'Not a good time': Assessing the economic impact of COVID-19 in Africa using a macro-micro simulation approach.
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ABSTRACT:
SUBMITTER: Morsy H
PROVIDER: S-EPMC8207119 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMaintaining a sufficient consultation length in primary health care (PHC) is a fundamental part of providing quality care that results in patient safety and satisfaction. Many facilities have limited capacity and increasing consultation time could result in a longer waiting time for patients and longer working hours for physicians. The use of simulation can be practical for quantifying the impact of workflow scenarios and guide the decision-making.ObjectiveTo examine the impact of increasing consultation time on patient waiting time and physician working hours.MethodsUsing discrete events simulation, we modeled the existing workflow and tested five different scenarios with a longer consultation time. In each scenario, we examined the impact of consultation time on patient waiting time, physician hours, and rate of staff utilization.ResultsAt baseline scenarios (5-minute consultation time), the average waiting time was 9.87 minutes and gradually increased to 89.93 minutes in scenario five (10 minutes consultation time). However, the impact of increasing consultation time on patients waiting time did not impact all patients evenly where patients who arrive later tend to wait longer. Scenarios with a longer consultation time were more sensitive to the patients' order of arrival than those with a shorter consultation time.ConclusionBy using simulation, we assessed the impact of increasing the consultation time in a risk-free environment. The increase in patients waiting time was somewhat gradual, and patients who arrive later in the day are more likely to wait longer than those who arrive earlier in the day. Increasing consultation time was more sensitive to the patients' order of arrival than those with a shorter consultation time.
| S-EPMC7758153 | biostudies-literature
Project description:The present work is aimed to investigate the capability of the discrete element method (DEM) to model properly wave propagation in solid materials, with special focus on the determination of elastic properties through wave velocities. Reference micro-macro relationships for elastic constitutive parameters have been based on the kinematic hypothesis as well as obtained numerically by simulation of a quasistatic uniaxial compression test. The validity of these relationships in the dynamic analysis of the wave propagation has been checked. Propagation of the longitudinal and shear wave pulse in rectangular sample discretized with discs has been analysed. Wave propagation velocities obtained in the analysis have been used to determine elastic properties. Elastic properties obtained in the dynamic analysis have been compared with those determined by simulation of the quasistatic compression test.
| S-EPMC6947539 | biostudies-literature
Project description:Economic recessions occur with varying duration and intensity and may entail substantial losses in terms of GDP, employment, household income, and investment spending. In this work, we propose a statistical model for the time intervals between recessions that accounts for the state of the economy and the impact of market adjustments and regulatory changes. The model uses a generalized renewal process based on the Gumbel distribution (GuGRP) in which times between consecutive events are conditionally independent. We also present a novel goodness of fit test tailored to the GuGRP that validates the use of the statistical model for the analysis of recessions. Analyzing recessions in the U.S. and Europe, we demonstrate that the statistical model characterizes well recession inter-arrival times and that the model performs better than simpler, commonly used distributions. In addition, the presented statistical model enables us to compare the adjustment processes in different economies and to forecast the occurrence of future recessions.
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Project description:Background: Aquaculture in Ghana is very profitable, but faces sustainability challenges. This paper assessed the impact pathways by which climate change affects the production and profitability of small-scale aquaculture in Ghana. The study analyzed and compared the economic value of smallholder fish farms with and without the incidence of climatic parameters. Methods: Simple random sampling and purposive sampling techniques were used to select the study area and farms. A total of 30 farmers were interviewed using a questionnaire-based interview. Additionally, using document analysis, observation, and data on farms' production input and output values, the economic impact of climate change on fish farms was assessed. Results: Extreme temperatures, erratic rainfall, floods, drought, storm and erosion are prevalent in fish farms. Available data shows a decrease of 53.4% of small-scale revenue, a 6.9% reduction in small-scale aquaculture value from GH¢ 83,000 to GH¢ 120,000 reducing fish supply by 25%. The findings indicate that the profitability, economic value, and livelihoods of the small-scale aquaculture industry is greatly affected by changes in climate. The incidence of floods, drought, erratic rainfall, erosion, and extreme temperature synergistically induce poverty. The implication on the livelihoods of fish farming households is very alarming and poses a serious threat to food security in the country. Conclusion: Based on the findings, this study concludes that; floods, rainfall temperature, and drought are the major climatic factors affecting the profitability and sustainability of the pond aquaculture industry. The preliminary recommendation is that there is an urgent need to map out flood-free zones close to perennial water bodies to overcome floods and droughts. Planting trees around ponds to create a micro-ecologies ideal for fish culture and also the construction of water storage facilities and proper dyke design would overcome drought and erosion issues. The adaptive capacity of fish-farmers must be built.
