Transmission Pairs Research Articles

Temporal dynamics in viral shedding and transmissibility of COVID-19.

We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 25-69%) of secondary cases were infected during the index cases' presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home. Disease control measures should be adjusted to account for probable substantial presymptomatic transmission.

Pair Auction and Matching for Resource Allocation in Full-Duplex Cellular Systems

Full-duplex techniques improve spectral efficiency in cellular networks by allowing a transceiver to simultaneously transmit and receive data with the same radio resource. To minimize self-interference and inter-node interference due to the deployment of full-duplex radio, users have to feed back their measurements of interference to allow the base station to effectively allocate resources and form transmission pairs. Considering that the interference measurements are private information, users may not report the true values and may try to gain their own benefits. To solve this problem, we propose a strategy-proof resource allocation mechanism for full-duplex cellular networks. The proposed scheme, which is based on auction and matching theories, guarantees that users report true values of their channel quality and utilities, and therefore guarantees the correctness of feedback information and the efficiency of resource allocation. Moreover, the proposed matching-based mechanism is theoretically proved to be stable and Pareto efficient. Simulation results confirm that, compared to a centralized scheme with non-truthful information from users, the proposed scheme can achieve an 11 $\%$ gain.

Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures

BackgroundThree clusters of coronavirus disease 2019 (COVID-19) linked to a tour group from China, a company conference, and a church were identified in Singapore in February, 2020.MethodsWe gathered epidemiological and clinical data from individuals with confirmed COVID-19, via interviews and inpatient medical records, and we did field investigations to assess interactions and possible modes of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Open source reports were obtained for overseas cases. We reported the median (IQR) incubation period of SARS-CoV-2.FindingsAs of Feb 15, 2020, 36 cases of COVID-19 were linked epidemiologically to the first three clusters of circumscribed local transmission in Singapore. 425 close contacts were quarantined. Direct or prolonged close contact was reported among affected individuals, although indirect transmission (eg, via fomites and shared food) could not be excluded. The median incubation period of SARS-CoV-2 was 4 days (IQR 3–6). The serial interval between transmission pairs ranged between 3 days and 8 days.InterpretationSARS-CoV-2 is transmissible in community settings, and local clusters of COVID-19 are expected in countries with high travel volume from China before the lockdown of Wuhan and institution of travel restrictions. Enhanced surveillance and contact tracing is essential to minimise the risk of widespread transmission in the community.FundingNone.

Bioinformatic analysis of post-transmission viral readaptation in Argentine patients with acute HIV-1 infection

During the acute phase of HIV-1 infection, a strong readaptation occurs in the viral population. Our objective was to analyze the post-transmission mutations associated with escape to the cytotoxic immune response and its relationship with the progression of the infection. In this study, a total of 17 patients were enrolled during acute/early primary HIV infection and 8 subjects that were the HIV positive partner resulting in 8 transmission pairs. Genotyping of the genetic polymorphisms of HLA class I A and B was performed using PCR-SSOP. Viral RNA extraction was from plasma. 570 single Gag-gene amplifications were obtained by limiting-dilution RT-PCR. Epitope prediction was performed with NetMHC CBS prediction server for the 19 HLA-A and B alleles. Cytotoxic response prediction was performed by using the IEDB Analysis Resource. From our results, we deduce that the transmitted CTL / gag escape frequency in the founder virus was at least double compared to the post-transmission events. Additionally, by means of an algorithm that combines these frequencies, we observed that the founder viruses better adapted to the HLA A / B alleles of the recipient could contribute to a greater progression of the infection. Our results suggest that there is a large adaptation of HIV-1 to the HLA A / B alleles prevalent in our population. However, despite this adaptive advantage, the virus needs to make “readjustments” through new escape and compensatory mutations. Interestingly, according to our results, this readaptation could have a role in the progression of the infection.

