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Journal ArticleDOI

A network-based model to explore the role of testing in the epidemiological control of the COVID-19 pandemic.

12 Jan 2021-BMC Infectious Diseases (BioMed Central)-Vol. 21, Iss: 1, pp 58
TL;DR: In this paper, a network-based epidemic transmission model combined with a testing mechanism was proposed to study the role of testing in epidemic control and determine how testing affects the spread of epidemics and the daily testing volume needed to control infectious diseases.
Abstract: Testing is one of the most effective means to manage the COVID-19 pandemic. However, there is an upper bound on daily testing volume because of limited healthcare staff and working hours, as well as different testing methods, such as random testing and contact-tracking testing. In this study, a network-based epidemic transmission model combined with a testing mechanism was proposed to study the role of testing in epidemic control. The aim of this study was to determine how testing affects the spread of epidemics and the daily testing volume needed to control infectious diseases. We simulated the epidemic spread process on complex networks and introduced testing preferences to describe different testing strategies. Different networks were generated to represent social contact between individuals. An extended susceptible-exposed-infected-recovered (SEIR) epidemic model was adopted to simulate the spread of epidemics in these networks. The model establishes a testing preference of between 0 and 1; the larger the testing preference, the higher the testing priority for people in close contact with confirmed cases. The numerical simulations revealed that the higher the priority for testing individuals in close contact with confirmed cases, the smaller the infection scale. In addition, the infection peak decreased with an increase in daily testing volume and increased as the testing start time was delayed. We also discovered that when testing and other measures were adopted, the daily testing volume required to keep the infection scale below 5% was reduced by more than 40% even if other measures only reduced individuals’ infection probability by 10%. The proposed model was validated using COVID-19 testing data. Although testing could effectively inhibit the spread of infectious diseases and epidemics, our results indicated that it requires a huge daily testing volume. Thus, it is highly recommended that testing be adopted in combination with measures such as wearing masks and social distancing to better manage infectious diseases. Our research contributes to understanding the role of testing in epidemic control and provides useful suggestions for the government and individuals in responding to epidemics.

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Citations
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Posted ContentDOI
12 Feb 2021-medRxiv
TL;DR: Repeated testing of year-group bubbles following case detection or regular mass-testing strategies result in a modest increase in infections, but substantially reduce absences, highlighting the conflict between the goals of minimising within-school transmission, minimising absences and minimising testing burden.
Abstract: Background Strategies involving rapid testing have been suggested as a way of reopening schools that minimises absences while controlling transmission. We assess the likely impact of rapid testing strategies using lateral flow tests (LFTs) on infections and absences in secondary schools, compared to a policy of isolating year group bubbles upon a pupil returning a positive polymerase chain reaction (PCR) test. Methods We developed an individual-based model of a secondary school formed of exclusive year group bubbles (five year groups, with 200 pupils per year). By simulating infections over the course of a seven-week half-term, we compared the impact of differing strategies on transmission, absences, and testing volume. We also considered the sensitivity of results to underlying model assumptions. Findings Repeated testing of year-group bubbles following case detection or regular mass-testing strategies result in a modest increase in infections compared to the policy of isolating year-group bubbles, but substantially reduce absences. When combined these two testing strategies can reduce infections to levels lower than would occur under year-group isolation, although such a policy requires a high volume of testing. Interpretation Our results highlight the conflict between the goals of minimising within-school transmission, minimising absences and minimising testing burden. While mass and targeted testing strategies can reduce school transmission and absences, it may lead to a large number of daily tests.

13 citations

Journal ArticleDOI
TL;DR: In this article , a mathematical epidemic model (MEM), statistical model, and recurrent neural network (RNN) variants were used to forecast the cumulative confirmed cases of the COVID-19 pandemic.
Abstract: The COVID-19 pandemic has caused a global crisis with 47,209,305 confirmed cases and 1,209,505 confirmed deaths worldwide as of November 2, 2020. Forecasting confirmed cases and understanding the virus dynamics is necessary to provide valuable insights into the growth of the outbreak and facilitate policy-making regarding virus containment and utilization of medical resources. In this study, we applied a mathematical epidemic model (MEM), statistical model, and recurrent neural network (RNN) variants to forecast the cumulative confirmed cases. We proposed a reproducible framework for RNN variants that addressed the stochastic nature of RNN variants leveraging z-score outlier detection. We incorporated heterogeneity in susceptibility into the MEM considering lockdowns and the dynamic dependency of the transmission and identification rates which were estimated using Poisson likelihood fitting. While the experimental results demonstrated the superiority of RNN variants in forecasting accuracy, the MEM presented comprehensive insights into the virus spread and potential control strategies.

