Sporadic Transmission Research Articles

Abstracts from the ISSAID 2021 Periodic Congress

Abstracts from the ISSAID 2021 Periodic Congress

Seropositivity to Coxiella burnetii in primiparous and multiparous ewes from southern Australia: A cross-sectional study

The role of infectious diseases including coxiellosis in causing poorer reproductive performance of primiparous ewes are not well studied. The aims of this study were to determine if natural exposure to Coxiella burnetii is widespread in breeding ewes and whether seropositivity is associated with poor reproductive performance of primiparous ewes. Seropositivity to Coxiella burnetii was 0.08% (CI95% 0.01, 0.36) in primiparous ewes and 0.36% (CI95% 0.07, 1.14) in mature ewes. Coxiella burnetii was not detected in aborted or stillborn lambs using qPCR. These findings suggest C. burnetii infection was unlikely to be an important contributor to abortion and perinatal mortalities observed for primiparous ewe flocks, and exposure to C. burnetii was not widespread in ewes on farms located over wide geographical region of southern Australia. Whilst ewes on these farms were not an important reservoir for C. burnetii, sporadic zoonotic transmission from sheep is reported and has public health implications.

A DNN-based estimate of the PRACH traffic load for massive IoT scenarios in 5G networks and beyond

The massive Internet of Things (IoT) scenario refers to a huge number of Machine Type Communications (MTC) characterized by sporadic transmissions of small-sized packets. In order to manage the uplink radio resource allocation in cellular networks, several access schemes have been proposed. These schemes are mainly based on a grant-based Random Access (RA) procedure and proper load-aware access controls, e.g., Access Class Barring (ACB) techniques, dynamic uplink radio resource allocation, and so on. The development of an efficient approach to estimate the traffic load is extremely important for the proper functioning of these access schemes. With the ever-increasing number of transmitting MTC devices, expected with Beyond 5G (B5G) and 6G networks, additional challenges to obtain a correct real-time traffic load estimation are posed. Deep learning techniques, in this context, offer learning ability and optimization capability to properly support this scenario. In this paper, we propose a current access attempts estimation, based on Deep Neural Network (DNN), which accepts as input only the information really available at the next generation Node B (gNB). The network was trained and tested with a dataset properly created and composed by more than 21 million points. The DNN-based traffic load estimation method is then compared with other benchmark schemes available in the literature, in terms of regression accuracy, both in a static analysis, which considers a stand-alone RA cycle, and through a long-term analysis with a time-varying offered load. The latter analysis was performed both by adopting a theoretical arrival process proposed by 3GPP, and by using traces of real traffic data.

COVID-19 in WHO African Region: Account and Correlation of Epidemiological Indices with Some Selected Health-related Metrics.

The coronavirus disease 2019 (COVID-19) is a highly contagious and pathogenic viral disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Since it was first reported in Wuhan, China, it has spread across the continents. The study is aimed at describing epidemiological indices of COVID-19 as reported by the World Health Organization and to examine correlations with some country specific measures of general health status. Data from the WHO African region were extracted from World Health Organization, Global Health Security Index, Worldometer and World Bank databases, as at September 8, 2020. Other epidemiological indices were computed for the various countries. Epidemiological indices of COVID-19 were correlated with some selected health related metrics: Global Health Security index (GHSI) and current health expenditure (CHE). Pearson correlation was used to access the relationship between the health-related metrics and epidemiological indices. Forty-seven (47) countries belonging to the WHO African region were evaluated. A total of 1,086,499 confirmed cases and 23,213 deaths were recorded giving a fatality rate of 2.1%. South Africa recorded the highest cumulative confirmed cases as well as deaths (Cases: 639,362; Deaths: 15,004) while Seychelles (Cases:135) and Eritrea/Seychelles (Deaths:0) had the least cumulative cases and deaths (135;0 and 330;0), respectively. South Africa recorded the highest attack rate (1127.67/100,000) while Republic of Tanzania recorded the least attack rate (0.78/100,000). The highest case fatality rate/ratio was observed in Chad (7.60%) while the least value was observed in Seychelles (0.0%). France was the most common country involved in travel history of index cases. Sporadic transmission was recorded in 3 countries, 9 countries had cluster of cases while the rest had community transmission. The first WHO African region country to record COVID-19 case was Algeria, while Comoros was the last. Significant positive correlation was found between COVID-19 case number/deaths and Global Health Security Index. The WHO African region has had its own share of the pandemic with all the countries being affected. The trio of cluster cases, sporadic and community transmission were recorded with majority being community transmission.

