Initial Transmission Research Articles

Comparing micro-level and macro-level models for epidemic diffusion in the metro system

ABSTRACT Few studies focus on how the ground transport system has increased COVID-19 transmission; the details of its spread remain unclear. The absence of station-level data obstructs healthcare professionals from effectively targeting anti-epidemic measures. This study employs agent-based modeling through GAMA software to identify Taipei metro stations implicated in initial transmission. In addition, a macro-level estimator is applied as a baseline model to compare COVID-19 arrival sequences at each station. Utilizing electronic metro ticket data, passenger travel patterns are discerned. We found (1) the average infection order of all stations, according to both models were not significantly different; (2) however, this difference between two model results became significant when the sample size was decreased. (3) Of all the stations, Taipei Main Station was the first because it has the highest passenger volume and the most connections. These early infected stations are near Taipei Main station and commercial or hub stations.

Optimal control of an epidemic model with treatment in the presence of media coverage

During large scale outbreaks of infectious diseases, it is imperative that media report about the potential risks. Because media reporting plays a vital role in disseminating crucial information about diseases and its associated risk, understanding how media reports could influence individuals’ behavior and its potential impact on disease transmission dynamics is important. A mathematical model within an optimal control framework of a generic disease, accounting for treatment and media reporting of disease-induced deaths is formulated. Due to the complexity of choosing the best media function, our goal is to attempt to address the following research question: what is the effect of the media-induced functional response on mitigating the spread of the disease? Connecting the functional forms to the control problem is an approach that is not very developed in the literature. Thus, this study analyses the effect of different incidence functions on disease transmission, and the qualitative nature of epidemic dynamics by carrying out optimal control analysis using three different contact rates and a media function that is dependent on the number of deaths. Theoretical analyses show that the functional forms of the effective contact rate have no effect on initial disease transmission. Time-dependent controls for treatment and vaccination with a constant effective contact rate are incorporated to determine optimal control strategies. Numerical simulations show the short-term impact of media coverage on mitigating the spread of the disease, and it is observed that with three incidence functions used, the qualitative nature of the controls remains the same. The effective contact rates are graphically shown to have a population-level effect on the disease dynamics as the number of treated and recovered individuals could be significantly different. Finally, it is shown that treatment of infectives should be at its maximum rate for a longer period compared to vaccination, while concurrent implementation of vaccination and treatment is more impactful in mitigating the spread of the disease. Thus, it is imperative that media reports and health policy decision making on infectious diseases are contextualized.

A mathematical model for investigating the effect of media awareness programs on the spread of COVID-19 with optimal control

The coronavirus pandemic is a global health crisis creating an unprecedented socio-economic catastrophe. This pandemic is the biggest challenge the world has faced since World War II and is the main turning point in the history of humanity. Media coverage can change citizens’ attention to emerging infectious diseases and consequently change individual behaviors and attitudes. This study proposes and analyzes a seven-compartmental mathematical model to investigate the impact of media coverage on the spread and control of COVID-19. The threshold condition Ro for the initial transmission of infection is achieved by the next-generation approach. Stability analysis of the proposed model on disease-free and endemic equilibria is investigated in terms of basic reproduction numbers locally and globally. The sensitivity analysis of the reproduction number is visualized to distinguish the most sensitive parameters that can be regulated to control the transmission dynamics of coronavirus disease. Moreover, the theoretical results of the deterministic model are compared using numerical simulations. The outcomes of the analysis suggest that the disease prevalence can be terminated by suitable management of quarantine/medical care. We further extend the model to the optimal control framework. It is analyzed using Pontryagin’s maximum principle to characterize preventive control, testing facility, and treatment measures for managing COVID-19 transmission.

Effect of short stem alignment on initial fixation, stress transfer, and failure risk.

