Input Costs Research Articles

Cost-effectiveness of first-line systemic therapies for unresectable hepatocellular carcinoma.

To examine the cost-effectiveness of first-line systemic therapies recommended by the National Comprehensive Cancer Network guidelines for Unresectable Hepatocellular Carcinoma (uHCC) from the US social and payer's perspective. A cost-effectiveness analysis was conducted using a three-state partitioned survival model to assess the cost-effectiveness of atezolizumab plus bevacizumab, tremelimumab plus durvalumab, durvalumab, lenvatinib and sorafenib as first-line treatments for uHCC. Clinical efficacy was derived from a published network meta-analysis. Cost and utility inputs were collected from literature. Main outcomes measured were quality-adjusted life year (QALY), and incremental cost-effectiveness ratio (ICER). Univariate and probabilistic sensitivity analyses, as well as scenario analyses were performed. Over a 10-year time horizon, atezolizumab plus bevacizumab yielded the highest QALYs. Compared to sorafenib, atezolizumab plus bevacizumab, tremelimumab plus durvalumab and lenvatinib had ICERs of $196 704/QALY, $800 755/QALY and $2 032 756/QALY, respectively. Sorafenib was dominated by durvalumab due to lower QALYs and higher costs. At a willingness-to-pay threshold of $150 000/QALY, probabilistic sensitivity analysis revealed that durvalumab had a 99.96% probability of providing the highest net monetary benefit. At a willingness-to-pay threshold of $150 000/QALY, durvalumab is likely the most cost-effective first-line systemic therapy for uHCC compared to sorafenib. Although atezolizumab plus bevacizumab yielded the highest QALYs, their ICERs exceeded the commonly accepted cost-effectiveness threshold ($150 000$ per QALY gained). These findings can inform clinical decision-making, resource allocation and future research priorities in managing uHCC.

Study on Cost and Returns of Cash Crops in Sirmour District, Himachal Pradesh, India

The present study examines the cost and returns of major cash crops raised by different category of farmers in district Sirmour, Himachal Pradesh. The study also identified the different production problems faced by farmers using weighted rank method. Two stage stratified random sampling technique was followed to select a sample of villages and the ultimate farmers. A random sample of 60 farmers was chosen for the study. The major findings revealed that production of vegetables varied from 6.42 qtl for peas to as high as 25.93 qtl of tomato per farm. Garlic being a spice crop recorded the production of 14.37 quintal per farm. In the study, per hectare cost of cultivation was found to be highest for tomato, i.e., Rs. 34200, followed by garlic (Rs. 26134) and beans (Rs. 15427) and lowest for peas (Rs. 11247), The per hectare net return was found to be higher for garlic crop (Rs.115066) when compared to tomato crop (Rs. 55785), beans and peas (Rs. 17108 to Rs. 6703). Therefore, garlic crop was found to be the most profitable crop with the net return of Rs. 115066 which was more and double of profit earned from tomato (Rs. 55785), peas (Rs. 6703) and beans (Rs. 17108). Similarly, the cost of cultivation was found to be highest for the large farmers and the per hectare net return also seemed to be the highest for the large farmers. Likewise, gross returns were also found highest for large farmers than that of small farmers. Further, the study revealed that major production problems faced by the farmers were availability of quality seed, high cost of inputs which were rated at top, followed by monkey & stray animals, quality of seed not available, high cost of inputs and high incidence of pest and pesticides etc. In order to increasing farm production and to minimise operational costs, the availability of high yielding variety seeds, reasonable prices of inputs like seed, fertilizers, pesticides etc., may enhance the farmers’ net return and income.

Exploring Feed Efficiency in Beef Cattle: From Data Collection to Genetic and Nutritional Modeling

Increasing feed efficiency in beef cattle is critical for meeting the growing global demand for beef while managing rising feed costs and environmental impacts. Challenges in recording feed intake and combining genomic and nutritional models hinder improvements in feed efficiency for sustainable beef production. This review examines the progression from traditional data collection methods to modern genetic and nutritional approaches that enhance feed efficiency. We first discuss the technological advancements that allow precise measurement of individual feed intake and efficiency, providing valuable insights for research and industry. The role of genomic selection in identifying and breeding feed-efficient animals is then explored, emphasizing the benefits of combining data from multiple populations to enhance genomic prediction accuracy. Additionally, the paper highlights the importance of nutritional models that could be used synergistically with genomic selection. Together, these tools allow for optimized feed management in diverse production systems. Combining these approaches also provides a roadmap for reducing input costs and promoting a more sustainable beef industry.

