scholarly journals Guidance for Demonstrating the Societal Value of new Antibiotics

2021 ◽  
Vol 11 ◽  
Author(s):  
Steven Simoens ◽  
Isabel Spriet
Keyword(s):  
Economic Evaluation ◽  
Disease Transmission ◽  
Good Practice ◽  
Population Level ◽  
Antibiotic Use ◽  
Economic Evaluations ◽  
Discussion Paper ◽  
Societal Value ◽  
New Antibiotics ◽  
The Impact

Given that antibiotic use is associated with externalities, standard economic evaluation which considers costs and health gains accruing to patients under-values antibiotics. Informed by a scoping review, this discussion paper aims to identify the societal value elements of antibiotics and to provide guidance on how these value elements can be incorporated in economic evaluation. With a view to appropriately quantify the societal value of antibiotics, there is a need for good practice guidelines on the methodology of economic evaluation for such products. We argue that it is important to assess antibiotics at population level to account for their transmission, diversity, insurance, spectrum, novel action and enablement values. In addition to the value of antibiotics to infected patients, economic evaluations need to use modeling approaches to explore the impact of different modes of employing new and existing antibiotics (for example, as last resort treatment) on disease transmission and resistance development in current and future patients. Hence, assessing the value of antibiotics also involves an ethical dimension. Further work is required about how the multiple value elements of antibiotics are linked to each other and how they can be aggregated.

scholarly journals Vaccinating Adolescents and Children Significantly Reduces COVID-19 Morbidity and Mortality across All Ages: A Popula-Tion-Based Modeling Study Using the UK as an Example

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1180
Author(s):  
Tinevimbo Shiri ◽  
Marc Evans ◽  
Carla A. Talarico ◽  
Angharad R. Morgan ◽  
Maaz Mussad ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Age Groups ◽  
Population Level ◽  
Vital Role ◽  
Morbidity And Mortality ◽  
Transmission Model ◽  
Base Case ◽  
Global Public Health ◽  
The Uk ◽  
The Impact

Debate persists around the risk–benefit balance of vaccinating adolescents and children against COVID-19. Central to this debate is quantifying the contribution of adolescents and children to the transmission of SARS-CoV-2, and the potential impact of vaccinating these age groups. In this study, we present a novel SEIR mathematical disease transmission model that quantifies the impact of different vaccination strategies on population-level SARS-CoV-2 infections and clinical outcomes. The model employs both age- and time-dependent social mixing patterns to capture the impact of changes in restrictions. The model was used to assess the impact of vaccinating adolescents and children on the natural history of the COVID-19 pandemic across all age groups, using the UK as an example. The base case model demonstrates significant increases in COVID-19 disease burden in the UK following a relaxation of restrictions, if vaccines are limited to those ≥18 years and vulnerable adolescents (≥12 years). Including adolescents and children in the vaccination program could reduce overall COVID-related mortality by 57%, and reduce cases of long COVID by 75%. This study demonstrates that vaccinating adolescents and children has the potential to play a vital role in reducing SARS-CoV-2 infections, and subsequent COVID-19 morbidity and mortality, across all ages. Our results have major global public health implications and provide valuable information to inform a potential pandemic exit strategy.

The Economics of Infectious Diseases

2018 ◽  
Author(s):  
Katharina Hauck
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Health Interventions ◽  
Health System Strengthening ◽  
Economic Research ◽  
Economic Evaluations ◽  
Research Needs ◽  
Public Health Interventions ◽  
The Impact

Economics can make immensely valuable contributions to our understanding of infectious disease transmission and the design of effective policy responses. The one unique characteristic of infectious diseases makes it also particularly complicated to analyze: the fact that it is transmitted from person to person. It explains why individuals’ behavior and externalities are a central topic for the economics of infectious diseases. Many public health interventions are built on the assumption that individuals are altruistic and consider the benefits and costs of their actions to others. This would imply that even infected individuals demand prevention, which stands in conflict with the economic theory of rational behavior. Empirical evidence is conflicting for infected individuals. For healthy individuals, evidence suggests that the demand for prevention is affected by real or perceived risk of infection. However, studies are plagued by underreporting of preventive behavior and non-random selection into testing. Some empirical studies have shown that the impact of prevention interventions could be far greater than one case prevented, resulting in significant externalities. Therefore, economic evaluations need to build on dynamic transmission models in order to correctly estimate these externalities. Future research needs are significant. Economic research needs to improve our understanding of the role of human behavior in disease transmission; support the better integration of economic and epidemiological modeling, evaluation of large-scale public health interventions with quasi-experimental methods, design of optimal subsidies for tackling the global threat of antimicrobial resistance, refocusing the research agenda toward underresearched diseases; and most importantly to assure that progress translates into saved lives on the ground by advising on effective health system strengthening.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: A modelling study