Endemic persistence of a highly contagious pathogen: Foot-and-mouth disease in its wildlife host.

Extremely contagious pathogens are a global biosecurity threat because of their high burden of morbidity and mortality, as well as their capacity for fast-moving epidemics that are difficult to quell. Understanding the mechanisms enabling persistence of highly transmissible pathogens in host populations is thus a central problem in disease ecology. Through a combination of experimental and theoretical approaches, we investigated how highly contagious foot-and-mouth disease viruses persist in the African buffalo, which serves as their wildlife reservoir. We found that viral persistence through transmission among acutely infected hosts alone is unlikely. However, the inclusion of occasional transmission from persistently infected carriers reliably rescues the most infectious viral strain from fade-out. Additional mechanisms such as antigenic shift, loss of immunity, or spillover among host populations may be required for persistence of less transmissible strains.

Spectral Coexistence of QoS-Constrained and IoT Traffic in Satellite Systems.

The flourishing of Internet of Things (IoT) applications, characterized by vast transmitter populations and the sporadic transmission of small data units, demands innovative solutions for the sharing of the wireless medium. In this context, satellite connectivity is an important enabler for all scenarios in which terminals are under-served by terrestrial communications and are thus fundamental for providing worldwide coverage. In turn, the design of medium access policies that attain efficient use of the scarce spectrum and can cope with flexible yet unpredictable IoT traffic is of the utmost importance. Starting from these remarks, we investigate in this work the coexistence of a quality of service (QoS)-constrained service with IoT traffic in a shared spectrum as alternative to a more traditional orthogonal allocation among the two services, with an eye on satellite applications. Leaning on analytical tools, we provide achievable rate regions, assuming a slotted ALOHA access method for IoT terminals and accounting for practical aspects, such as the transmission of short packets. Interesting trends emerge, showcasing the benefit of an overlay allocation with respect to segregating the resources for the two services.

SARS-CoV-2 quantitative real time PCR and viral loads analysis among asymptomatic and symptomatic patients: an observational study on an outbreak in two nursing facilities in Campania Region (Southern Italy)

BackgroundIn December 2019 an outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 was first observed in Wuhan, China. The virus has spread rapidly throughout the world creating a pandemic scenario. Several risk factors have been identified, such as age, sex, concomitant diseases as well as viral load. A key point is the role of asymptomatic people in spreading SARS-CoV-2. An observational study in Southern Italy was conducted in order to elucidate the possible role of asymptomatic individuals related to their viral loads in the transmission of the virus within two nursing facilities.MethodsOro-nasopharyngeal swabs from 179 nursing health care workers and patients were collected. SARS-CoV-2 RT-qPCR was performed and viral loads were calculated by using standard curve. A statistical correlation between viral loads, the presence/absence of symptoms, age and sex variables was investigated.ResultsSARS-CoV-2 was confirmed in the 50.8 % (n = 91) of the cases. Median age of positive individuals resulted higher than negative ones. Over 65 year as well as female individuals showed higher susceptibility to SARS-CoV-2 infection, OR = 3.93 and 2.86, respectively. Among 91 tested positive, the 70.3 % was symptomatic while the 29.7 % was asymptomatic. Median viral loads of asymptomatic individuals were found statistically significant higher than symptomatic ones (p = 0.001), while no influence was observed in age and sex variables. The presence of comorbidities was 8.9 folds higher in patients who showed and developed symptoms compared to non-symptomatic ones. Moreover, higher viral loads were found in patients who remained asymptomatic than pre-symptomatic (p = 0.022).ConclusionsA range from 9.2 to 69 % of confirmed SARS-CoV-2 cases remains asymptomatic, moreover, sporadic transmissions from asymptomatic people are reported, that makes their involvement an important issue to take into account in the spreading control of the virus. An asymptomatic clinical course was observed in the 29.7 % of positive individuals, moreover, median viral loads resulted to be statistically significant when compared to symptomatic ones. Surely, such a relevant frequency should not be ignored in relation to the spread of the disease in an environment which has not only important intrinsic (age, sex, concomitant diseases) but also extrinsic factors such as high population density and close contacts.