Constraints Encountered by Groundnut Growers in Adopting Recommended TNAU Groundnut Production Technologies in Villupuram District

Background: Groundnut (Arachis hypogaea L.) is a vital crop for the agricultural economy in Villupuram district, Tamil Nadu. Despite the Tamil Nadu Agricultural University’s (TNAU) recommended production technologies aimed at improving yield and sustainability, adoption rates among groundnut growers remain low. This study investigates the challenges faced by these farmers in adopting these technologies. Methods: The study employs an ex-post facto research design, focusing on Melmalayanur and Vallam blocks within Villupuram district. A total of 120 groundnut growers were randomly selected from four villages. Primary data was collected using a structured interview schedule, while secondary data was sourced from relevant agricultural reports and publications. Constraints faced by farmers were analyzed using Garrett’s ranking technique. Result: The study identified key constraints impacting technology adoption, ranked by severity. Non-sremunerative prices and price fluctuations emerged as the most significant barrier, followed by high input costs and inadequate credit facilities. Other notable challenges included a lack of timely and appropriate extension services, insufficient technical know-howand pest and disease infestations. Scarcity and high wages of labor, inadequate processing machinesand delays in the availability of inputs further hindered adoption rates.

Using Aquaculture Waste Sludge and Agricultural By-products to Produce Organic Fertilizer

The study was conducted to turn aquaculture sludge and agricultural by-products into organic fertilizer as part of the circular production. The main raw materials included sludge from catfish ponds after harvest and organic materials from agricultural by-products (25% from growing cordyceps, 25% from growing oyster mushrooms, 25% from peanut shells, and 25% from coconut fiber). The aquaculture sludge (AS) and agricultural by products (ABP) are mixed at five different ratios: 10% AS + 90% ABP; 30% AS + 70% ABP; 50% AS + 50% ABP; 70% AS + 30% ABP, and 90% AS + 10% ABP. The results showed that the experiment with the ratio of 30% AS + 70% ABP optimized the decomposition of organic compounds and produced organic fertilizer with higher nutrient content than the other four mixing ratios. Comparing the quality of organic fertilizer produced with the organic fertilizer quality standards of the Ministry of Agriculture and Rural Development, 15/18 biochemical indicators have met the regulations. The results of the study can provide a guideline for the local people to optimize organic fertilizer production utilizing aquaculture sludge and agricultural byproducts, save input costs for agricultural production, and contribute to reducing waste to the natural environment.

Strategies to scale up the Technical, Allocative and Economic Efficiency of Major Millet Growing Farmers in India – A Primal System Approach

Millet farming, a sustainable and economically viable option for farmers, providing resilience against climate variability and market fluctuations. Despite the increasing significance of millets in agriculture, there is a notable research gap concerning the efficiency of their cultivation and its impact on input demand and costs. This study leverages data from CCPC for the AY 2021-22, focusing on major millets—Bajra, Jowar, and Ragi cultivated across various Indian states. The research aims to understand the technical, allocative, and economic inefficiencies in millet farming to enhance productivity and resource utilization. It is hypothesized that inefficiencies in millet cultivation significantly impact input demand and cultivation costs, and addressing these inefficiencies can lead to improved agricultural practices and yields. Employing primal Cobb-Douglas production function showed that human labor, seed quantity, and fertilizers positively impact millet cultivation. Technical inefficiency is a major issue with Bajra farmers in Gujarat, Haryana, Maharashtra, Rajasthan and Uttar Pradesh. For Jowar, farmers in Andhra Pradesh, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan and Tamil Nadu are facing significant inefficiencies. In contrast, Karnataka and Odisha efficiently produce Ragi. Allocative inefficiency is noted in the over-utilization of animal and machine labor and fertilizers in Bajra cultivation, while these inputs are under-utilized in Jowar and Ragi cultivation. Both technical and allocative inefficiencies lead to increased input demand and higher cultivation costs across all three millets. The findings underscore the importance of state-specific strategies to address inefficiencies. These insights can guide policymakers in developing customized strategies to optimize millet cultivation, enhance yields and reduce costs.