Short stems are advantageous for revision as they preserve autogenous bone. At present, the method of short-stem installation is determined based on the surgeon's experience. To provide the guideline for installing a short stem, we aimed to investigate the alignment effect on the initial fixation of the stem, stress transfer, and the risk of failure numerically. Models in which the caput-collum-diaphyseal (CCD) angle and flexion angle were hypothetically changed based on the two clinical cases of hip osteoarthritis were analyzed using the non-linear finite element method. The medial settlement of the stem increased in the varus model and decreased in the valgus model. With varus alignment, the stresses acting on the femur were high in the distal to the femoral neck. In contrast, the stresses in the proximal to the femoral neck tend to be higher with valgus alignment, although the difference in the femur stress between varus and valgus alignment was slight. Both initial fixation and stress transmission are lower when the device was placed in the valgus model than in the actual surgical case. In order to obtain initial fixation and suppress stress shielding, it is essential to extend the contact area between the medial portion of the stem and the femur along the bone axis, and to ensure adequate contact between the lateral portion of the stem tip and the femur.

Initial Transmission Influence on Saturable Absorber Absorption Activity of Passive Q-Switching Erbium -Doped Fiber Laser System

The initial transmission effect on the activity of Cr+4: YAG saturable absorber with Er +3 doped fiber laser was investigated. Software computer program was built in this study for solving the rate equations model by Rung - Kutta –Fehlberg numerical method. The study reported that the absorption activity of ground state of saturable absorber decreases with the decreasing of the initial transmission, while the activity absorption of excited state begins to increase. Moreover, the total absorption activity of saturable absorber also decreases with the decreasing of the initial transmission.

A deterministic model of COVID-19 with differential infectivity and vaccination booster

Vaccine boosters have been recommended to mitigate the spread of the coronavirus disease 2019 (COVID-19) pandemic. A mathematical model with three vaccine doses and susceptibility is formulated. The model is calibrated using the cumulative number of hospitalized cases from Alberta, Canada. Estimated values from the fitting are used to explore the potential impact of the booster doses to mitigate the spread of COVID-19. Sensitivity analysis on initial disease transmission shows that the most sensitive parameters are the contact rate, the vaccine efficacy, the proportion of exposed individuals moving into the symptomatic and asymptomatic classes, and the recovery rate from asymptomatic infection. Simulation results support the positive population-level impact of the second and third COVID-19 vaccine boosters to reduce the number of infections and hospitalizations. Public health policy and decision-makers should continue advocating and encouraging people to get booster doses. As the end of the pandemic is in sight, there should be no complacency before it resolves.

1835. Factors impact Longevity in Persons Living with HIV

Abstract Background In contrast to high mortality including young patient in 1990’s, persons living with HIV (PLWHIV) can expect a near-normal life expectancy of 77 years. Recent mortality data suggests significant number of HIV positive patients pass before the age of 70 years. There is a current paucity of literature looking at characteristics of the elderly PLWHIV when comparing to patients who died from HIV at a younger age. The goal of this study was to compare factors between the current HIV population living longer than age 70 and the population that did not survive until age 70 at the Positive Health Clinic (PHC). PHC is an urban city Ryan White funded HIV Care Medical Home Clinic, at Pittsburgh, PA, that provides care to ∼920 PLWHIV Methods A retrospective chart review of patient records at PHC; with patients from period between 2015 -2022 was queried for HIV viral load, recent CD4 counts, and social history. Smoking, alcohol, and drug use were used as primary social measures due to their known impact in early development of prevalent chronic comorbidities. A Chi squared test was then employed to analyze for statistical significance of these factors (P < 0.05) between the cohort of patients that are living beyond the age of 70 (longevity) and the cohort of patients who died prior to age of 70 Results A total of 149 records were obtained (122M/ 27F, 95W/54B). The median age of HIV diagnosis and death was 44 and 60, respectively. There was no statistical difference between two groups in gender, race, and initial HIV transmission route, but being diagnosed with HIV after the age of 40 was associated with longevity. Unsurprisingly, patient with last viral load above 500 or CD4 below 200 were less likely to survive past age 70. HIV viral load < 200, persistently, in past 5 years and absence of smoking in last 15 years were the 2 factors most strongly associated longevity. Alcohol abuse and drug use were less likely to survive age 70. Statistical data between the two groups are listed in Table attached. Comparing factors associated with living beyond 70 versus dying before 70 Conclusion Common comorbidities such as diseases of heart, lung, kidney and cancer are impacted by substance misuse, and as a result may serve as a barrier to reaching old age in PLWHIV. Counseling against tobacco use, treatment of alcohol and drug addiction while sustaining viral control with HAART can promote the longevity of PLWHIV. Disclosures Chiu-bin hsiao, MD, Gilead: Grant/Research Support|ViiV: Advisor/Consultant|ViiV: Grant/Research Support|ViiV: Honoraria