Uplink Grant-Free NOMA With Sinusoidal Spreading Sequences

Grant-access based legacy networks are unable to deliver Uplink (UL) dominated sporadic transmission of short packets with low signalling overhead, which are the requirements of Massive Machine Type Communication (mMTC). Hence, grant-free Non-Orthogonal Multiple Access (NOMA) techniques are more suited for mMTC. Due to the inherent sparsity in the user activity pattern in an mMTC system, the existing literature revolves around Compressive Sensing based Multi User Detection (CS-MUD) algorithms, which employ random or Zadoff-Chu spreading sequences for NOMA. In this paper we explore the utility of sinusoidal spreading sequences, which allow some non-iterative algorithms to be employed in the context of active user detection, channel estimation and data detection in a UL grant-free mMTC system. These algorithms do not need prior knowledge about the user behaviour statistics, noise statistics, and the level of sparsity in the user activity, which might be difficult to obtain at the Base Station (BS). We present a comprehensive performance and complexity analysis to assess the feasibility of our proposal. Extensive numerical trials demonstrate the utility of sinusoidal codes for mMTC.

Canine Visceral Leishmaniasis in an Area of Sporadic Transmission in Brazil.

Canine visceral leishmaniasis is a zoonotic disease caused by the protozoan Leishmania infantum in Latin America. Visceral leishmaniasis (VL) diagnosis in Brazil includes two serological tests according to the Ministry of Health (MH) protocol. Sensitivity and specificity of diagnostic tests, as well as clinical signs of VL, are usually reported in disease-endemic areas; however, it is known that local epidemiological factors can influence these results. This study aimed to evaluate the clinical features, sensitivity, and specificity of TR-DPP® and EIE-LVC in naturally infected dogs in a region of sporadic VL transmission to humans in Brazil. A total of 288 dogs were clinically evaluated and serological and parasitological (lymph node aspirates) samples were collected for VL diagnosis. TR-DPP and EIE-LVC showed poor sensitivity (0.62 and 0.44, respectively) to detect infected animals, compared with the direct parasitological examination, which is considered a gold standard method. Thus, the protocol of MH presented low sensitivity (0.42) to estimate prevalence and control measures in this region. TR-DPP presented a high negative predictive value (0.89), resulting in its indication as a confirmatory test in sporadic transmission areas. Classical clinical signs of VL were not frequently observed; therefore, clinical scoring systems might not be useful in this region. Veterinarians of nonendemic areas should be alert for asymptomatic dogs, especially those presenting lymph adenomegaly.

Subtyping Blastocystis in pigs and humans revealed unusual avian-specific subtype ST6 in humans in Serbia.

Blastocystis is a common protist colonizing the gastrointestinal tract of humans and various animals. The first subtyping of Blastocystis isolates in pigs and humans in Serbia revealed unusual avian-specific subtype ST6 in humans. In total, 48 pig faecal specimens collected on seven pig farms and 50 human faecal specimens positive to Blastocystis by microscopic examination were selected for the study. Eleven randomly selected PCR-positive pig samples and 10 samples from human patients (with gastrointestinal complaints) were subjected to SSU rDNA sequencing. Three subtypes were identified (ST3, ST5 and ST6) by phylogenetic analysis. ST5 was found in all pig samples; while in human samples, we detected ST3 and ST6. The latter subtype is relatively uncommon in Europe and highly adapted to avian hosts; therefore, the possibility of sporadic zoonotic transmission to human patients should not be ignored.

A Case for Systematic Quality Management in Mosquito Control Programmes in Europe.