Ifs Model Determinant in Sepahijala District of Tripura

The present study was undertaken to study the determinant for adoption of different farming system and major constraints faced by the respondents in the selected area. The research work was conducted under Charilam and Boxanagar blocks and from each block six villages were selected. Total 120 respondents were selected by adopting purposive stratified simple random sampling technique. The results of the study reveal that majority (59.00 per cent) of the respondents were of middle age, out of that 96 per cent were male respondents; married are 96.70 per cent; majority (45.00 per cent) respondents were up to middle school and 45.00 per cent respondents lives in semi-pucca house; majority (62.00 per cent) respondents were medium (2.00 to 3.50 ha) land holding. 71.00 per cent of the respondents were medium (4 to 8 family members); majority (65.80 per cent) were engaged under agriculture and majority (70.80 per cent) respondents were having experience of 7 to 11 years. During the research work total 8 IFS were identified in the study area viz; paddy + potato + dairy; paddy + tomato + dairy; paddy + potato + fishery + duckery; paddy + potato + fishery + piggery; paddy + brinjal + fishery + dairy; paddy + brinjal + fishery + poultry; paddy + cabbage + dairy; paddy + cabbage + dairy + vermicompost; out of that IFS-III recorded as highest contribution, followed by IFS-IV towards the benefit: cost ratio recorded as 3.31 and 3.30, respectively. Also, the age, education, land holding, experience and perception of the farmer contributed significant role for the adoption of integrated farming system. High input cost and scarcity of family labour were the major constraints faced by farmers. Government subsidies must released the enormous amount / number with low interest rate of bank loans; while the enterprise comprising of crops, livestock and fishery turns out to be remunerative for enhancing the income as well as increasing the employment opportunities to farmers.. KEYWORDS :Integrated farming system (IFS), Determinant, Economics, Respondents, Adoption, Income.

Assessments of Challenges and Opportunities for Practicing Irrigated Rice Production in Ethiopia

Rice production in Ethiopia, though not traditionally a staple, has become a key focus in the country’s efforts to enhance food security and reduce dependency on imports. Despite favorable agroecological conditions for rice farming, productivity remains low due to several challenges, including inadequate access to improved seeds, irrigation systems, and modern mechanization. This study evaluates the challenges and opportunities for practicing irrigated rice production in Ethiopia, analyzing both challenges and opportunities through a mixed-methods approach. Primary data was collected via field surveys, key informant interviews, and focus group discussions with farmers, agricultural experts, and policymakers across diverse regions. Key challenges include poor water management, limited adoption of modern technologies, high input costs, weak market access, climate variability, and infrastructure limitations. However, Ethiopia's diverse agroecological zones and government support provide opportunities for sustainable rice cultivation, particularly through improved irrigation, adoption of modern technologies, and enhanced market linkages. The study concludes that a comprehensive, multi-faceted approach involving government, NGOs, and farmers is essential to unlocking the potential of irrigated rice production in Ethiopia. Recommendations include improving water management, promoting public-private partnerships, expanding access to credit, and implementing climate-smart agricultural strategies to boost rice production and enhance food security.

COTTON FARMERS' PERCEIVED RISK AND INCOME VARIABILITY AFFECTED BY COMMODITY DERIVATIVE MARKETS: A CASE STUDY ON ODISHA (INDIA)

Agricultural production, particularly cotton farming, is highly vulnerable to fluctuating commodity prices and unpredictable weather, making risk mitigation crucial for sustainability and profitability. Cotton growers face market volatility and climate challenges that impact yields and income. Previous studies, such as Sharma & Bhushan (2019), highlighted the correlation between market instability and income fluctuation for smallholder cotton farmers, emphasizing improved risk management strategies. The quantitative study used data from 1000 cotton farmers from Odisha (India), selected via stratified random sampling to capture demographic diversity. A structured questionnaire was employed to gather information on key variables, with electronic distribution increasing accessibility. While the research provides. valuable insights, its cross-sectional design limits causal conclusions, and reliance on self-reported information may introduce bias and utilize SPSS to perform structural equation modeling (SEM) to understand the relationships between farmers' perceived risk, income variability, and the use of commodity derivatives. The result shows the negligible effect of commodity derivatives on the revenue stability of cotton growers, except for input costs. The varied risk assessments of farmers indicate that essential financial aspects are overlooked.