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Public Health Intervention ◽  
Population Level ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions

Background: Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods: We fit a metapopulation Susceptible-Exposed-Infectious-Recovered (SEIR) model to reported cases stratified by two groups to estimate the impact of a lockdown on the effective reproduction number (Re). We estimated the basic reproduction number (R0) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the lockdown. We estimated R­e values of both groups before and after the lockdown, simulated the effect of these values on epidemic curves and explored a range of cross-transmission scenarios. Results: We estimate R0 at 1·06 (95% CI: 1·05-1·28) for P1 and 1·83 (1·58-2·33) for P2. On March 22nd, Re for P1 and P2 are estimated at 1·13 (1·07-1·17) and 1·38 (1·25-1·63) respectively. After the curfew had taken effect, Re for P1 dropped modestly to 1·04 (1·02-1·06) but almost doubled for P2 to 2·47 (1·98-3·45). Our simulated epidemic trajectories show that the partial curfew measure modestly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission from P2 to P1 elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2.    Conclusion: Our results demonstrate that a lockdown can reduce SARS-CoV2 transmission in one subpopulation but accelerate it in another. At the population level, the consequences of lockdowns may vary across the socioeconomic spectrum. Any public health intervention needs to be sensitive to disparities within populations.

Probabilistic Economical Evaluation for Business Decisions Through Integrated Uncertainty Assessment and Reliable Ensemble-Based Production Forecasts

2021 ◽  
Author(s):  
Mohammed Abd-Allah ◽  
Ahmed Abdelrahman ◽  
Luke Van Den Brul ◽  
Taha Taha ◽  
Mohammad Ali Javed
Keyword(s):  
Economic Evaluation ◽  
History Matching ◽  
Dynamic Models ◽  
Traditional Approach ◽  
Integrated Modelling ◽  
Economic Evaluations ◽  
Reservoir Model ◽  
Model Uncertainties ◽  
Reservoir Models ◽  
The Impact

Abstract Economic evaluation of exploration and production projects ensures a positive return for asset operators and stakeholders and evaluates risk in field development decisions related to both reservoir model uncertainties and fluctuations in oil and gas prices. Traditionally, such evaluation is performed manually and deterministically using single or limited number of cases (limited number of reservoir models and few values of economic parameters). Such traditional approach does not integrate seismic-to-simulation reservoir model uncertainties, the reservoir model used is often unreliable due to inconsistent property modifications during the history matching process, full span of prediction uncertainty isn't properly propagated for economic evaluation and the whole process is not fully automated. This paper presents an integrated and automated forward modelling approach where static and dynamic models are connected to integrate the impact of uncertainties at the different modelling stages (seismic interpretation through geological modelling to dynamic simulation and further to economic evaluations). The approach is demonstrated using synthetic 3D model data mimicking a real North Sea field. It starts by building an integrated modelling workflow that can capture the various reservoir model uncertainties at different stages to automatically generate multiple probable model realisations. Proxy models are constructed and used to refine the history match in successive batches. For each prediction development scenario, prediction probabilities are estimated using posterior ensemble of geologically consistent runs that matches historical observed data. The ensemble of reservoir models is automatically evaluated against different possible economic scenarios. The approach presents a seamless and innovative workflow that benefits from new-generation hardware and software, enables faster simultaneous realisations, produces consistent and more reliable reservoir models. Probabilistic economic evaluation concept is implemented to calculate the statistical probabilities of economic indicators.

scholarly journals Exogenous re-infection and the dynamics of tuberculosis epidemics: local effects in a network model of transmission

2006 ◽  
Vol 4 (14) ◽  
pp. 523-531 ◽  
Author(s):  
Ted Cohen ◽  
Caroline Colijn ◽  
Bryson Finklea ◽  
Megan Murray
Keyword(s):  
Network Model ◽  
Disease Transmission ◽  
Control Strategies ◽  
Disease Incidence ◽  
Infected Individual ◽  
Population Level ◽  
Recent Infection ◽  
Tb Control ◽  
Relative Contribution ◽  
The Impact

Infection with Mycobacterium tuberculosis leads to tuberculosis (TB) disease by one of the three possible routes: primary progression after a recent infection; re-activation of a latent infection; or exogenous re-infection of a previously infected individual. Recent studies show that optimal TB control strategies may vary depending on the predominant route to disease in a specific population. It is therefore important for public health policy makers to understand the relative frequency of each type of TB within specific epidemiological scenarios. Although molecular epidemiologic tools have been used to estimate the relative contribution of recent transmission and re-activation to the burden of TB disease, it is not possible to use these techniques to distinguish between primary disease and re-infection on a population level. Current estimates of the contribution of re-infection therefore rely on mathematical models which identify the parameters most consistent with epidemiological data; these studies find that exogenous re-infection is important only when TB incidence is high. A basic assumption of these models is that people in a population are all equally likely to come into contact with an infectious case. However, theoretical studies demonstrate that the social and spatial structure can strongly influence the dynamics of infectious disease transmission. Here, we use a network model of TB transmission to evaluate the impact of non-homogeneous mixing on the relative contribution of re-infection over realistic epidemic trajectories. In contrast to the findings of previous models, our results suggest that re-infection may be important in communities where the average disease incidence is moderate or low as the force of infection can be unevenly distributed in the population. These results have important implications for the development of TB control strategies.

