COVID-19 in Shanghai: IPC Policy Exploration in Support of Work Resumption Through System Dynamics Modeling

Addressing Hospital Overwhelm During the COVID-19 Pandemic by Using a Primary Health Care-Based Integrated Health System: Modeling Study

Background

After strict COVID-19-related restrictions were lifted, health systems globally were overwhelmed. Much has been discussed about how health systems could better prepare for future pandemics; however, primary health care (PHC) has been largely ignored.

Objective

We aimed to investigate what combined policies PHC could apply to strengthen the health care system via a bottom-up approach, so as to better respond to a public health emergency.

Methods

We developed a system dynamics model to replicate Shanghai's response when COVID-19-related restrictions were lifted. We then simulated an alternative PHC-based integrated health system and tested the following three interventions: first contact in PHC with telemedicine services, recommendation to secondary care, and return to PHC for recovery.

Results

The simulation results showed that each selected intervention could alleviate hospital overwhelm. Increasing the rate of first contact in PHC with telemedicine increased hospital bed availability by 6% to 12% and reduced the cumulative number of deaths by 35%. More precise recommendations had a limited impact on hospital overwhelm (<1%), but the simulation results showed that underrecommendation (rate: 80%) would result in a 19% increase in cumulative deaths. Increasing the rate of return to PHC from 5% to 20% improved hospital bed availability by 6% to 16% and reduced the cumulative number of deaths by 46%. Moreover, combining all 3 interventions had a multiplier effect; bed availability increased by 683%, and the cumulative number of deaths dropped by 75%.

Conclusions

Rather than focusing on the allocation of medical resources in secondary care, we determined that an optimal PHC-based integrated strategy would be to have a 60% rate of first contact in PHC, a 110% recommendation rate, and a 20% rate of return to PHC. This could increase health system resilience during public health emergencies.

Optimizing national border reopening policies in the COVID-19 pandemic: A modeling study

Objective

After emergence of the COVID-19 pandemic and subsequent restrictions, countries worldwide have sought to reopen as quickly as possible. However, reopening involves the risk of epidemic rebound. In this study, we investigated the effective policy combination to ensure safe reopen.

Methods

On the basis of the classical SEIR epidemic model, we constructed a COVID-19 system dynamics model, incorporating vaccination, border screening, and fever clinic unit monitoring policies. The case of China was used to validate the model and then to test policy combinations for safe reopening.

Findings

Vaccination was found to be crucial for safe reopening. When the vaccination rate reached 60%, the daily number of newly confirmed COVID-19 cases began to drop significantly and stabilized around 1,400 [1/1,000,000]. The border screening policy alone only delayed epidemic spread for 8 days but did not reduce the number of infections. Fever clinic unit monitoring alone could reduce the peak of new confirmed cases by 44% when the case identification rate rose from 20 to 80%. When combining polices, once the vaccination rate reached 70%, daily new confirmed cases stabilized at 90 [0.64/1,000,000] with an 80% case identification rate at fever clinic units and border screening. For new variants, newly confirmed cases did not stabilize until the vaccination rate reached 90%.

Conclusion

High vaccination rate is the base for reopening. Vaccination passport is less effective compared with a strong primary care monitoring system for early detection and isolation of the infected cases.

Using simulation modelling and systems science to help contain COVID-19: A systematic review

This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent-based model (ABM) and discrete event simulation (DES), and their hybrids in COVID-19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID-19 transmission dynamics, 204 evaluated both pharmaceutical and non-pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID-19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID-19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio-economic systems involved.

Policy choices for Shanghai responding to challenges of Omicron

Background

A new wave of Coronavirus disease 2019 (COVID-19) infection driven by Omicron BA.2 subvariant hit Shanghai end of February 2020. With higher transmissibility and milder symptoms, the daily new confirmed cases have soared to more than 20 K within one and a half months. The greatest challenge of Omicron spreading is that the rapidly surging number of infected populations overwhelming the healthcare system. What policy is effective for huge cities to fight against fast-spreading COVID-19 new variant remains a question.

Methods

A system dynamics model of the Shanghai Omicron epidemic was developed as an extension of the traditional susceptible-exposed-infected-susceptible recovered (SEIR) model to incorporate the policies, such as contact tracing and quarantine, COVID-19 testing, isolation of areas concerned, and vaccination. Epidemic data from Shanghai Municipal Health Commission were collected for model validation.

