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China Chapter – Events – 2021ISDC

2021 International Conference of the System Dynamics Society

Investigating the effectiveness of reopening policies before vaccination during a pandemic

Ying Qian 钱颖

Parallel present at July 26, 2021

Lockdown policies were widely applied during the COVID-19 pandemic to control the spread of the virus before the availability of a vaccine, causing significant economic impact and social disruption. Early reopening is preferred, yet it introduces the risk of further outbreaks. So far, the effectiveness of reopening policies remains unclear. A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model. Simulation results showed that track-and-trace measures were of significance in affecting reopen risk. In Wuhan’s case, with comprehensive contact tracing implemented, there would have been almost no risk for reopening. With partial contact tracing, reopening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. When the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. A matrix was developed to evaluate the effectiveness of the reopening policies, based on simulation results. The model simulation provides evidence-based decision support for safe reopening during an ongoing epidemic.

Combining System Dynamics with Bayesian Networks: A Literature Review of Multi-Method Designs

Wang Zhao

Poster at July 25, 2021

A new research design that combines System Dynamics Models and Bayesian Networks is emerging and has proved useful in solving real world problems. The new design allows to take advantage of System Dynamics’ strength in modelling feedback causal relationships at a higher level of abstraction, as well as Bayesian Networks’ strength in dealing with uncertainty and integrating interdisciplinary data. In this paper, we briefly introduce and compare System Dynamics and Bayesian Networks, then review the existing empirical studies where the two modelling approaches are used in combination. We conclude this review by discussing potential opportunities for future research.

How Does Fee-for-Service Payment System Affect Healthcare Expenditures?

Wang Zhao

Poster at July 27, 2021

Fee-For-Service (FFS) is one of the conventional payment systems which is applied alone or mixed in many countries. The goal of this system is to increase efficiency through financial incentives. However, excessive services and unnecessary or inappropriate care may be encouraged, which adversely affects healthcare expenditure and quality. Although many system dynamics (SD) models are investigating the dynamic of health expenditures, they rarely investigate the effect of payment systems on health expenditures. This paper responds to this theoretical gap by developing a qualitative SD model that investigates crucial feedback loops in FFS. The model shows how interaction between 27 loops (14 positive loops and 13 balancing loops) embedded in FFS can increase health care expenditures without necessarily improving the population’s health. Quantitative extensions may result in a better understanding and policy testing can help decision-makers to follow more effective interventions. Also, loop analysis (and eliminating unimportant substructures and ineffective links/feedbacks) can help to simplify the model, distil essential structures, and increase the quality and understanding of the model.

A System Dynamics Approach for Analysis of the Impacts of Bergen’ Green Strategy Goal T9

Min Xiang 向敏

Presentation at

July 27, 2021

Bergen Kommune published the Green Strategy in 2016 which contains 35 sustainability goals. In this project, we aim to contribute to helping Bergen to become the greenest city in Norway by ensuring that Bergen can meet the T9 goal that ‘all new passenger cars are fossil-free from 2025’. The research objective is to gain insights into how the progress is coming to meet this goal and what further steps will be needed to see this goal achieved by 2025. The project intends to identify the underlying causal relationships linking the different factors affecting a 100 % switch to fossil-free passenger vehicles.

Population Ageing in China

Min Xiang 向敏

WIP at July 28, 2021

China is entering the ‘ageing’ era, with reducing demographic dividend and increasing pension deficit. So, is China ready for that?

Implementation of carbon reduced cement manufacturing – A concrete example

Ella Shen 沈无知

Parallel present at July 27, 2021

The combined emissions from the cement industry are contributing significantly to global CO2 emissions. Norcem has announced its ambitions to be carbon neutral by 2050. To achieve carbon neutrality, Norcem has plans to implement carbon capture technology, willing to reduce the yearly emissions from one plants by 50 %. The policy proposed in this paper, is to further reduce CO2 emissions from this plant, by replacing coal-fueled heating with electric heating.The policy suggests this work will take place in two separate phases – first the calciner should be commissioned and later the rotary kiln. Model simulations reveal that the combination of CO2 capture and electrification of calciner and rotary kiln, would prevent around 14.4 million tonnes of CO2 to atmosphere between 2020 and 2050.A major obstacle to the implementation is the additional costs expected to arise due to high electricity prices relative to coal prices. The model suggests that the source of funding for the coal to electricity transition, should be through borrowing in the financial market. The policy proposes that green cement can be sold at a higher price and the simulations suggest that potential additional income will be significant and will justify a short-term increase in debt.