Robust multi-scale weighting-based edge-smoothing filter for single image dehazing

The guided image filter (GIF) and weighted guided image filter (WGIF) are local linear model-based good edge-preserving filters. However, due to fixed regularization parameter, they suffer from halo artifacts (morphological artifacts) in the sharp regions. To overcome this issue, a robust multi-scale weighting-based edge-smoothing filter (RMWEF) for single image dehazing is proposed in this paper. It removes morphological artifacts and over-smoothness strongly and preserves edge information precisely in both flat and sharp regions. The proposed dehaze method has four-steps. First, initial transmission map and atmospheric map are estimated by using a novel dark channel prior (DCP) method. Then, the morphological artifacts of initial transmission map are reduced by using non-local haze line averaging (NL-HLA) method. In the third step, transmission map is refined by using the proposed RMWEF. Finally, the haze free image is restored. Theoretical and experimental analysis proves that the proposed algorithm produce effective dehaze results quicker than the existing methods.

Evaluating early pandemic response through length-of-stay analysis of case logs and epidemiological modeling: A case study of Singapore in early 2020

Abstract It is now known that early government interventions in pandemic management helps in slowing down the pandemic in the initial phase, during which a conservative basic reproduction number can be maintained. There have been several ways to evaluate these early response strategies for COVID-19 during its outbreak globally in 2020. As a novelty, we evaluate them through the lens of patient recovery logistics. Here, we use a data-driven approach of recovery analysis in a case study of Singapore during January 22–April 01, 2020, which is effectively the analysis of length-of-stay in the government healthcare facility, National Center for Infectious Diseases. We propose the use of a data-driven method involving periodization, statistical analysis, regression models, and epidemiological models. We demonstrate that the estimates of reproduction number in Singapore shows variation in different age groups and periods, indicating the success of early intervention strategy in the initial transmission stages of the pandemic.

Modified optical computed tomography scanner for low temperature scanning

Large radiochromic hydrogels, such as ferrous xylenol formulations require several hours to warm from the storage temperature of 278 K to 293 K for optical CT scanning and irradiation. This warm-up time can be avoided if gels are scanned at 278 K, resulting in a more practical 3D dose measurement. In this study a Vista 16 optical CT scanner was modified to allow scanning at 278 K, below the temperature where condensation forms on the aquarium windows. The refractive index matching liquid was first cooled to 276K in order to cool the aquarium as it was filled. The modification involved pumping cool, dry air into the aquarium scanner compartment to provide a positive pressure, preventing condensation on the aquarium windows. A warming rate of 2 K per hour was achieved with passive cooling which relied on the liquid-filled aquarium’s thermal mass. The radiochromic reaction rate decreased with temperature, requiring an increased post-irradiation wait time from 1 hour at 293 K to 1.5 hours at 278 K. In addition, initial sample transmission was greater by avoiding the auto-darkening that occurred as the samples were warmed from 278 K to 293 K over several hours. This increase in transmission resulted in a larger dynamic range for the dosimeter system.