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Project description:Bacterial bioluminescence is widely used to study the spatiotemporal dynamics of bacterial populations and gene expression in vivo at a population level but cannot easily be used to study bacterial activity at the level of individual cells. In this study, we describe the development of a new library of mini-Tn7-lux and lux::eyfp reporter constructs that provide a wide range of lux expression levels, and which combine the advantages of both bacterial bioluminescence and fluorescent proteins to bridge the gap between macro- and micro-scale imaging techniques. We demonstrate that a dual bioluminescence-fluorescence approach using the lux operon and eYFP can be used to monitor bacterial movement in plants both macro- and microscopically and demonstrate that Pseudomonas syringae pv phaseolicola can colonize the leaf vascular system and systemically infect leaves of common bean (Phaseolus vulgaris). We also show that bacterial bioluminescence can be used to study the impact of plant immune responses on bacterial multiplication, viability and spread within plant tissues. The constructs and approach described in this study can be used to study the spatiotemporal dynamics of bacterial colonization and to link population dynamics and cellular interactions in a wide range of biological contexts.
| S-EPMC8614114 | biostudies-literature
Project description:BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has disrupted lives across all countries and communities. It significantly reduced the global economic output and dealt health systems across the world a serious blow. There is growing evidence showing the progression of the COVID-19 pandemic and the impact it has on health systems, which should help to draw lessons for further consolidating and realizing universal health coverage (UHC) in all countries, complemented by more substantial government commitment and good governance, and continued full implementation of crucial policies and plans to avert COVID-19 and similar pandemic threats in the future. Therefore, the objective of the study was to assess the impact of good governance, economic growth and UHC on the COVID-19 infection rate and case fatality rate (CFR) among African countries.MethodsWe employed an analytical ecological study design to assess the association between COVID-19 CFR and infection rate as dependent variables, and governance, economic development and UHC as independent variables. We extracted data from publicly available databases (i.e., Worldometer, Worldwide Governance Indicators, Our World in Data and WHO Global Health Observatory Repository). We employed a multivariable linear regression model to examine the association between the dependent variables and the set of explanatory variables. STATA version 14 software was used for data analysis.ResultsAll 54 African countries were covered by this study. The median observed COVID-19 CFR and infection rate were 1.65% and 233.46%, respectively. Results of multiple regression analysis for predicting COVID-19 infection rate indicated that COVID-19 government response stringency index (β = 0.038; 95% CI 0.001, 0.076; P = 0.046), per capita gross domestic product (GDP) (β = 0.514; 95% CI 0.158, 0.87; P = 0.006) and infectious disease components of UHC (β = 0.025; 95% CI 0.005, 0.045; P = 0.016) were associated with COVID-19 infection rates, while noncommunicable disease components of UHC (β = -0.064; 95% CI -0.114; -0.015; P = 0.012), prevalence of obesity among adults (β = 0.112; 95% CI 0.044; 0.18; P = 0.002) and per capita GDP (β = -0.918; 95% CI -1.583; -0.254; P = 0.008) were associated with COVID-19 CFR.ConclusionsThe findings indicate that good governance practices, favourable economic indicators and UHC have a bearing on COVID-19 infection rate and CFR. Effective health system response through a primary healthcare approach and progressively taking measures to grow their economy and increase funding to the health sector to mitigate the risk of similar future pandemics would require African countries to move towards UHC, improve governance practices and ensure economic growth in order to reduce the impact of pandemics on populations.
| S-EPMC9702649 | biostudies-literature
Project description:We use agent-based modeling to investigate the effect of conservatism and partisanship on the efficiency with which large populations solve the density classification task - a paradigmatic problem for information aggregation and consensus building. We find that conservative agents enhance the populations' ability to efficiently solve the density classification task despite large levels of noise in the system. In contrast, we find that the presence of even a small fraction of partisans holding the minority position will result in deadlock or a consensus on an incorrect answer. Our results provide a possible explanation for the emergence of conservatism and suggest that even low levels of partisanship can lead to significant social costs.
