves in The Gambia

Little is known about SARS-CoV-2 infection risk in African countries with high levels of infection-driven immunity and low vaccine coverage. We conducted a prospective cohort study of 349 participants from 52 households in The Gambia between March 2021 and June 2022, with routine weekly SARS-CoV-2 RT-PCR and 6-monthly SARS-CoV-2 serology. Attack rates of 45% and 57% were seen during Delta and Omicron BA.1 waves respectively. Eighty-four percent of RT-PCR-positive infections were asymptomatic. Children under 5-years had a lower incidence of infection than 18-49-year-olds. One prior SARS-CoV-2 infection reduced infection risk during the Delta wave only, with immunity from ≥2 prior infections required to reduce the risk of infection with early Omicron lineage viruses. In an African population with high levels of infection-driven immunity and low vaccine coverage, we find high attack rates during SARS-CoV-2 waves, with a high proportion of asymptomatic infections and young children remaining relatively protected from infection.

Sand Supply Affects Wind Erosion Efficiency and Sand Transport on Sand-Cemented Body Mulch Bed

Sand-cemented bodies (SCBs) are naturally distributed in some interdune corridors in the central Taklimakan Desert, northwest China. In this study, field-collected SCB particles were used as the experimental material, and wind tunnel experiments were conducted with different sand supplies, wind velocities, and SCB coverages to evaluate SCB wind erosion efficiency and vertical mass flux. The results showed that wind erosion efficiency decreased as SCB coverage increased. When the SCB coverage was above 40%, sand deposition processes occurred only under saturated sand flow, while sand transport remained unaffected by increases in SCB coverage under unsaturated sand flow. Under saturated flow, the highest concentrations of transported sand were found at 0–6 cm above the surface, and the main sand bed process was deposition. The sand bed process changed from aeolian erosion to deposition with increasing SCB coverage and tended to remain stable until the SCB coverage exceeded 40%. By contrast, under unsaturated sand flow, the sand bed process was primarily aeolian erosion, and the highest concentrations of transported sand were found at 0–4 cm above the surface. At high SCB coverage levels (more than 40%), a general balance between aeolian erosion and deposition processes was reached. In summary, increasing SCB coverage had a significant impact on surface wind erosion processes. Thus, SCBs can be used as a novel sand retention material.

Factors influencing United States cattle producers use of livestock risk protection

AbstractUnited States cattle producers have various government‐sponsored programs to protect against weather and disease related risks, but livestock risk protection (LRP) insurance is the only program that protects against price risk. However, adoption of LRP insurance is low even though cattle price declines are the primary cause of economic loss, and LRP premium subsidies have recently been increased. Therefore, the objective of this study is to explore how informational nudges about receiving an indemnity payment, LRP contract characteristics, and individual risk preferences affect the use of LRP. Producer survey results were estimated using a Cragg model to determine the factors affecting producers’ likelihood of purchasing LRP and the number of head they would insure. Producers were more likely to purchase 100% LRP coverage and would also insure more head at 100% coverage when compared to lower coverage levels. We found providing information on the probability of receiving an indemnity did not impact LRP purchasing decisions. However, counter to expectations, producers were more likely to buy LRP when the randomly provided cattle prices in the survey were successively increasing each month, and if participants considered themselves more willing to take risks in their cattle operation. Results provide insights into behavioral factors affecting LRP participation which could help inform future insurance policies.