Unraveling COVID-19 investigation hurdles with viral genomics

Abstract In the context of a COVID-19 outbreak, identifying transmission chains is crucial for effective public health response. However, relying solely on epidemiological investigation can lead to misidentification of links. This study aimed to assess the concordance between epidemiologically linked cases and viral genetic profiles in the Baixo Vouga Region of Portugal, from March to June 2020. We conducted a retrospective analysis of 1925 COVID-19 cases, of which 1143 were assigned to 154 epiclusters. Viral genomic data was available for 128 cases. We used this data to assess the accuracy of the initial transmission dynamics reconstruction, identify misidentified links, and resolve sporadic cases. Public health authorities identified two large epiclusters with a central role in disease spread, but the genomic data revealed that each epicluster included more than one transmission network. The increasing size of epiclusters and their extension to densely populated settings triggered the misidentification of links. Genomics also helped resolve some sporadic cases and misidentified directions of transmission. The epidemiological investigation had a sensitivity of 70%−86% in detecting transmission chains. Our findings demonstrate the challenges associated with the epidemiological investigation of hundreds of community cases in the context of a massive outbreak caused by a highly transmissible and new respiratory virus. We recommend incorporating viral genomics into outbreak investigations to improve the accuracy of transmission chain reconstructions. This could lead to the development of more effective public health actions such as prevention activities, policies, and surveillance systems. The innovative use of genomics in epidemiological investigations can have a significant impact on public health outcomes. Key messages • Large COVID-19 epiclusters and densely populated settings led to misidentified links. Epidemiological investigation had 70%−86% sensitivity to detect chains. • Using viral genomics in outbreak investigations can improve accuracy of transmission chain reconstructions, helping to resolve misidentified links and sporadic cases.

Image Defogging Based on Regional Gradient Constrained Prior

Foggy days limit the functionality of outdoor surveillance systems. However, it is still a challenge for existing methods to maintain the uniformity of defogging between image regions with a similar depth of field and large differences in appearance. To address above problem, this article proposes a regional gradient constrained prior (RGCP) for defogging that uses the piecewise smoothing characteristic of the scene structure to achieve accurate estimation and reliable constraint of the transmission. RGCP first derives that when adjacent similar pixels in the fog image are aggregated and spatially divided into regions, clusters of region pixels in RGB space conform to a chi-square distribution. The offset of the confidence boundary of the clusters can be regarded as the initial transmission of each region. RGCP further uses a gradient distribution to distinguish different regional appearances and formulate an interregional constraint function to constrain the overestimation of the transmission in the flat region, thereby maintaining the consistency between the estimated transmission map and the depth map. The experimental results demonstrate that the proposed method can achieve natural defogging performance in terms of various foggy conditions.

Dynamic tunable multiple plasmon induced transparency sensor and optical switch in dual-polarization excitation in a terahertz graphene metamaterial

This paper proposes the development of a simplified graphene-based terahertz device that exhibits multiple plasmon induced transparency (PIT) effects in x-polarized and y-polarized waves. The PIT device is composed of “Z-shaped” and “parallel strips” structures, which demonstrate multiple transparency windows under x-polarized and y-polarized incident light within the frequency range of 2-15 THz. Additionally, under x-polarized incident, the device demonstrates wideband transparency at 3.4 THz. By comparing the transmission spectra of individual and combined structures, we observe that the initial transmission valley of the single two horizontal stripes structure transforms into a PIT curve in the combined structure, while the transmission valley of the other individual structures remains transmission. The PIT device demonstrates a peak sensitivity of 3THz/RIU for x-polarized waves and 2.9THz/RIU for y-polarized waves when employed as a light sensor. PIT as a light switch can attain a maximum modulation depth of 81.4% for x-polarized waves and 71.2% for y-polarized waves at Fermi energy levels ranging from 0.5eV to 1.2eV. The presented PIT device shows promise for applications in high-sensitivity optical sensing and optical switching.

Dual-mode vortex beam transmission metasurface antenna based on linear-to-circular polarization converter.

The generation of multi-mode vortex beams at the same aperture is currently emerging as a research hotspot. In this paper, a method based on a linearly polarized-circularly polarized translational transmission metasurface (TM) is proposed to enable a dual-circularly polarized dual-mode vortex beam generation. Through the judicious implementation of an additional rotational phase and the combination of the initial transmission phase, the phases of the left-hand circularly polarized (LHCP) and right-hand circularly polarized (RHCP) waves can be manipulated arbitrarily and independently. Meanwhile, the design of the array phase is utilized for the dual-mode dual-circularly polarized beam generation. Simulation and sample measurements provide validation data for the feasibility of this method, in which the measurement results are in excellent consistency with the simulation ones. This proposed method paves the way toward the enhancement of the channel capacity of mobile communication.