The recent spread of invasive mosquito species, such as Aedes albopictus and the seasonal sporadic transmission of autochthonous cases of arboviral diseases (e.g., dengue, chikungunya, Zika) in temperate areas, such as Europe and North America, highlight the importance of effective mosquito-control interventions to reduce not only nuisance, but also major threats for public health. Local, regional, and even national mosquito control programs have been established in many countries and are executed on a seasonal basis by either public or private bodies. In order for these interventions to be worthwhile, funding authorities should ensure that mosquito control is (a) planned by competent scientific institutions addressing the local demands, (b) executed following the plan that is based on recommended and effective methods and strategies, (c) monitored regularly by checking the efficacy of the implemented actions, (d) evaluated against the set of targets, and (e) regularly improved according to the results of the monitoring. Adherence to these conditions can only be assured if a formal quality management system is adopted and enforced that ensures the transparency of effectiveness of the control operation. The current paper aims at defining the two components of this quality management system, quality assurance and quality control for mosquito control programs with special emphasis on Europe, but applicable over temperate areas.

Iberian oak decline caused by Phytophthora cinnamomi: A spatiotemporal analysis incorporating the effect of host heterogeneities at landscape scale

AbstractThe pathogen Phytophthora cinnamomi is considered a main driver of Iberian oak decline (IOD), a forest disease which decimates holm oaks (Quercus ilex) and cork oaks (Quercus suber) in a multipurpose, silvo‐pastoral and seminatural ecosystem of 3.1 million hectares in the south‐west of Europe. Little is known about the spatial dynamics of Phytophthora cinnamomi and how forest stand characteristics affect the IOD epidemic. Here, we analyse IOD spread over several decades in one such ecosystem by means of a multilevel approach based on (a) identification of diseased sites via repeated aerial imagery at landscape scale, (b) confirmation by subsampling of soil and roots, and iii) an epidemic model accounting for host population heterogeneities. We use a 'self‐exciting' spatiotemporal point process with two additive risk components: an epidemic component represents the inoculum pressure from nearby disease foci, and a background component describes sporadic disease transmission over larger distances or from unobserved sources. Both risk components are found to increase over time, and a lagged power‐law spatial kernel provides the best fit for the observed disease pattern. We estimate that 49% of the secondary infections triggered by a primary source occur within a distance of 250 m. Our results also highlight the role of density and diversity of the host population; we find that the rate of sporadic infections in silvo‐pastoral systems (dehesas) is lower than in forests, and higher in mixed stands and shrub encroached oak lands than in pure stands. These results have direct implications for IOD management, for example the estimated spatial kernel may guide the definition of suitable target areas for localized control measures and help to quantify their success. Our results also suggest that silviculture treatments aimed at controlling the density and species composition of oak stands, as well as the abundance of shrubs, are crucial to the containment of IOD.

Gaps in Serologic Immunity against Contemporary Swine-Origin Influenza A Viruses among Healthy Individuals in the United States.

Influenza A Viruses (IAV) in domestic swine (IAV-S) are associated with sporadic zoonotic transmission at the human–animal interface. Previous pandemic IAVs originated from animals, which emphasizes the importance of characterizing human immunity against the increasingly diverse IAV-S. We analyzed serum samples from healthy human donors (n = 153) using hemagglutination-inhibition (HAI) assay to assess existing serologic protection against a panel of contemporary IAV-S isolated from swine in the United States (n = 11). Age-specific seroprotection rates (SPR), which are the proportion of individuals with HAI ≥ 1:40, corresponded with lower or moderate pandemic risk classifications for the multiple IAV-S examined (one H1-δ1, one H1-δ2, three H3-IVA, one H3-IVB, one H3-IVF). Individuals born between 2004 and 2013 had SPRs of 0% for the five classified H3 subtype IAV-S, indicating youth may be particularly predisposed to infection with these viruses. Expansion of existing immunologic gaps over time could increase likelihood of future IAV-S spillover to humans and facilitate subsequent sustained human-to-human transmission resulting in disease outbreaks with pandemic potential.