Research on talent cultivation for rural revitalization based on three-party evolutionary game.

The sustainable development of Rural Revitalization Talent Training (RRTT) is a key prerequisite for realizing the rural revitalization strategy. In order to study the influence of various stakeholders on RRTT, explore its optimal development path, and clarify the key control factors, this study analyzes the behavioral decision-making of RRTT stakeholders for the first time, and constructs an evolutionary game model of the government, universities and village collectives. Through dynamic decision replication analysis and evolutionary stability analysis, the game relationship among the three stakeholders is discussed. Furthermore, through numerical simulation, the decision-making characteristics of the three parties "behaviors and the evolution trend of the stakeholders" behaviors under the current situation are evaluated, the sensitivity of the key control factors with the policy changes is analyzed, and the feasibility of its implementation is discussed. The results show that the input cost of village collectives is the main determinant of RRTT, and appropriate financial input and low incentive policies are more conducive to universities and village collectives to actively promote RRTT. The research results provide decision-making basis for the implementation of rural revitalization strategy.

Economic Assessment of Soybean Production in Amravati District: Costs, Returns, and Farm Size Dynamics

Economic Assessment of Soybean Production in Amravati District: Costs, Returns, and Farm Size Dynamics

Challenges in Sesame Production and Marketing: Insights from Kerala's Onattukara Region, India

Sesame is one of the nine major oilseeds grown in India, with cultivation spread across every state. Although sesame is grown in 11 districts in Kerala, the sesame cultivated in the Onattukara tract has unique characteristics. In Kerala, sesame is cultivated on 326.51 hectares, with a total production of 163.1 tonnes and a productivity rate of 499 kg per hectare. This study aims to analyze the challenges faced by farmers in the production and marketing of sesame in the Onattukara region of Kerala. The districts of Alappuzha, Pathanamthitta, and Kollam were purposively selected for the study, as the Onattukara region is located within these three districts. A total of 163 farmers were included in the sample, comprising eighty farmers each from Kollam and Alappuzha districts and three farmers from Pathanamthitta. Constraints faced by farmers in sesame cultivation were ranked using the Garrett ranking technique. Sesame cultivation in the Onattukara region faces various challenges in both production and marketing, such as inadequate seed availability, high input costs, low yields, labor shortages, low prices, weather-related issues, price fluctuations, delayed payments, low demand for the final product, and the lack of institutional market mechanism. Similarly, sesame processing unit owners also encounter issues in production and marketing, including raw material shortages, a lack of skilled labor, poor raw material quality, costly production methods, lack of support, low product prices, price volatility, inadequate storage facilities, inefficient markets for final products, and limited consumer awareness. A micro-level study on sesame production and marketing would help producers make informed and specific decisions to improve their income. These insights can guide producers in making informed decisions and assist policymakers in implementing corrective measures like resource allocation for inputs, training and capacity building, improving market linkages to enhance sesame production, productivity, and market stability. These interventions, grounded in micro-level data, could substantially support both short-term gains and long-term sustainability in sesame production, demonstrating the practical utility of the research in enhancing both farmers livelihoods and local agricultural policy.