Highly-Efficient Low-Latency HARQ Built on NOMA for URLLC: Radio Resource Allocation and Transmission Rate Control Aspects

Hybrid automatic repeat request (HARQ) is an essential technology that efficiently reduces the transmission error rate. However, for ultra-reliable low latency communications (URLLC) in the 5th generation mobile communication systems and beyond, the increase in latency due to retransmission must be minimized in HARQ. In this paper, we propose a highly-efficient low-latency HARQ method built on non-orthogonal multiple access (NOMA) for URLLC while minimizing the performance loss for coexisting services (use cases) such as enhanced mobile broadband (eMBB). The proposed method can be seen as an extension of the conventional link-level non-orthogonal HARQ to the system-level protocol. This mitigates the problems of the conventional link-level non-orthogonal HARQ, which are decoding error under poor channel conditions and an increase in transmission delay due to restrictions in retransmission timing. In the proposed method, delay-sensitive URLLC packets are preferentially multiplexed with best-effort eMBB packets in the same channel using superposition coding to reduce the transmission latency of the URLLC packet while alleviating the throughput loss in eMBB. This is achieved using a weighted channel-aware resource allocator (scheduler). The inter-packet interference multiplexed in the same channel is removed using a successive interference canceller (SIC) at the receiver. Furthermore, the transmission rates for the initial transmission and retransmission are controlled in an appropriate manner for each service in order to deal with decoding errors caused by error in transmission rate control originating from a time varying channel. We show that the proposed method significantly improves the overall performance of a system that simultaneously provides eMBB and URLLC services.

High repetition rate π-polarized 1084 nm passively Q-switched Nd:MgO:LiNbO3 laser based on 888 nm thermally boosted pumping

We report a high-repetition-rate π-polarized 1084 nm passively Q-switched (PQS) Nd:MgO:LiNbO3 (Nd:MgO:LN) laser under 888 nm thermally boosted pumping. The 888 nm pumping is selected based on Nd:MgO:LN crystal absorption and energy level properties. Under 813 nm pumping, the continuous wave (CW) 1084 nm average output power (AOP) increased to 2.85 W. After that, 1084 nm is suppressed and gradually disappears as the pump power increases. At the same time, the 1093 nm AOP increases, and 4.4 W of 1093 nm laser is obtained. In contrast, under 888 nm pumping, the CW 1084 nm laser AOP of 5.16 W is obtained. The thermally boosted pumping can eliminate quantum defects caused by conventional 813 nm pumping non-radiative transitions and suppress unmatched σ-polarized 1093 nm output. Moreover, the Cr4+: YAG is replaced into the resonant cavity as the output mirror to obtain 1084 nm pulsed laser output. AOP with different initial transmission (T0) on laser output characteristics is measured under the compact resonant cavity structure. Finally, an AOP of 3.52 W pulsed laser with a repetition rate of 24.43 kHz and the highest peak power of 5.26 kW is obtained when T0 = 87 %, and the absorbed pump power is 20.87 W. The optical conversion efficiency is 16.87 %, and the slope efficiency is about 29.38 %.

Understanding the Necessity and Economic Benefits of Lockdown Measures to Contain COVID-19

Since the outbreak of the coronavirus disease 2019 (COVID-19), the issue of how to maintain economic development while containing the epidemic has become a significant concern for decision-makers. Though lockdown measures are verified to be very effective in containing the epidemic, its economic costs and other influences have not been fully explored. As a result, decision-makers in many countries are still hesitant to include the lockdown measure in an intervention strategy in response to COVID-19. To address this issue, we propose a universal computational experiment approach for policy evaluation and adjustment based on the Artificial societies, Computational experiments, Parallel execution (ACP) concept. First, we innovatively construct a model via observable CO<inline-formula> <tex-math notation="LaTeX">$_2$</tex-math> </inline-formula> emissions, which is able to estimate the economic costs affected by nonpharmaceutical interventions. Furthermore, based on the population movement data, a risk source model is proposed to estimate the local transmission risk for any prefectures outside the epicenter. Finally, we integrate the data models in a high-resolution agent-based artificial society and carry out large-scale computational experiments supported by the Tianhe supercomputer. Policy adjustments and evaluations are carried out in four cities: Wenzhou, Guangzhou, Beijing, and Wuhan. Our research findings show important implications for policy-making: 1) the local transmission of a city can be almost contained if lockdowns are adopted immediately when the risk index is larger than 1.645, 1.960, or 2.576 at the 90%, 95%, or 99% confidence interval, respectively; 2) if lockdowns are required, in-advance lockdown measures facilitate mitigation efficacy and reduce economic loss; and 3) lockdowns lasting for 7&#x2013;14 days in a prefecture would be effective in controlling the spread of the epidemic. The duration of the measure should be prolonged with the increment of the initial transmission risk.