The Timing of COVID-19 Transmission

Background: The timing of SARS-CoV-2 transmission is a critical factor to understand the epidemic trajectory and the impact of isolation, contact tracing and other non-pharmaceutical interventions on the spread of COVID-19 epidemics. Methods: We examined the distribution of transmission event times with respect to exposure and onset of symptoms. We analysed 119 transmission pairs with known date of onset of symptoms for both index and secondary cases and partial information on their intervals of exposure. We inferred the distribution for generation time and time from onset of symptoms to transmission by maximum likelihood. We modelled different relations between time of infection, onset of symptoms and transmission, inferring the most appropriate one according to the Akaike Information Criterion. Finally, we estimated the fraction of pre-symptomatic and early symptomatic transmissions among all pairs using a Bayesian approach.Findings: For symptomatic individuals, the timing of transmission of SARS-CoV-2 was more directly linked to the onset of clinical symptoms of COVID-19 than to the time since infection. The time of transmission was approximately centered and symmetric around the onset of symptoms, with three quarters of events occurring in the window from 2-3 days before to 2-3 days after. The pre-symptomatic infectious period extended further back in time for individuals with longer incubation periods. Overall, the fraction of transmission from strictly pre-symptomatic infections was high (41%; 95%CI 31-50%), but a comparably large fraction of transmissions occurred on the same day as the onset of symptoms or the next day (35%; 95%CI 26-45%). We caution against overinterpretation of the fraction and timing of late symptomatic transmissions, due to their dependence on behavioural factors and interventions. Interpretation: Infectiousness is causally driven by the onset of symptoms. Public health authorities should reassess their policies on the contact tracing window in the light of individual variability in presymptomatic infectious period. Information about when a case was infected should be collected where possible, in order to assess how far into the past their contacts should be traced. The large fraction of transmission from strictly pre-symptomatic infections limits the efficacy of symptom-based interventions, while the large fraction of early symptomatic transmissions underlines the critical importance of individuals distancing themselves from others as soon as they notice any symptoms, even if mild. Rapid or at-home testing and contextual risk information could greatly facilitate efficient early isolation.Funding Statement: The study was funded by an award from the Li Ka Shing Foundation to CF.Declaration of Interests: None of the authors have competing financial or non-financial interests.

Deep sequence analysis of HIV adaptation following vertical transmission reveals the impact of immune pressure on the evolution of HIV.

Human immunodeficiency virus (HIV) can adapt to an individual’s T cell immune response via genomic mutations that affect antigen recognition and impact disease outcome. These viral adaptations are specific to the host’s human leucocyte antigen (HLA) alleles, as these molecules determine which peptides are presented to T cells. As HLA molecules are highly polymorphic at the population level, horizontal transmission events are most commonly between HLA-mismatched donor/recipient pairs, representing new immune selection environments for the transmitted virus. In this study, we utilised a deep sequencing approach to determine the HIV quasispecies in 26 mother-to-child transmission pairs where the potential for founder viruses to be pre-adapted is high due to the pairs being haplo-identical at HLA loci. This scenario allowed the assessment of specific HIV adaptations following transmission in either a non-selective immune environment, due to recipient HLA mismatched to original selecting HLA, or a selective immune environment, mediated by matched donor/recipient HLA. We show that the pattern of reversion or fixation of HIV adaptations following transmission provides insight into the replicative cost, and likely compensatory networks, associated with specific adaptations in vivo. Furthermore, although transmitted viruses were commonly heavily pre-adapted to the child’s HLA genotype, we found evidence of de novo post-transmission adaptation, representing new epitopes targeted by the child’s T cell response. High-resolution analysis of HIV adaptation is relevant when considering vaccine and cure strategies for individuals exposed to adapted viruses via transmission or reactivated from reservoirs.

Improved characterisation of MRSA transmission using within-host bacterial sequence diversity.

Methicillin-resistant Staphylococcus aureus (MRSA) transmission in the hospital setting has been a frequent subject of investigation using bacterial genomes, but previous approaches have not yet fully utilised the extra deductive power provided when multiple pathogen samples are acquired from each host. Here, we used a large dataset of MRSA sequences from multiply-sampled patients to reconstruct colonisation of individuals in a high-transmission setting in a hospital in Thailand. We reconstructed transmission trees for MRSA. We also investigated transmission between anatomical sites on the same individual, finding that this either occurs repeatedly or involves a wide transmission bottleneck. We examined the between-subject bottleneck, finding considerable variation in the amount of diversity transmitted. Finally, we compared our approach to the simpler method of identifying transmission pairs using single nucleotide polymorphism (SNP) counts. This suggested that the optimum threshold for identifying a pair is 39 SNPs, if sensitivities and specificities are equally weighted.