Blockchain’s role in operation strategy of power battery closed-loop supply chain

With the rapid development of the electric vehicle industry, the issue of recycling retired power batteries is becoming increasingly prominent. Considering the adoption of blockchain technology to enhance information traceability for retired power batteries, we construct three closed-loop supply chain decision-making models: a supply chain that does not adopt blockchain technology, a manufacturing enterprise that independently bears the input cost of blockchain technology, and a scenario which both manufacturing and selling enterprises jointly bear the blockchain technology input costs. Through the comparative analysis of the equilibrium solutions of these models, including the profits of each supply chain member, consumer surplus, environmental impact, and social welfare, it is concluded that the level of information traceability increases with the increase of the blockchain technology input cost-sharing ratio λ by the selling enterprise. However, there is a threshold for λ and λ cannot be infinitely increased. The profits of both manufacturing and selling enterprises increase with the adoption of blockchain technology, yet the ladder-utilizing enterprise achieves the highest profits when not adopting blockchain technology. Furthermore, the adoption of blockchain technology can increase consumer surplus and social welfare while reducing the impact on the environment. These studies provide theoretical guidance on both economic and social environment for the operation decision of each member in the closed-loop supply chain of power batteries.

The Timing of Phosphorus Availability to Corn: What Growth Stages Are Most Critical for Maximizing Yield?

Phosphorus (P) is critical for maximizing agricultural production and represents an appreciable input cost. Geologic sources of P that are most easily mined are a finite resource, while P transported from agricultural land to surface waters contributes to water quality degradation. Improved knowledge of P timing needs by corn (maize) can help inform management decisions that increase P use efficiency, which is beneficial to productivity, economics, and environmental quality. The objective of this study was to evaluate P application timing on the growth and yield components of corn. Corn was grown in a sand-culture hydroponics system that eliminated confounding plant–soil interactions and allowed for precise control of nutrient availability and timing. All nutrients were applied via drip irrigation and were therefore 100% bioavailable. Eight P timing treatments were tested using “low” (L) and “sufficient” (S) P concentrations. In each of the three growth phases, solution P application levels were changed or maintained, resulting in eight possible combinations, LLL, LLS, LSL, LSS, SLL, SSL, SLS, and SSS, where the first, second, and third letters indicate P solution application levels from planting to V6, V6 to R1, and R1 to R6, respectively. All other nutrients were applied at sufficient levels. Sacrificial samples were harvested at V6, R1, and R6 and evaluated for various yield parameters. Plants that received sufficient P between V6 and R1 produced a significantly higher grain yield than plants that received low P between V6 and R1 regardless of the level of P supply before V6 or after R1. The grain yield of plants that received sufficient P only between V6 and R1 did not differ significantly from plants that received only sufficient P (SSS), due to (1) a greater ear P concentration at R1; (2) an efficient remobilization of assimilates from the stem and leaf to grains between R1 and R6 (source–sink relationship); (3) a higher kernel/grain weight; and (4) less investment into root biomass.

A Cost-Effectiveness Analysis of Gonadotropins Used for Ovarian Stimulation during Assisted Reproductive Technology Based on Data from the French Nationwide Claims Database (SNDS)

Objective: Various gonadotropins are used for ovarian stimulation (OS). This study investigated the cost-effectiveness of different gonadotropins based on real-world data from the French National Health Database (SNDS) over a 7-year follow-up of assisted reproductive technology (ART) treatments. Design: Cost-effectiveness analysis of different gonadotropins based on real-world data from the SNDS was conducted. Participants: Women from SNDS undergoing OS leading to oocyte pick-up registered between January 31, 2013, and December 31, 2018 (N = 245,534 stimulations), and receiving either recombinant human follicle stimulating hormone (r-hFSH alfa originator; 110,439), its biosimilars (12,287), or urinaries (mainly highly purified human menopausal gonadotropin [HP-hMG; 65,654] and marginally highly purified urinary-human follicle stimulating hormone [7,821]) were included (follow-up: December 31, 2019). Settings and Methods: Clinical inputs for this model, including live birth (LB) and cumulative LB (CLB) were calculated from data as published in [Best Pract Res Clin Obstet Gynaecol. 2023;88:102308]. A decision-tree model was developed comprising pregnancy and live birth rate (LBR) states for a complete ART cycle, including one fresh and ≤4 frozen/thawed embryo transfers and related costs. Cost inputs included those of drugs, ART procedure, pregnancy and delivery, and adverse events. Cost per LB and CLB and incremental cost-effectiveness ratio (ICER) were assessed. Robustness of results was determined by comprehensive sensitivity analyses. Results: Overall, r-hFSH alfa originator was found to be associated with a lower cost per LB and per CLB (cost per LB: EUR 26,010; CLB: EUR 22,278) versus its biosimilars (cost per LB: EUR 28,037; CLB: EUR 23,807) and versus urinaries (cost per LB: EUR 26,636; CLB: EUR 23,335). Calculated ICERs with r-hFSH alfa for LB were EUR 5,538 and EUR 14,090, whereas for CLB were EUR 1,945 and EUR 13,742 versus biosimilars and urinaries, respectively. Cost-effectiveness acceptability curve showed that in a majority of iterations, r-hFSH alfa originator had a probability of being cost-effective at a hypothetical threshold of EUR 20,000/LB. Sensitivity analyses showed that the most important variable impacting the outcome in fresh transfers was the probability of birth for biosimilars and the probability of pregnancy for urinaries, while for cumulative transfers, it was the probability of pregnancy for biosimilars and the probability of birth for urinaries. Limitations: As the clinical data were obtained from a non-interventional study and not a randomized controlled trial, the results may still be susceptible to residual confounding or other biases. Conclusions: r-hFSH alfa originator is cost-effective compared to its biosimilars and to urinaries (mainly HP-hMG) and is associated with a lower cost per LB compared to these gonadotropins, where the main driver is the higher LB efficacy rate achieved with it.