Assessment of a SARS-CoV-2 population-wide rapid antigen testing in Italy: a modeling and economic analysis study.

This study aimed to compare the cost-effectiveness of coronavirus disease 2019 (COVID-19) mass testing, carried out in November 2020 in the Italian Bolzano/Südtirol province, to scenarios without mass testing in terms of hospitalizations averted and quality-adjusted life-year (QALYs) saved. We applied branching processes to estimate the effective reproduction number (Rt) and model scenarios with and without mass testing, assuming Rt = 0.9 and Rt = 0.95. We applied a bottom-up approach to estimate the costs of mass testing, with a mixture of bottom-up and top-down methodologies to estimate hospitalizations averted and incremental costs in case of non-intervention. Lastly, we estimated the incremental cost-effectiveness ratio (ICER), denoted by screening and related social costs, and hospitalization costs averted per outcome derived, hospitalizations averted and QALYs saved. The ICERs per QALY were €24249 under Rt = 0.9 and €4604 under Rt = 0.95, considering the official and estimated data on disease spread. The cost-effectiveness acceptability curves show that for the Rt = 0.9 scenario, at the maximum threshold willingness to pay the value of €40000, mass testing has an 80% probability of being cost-effective compared to no mass testing. Under the worst scenario (Rt = 0.95), at the willingness to pay threshold, mass testing has an almost 100% probability of being cost-effective. We provide evidence on the cost-effectiveness and potential impact of mass COVID-19 testing on a local healthcare system and community. Although the intervention is shown to be cost-effective, we believe the initiative should be carried out when there is initial rapid local disease transmission with a high Rt, as shown in our model.

Determination of key transmission section and strong correlation section based on matrix aggregation algorithm

With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper.

Intranasal Single-Replication Influenza Vector Induces Cross-Reactive Serum and Mucosal Antibodies against SARS-CoV-2 Variants.

Current SARS-CoV-2 vaccines provide protection for COVID-19-associated hospitalization and death, but remain inefficient at inhibiting initial infection and transmission. Despite updated booster formulations, breakthrough infections and reinfections from emerging SARS-CoV-2 variants are common. Intranasal vaccination to elicit mucosal immunity at the site of infection can improve the performance of respiratory virus vaccines. We developed SARS-CoV-2 M2SR, a dual SARS-CoV-2 and influenza vaccine candidate, employing our live intranasal M2-deficient single replication (M2SR) influenza vector expressing the receptor binding domain (RBD) of the SARS-CoV-2 Spike protein of the prototype strain, first reported in January 2020. The intranasal vaccination of mice with this dual vaccine elicits both high serum IgG and mucosal IgA titers to RBD. Sera from inoculated mice show that vaccinated mice develop neutralizing SARS-CoV-2 antibody titers against the prototype and Delta virus strains, which are considered to be sufficient to protect against viral infection. Moreover, SARS-CoV-2 M2SR elicited cross-reactive serum and mucosal antibodies to the Omicron BA.4/BA.5 variant. The SARS-CoV-2 M2SR vaccine also maintained strong immune responses to influenza A with high titers of anti H3 serum IgG and hemagglutination inhibition (HAI) antibody titers corresponding to those seen from the control M2SR vector alone. With a proven safety record and robust immunological profile in humans that includes mucosal immunity, the M2SR influenza viral vector expressing key SARS-CoV-2 antigens could provide more efficient protection against influenza and SARS-CoV-2 variants.