scholarly journals When the Best Pandemic Models are the Simplest

Biology ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 353 ◽  
Author(s):  
Sana Jahedi ◽  
James A. Yorke

As the coronavirus pandemic spreads across the globe, people are debating policies to mitigate its severity. Many complex, highly detailed models have been developed to help policy setters make better decisions. However, the basis of these models is unlikely to be understood by non-experts. We describe the advantages of simple models for COVID-19. We say a model is “simple” if its only parameter is the rate of contact between people in the population. This contact rate can vary over time, depending on choices by policy setters. Such models can be understood by a broad audience, and thus can be helpful in explaining the policy decisions to the public. They can be used to evaluate the outcomes of different policies. However, simple models have a disadvantage when dealing with inhomogeneous populations. To augment the power of a simple model to evaluate complicated situations, we add what we call “satellite” equations that do not change the original model. For example, with the help of a satellite equation, one could know what his/her chance is of remaining uninfected through the end of an epidemic. Satellite equations can model the effects of the epidemic on high-risk individuals, death rates, and nursing homes and other isolated populations. To compare simple models with complex models, we introduce our “slightly complex” Model J. We find the conclusions of simple and complex models can be quite similar. However, for each added complexity, a modeler may have to choose additional parameter values describing who will infect whom under what conditions, choices for which there is often little rationale but that can have big impacts on predictions. Our simulations suggest that the added complexity offers little predictive advantage.

2020 ◽  
Author(s):  
Sana Jahedi ◽  
James A. Yorke

AbstractAs a pandemic of coronavirus spreads across the globe, people debate policies to mitigate its severity. Many complex, highly detailed models have been developed to help policy setters make better decisions. However, the basis of these models is unlikely to be understood by non-experts.We describe the advantages of simple models for covid-19. We say a model is “simple” if its only parameter is the rate of contact between people in the population. This contact rate can vary over time, depending on choices by policy setters. Such models can be understood by a broad audience, and thus can be helpful in explaining the policy decisions to the public. They can be used to evaluate outcomes of different policy strategies. However, simple models have a disadvantage when dealing with inhomogeneous populations.To augment the power of a simple model to evaluate complicated situations, we add what we call “satellite” equations that don’t change the original model. For example, with the help of a satellite equation, one could know what his/her chance is of remaining uninfected through the end of epidemic. Satellite equations can model the effect of the epidemic on high-risk individuals, or death rates, or on nursing homes, and other isolated populations.To compare simple models with complex models, we introduce our “slightly complex” Model J. We find the conclusions of simple and complex models can be quite similar. But, for each added complexity, a modeler may have to choose additional parameter values describing who will infect whom under what conditions, choices for which there is often little rationale but that can have a big impact on predictions. Our simulations suggest that the added complexity offers little predictive advantage.Author SummaryThere is a large variety of available data about the coronavirus pandemic, but we still lack data about some important factors. Who is likely to infect whom and under what conditions and how long after becoming infected? These factors are the essence of transmission dynamics. Two groups using identical complex models can be expected to make different predictions simply because they make different choices for such transmission parameters in the model. The audience has no way to choose between their predictions. We explain how simple models can be used to answer complex questions by adding what we call satellite equations, addressing questions involving age groups, death rates, and likelihood of transmission to nursing homes and to uninfected, isolated populations. Simple models are ideal for seeing what kinds of interventions are needed to achieve goals of policy setters.


Author(s):  
Adeela Arshad-Ayaz ◽  
M. Ayaz Naseem

AbstractAs a once in a 100 years emergency, the COVID-19 pandemic has resulted in repercussions for the economy, the polity, and the social. Also, the ongoing pandemic is as much a teaching moment as it to reflect on the lack of critical citizenship education. The fault lines of the health system have become visible in terms of infection and death rates; the fault lines of the educational system are now apparent in the behavior of the citizens who are flouting the public health guidelines and, in certain cases, actively opposing these guidelines. The main objective of this commentary is to initiate a dialogue on the social contract between the state and the subjects and to see how education and educators can respond to the challenge of the new normal. It is contended that education under the new normal cannot afford to keep educating for unbridled productivity education under the new normal. It must have welfare, human connections, ethical relationships, environmental stewardship, and social justice front and center.


