We discuss a pandemic management framework using symptom-based quick response (QR) codes to contain the spread of COVID-19. In this approach, symptom-based QR health codes are issued by public health authorities. The codes do not retrieve the location data of the users; instead, two different colors are displayed to differentiate the health status of individuals. The QR codes are officially regarded as electronic certificates of individuals’ health status, and can be used for contact tracing, exposure risk self-triage, self-update of health status, health care appointments, and contact-free psychiatric consultations. This approach can be effectively deployed as a uniform platform interconnecting a variety of responders (eg, individuals, institutions, and public authorities) who are affected by the pandemic, which minimizes the errors of manual operation and the costs of fragmented coordination. At the same time, this approach enhances the promptness, interoperability, credibility, and traceability of containment measures. The proposed approach not only provides a supplemental mechanism for manual control measures but also addresses the partial failures of pandemic management tools in the abovementioned facets. The QR tool has been formally deployed in Fujian, a province located in southeast China that has a population of nearly 40 million people. All individuals aged ≥3 years were officially requested to present their QR code during daily public activities, such as when using public transportation systems, working at institutions, and entering or exiting schools. The deployment of this approach has achieved sizeable containment effects and played remarkable roles in shifting the negative gross domestic product (–6.8%) to a positive value by July 2020. The number of cumulative patients with COVID-19 in this setting was confined to 363, of whom 361 had recovered (recovery rate 99.4%) as of July 12, 2020. A simulation showed that if only partial measures of the framework were followed, the number of cumulative cases of COVID-19 could potentially increase ten-fold. This approach can serve as a reliable solution to counteract the emergency of a public health crisis; as a routine tool to enhance the level of public health; to accelerate the recovery of social activities; to assist decision making for policy makers; and as a sustainable measure that enables scalability.
We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users’ privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.
A new preparation method of a light-focusing plastic rod (LFR) is reported, where the photocopolymerization of methacrylic esters (M1) such as methyl methacrylate (MMA) with vinyl benzoates (M2) such as vinyl benzoate (VB), vinyl o-chlorobenzoate, and vinyl o,p-dichloro-benzoate was carried out. The M1-M2 mixture placed in a glass tube was exposed to uv light by rotating a glass tube about its axis. LFR prepared from a MMA-VB pair has a quadratic gradient constant with a refractive index A= (3∼11) ×10−3 mm−2, an internal loss of light transmission IL= (3∼12) dB/m, and a ratio of the radius of the imaging region to the rod radius (ri/rp) =0.5∼0.7.
Estimation of the undocumented cases of COVID-19 is critical for understanding the epidemic potential of the disease and informing pandemic response. The COVID-19 pandemic originated from a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus similar to severe acute respiratory syndrome (SARS) that was formerly identified in 2003. The contagiousness, dynamics of the pathogen, and mobility of the general population incurred the occurrence of underestimation of infection (i.e., the unidentified cases and the gap with the identified cases) that was potentially substantial in magnitude, which was supposed to connect with subsequent cyclical outbreaks in practice. We employed a Susceptible-Infected-Removed-Contained (SIR-C) mathematical model to infer critical epidemiological characteristics associated with COVID-19, then asymptotically simulated the peak sizes and peak dates of the identified and unidentified cases, the underestimation, and the dynamics of the gap. The simulation outcomes indicated that unidentified peak dates in practice could predate the reported peak dates for a variable period of weeks or months. In comparison, the saturation sizes of infection remained at commensurate levels. The curve of the initial exponential-like outbreak for the undocumented cases would flatten when the gap between concurrent identified cases and unidentified cases decreased. The rate of non-pharmaceutical containment could impact the trend of disease transmission ceteris paribus, and the greater the rate the larger reduction of infections. When the rate reached a certain level of threshold, the undocumented curve would shift from flattening effect to decaying effect. A similar trend was observed when it applied to the rate of pharmaceutical containment measures ceteris paribus. The results were sensitive to the duration of infection (DOI), it manifested that greater values of DOI were associated with greater peak sizes and greater peak dates for both documented and undocumented cases. Conditional on assumptions, calibration of DOI from 8 days to 18 days would increase the unidentified peak size by nearly 56% and the peak date by almost 18 days.
Since the outbreak of COVID-19, it became urgent to deal with the relationship between the prevention and control of the epidemic and the resumption of work and production. The purpose of this study is to observe and describe which approach seemed more important for the Chinese government and people, and how this trend evolved through time. To this end, a game model of resuming production and preventing the epidemic is constructed, using the evolutionary stable strategy (ESS). By combing China’s measures on epidemic prevention and resuming production during critical periods of epidemic outbreak, it is clarified that the present stage is considered a period of equal emphasis on both epidemic prevention and resuming production. Based on the dynamic between these two strategies and further theoretical research, present policies should equally focus on both preventive and controlling measures as well as on the socioeconomic development for most countries in the world.
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