Reconfigurable Intelligent Surface for Massive Connectivity: Joint Activity Detection and Channel Estimation

This paper considers the massive connectivity with the aid of a reconfigurable intelligent surface (RIS), where an enormous number of devices transmit sporadically to a base station (BS). The RIS establishes favorable signal propagation environments to enhance data transmission in massive connectivity in such a scenario. Nevertheless, the BS needs to detect active devices and estimate channels to support data transmission in RIS-assisted massive access systems. Furthermore, due to a large number of devices, it is impossible to assign orthogonal signature sequences to the devices as in most of the existing works on RIS-related channel estimation, which yields unique challenges. This paper shall consider a RIS-assisted uplink IoT network and solve the RIS-related activity detection and channel estimation problem. The BS detects the active devices and estimates the separated channels of the RIS-to-device link and the RIS-to-BS link by using non-orthogonal pilot sequences. Due to limited scattering between the RIS and the BS, we model the RIS-to-BS channel as a sparse channel. As a result, by simultaneously exploiting both the sparsity of sporadic transmission in massive connectivity and the RIS-to-BS channels, we formulate the RIS-related activity detection and channel estimation problem as a sparse matrix factorization problem. Furthermore, we develop an approximate message passing (AMP) based algorithm to solve the problem based on the Bayesian inference framework and reduce the computational complexity by approximating the algorithm with the central limit theorem and Taylor series expansion. Finally, extensive numerical experiments are conducted to verify the effectiveness of the proposed algorithm.

COVID-19 in the WHO African region: using risk assessment to inform decisions on public health and social measures.

Successive waves of COVID-19 transmission have led to exponential increases in new infections globally. In this study, we have applied a decision-making tool to assess the risk of continuing transmission to inform decisions on tailored public health and social measures (PHSM) using data on cases and deaths reported by Member States to the WHO Regional Office for Africa as of 31 December 2020. Transmission classification and health system capacity were used to assess the risk level of each country to guide implementation and adjustments to PHSM. Two countries out of 46 assessed met the criteria for sporadic transmission, one for clusters of cases, and 43 (93.5%) for community transmission (CT) including three with uncontrolled disease incidence (Eswatini, Namibia and South Africa). Health system response's capacities were assessed as adequate in two countries (4.3%), moderate in 13 countries (28.3%) and limited in 31 countries (64.4%). The risk level, calculated as a combination of transmission classification and health system response's capacities, was assessed at level 0 in one country (2.1%), level 1 in two countries (4.3%), level 2 in 11 countries (23.9%) and level 3 in 32 (69.6%) countries. The scale of severity ranged from 0 to 4, with 0 the lowest. CT coupled with limited response capacity resulted in a level 3 risk assessment in most countries. Countries at level 3 should be considered as priority focus for additional assistance, in order to prevent the risk rising to level 4, which may necessitate enforcing hard and costly lockdown measures. The large number of countries at level 3 indicates the need for an effective risk management system to be used as a basis for adjusting PHSM at national and sub-national levels.

Grant-Free Massive Connectivity in Massive MIMO Systems: Collocated Versus Cell-Free

We consider the problem of user activity detection for grant-free massive connectivity, where a base station, equipped with a large number of antennas, serves a large number of machine type devices. Two massive multiple-input multiple-output (mMIMO) systems are studied, namely, a collocated mMIMO with physically collocated antennas and a cell-free mMIMO with geographically separated antennas. By utilizing the sporadic transmission nature and the asymptotical orthogonality of channel vectors associated with different users, we propose a correlation-based sparse signal recovery scheme to detect active users. Simulation results are provided to evaluate the performance of the proposed method. Our results show that the cell-free mMIMO achieves much better user activity detection performance than the collocated mMIMO, and thus is more suitable for grant-free massive connectivity. An empirical analysis is performed to explain the superiority of the cell-free system over the collocated system.

AI-enhanced constellation design for NOMA system: A model driven method

Grant-free Non-orthogonal Multiple Access (GF-NOMA) is a promising technology for massive access users and sporadic small-packet transmission for Beyond the 5th Generation mobile communication system(B5G) / the 6th Generation mobile communication system (6G). One of the key aspects in GF-NOMA system is the signature/constellation design. However, due to the channel variation and random activation of users, conventional optimization approaches seem unsuitable for such complex models. In this paper, as an initial attempt, we propose a human intelligence (HI)-guided artificial intelligence (AI)-enhanced signature/constellation design method. By separate design of modulation and power allocation inspired by prior knowledge, the proposed deep neuron network (DNN) for NOMA signature/constellation design not only has smaller size of DNN and less training data, but also has stronger interpret-ability. In the last section, via simulations we demonstrate that in terms of bit error rate, the proposed scheme can achieve significant performance gain over the conventional NOMA schemes.