Results

Three policies were tested with the model: COVID-19 testing, isolation of areas concerned, and vaccination. Maintaining a high level of COVID-19 testing and transfer rate of the infected population can prevent the number of daily new confirmed cases from recurring growth. In the scenario that 50% of the infected population could be transferred for quarantine on daily bases, the daily confirmed asymptomatic cases and symptomatic cases remained at a low level under 100. For isolation of areas concerned, in the scenario with most isolation scope, the peak of daily confirmed asymptomatic and symptomatic cases dropped 18 and 16%, respectively, compared with that in the scenario with least isolation. Regarding vaccination, increasing the vaccination rate from 75 to 95% only slightly reduced the peak of the confirmed cases, but it can reduce the severe cases and death by 170%.

Conclusions

The effective policies for Omicron include high level of testing capacity with a combination of RAT and PCR testing to identify and quarantine the infected cases, especially the asymptomatic cases. Immediate home-isolation and fast transfer to centralized quarantine location could help control the spread of the virus. Moreover, to promote the vaccination in vulnerable population could significantly reduce the severe cases and death. These policies could be applicable to all metropolises with huge population facing high transmissible low severity epidemic.

Assessing the dynamic impacts of non-pharmaceutical and pharmaceutical intervention measures on the containment results against COVID-19 in Ethiopia

The rapid spread of COVID-19 in Ethiopia was attributed to joint effects of multiple factors such as low adherence to face mask-wearing, failure to comply with social distancing measures, many people attending religious worship activities and holiday events, extensive protests, country election rallies during the pandemic, and the war between the federal government and Tigray Region. This study built a system dynamics model to capture COVID-19 characteristics, major social events, stringencies of containment measures, and vaccination dynamics. This system dynamics model served as a framework for understanding the issues and gaps in the containment measures against COVID-19 in the past period (16 scenarios) and the spread dynamics of the infectious disease over the next year under a combination of different interventions (264 scenarios). In the counterfactual analysis, we found that keeping high mask-wearing adherence since the outbreak of COVID-19 in Ethiopia could have significantly reduced the infection under the condition of low vaccination level or unavailability of the vaccine supply. Reducing or canceling major social events could achieve a better outcome than imposing constraints on people's routine life activities. The trend analysis found that increasing mask-wearing adherence and enforcing more stringent social distancing were two major measures that can significantly reduce possible infections. Higher mask-wearing adherence had more significant impacts than enforcing social distancing measures in our settings. As the vaccination rate increases, reduced efficacy could cause more infections than shortened immunological periods. Offsetting effects of multiple interventions (strengthening one or more interventions while loosening others) could be applied when the levels or stringencies of one or more interventions need to be adjusted for catering to particular needs (e.g., less stringent social distancing measures to reboot the economy or cushion insufficient resources in some areas).

Which Matters More in Fighting COVID-19—Government Policy or Community Participation?

Objective

As a heavily populated megacity, Shanghai faces major epidemic risks. However, Shanghai's control of COVID-19 has been successful owing to both the strict government policy and wide community participation. Here, we investigated the impact of these stakeholders and examined who played a major role across different epidemic stages.

Design

We extended the classic susceptible-exposed-infectious-recovered (SEIR) model considering the heterogeneous contact structure in four social sceneries, i.e., school, workplace, public entertainment venues, and neighborhood community, which could reflect the impact of lockdown policy and wide participation of residents happened at the community level.

Result

The simulation results showed that without lockdown policy and only with community participation, the daily new confirmed cases would gradually increase to more than 7,000 [292/1,000,000] at the end of Sep. However, without community participation and only with a lockdown policy, the daily new confirmed cases sharply decreased to 30 [1.2/1,000,000] at the end of the 1st month and remained low for several months. However, when a lockdown policy was gradually lifted, the new confirmed cases increased exponentially, eventually reaching more than 17,000 [708/1,000,000]. Therefore, a government lockdown policy was necessary for the rapid control of COVID-19 during the outbreak stage while community participation is more important in keeping the number of new confirmed cases low during the reopening stage.

Conclusion

Government lockdown policy and community participation play different roles in the control of COVID-19 at different stages of the epidemic: although the government played a leading role in setting up policies, the broader participation of community fever clinics (CFCs) and the general public were especially crucial in winning the battle against COVID-19 in the long run.