scholarly journals THE IMPACT OF ECONOMIC ANALYSIS METHODS ON PROJECT DECISION-MAKING IN AIRPORT PAVEMENT MANAGEMENT

2021 ◽  
Vol 83 (3) ◽  
pp. 11-19
Author(s):  
Buhaaldeen Mohammed Zaki ◽  
Peyman Babashamsi ◽  
Aini Hazwani Shahrir ◽  
Abdalrhman Milad ◽  
Noor Halizah Abdullah ◽  
...  
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Economic Evaluation ◽  
Economic Analysis ◽  
Pavement Management ◽  
Economic Evaluations ◽  
Analysis Methods ◽  
Airport Pavement ◽  
The Impact ◽  
Project Decision

Airports are a part of the world transportation network. Huge investments are made annually for airport pavement construction, maintenances and  rehabilitations. The idea of integrating life-cycle cost analysis (LCCA) and life cycle assessment (LCA) is the latest approach to develop a method for assessing pavement sustainability. In this regard, research on economic evaluation analysis methods has resulted in the development and improvement of pavement management systems (PMS). This paper compares two main economic evaluations which mainly could use in LCCA namely net future value (NFV) and net present Value (NPV). To indicate the effect of economic evaluation a case study is examined. In this research LCCA comprises three main components which are direct costs, indirect costs, and salvage value. Airport Revenue Reduction Cost (ARRC) and Airline Delay Cost (ADC) considered as two specific indirect/user costs. The results show the impact of different economic analysis method on project decision-making where the use of crack sealing overlay (CSOL) is 35.8% and 28.3% more cost-effective than Portland cement concrete (PCC) and hot-mix asphalt (HMA), respectively.

scholarly journals Inferring high-resolution human mixing patterns for disease modeling

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dina Mistry ◽  
Maria Litvinova ◽  
Ana Pastore y Piontti ◽  
Matteo Chinazzi ◽  
Laura Fumanelli ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Disease Modeling ◽  
Population Level ◽  
Effective Population ◽  
Human Contact ◽  
Contact Patterns ◽  
Data Driven Approach ◽  
Mixing Patterns ◽  
The Impact

AbstractMathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for realism in addressing complex public health questions is, however, calling for accurate models of the human contact patterns that govern the disease transmission processes. Here we present a data-driven approach to generate effective population-level contact matrices by using highly detailed macro (census) and micro (survey) data on key socio-demographic features. We produce age-stratified contact matrices for 35 countries, including 277 sub-national administratvie regions of 8 of those countries, covering approximately 3.5 billion people and reflecting the high degree of cultural and societal diversity of the focus countries. We use the derived contact matrices to model the spread of airborne infectious diseases and show that sub-national heterogeneities in human mixing patterns have a marked impact on epidemic indicators such as the reproduction number and overall attack rate of epidemics of the same etiology. The contact patterns derived here are made publicly available as a modeling tool to study the impact of socio-economic differences and demographic heterogeneities across populations on the epidemiology of infectious diseases.

scholarly journals COVID-19 aerosol transmission simulation-based risk analysis for in-person learning

2021 ◽  
Author(s):  
Tessa Swanson ◽  
Seth Guikema ◽  
James Bagian ◽  
Christopher Schemanske ◽  
Claire Payne
Keyword(s):  
Decision Making ◽  
Risk Analysis ◽  
Disease Transmission ◽  
Population Level ◽  
School Year ◽  
Aerosol Exposure ◽  
Simulation Based ◽  
Impact Risk ◽  
The Individual ◽  
The Impact

AbstractAs educational institutions begin a school year following a year and a half of disruption from the COVID-19 pandemic, risk analysis can help to support decision-making for resuming in-person instructional operation by providing estiamtes of the relative risk reduction due to different interventions. In particular, a simulation-based risk analysis approach enables scenario evaluation and comparison to guide decision making and action prioritization under uncertainty. We develop a simulation model to characterize the risks and uncertainties associated with infections resulting from aerosol exposure in in-person classes. We demonstrate this approach by applying it to model a semester of courses in a real college with approximately 11,000 students embedded within a larger university. To have practical impact, risk cannot focus on only infections as the end point of interest, we estimate the risks of infection, hospitalizations, and deaths of students and faculty in the college. We incorporate uncertainties in disease transmission, the impact of policies such as masking and facility interventions, and variables outside of the college’s control such as population-level disease and immunity prevalence. We show in our example application that universal use of masks that block 40% of aerosols and the installation of near-ceiling, fan-mounted UVC systems both have the potential to lead to substantial risk reductions and that these effects can be modeled at the individual room level. These results exemplify how such simulation-based risk analysis can inform decision making and prioritization under great uncertainty.