HIV Transmission Chains Exhibit Greater HLA-B Homogeneity Than Randomly Expected.

HIV's capacity to escape immune recognition by human leukocyte antigen (HLA) is a core component of HIV pathogenesis. A better understanding of the distribution of HLA class I in HIV-infected patients would improve our knowledge of pathogenesis in relation to the host HLA type and could better improve therapeutic strategies against HIV. Three hundred one to 325 transmission pairs and 469-496 clusters were identified for analysis among Swiss HIV Cohort Study (SHCS) participants using HIV pol sequences from the drug resistance database. HLA class I data were compiled at 3 specificity levels: 4-digit, 2-digit alleles, and HLA-B supertype. The analysis tabulated HLA-I homogeneity as 2 measures: the proportion of transmission pairs, which are HLA concordant, and the average percentage of allele matches within all clusters. These measures were compared with the mean value across randomizations with randomly assorted individuals. We repeated the analysis for different HLA classification levels and separately for HLA-A, -B, and -C. Subanalyses by the risk group were performed for HLA-B. HLA-B showed significantly greater homogeneity in the transmission chains (2-digit clusters: 0.291 vs. 0.251, P value = 0.009; supertype clusters: 0.659 vs. 0.611, P value = 0.002; supertype pairs: 0.655 vs. 0.608, P value = 0.014). Risk group restriction caused the effect to disappear for men-who-have-sex-with-men but not for other risk groups. We also examined if protective HLA alleles B27 and B57 were under- or overrepresented in the transmission chains, although this yielded no significant pattern. The HLA-B alleles of patients within HIV-1 transmission chains segregate in homogenous clusters/pairs, potentially indicating preferential transmission among HLA-B concordant individuals.

Robust resource allocation for rates maximization using fuzzy estimation of dynamic channel states in OFDMA femtocell networks

One of the challenging issues in dynamic resource management scheme of wireless communications is to achieve the instantaneous channel gain for transmission pairs. When designing the resource allocation algorithms, the previous works usually rely on the statistical information of the channel distribution and the harsh assumption of uncertain channel, and they are with much conservatism for the dynamic channel gain. To overcome the limitations of the existing methods, the Fuzzy Logic System (FLS) is adopted in this paper to estimate the instantaneous channel gain for the dynamic communication environments. Based on the estimated channel gains, the power allocation scheme is proposed for the orthogonal frequency division multiple access (OFDMA) femtocell network. The proposed scheme attempts to maximize the total rate of the communication system and to guarantee the quality of service of each user. The original optimization problem is a nonconvex optimization problem which is difficult to solve. The successive convex approximation (SCA) is adopted to transform the nonconvex original problem into a tractable one. The distributed iterative algorithm is developed to integrate with the proposed scheme in real-time dynamic communication environments. The effectiveness of the proposed scheme is demonstrated through the simulations, and the results show that the sum rate and energy efficiency of users can be improved by the proposed scheme, compared to the existing schemes.

Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data.