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Project description:BackgroundAlthough Good Samaritan laws (GSLs) have been widely adopted throughout the United States, their efficacy in individual states is often unknown. This paper offers an approach for assessing the impact of GSLs and insight for policy-makers and public health officials who wish to know whether they should expect to see outcomes from similar policy interventions.MethodsUtilizing a system dynamics (SD) modeling approach, the research team conducted a policy evaluation to determine the impact of GSLs on opioid use disorder (OUD) in Connecticut and evaluated the GSL based upon the following health outcomes: (1) emergency department (ED) visits for overdose, (2) behavioral changes of bystanders, and (3) overdose deaths.ResultsThe simulation model suggests that Connecticut's GSL has not yet affected overdose deaths but has resulted in bystander behavioral changes, such as increased 911 calls for overdose. ED visits have increased as the number of opioid users has increased.ConclusionsThe simulation results indicate that the number of opioid-related deaths will continue to increase and that the GSL alone cannot effectively control the crisis. However, the SD approach that was used will allow policymakers to evaluate the effectiveness of the GSL over time using a simulation framework. This SD model demonstrates great potential by producing simulations that allow policymakers to assess multiple strategies for combating the opioid crisis and select optimal public health interventions.
| S-EPMC8734429 | biostudies-literature
Project description:ObjectivesWe conducted a health economic sub-study within a feasibility RCT comparing a non-operative treatment pathway as an alternative to appendicectomy for the treatment of uncomplicated acute appendicitis in children. The objectives were to understand and assess data collection tools and methods and to determine indicative costs and benefits assessing the feasibility of conducting a full economic evaluation within the definitive trial.MethodsWe compared different methods of estimating treatment costs including micro-costing, hospital administrative data (PLICS) and health system (NHS) reference costs. We compared two different HRQoL instruments (CHU-9D and EQ-5D-5L) in terms of data completeness and sensitivity to change over time, including potential ceiling effects. We also explored how the timing of data collection and duration of the analysis could affect QALYs (Quality Adjusted Life Years) and the results of the cost-utility analysis (CUA) within the future RCT.ResultsUsing a micro-costing approach, the total per treatment costs were in alignment with hospital administrative data (PLICS). Average health system reference cost data (macro-costing using NHS costs) could potentially underestimate these treatment costs, particularly for non-operative treatment. Costs incurred following hospital discharge in the primary care setting were minimal, and limited family borne costs were reported by parents/carers. While both HRQoL instruments performed relatively well, our results highlight the problem of ceiling effect and the importance of the timing of data collection and the duration of the analysis in any future assessment using QALYs and CUA.ConclusionsWe highlighted the importance of obtaining accurate individual-patient cost data when conducting economic evaluations. Our results suggest that timing of data collection and duration of the assessment are important considerations when evaluating cost-effectiveness and reporting cost per QALY.Clinical trial registrationCurrent Controlled Trials ISRCTN15830435.
| S-EPMC10473981 | biostudies-literature
Project description:Much research has suggested that night-time light (NTL) can be used as a proxy for a number of variables, including urbanization, density, and economic growth. As governments around the world either collect census data infrequently or are scaling back the amount of detail collected, alternate sources of population and economic information like NTL are being considered. But, just how close is the statistical relationship between NTL and economic activity at a fine-grained geographical level? This paper uses a combination of correlation analysis and geographically weighted regressions in order to examine if light can function as a proxy for economic activities at a finer level. We use a fine-grained geo-coded residential and industrial full sample micro-data set for Sweden, and match it with both radiance and saturated light emissions. We find that the correlation between NTL and economic activity is strong enough to make it a relatively good proxy for population and establishment density, but the correlation is weaker in relation to wages. In general, we find a stronger relation between light and density values, than with light and total values. We also find a closer connection between radiance light and economic activity, than with saturated light. Further, we find the link between light and economic activity, especially estimated by wages, to be slightly overestimated in large urban areas and underestimated in rural areas.
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