scholarly journals Modelling the performance of isoniazid preventive therapy for reducing tuberculosis in HIV endemic settings: the effects of network structure

2011 ◽  
Vol 8 (63) ◽  
pp. 1510-1520 ◽  
Author(s):  
H. L. Mills ◽  
T. Cohen ◽  
C. Colijn
Keyword(s):  
Network Structure ◽  
Disease Transmission ◽  
Population Level ◽  
Preventive Therapy ◽  
Isoniazid Preventive Therapy ◽  
World Health ◽  
Individual Level ◽  
Health Organization ◽  
The Individual ◽  
The Impact

Individuals living with HIV experience a much higher risk of progression from latent M. tuberculosis infection to active tuberculosis (TB) disease relative to individuals with intact immune systems. A several-month daily course of a single drug during latent infection (i.e. isoniazid preventive therapy (IPT)) has proved in clinical trials to substantially reduce an HIV-infected individual's risk of TB disease. As a result of these findings and ongoing studies, the World Health Organization has produced strong guidelines for implementing IPT on a community-wide scale for individuals with HIV at risk of TB disease. To date, there has been limited use of IPT at a community-wide level. In this paper, we present a new co-network model for HIV and TB co-epidemics to address questions about how the population-level impact of community-wide IPT may differ from the individual-level impact of IPT offered to selected individuals. In particular, we examine how the effect of clustering of contacts within high-TB incidence communities may affect the rates of re-infection with TB and how this clustering modifies the expected population-level effects of IPT. We find that populations with clustering of respiratory contacts experience aggregation of TB cases and high numbers of re-infection events. While, encouragingly, the overall population-level effects of community-wide IPT appear to be sustained regardless of network structure, we find that in populations where these contacts are highly clustered, there is dramatic heterogeneity in the impact of IPT: in some sub-regions of these populations, TB is nearly eliminated, while in others, repeated re-infection almost completely undermines the effect of IPT. Our findings imply that as IPT programmes are brought to scale, we should expect local heterogeneity of effectiveness as a result of the complex patterns of disease transmission within communities.

scholarly journals A cost–benefit analysis framework for preventive health interventions to aid decision-making in Australian governments

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jaithri Ananthapavan ◽  
Marj Moodie ◽  
Andrew Milat ◽  
Lennert Veerman ◽  
Elizabeth Whittaker ◽  
...  
Keyword(s):  
Decision Making ◽  
Economic Evaluation ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Preventive Health ◽  
Health Interventions ◽  
Economic Evaluations ◽  
Benefit Analysis ◽  
Analysis Framework ◽  
The Impact

Abstract Background Australian governments are increasingly mandating the use of cost–benefit analysis (CBA) to inform the efficient allocation of government resources. CBA is likely to be useful when evaluating preventive health interventions that are often cross-sectoral in nature and require Cabinet approval prior to implementation. This study outlines a CBA framework for the evaluation of preventive health interventions that balances the need for consistency with other agency guidelines whilst adhering to guidelines and conventions for health economic evaluations. Methods We analysed CBA and other evaluation guidance documents published by Australian federal and New South Wales (NSW) government departments. Data extraction compared the recommendations made by different agencies and the impact on the analysis of preventive health interventions. The framework specifies a reference case and sensitivity analyses based on the following considerations: (1) applied economic evaluation theory; (2) consistency between CBA across different government departments; (3) the ease of moving from a CBA to a more conventional cost-effectiveness/cost-utility analysis framework often used for health interventions; (4) the practicalities of application; and (5) the needs of end users being both Cabinet decision-makers and health policy-makers. Results Nine documents provided CBA or relevant economic evaluation guidance. There were differences in terminology and areas of agreement and disagreement between the guidelines. Disagreement between guidelines involved (1) the community included in the societal perspective; (2) the number of options that should be appraised in ex ante analyses; (3) the appropriate time horizon for interventions with longer economic lives; (4) the theoretical basis and value of the discount rate; (5) parameter values for variables such as the value of a statistical life; and (6) the summary measure for decision-making. Conclusions This paper addresses some of the methodological challenges that have hindered the use of CBA in prevention by outlining a framework that is consistent with treasury department guidelines whilst considering the unique features of prevention policies. The effective use and implementation of a preventive health CBA framework is likely to require considerable investment of time and resources from state and federal government departments of health and treasury but has the potential to improve decision-making related to preventive health policies and programmes.

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