12 citations

Journal ArticleDOI
TL;DR: The results indicated that in light of South Africa's demographics, vaccinating older age groups (>60 years) largely reduced the cumulative deaths and the “0–20 first” strategy was the most effective way to reduce confirmed cases, while comprehensive reduction in infections was mainly affected by the vaccine proportion of the target age group.
Abstract: The vaccines are considered to be important for the prevention and control of coronavirus disease 2019 (COVID-19). However, considering the limited vaccine supply within an extended period of time in many countries where COVID-19 vaccine booster shot are taken and new vaccines are developed to suppress the mutation of virus, designing an effective vaccination strategy is extremely important to reduce the number of deaths and infections. Then, the simulations were implemented to study the relative reduction in morbidity and mortality of vaccine allocation strategies by using the proposed model and actual South Africa's epidemiological data. Our results indicated that in light of South Africa's demographics, vaccinating older age groups (>60 years) largely reduced the cumulative deaths and the “0–20 first” strategy was the most effective way to reduce confirmed cases. In addition, “21–30 first” and “31–40 first” strategies have also had a positive effect. Partial vaccination resulted in lower numbers of infections and deaths under different control measures compared with full vaccination in low-income countries. In addition, we analyzed the sensitivity of daily testing volume and infection rate, which are critical to optimize vaccine allocation. However, comprehensive reduction in infections was mainly affected by the vaccine proportion of the target age group. An increase in the proportion of vaccines given priority to “0–20” groups always had a favorable effect, and the prioritizing vaccine allocation among the “60+” age group with 60% of the total amount of vaccine consistently resulted in the greatest reduction in deaths. Meanwhile, we observed a significant distinction in the effect of COVID-19 vaccine allocation policies under varying priority strategies on relative reductions in the effective reproduction number. Our results could help evaluate to control measures performance and the improvement of vaccine allocation strategy for COVID-19 epidemic.

8 citations

Journal ArticleDOI
TL;DR: Understanding DHCWs' perception of risk and safety is crucial, as it likely influences attitudes toward testing and implementation of office risk mitigation policies, and clinical studies that correlate risk perception and RiMS with SARS-CoV-2 testing are needed.
Abstract: Objectives: To estimate the association between safety perception on vaccine acceptance and adoptions of risk mitigation strategies among dental health care workers (DHCWs). Methods: A survey was emailed to DHCWs in the New Jersey area from December 2020 to January 2021. Perceived safety from regular SARS-CoV-2 testing of self, coworkers, and patients and its association with vaccine hesitancy and risk mitigation were ascertained. Risk Mitigation Strategy (RiMS) scores were computed from groupings of office measures: 1) physical distancing (reduced occupancy, traffic flow, donning of masks, minimal room crowding), 2) personal protective equipment (fitted for N95; donning N95 masks; use of face shields; coverings for head, body, and feet), and 3) environmental disinfection (suction, air filtration, ultraviolet, surface wiping). Results: SARS-CoV-2 testing of dental professionals, coworkers, and patients were perceived to provide safety at 49%, 55%, and 68%, respectively. While dentists were least likely to feel safe with regular self-testing for SARS-CoV-2 (P < 0.001) as compared with hygienists and assistants, they were more willing than hygienists (P = 0.004; odds ratio, 1.79 [95% CI, 1.21 to 2.66]) and assistants (P < 0.001; odds ratio, 3.32 [95% CI, 1.93 to 5.71]) to receive the vaccine. RiMS scores ranged from 0 to 19 for 467 participants (mean [SD], 10.9 [2.9]). RiMS scores did not significantly differ among groups of DHCWs; however, mean RiMS scores were higher among those who received or planned to receive the COVID-19 vaccine than those with who did not (P = 0.004). DHCWs who felt safer with regular testing had greater RiMS scores than those who did not (11.0 vs. 10.3, P = 0.01). Conclusions: Understanding DHCWs’ perception of risk and safety is crucial, as it likely influences attitudes toward testing and implementation of office risk mitigation policies. Clinical studies that correlate risk perception and RiMS with SARS-CoV-2 testing are needed to demonstrate the effectiveness of RiMS in dental care settings. Knowledge Transfer Statement: Educators, clinicians, and policy makers can use the results of this study when improving attitudes toward testing and implementation of risk mitigation policies within dental offices, for current and future pandemics.

6 citations

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