2020 ◽  
Vol 12 (10) ◽  
pp. 4200 ◽  
Author(s):  
Thanh-Long Giang ◽  
Dinh-Tri Vo ◽  
Quan-Hoang Vuong

Using data from the WHO’s Situation Report on the COVID-19 pandemic from 21 January 2020 to 30 March 2020 along with other health, demographic, and macroeconomic indicators from the WHO’s Application Programming Interface and the World Bank’s Development Indicators, this paper explores the death rates of infected persons and their possible associated factors. Through the panel analysis, we found consistent results that healthcare system conditions, particularly the number of hospital beds and medical staff, have played extremely important roles in reducing death rates of COVID-19 infected persons. In addition, both the mortality rates due to different non-communicable diseases (NCDs) and rate of people aged 65 and over were significantly related to the death rates. We also found that controlling international and domestic travelling by air along with increasingly popular anti-COVID-19 actions (i.e., quarantine and social distancing) would help reduce the death rates in all countries. We conducted tests for robustness and found that the Driscoll and Kraay (1998) method was the most suitable estimator with a finite sample, which helped confirm the robustness of our estimations. Based on the findings, we suggest that preparedness of healthcare systems for aged populations need more attentions from the public and politicians, regardless of income level, when facing COVID-19-like pandemics.


Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 792 ◽  
Author(s):  
Zenonas Turskis ◽  
Jurgita Antuchevičienė ◽  
Violeta Keršulienė ◽  
Gintaras Gaidukas

Sustainable and efficient development is one of the most critical challenges facing modern society if it wants to save the world for future generations. Airports are an integral part of human activity. They need to be adapted to meet current and future sustainable needs and provide useful services to the public, taking into account prospects and requirements. Many performance criteria need to be assessed to address issues that often conflict with each other and have different units of measurement. The importance of the criteria to evaluate the effectiveness of alternatives varies. Besides, the implementation of such decisions has different—not precisely described in advance—effects on the interests of different groups in society. Some criteria are defined using different scales. Stakeholders could only evaluate the implemented project alternatives for efficiency throughout the project life cycle. It is essential to find alternative assessment models and adapt them to the challenges. The use of hybrid group multi-criteria decision-making models is one of the most appropriate ways to model such problems. This article presents a real application of the original model to choose the best second runway alternative of the airport.


2020 ◽  
Vol 52 (5) ◽  
pp. 1848-1866
Author(s):  
Ronald Hübner ◽  
Thomas Pelzer

Abstract Several drift-diffusion models have been developed to account for the performance in conflict tasks. Although a common characteristic of these models is that the drift rate changes within a trial, their architecture is rather different. Comparative studies usually examine which model fits the data best. However, a good fit does not guarantee good parameter recovery, which is a necessary condition for a valid interpretation of any fit. A recent simulation study revealed that recovery performance varies largely between models and individual parameters. Moreover, recovery was generally not very impressive. Therefore, the aim of the present study was to introduce and test an improved fit procedure. It is based on a grid search for determining the initial parameter values and on a specific criterion for assessing the goodness of fit. Simulations show that not only the fit performance but also parameter recovery improved substantially by applying this procedure, compared to the standard one. The improvement was largest for the most complex model.


2019 ◽  
Vol 35 (7) ◽  
Author(s):  
Shamyr Castro ◽  
Camila Ferreira Leite ◽  
Michaela Coenen ◽  
Cassia Maria Buchalla

Functioning and disability are concepts in increasing use in clinical settings and in public health. From the public health perspective, the use of functioning as a third health indicator could show more than the frequency of a disease and its death rates, offering information on how the population performs its activities and participation. Clinically, the functioning assessment can provide information for patient-centered health care and specific clinical interventions according to their functioning profile. WHODAS 2.0 is a generic tool to assess health and functioning according to the ICF functioning model. It is an alternative to assess functioning in a less time-consuming way, whereas the duration of the application is one of the main ICF critiques. This paper aims to present some of WHODAS 2.0 inconsistencies and weaknesses as well as strategies to cope with them. In this paper, we present some weaknesses related to the WHODAS layout; wording and scoring process. Some suggestions for strategies to correct these weaknesses are presented, as well.