Returning to Work after the COVID-19 Pandemic Earthquake: A Systematic Review

Background: The ongoing SARS-CoV-2 pandemic has disrupted life and work habits and has produced landmark changes worldwide. This systematic review aimed to analyse the management of Return to Work (RTW) by work organisations following the virus spread. Methods: A selection of 2477 papers, using string research on PubMed, Embase, Web of Science and Scopus from January 2020 to October 2021, were analysed. Results: Fifty-one articles were finally included, and the results obtained were discussed from three different points of view. Twenty articles concerning ‘Remodelling of Work Organization’ proposed some model strategies for resumption to work. Twenty-one papers, including ‘Clinical Evaluation of Workers’, mostly explored the psychosocial impact of returned workers. Finally, twelve articles explored the best ‘Testing Strategies related to RTW’. Despite the heterogeneity of included articles, several interesting approaches have emerged in managing RTW. Conclusions: The reported experiences could help to develop an RTW model for COVID-19 and future pandemics.

Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan

BACKGROUND

Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear.

METHODS

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 and was validated with real-world data. The input data were obtained from official websites and the published literature.

RESULTS

The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening 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. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies.

CONCLUSIONS

The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic.

KEYORDS

COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

System-Dynamics Modeling for Exploring the Impact of Industrial-Structure Adjustment on the Water Quality of the River Network in the Yangtze Delta Area

The coordinated development of the environment and economy is the core of sustainable development. This research investigated sustainable water-quality management by exploring the impact of socioeconomic activities on water quality associated with a major global city. To achieve this goal, a system dynamics (SD) model was developed to capture the feedback processes and interactions between the water quality; population; water resource; and the primary, secondary, and tertiary sectors of the Yangtze Delta area, especially Jiaxing City. More importantly, we further subdivided and identified the nine key subindustries within three sectors as high-polluting factors. Using this model, five scenarios based on different industrial restructurings were investigated. The simulation results suggested that Jiaxing City’s water quality would conform to a steadily increasing trend over 2021–2035. Changes in the farming industry have the most significant impact on water quality, followed by those in the paper and paper production (PPP) industry and the livestock and poultry breeding (LPB) industry. In terms of individual pollutant concentrations, the concentrations of COD and TN were most sensitive to changes in the farming industry, while PPP and LPB were identified as having the most influence on the concentrations of NH3-N and TP, respectively. It is feasible for Jiaxing City to improve its water quality through collaborative optimization of three industries. However, the effect of industrial structure adjustment is limited. Strategies comprising cleaner production should be undertaken to reduce pollution generation.

COVID-19 and Return-To-Work for the Construction Sector: Lessons From Singapore

Singapore’s construction sector employs more than 450,000 workers. During the height of the COVID-19 pandemic in Singapore from April to June 2020, migrant workers were disproportionately affected, including many working in the construction sector. Shared accommodation and construction worksites emerged as nexuses for COVID-19 transmission. Official government resources, including COVID-19 epidemiological data, 43 advisories and 19 circulars by Singapore’s Ministries of Health and Manpower, were reviewed over 8 month period from March to October 2020. From a peak COVID-19 incidence of 1,424.6/100,000 workers in May 2020, the incidence declined to 3.7/100,000 workers by October 2020. Multilevel safe management measures were implemented to enable the phased reopening of construction worksites from July 2020. Using the Swiss cheese risk management model, the authors described the various governmental, industry, supervisory and worker-specific interventions to prevent, detect and contain COVID-19 for safe resumption of work for the construction sector.

Characterizing the patterns of China's policies against COVID-19: A bibliometric study

Since the beginning of 2020, the Chinese government has implemented substantial policies to prevent and control the COVID-19 epidemic. This research attempts to reveal and characterize the patterns of China's policy against COVID-19. Bibliometric methods are applied for studying policy evolution, with the aim of discovering the transitions of the policies over time, the collaborations among policy makers, and the effects of the policies. A total of 366 policies of epidemic prevention are collected. Policy topic shifting, the cooperation of policy-issuing agencies, and the policy content of agencies are analyzed. According to the results, China's policies are implemented in four stages. Moreover, the policy's foci against COVID-19 shifted from medical support in the early stage to economic development in the late stage. Agencies involved in the policymaking can be categorized into three types: leading agencies, key agencies, and auxiliary agencies, with their corresponding administrative influence ranked in this order. Especially, the Chinese government adopted a multi-agency, joint epidemic prevention and control mechanism to ensure the efficiency of the policymaking cooperation. Furthermore, aside from ensuring cooperation among the policy-issuing agencies, they each had their own primary focus of policies in the early stage, but their foci were gradually shared as the epidemic situation changed. This research reveals how China responded to the public health emergency of COVID-19 from the perspective of policy making.