Capturing Discrete Choice and Deliberation Time Endogenously Using Sequential Sampling and Accumulation-to-Threshold Principles

Jiangbo Gabe Yu 余江博

Parallel present at July 28, 2021

Modeling the adjustment delays for perceptions has been studied comprehensively in the system dynamics (SD) literature. However, the associated decisions have been commonly assumed to be made (as if) in every model step. Therefore, there seems a missing set of theoretically-sound techniques in explicitly capturing the deliberation time during a discrete choice, which may take variable steps to trigger, regardless of whether there is any perception delay. For example, the harder a decision is perceived, the longer it may take to decide, after the deliberation is triggered. Moreover, the deliberation time distributions associated with different alternatives might vary for a given decision problem. Since new information or events might occur during the deliberation, this variation has implication on the final decision and the systemwide path-dependency. Adding even more complexity is the varying degrees of perceived pressure when deciding. On the other hand, models based on the sequential-sampling (SS) and stochastic-accumulation-to-threshold (SAT) principles have been dominant in cognitive psychology (CP) for simultaneously capturing preference and deliberation delays for decades. This paper aims at establishing a connection between SD and CP in terms of modeling stochastic discrete choices and their associated decision time distributions. Five major generalizations and their suitable application contexts are then proposed by synthesizing the techniques and wisdom from the two fields.

Risk-driven responses to COVID-19 eliminate the tradeoff between lives and livelihoods

Tse Yang Lim 林思扬

Parallel present at July 27, 2021

Responses to the COVID-19 pandemic have been conditioned by a perceived tradeoff between saving lives and the economic costs of contact-reduction measures. We develop a model of SARS-CoV-2 transmission where populations endogenously reduce contacts in response to the risk of death. We estimate the model for 118 countries and assess the existence of a tradeoff between death rates and changes in contacts. In this model communities go through three phases – rapid early outbreaks, control through initial response, and a longer period of quasi-equilibrium endemic infection with effective reproduction number (Re) fluctuating around one. Analytical characterization of this phase shows little tradeoff between contact reduction levels (underpinning economic costs) and death rates. Empirically estimating the model, we find no positive correlation between (log) death rates and (normalized) contact levels across nations, whether contacts are estimated based on epidemic curves or mobility data. While contact reduction levels are broadly similar across countries, expected death rates vary greatly, by two orders of magnitude (5-95 percentile: 0.03-17 deaths per million per day). Results suggest nations could significantly reduce the human toll of the pandemic without more disruption to normal social and economic activity than they have already faced.

Behavioral dynamics of COVID-19: estimating under-reporting, multiple waves, and adherence fatigue across 92 nations

Tse Yang Lim 林思扬

Parallel present at July 26 & 28, 2021

Effective responses to the COVID-19 pandemic require integrating behavioral factors such as risk-driven contact reduction, improved treatment, and adherence fatigue with asymptomatic transmission, disease acuity, and hospital capacity. We build one such model and estimate it for all 92 nations with reliable testing data. Cumulative cases and deaths through 22 December 2020 are estimated to be 7.03 and 1.44 times official reports, yielding an infection fatality rate (IFR) of 0.51%, which has been declining over time. Absent adherence fatigue, cumulative cases would have been 47% lower. Scenarios through June 2021 show that modest improvement in responsiveness could reduce cases and deaths by about 14%, more than the impact of vaccinating half of the population by that date. Variations in responsiveness to risk explain two orders of magnitude difference in per-capita deaths despite reproduction numbers fluctuating around 1 across nations. A public online simulator facilitates scenario analysis over the coming months.

Reducing Opioid Use Disorder and Overdose in the United States: Policy Analysis

Tse Yang Lim 林思扬

Parallel present at July 28, 2021

The opioid crisis is one of the most pressing public health issues in the U.S. today. Opioid overdoses are the proverbial “tip of the iceberg,” arising within a complex adaptive system characterized by rapidly changing dynamics combined with significant time lags and large uncertainties in the data. System dynamics modeling is a critical tool to guide policymaking and avoid unintended consequences. We developed a simulation model of the opioid system, spanning from medical use of prescription opioids to opioid misuse and heroin use, use disorder, treatment, and remission. The model aims to help policymakers address the crisis by aiding in policy analysis and decision-making under uncertainty. In this paper, we project the effects of several policies to reduce opioid use disorder and overdose, and analyze intended and unintended effects of the policies over the next 10 years. Model simulations suggest most policies implemented on their own will achieve only modest reduction in either fatal overdoses or prevalence of OUD.

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