2004 ◽  
Vol 824 ◽  
Author(s):  
M.M. Askarieh ◽  
T.G. Heath ◽  
W.M. Tearle

AbstractA Monte Carlo-based approach has been adopted for development of a chemical thermodynamic model to describe the goethite surface in contact with sodium nitrate solutions. The technique involves the calculation of the goethite surface properties for the chemical conditions corresponding to each experimental data point. The representation of the surface was based on a set of model parameters, each of which was either fixed or was randomly sampled from a specified range of values. Thousands of such model representations were generated for different selected sets of parameter values with the use of the standard geochemical speciation computer program, HARPHRQ. The method allowed many combinations of parameter values to be sampled that might not be achieved with a simple least-squares fitting approach. It also allowed the dependence of the quality of fit on each parameter to be analysed. The Monte Carlo approach is most appropriate in the development of complex models involving the fitting of several datasets with several fitting parameters.Introduction of selenate surface complexes allowed the model to be extended to represent selenate ion sorption, selenium being an important radioelement in evaluation of the long-term safety of ILW disposal. The sorption model gave good agreement with a wide range of experimental sorption datasets for selenate.


2021 ◽  
Vol 118 (11) ◽  
pp. e2011142118
Author(s):  
Mark Dyble

The importance of warfare in the evolution of human social behavior remains highly debated. One hypothesis is that intense warfare between groups favored altruism within groups, a hypothesis given some support by computational modeling and, in particular, the work of Choi and Bowles [J.-K. Choi, S. Bowles, Science 318, 636–640 (2007)]. The results of computational models are, however, sensitive to chosen parameter values and a deeper assessment of the plausibility of the parochial altruism hypothesis requires exploring this model in more detail. Here, I use a recently developed method to reexamine Choi and Bowles’ model under a much broader range of conditions to those used in the original paper. Although the evolution of altruism is robust to perturbations in most of the default parameters, it is highly sensitive to group size and migration and to the lethality of war. The results show that the degree of genetic differentiation between groups (FST) produced by Choi and Bowles’ original model is much greater than empirical estimates of FST between hunter-gatherer groups. When FST in the model is close to empirically observed values, altruism does not evolve. These results cast doubt on the importance of war in the evolution of human sociality.


2020 ◽  
Vol 10 (3(S)) ◽  
pp. 1-11
Author(s):  
Wei-Bin Zhang

This paper makes an original contribution to the literature of optimal taxation by introducing Ramseytaxation to the Solow-Uzawa growth model to examine genuine dynamic interdependence between growth andoptimal taxation. We introduce a public sector to the Uzawa two-sector growth model. The public sector suppliespublic goods and services. The government financially supports by the public sector by collecting taxes on thehousehold’s wage income and wealth income under the assumption that the utility level is maximized. We derivethe optimal taxation rule and construct the dynamics of the national economy. The model studies a nonlineardynamics between national and sectoral growth, economic structural change, wealth/capital accumulation, andoptimal tax rates in perfect competitive markets with the government intervention. The model has a uniquestable equilibrium point with the chosen parameter values. We carry out comparative dynamic analysis toanalyze effects of exogenous changes in a few parameters on the transitional process and long-term economicstructure of the economic dynamics.


Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2660
Author(s):  
Chao Wang ◽  
Li Wan ◽  
Tifan Xiong ◽  
Yuanlong Xie ◽  
Shuting Wang ◽  
...  

Structural analysis is a method for verifying equation-oriented models in the design of industrial systems. Existing structural analysis methods need flattening of the hierarchical models into an equation system for analysis. However, the large-scale equations in complex models make structural analysis difficult. Aimed to address the issue, this study proposes a hierarchical structural analysis method by exploring the relationship between the singularities of the hierarchical equation-oriented model and its components. This method obtains the singularity of a hierarchical equation-oriented model by analyzing a dummy model constructed with the parts from the decomposing results of its components. Based on this, the structural singularity of a complex model can be obtained by layer-by-layer analysis according to their natural hierarchy. The hierarchical structural analysis method can reduce the equation scale in each analysis and achieve efficient structural analysis of very complex models. This method can be adaptively applied to nonlinear-algebraic and differential-algebraic equation models. The main algorithms, application cases and comparison with the existing methods are present in this paper. The complexity analysis results show the enhanced efficiency of the proposed method in the structural analysis of complex equation-oriented models. Compared with the existing methods, the time complexity of the proposed method is improved significantly


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