Technical Efficiency in Bitter Melon Plants Using Data Envelopment Analysis (DEA) Model in Tanah Laut District

Farm technical efficiency involves maximizing output while minimizing input costs. In Tanah Laut Regency, bitter melon production fluctuates annually due to climatic factors and inefficient input use. On average, farmers use 0.47 hectares of land, 166 grams/ha of seeds, 2,659 kg/ha of organic fertilizer, 208 kg/ha of inorganic fertilizer, 7.08 liters/ha of liquid pesticides, 7.24 kg/ha of solid pesticides, and 339 HKSP of labor. Data Envelopment Analysis (DEA) indicates that farmers are technically inefficient, with average technical efficiencies of 80.8% (CRS-DEA), 89.9% (VRS-DEA), and 89.8% (SE-DEA). Among the farmers, 32% operate under increasing returns to scale (IRS), 26% under constant returns to scale (CRS), and 42% under decreasing returns to scale (DRS). A logit regression model reveals that education level, farming experience, and number of family members significantly impact technical efficiency, while age, land ownership status, and off-farm income do not. To enhance efficiency, farmers should reduce input use by emulating the practices of their more efficient peers.

ANALISIS PEMENUHAN KEBUTUHAN EKONOMI RUMAH TANGGA PETANI KENTANG DI DESA TOSARI KECAMATAN TOSARI KABUPATEN PASURUAN

The selling price of potatoes fluctuated, and the rising production input costs affected income, leading farmers to work in off-farm and non-farm sectors to meet household economic needs. The research aimed to analyze potato farming income as well as total household income and expenditures. The sampling method used purposive sampling, with a total of 60 respondents. This study employed income analysis and descriptive analysis. The results showed that the income from potato farming was Rp13,465,899.12 per planting season. The total household income of the farmers was Rp20,993,565.78 over four months, consisting of on-farm, off-farm, and non-farm income sources. Household expenditures amounted to Rp7,116,555.56, which included food and non-food expenses. Keywords: Farming; Income Analysis; Farmers' Households

A New Proposal for Soybean Plant Stand: Variation Based on the Law of the Minimum.