Knowledge, attitudes and practices concerning visceral leishmaniasis among residents of a sporadic transmission area in southeast Brazil.

In the last four decades, visceral leishmaniasis (VL) has undergone an urbanization process in Brazil. This research aimed to assess the knowledge, attitudes and practices concerning VL among residents of a sporadic transmission urban area in southeast Brazil. A community-based, cross-sectional quantitative study was conducted. Scores for knowledge, attitudes and practices concerning VL were evaluated and the bivariate analysis was performed. The analysis indicated that 29.9% had good knowledge, 5.2% had appropriate attitudes and 62.1% had appropriate practices. Notwithstanding that, pivotal practices for controlling VL had unsatisfactory individual frequencies. Good knowledge on VL was related to women, a higher level of education, a higher income, the place of residence and having pets. Appropriate attitudes were related to the place of residence. The practices had no significant associations with the sociodemographic and epidemiological variables. This study demonstrated that even in the area of disease transmission, knowledge on VL is very limited, including at the most basic level. In order to achieve effectiveness in actions against VL in Brazil, the participation of the affected communities is imperative, therefore popular health education interventions are necessary to improve the population's understanding of the disease and to avoid inappropriate attitudes and practices.

Urogenital System Damaging Manifestations of 3 Human Infected Coronaviruses.

At present, there are no comparative studies on the damage of the 3 coronaviruses infections to the urinary system. Therefore, we reviewed the correlations and differences between invading mechanisms and resultant urogenital system damage by the 3 kinds of coronaviruses in an effort to help doctors in the prevention and treatment of these damages, which will be of significance in improving prognosis and quality of life after rehabilitation. We searched PubMed® for English language articles published since 2003 with the key words "Coronavirus disease 2019 (COVID-19)," "severe acute respiratory syndrome-2 (SARS-CoV-2)," "severe acute respiratory syndrome (SARS)-CoV" and "Middle East respiratory syndrome (MERS)-CoV "with "semen" and "kidney." We also used relevant data from websites including the World Health Organization and Centers for Disease Control and Prevention. Recent studies have revealed that both SARS-CoV and SARS-CoV-2 invade target cells through a membrane-bound angiotensin-converting enzyme 2, an important component of the renin-angiotensin system, which maintains human homeostasis, whereas MERS utilizes host cells' receptor dipeptidyl peptidase 4 for entry. While pneumonia is the most prominent symptom in patients infected by coronaviruses due to the transmission through respiratory droplets, the urogenital system can also suffer from infection with coronaviruses, resulting in renal failure, testicular atrophy etc. The impairments of the genitourinary system would be different with the 3 coronavirus infections but they still have a strong correlation. The pathogenesis and clinical symptoms of SARS-CoV, MERS-CoV and SARS-CoV-2 coronaviruses in the genitourinary system are comparable. All 3 coronaviruses have been found to affect kidney and testicular function. Therefore, both urologists and nephrologists should pay attention to the damage caused by coronavirus infection to the genitourinary system, especially monitoring renal and semen function.

Group-based delivery of critical traffic in cellular IoT networks

Fifth generation (5G) networks are expected to connect a huge number of Internet of Things (IoT) devices in many usage scenarios. The challenges of typical massive IoT applications with sporadic and short packet uplink transmissions are well studied, while not enough attention is given to the delivery of content of common interest, such as software/firmware updates and remote control, towards IoT devices in emerging point-to-multipoint scenarios. Moreover, the delivery of delay-sensitive IoT traffic is not sufficiently addressed in the literature. In this work we (i) identify the drawbacks of the current Single-Cell Point-to-Multipoint (SC-PTM) solution for unplanned critical traffic delivery in cellular IoT (cIoT) networks, and (ii) propose paging and multicast schemes for a fast distribution of critical updates after, e.g., bug fixes or system failures. We benchmark the performance of the proposed paging scheme against similar solutions available in the literature. Our extended SC-PTM framework is energy efficient and guarantees low service latency, as demonstrated both analytically and by simulations.