There exists significant interest in developing statistical and computational tools for inferring ‘who infected whom’ in an infectious disease outbreak from densely sampled case data, with most recent studies focusing on the analysis of whole genome sequence data. However, genomic data can be poorly informative of transmission events if mutations accumulate too slowly to resolve individual transmission pairs or if there exist multiple pathogens lineages within-host, and there has been little focus on incorporating other types of outbreak data. We present here a methodology that uses contact data for the inference of transmission trees in a statistically rigorous manner, alongside genomic data and temporal data. Contact data is frequently collected in outbreaks of pathogens spread by close contact, including Ebola virus (EBOV), severe acute respiratory syndrome coronavirus (SARS-CoV) and Mycobacterium tuberculosis (TB), and routinely used to reconstruct transmission chains. As an improvement over previous, ad-hoc approaches, we developed a probabilistic model that relates a set of contact data to an underlying transmission tree and integrated this in the outbreaker2 inference framework. By analyzing simulated outbreaks under various contact tracing scenarios, we demonstrate that contact data significantly improves our ability to reconstruct transmission trees, even under realistic limitations on the coverage of the contact tracing effort and the amount of non-infectious mixing between cases. Indeed, contact data is equally or more informative than fully sampled whole genome sequence data in certain scenarios. We then use our method to analyze the early stages of the 2003 SARS outbreak in Singapore and describe the range of transmission scenarios consistent with contact data and genetic sequence in a probabilistic manner for the first time. This simple yet flexible model can easily be incorporated into existing tools for outbreak reconstruction and should permit a better integration of genomic and epidemiological data for inferring transmission chains.

Caution is needed in interpreting HIV transmission chains by ultradeep sequencing.

Molecular epidemiology is applied to various aspects of HIV transmission analyses. With ultradeep sequencing (UDS), in-depth characterization of transmission episodes involving minority variants is permitted. We explored HIV-1 epidemiological linkage and evaluated characteristics of transmission dynamics and transmitted drug resistance (TDR) detection through the added value of UDS. HIV pol gene fragments were sequenced by UDS and Sanger sequencing on samples of 70 HIV-1-infected, treatment-naive recently diagnosed MSM. Pairwise genetic distances and maximum likelihood phylogenies were computed. Transmission events were identified as clades with branch support at least 70% and intraclade genetic difference less than 4.5%. TDR mutations were recognized from the TDR consensus list. Transmission directionality, directness and inoculum size were inferred from tree topologies. Both datasets concurred in the identification of seven transmission pairs and one cluster of three patients. With UDS, direction of transmission was inferred in four out of eight chains. Evidence for multiple founder viruses was found in two out of eight chains. No transmission of minority-resistant variants was evidenced. TDR mutations prevalence in protease and reverse transcriptase fragments was 4.3% with Sanger sequencing and 18.6% with UDS. Although Sanger sequencing and UDS identified the same transmission chains, UDS provided additional information on founder viruses, direction of transmission and levels of TDR. Nevertheless, topology of clusters was not always consistent across gene fragments, calling for a cautious interpretation of the data. Moreover, unobserved intermediary links cannot be excluded. Phylogenetic analysis use as a forensic technique for HIV transmission investigations is risky.

Superimposing incident sexually transmitted infections on HIV phylogram to investigate possible misclassification of men who have sex with men as heterosexuals in a cohort in Antwerp, Belgium.

In this study, we assessed if the superimposition of incident sexually transmitted infections (STIs) on HIV phylogenetic analyses could reveal possible sexual behaviour misclassifications in our HIV-infected population. HIV-1 sequences collected between 1997 and 2014 from 1169 individuals attending a HIV clinic in Antwerp, Belgium were analysed to infer a partial HIV transmission network. Individual demographic, clinical and laboratory data collected during routine HIV follow-up were used to compare clustered and non-clustered individuals using logistic regression analyses. In total, 438 (37.5%) individuals were identified in 136 clusters, including 76 transmission pairs and 60 clusters consisting of three or more individuals. Individuals in a cluster were more likely to have a history of syphilis, Chlamydia and/or gonorrhoea (P < 0.05); however, when analyses were stratified by HIV transmission risk groups (heterosexual and men who have sex with men [MSM]), this association only remained significant for heterosexuals with syphilis (P = 0.001). Under closer scrutiny, this association was driven by six heterosexual men who were located in six almost exclusively MSM clusters. A parsimonious conclusion is that these six individuals were potentially misclassified as heterosexual. Improving the accuracy of sexual behaviour reporting could improve care.