The hypothesis of this study is that it is possible to determine the plant stand in the soybean (Glycine max L. Merril) crop based on the spatial variability of management units, which are limiting factors in maximizing crop yield. Our objectives were as follows: (I) to evaluate the relationship between soil physical and chemical attributes to establish potential management units for variable-rate seeding; (II) to propose a method for varying plant stands based on the law of minimum soil nutrients; an (III) to relate the interaction between different plant stands on soybean grain yield, taking into account the interaction between the spatial variability of the mapped attributes. Field experiments were carried out on two plots over two agricultural years. The areas were seeded by randomly varying the soybean stand across strips in the first year. The most limiting soil nutrient was established and used, together with the soil CEC, to determine management units (MUs), which were also used to seed soybeans in VRT (Variable Rate Technology) in the same plots in the second year. MUs with the lowest restriction for maximizing yield were sown in the second year with the lowest plant stand. Data were processed using multivariate statistics. Our findings reveal that it is possible to establish MUs for seeding soybeans with different stands following the spatial variability of limiting soil nutrients according to the law of the minimum and thus increase the crop grain yield. Spatial variability of potassium (K) in the plot, identified as limiting, affected the spatial variability of grain yield. Decreasing plant stands in MUs with the lowest limitation level increases yield. However, increasing the stand in MUs with a higher limitation level can lead to increased intraspecific competition, affecting yield as well as increasing input costs.

Cost analysis of adding hypertension and diabetes management into routine HIV care in Mbarara and Ibanda districts, Uganda

BackgroundIn 2016, Uganda introduced services for hypertension and diabetes in selected HIV clinics. We evaluated the costs associated with scaling up these services in HIV clinics in Mbarara and Ibanda districts, Uganda.MethodsWe estimated the annual costs of providing hypertension and diabetes services using an activity-based costing approach from the health system perspective in ten randomly selected HIV clinics in Mbarara and Ibanda districts. Cost inputs included 2023 data on costs of medications, health provider time, salaries, training costs, and monitoring costs. We determined the average annual cost and medication costs for hypertension and diabetes treatment per enrolled adult patient, stratified by type of health facility.ResultsThe total annual cost of hypertension and diabetes management services in ten selected HIV clinics was estimated to be $413,850 (range: $8,386 − 186,973). The annual average clinic-level cost per enrolled patient was estimated at $14 (range: $7 − 31). Of the total annual cost, the cost of provider time for initial and follow-up visits represented the largest cost component in 5/10 clinics (mean: 37%, range [13–58%]). In 4/10 clinics, the major cost components were the costs of medication, diagnostic tests, and related supplies (mean: 37%, range [10–75%]). The average cost per enrolled adult patient was $11 at public facilities and $21 in private not-for-profit facilities. The average medication cost per patient for hypertension was $24 (range: $7 − 97) annually; $13 at public facilities and $50 at private not-for-profit facilities. For diabetes treatment, the average annual medication cost per patient was estimated at $14 (range: $6 − 35); $11 at public facilities and $22 at private not-for-profit facilities.ConclusionAdding hypertension and diabetes management to routine HIV care might be feasible based on the estimated annual cost per patient. Hypertension and diabetes treatment was more costly in private not-for-profit facility-based clinics than at public facilities. This variation was primarily driven by higher medication procurement prices at private facilities, revealing a potential area for optimizing costs through improved procurement practices.

Drone Technology in Agricultural Practices: A SWOC Analysis

Drone technology, also known as Unmanned Aerial Systems (UAS), is transforming modern agriculture by introducing precision farming techniques that enhance crop monitoring, resource management, and sustainability. By providing real-time data on plant health, soil conditions, and irrigation needs, drones enable farmers to make informed decisions that optimize yields while reducing input costs. In India, the rapid growth of the drone sector highlights its increasing importance in addressing challenges such as labor shortages, water scarcity, and the need for more sustainable farming practices. This case study explores the adoption and impacts of drone technology in agricultural practices within Coimbatore District, Tamil Nadu, India. The purposive sampling method was used to chosen the farmers. Data were collected through a structured questionnaire and interviews with farmers who had adopted in drone technology. The study investigates the profile characteristics of farmers and evaluates the Strengths, Weaknesses, Opportunities, and Challenges (SWOC) related to the adoption of drones in agriculture. Findings revealed that drone usage significantly improved farm efficiency, reduced labor dependency, and optimized the application of fertilizers and pesticides, resulting in lower input costs and more sustainable practices. However, challenges such as high upfront costs, fragmented land holdings, technical expertise gaps, and limited drone availability constrained wider adoption. This research concludes that while drones offer substantial potential to modernize agriculture and address labor and environmental challenges, further government support and farmer training are crucial to overcome adoption barriers. The study underscores the role of drones in promoting climate-resilient and sustainable farming practices.