Phylogeography of HIV-1 suggests that Ugandan fishing communities are a sink for, not a source of, virus from general populations

Although fishing communities (FCs) in Uganda are disproportionately affected by HIV-1 relative to the general population (GP), the transmission dynamics are not completely understood. We earlier found most HIV-1 transmissions to occur within FCs of Lake Victoria. Here, we test the hypothesis that HIV-1 transmission in FCs is isolated from networks in the GP. We used phylogeography to reconstruct the geospatial viral migration patterns in 8 FCs and 2 GP cohorts and a Bayesian phylogenetic inference in BEAST v1.8.4 to analyse the temporal dynamics of HIV-1 transmission. Subtype A1 (pol region) was most prevalent in the FCs (115, 45.1%) and GP (177, 50.4%). More recent HIV transmission pairs from FCs were found at a genetic distance (GD) <1.5% than in the GP (Fisher’s exact test, p = 0.001). The mean time depth for pairs was shorter in FCs (5 months) than in the GP (4 years). Phylogeographic analysis showed strong support for viral migration from the GP to FCs without evidence of substantial viral dissemination to the GP. This suggests that FCs are a sink for, not a source of, virus strains from the GP. Targeted interventions in FCs should be extended to include the neighbouring GP for effective epidemic control.

Analysis of the Influence of Parallelism Error on the Meshing Performance of Circular-Arc-Tooth-Trace Cylindrical Gears

In this paper, two types of point contact and line contact of spiral cylindrical gear transmission pair are studied and analyzed. The influences of the axis parallelism error and the center distance error on the contact area are analyzed. The numerical example shows that the line-contact transmission pair has larger contact area if the installation error is not considered. By using MATLAB software and simulation example, the influence of axis parallelism on contact area and meshing performance of spiral cylindrical gears under different error conditions are obtained.

Cooperative Spectrum Sharing Scheme for Overlay D2D-enable Cellular Network

This paper proposes a cooperative spectrum sharing scheme for overlay Device-to-Device (D2D) enable cellular network. Based on the proposed scheme, the cell edge user (EU) intends to share its spectrum resource with a D2D transmission pair by overlay approach. The D2D transmission pair has to forward data for the EU with the aid of Non-Orthogonal Multiple Access (NOMA) for accessing the licensed spectrum to transmit its own data and for improving the spectrum efficiency. Based on the NOMA technology, this paper develops a power allocation algorithm for the D2D in order to maximize its own utility. The simulation results demonstrate that the proposed scheme is capable of providing considerable rate improvements for the EU.

613. Transmission of Influenza Virus in Mother and Infant Transmission Events in Nepal

BackgroundInfluenza immunization of pregnant women provides protection of the infant against influenza disease. A potential mechanism of protection is prevention of maternal illness that may result in secondary transmission to infants. We aim to characterize influenza transmission in mother–infant pairs.MethodsPregnant mothers were enrolled in a randomized controlled trial of influenza immunization in rural Nepal from April 2011 to April 2013. Mothers and infants were surveyed weekly until 180 days post-partum for respiratory illness and mid-nasal swabs were collected at time of illness and tested for influenza virus by reverse-transcriptase polymerase chain reaction (RT-PCR). We defined a transmission episode as a mother–infant pair with an influenza-positive illness within 14 days of each other. Influenza viruses were strain-typed by RT-PCR and/or mass spectrometry.ResultsSeventeen mother–infant transmission episodes occurred with maternal illness preceding infant illness in 12 (70.6%). Of transmission pairs, 12 (70.6%) were influenza B, three (17.6%) H3N2 influenza A, one (5.9%) H1N1 influenza A, and one (5.9%) unspecified influenza A. Five (29.4%) mothers received the influenza vaccine. Successful strain-typing with RT-PCR/mass spectrometry of 11 pairs revealed that 10 (90.9%) were synonymous strains. Figure 1 shows the start of respiratory symptoms and virus type associated with influenza illness in the 17 mother–infant pairs.ConclusionMothers are an important source of infant influenza infection. Transmission was confirmed with nearly all paired transmissions demonstrating a similar strain. The majority of transmission events occurred in nonvaccinated mother–infant pairs. Figure 1: Influenza transmission events in mother–infant pairs. Symbols represent first day of respiratory symptoms associated with influenza-positive illness.Disclosures J. Englund, GlaxoSmithKline: Investigator, Research grant. MedImmune: Investigator, Research grant. Gilead: Investigator, Research grant. Novavax: Investigator, Research grant. Chimerix: Investigator, Research grant. Alios: Investigator, Research grant. H. Chu, Sanofi-Pasteur: Grant Investigator, Grant recipient.

A Reciprocal-Selection-Based ‘Win–Win’ Overlay Spectrum-Sharing Scheme for Device-to-Device-Enabled Cellular Network

This paper proposes a reciprocal-selection-based ‘Win–Win’ overlay spectrum-sharing scheme for device-to-Device-enabled cellular networks to address the resource sharing between Device-to-Device devices and the cellular users by using an overlay approach. Based on the proposed scheme, the cell edge users intend to lease part of its spectrum resource to Device-to-Device transmission pairs. However, the Device-to-Device users have to provide the cooperative transmission assistance for the cell edge users in order to improve the Quality of Service of the uplink transmission from the cell edge users to the base station. Compared to the underlay spectrum-sharing scheme, overlay spectrum-sharing scheme may reduce spectrum efficiency. Hence, Non-Orthogonal Multiple Access technology is invoked at the Device-to-Device transmitter in order to improve the spectrum efficiency. The Stackelberg game is exploited to model the behaviours of the cell edge users and Device-to-Device devices. Moreover, based on matching theory, the cell edge users and Device-to-Device pairs form one-to-one matching and the stability of matching is analysed. The simulation results show that the proposed reciprocal-selection-based ‘Win–Win’ overlay spectrum-sharing scheme is capable of providing considerable rate improvements for both EUs and D2D pairs and reducing transmit power dissipated by the D2D transmitter to forward data for the EU compared with the existing methods.

Charge-Then-Forward: Wireless-Powered Communication for Multiuser Relay Networks

This paper studies a relay-assisted wireless-powered communication network consisting of multiple source-destination pairs and a hybrid relay node (HRN). We consider a “charge-then-forward” protocol at the HRN, in which the HRN with constant energy supply first acts as an energy transmitter to charge the sources, and then forwards the information from the sources to their destinations through time division multiple access (TDMA) or frequency division multiple access (FDMA). Processing costs at the wireless-powered sources are taken into account. Our goal is to maximize the sum rate of all transmission pairs by jointly optimizing the time, frequency, and power resources. The formulated optimization problems for both TDMA and FDMA are non-convex. For the TDMA scheme, by appropriate transformation, the problem is reformulated as a convex problem and be optimally solved. For the FDMA case, we find the asymptotically optimal solution in the dual domain. Furthermore, suboptimal algorithms are proposed for both schemes to tradeoff the complexity and performance. Finally, the simulation results validate the effectiveness of the proposed schemes.

HIV-1's fingerprint.

This study used a large cohort of HIV-1 transmission pairs to determine the contribution of viral genetics on the development of neutralizing antibodies.

π-Splicer: Perceiving Accurate CSI Phases with Commodity WiFi Devices

WiFi technology has gained a wide prevalence for not only wireless communication but also pervasive sensing. A wide variety of emerging applications leverage accurate measurements of the Channel State Information (CSI) information obtained from commodity WiFi devices. Due to hardware imperfection of commodity WiFi devices, the frequency response of internal signal processing circuit is mixed with the real channel frequency response in passband, which makes deriving accurate channel frequency response from CSI measurements a challenging task. In this paper, we identify non-negligible non-linear CSI phase errors and report that IQ imbalance is the root source of non-linear CSI phase errors. We conduct intensive analysis on the characteristics of such non-linear errors and find that such errors are prevalent among various WiFi devices. Furthermore, they are rather stable along time and the received signal strength indication (RSSI) but sensitive to frequency bands used between a transmission pair. Based on these key observations, we propose new methods to compensate both non-linear and linear CSI phase errors. We demonstrate the efficacy of the proposed methods by applying them in CSI splicing and indoor distance ranging. Results of extensive real-world experiments indicate that accurate CSI phase measurements can significantly improve the performance of splicing and the stability of the derived power delay profiles (PDPs). Moreover, the estimated distance errors are reduced by 5.7 times on average comparing to the state-of-the-art schemes.