Chronic High-Level Parasitemia in HIV-Infected Individuals With or Without Visceral Leishmaniasis in an Endemic Area in Northwest Ethiopia: Potential Superspreaders?

BACKGROUND: People with human immunodeficiency virus (PWH) with recurrent visceral leishmaniasis (VL) could potentially drive Leishmania transmission in areas with anthroponotic transmission such as East Africa, but studies are lacking. Leishmania parasitemia has been used as proxy for infectiousness. METHODS: This study is nested within the Predicting Visceral Leishmaniasis in HIV-InfectedPatients (PreLeisH) prospective cohort study, following 490 PWH free of VL at enrollment for up to 24-37 months in northwest Ethiopia. Blood Leishmania polymerase chain reaction (PCR) was done systematically. This case series reports on 10 PWH with chronic VL (≥3 VL episodes during follow-up) for up to 37 months, and 3 individuals with asymptomatic Leishmania infection for up to 24 months. RESULTS: All 10 chronic VL cases were male, on antiretroviral treatment, with 0-11 relapses before enrollment. Median baseline CD4 count was 82 cells/µL. They displayed 3-6 VL treatment episodes over a period up to 37 months. Leishmania blood PCR levels were strongly positive for almost the entire follow-up (median cycle threshold value, 26 [interquartile range, 23-30]), including during periods between VL treatment. Additionally, we describe 3 PWH with asymptomatic Leishmania infection and without VL history, with equally strong Leishmania parasitemia over a period of up to 24 months without developing VL. All were on antiretroviral treatment at enrollment, with baseline CD4 counts ranging from 78 to 350 cells/µL. CONCLUSIONS: These are the first data on chronic parasitemia in PWH from Leishmania donovani-endemic areas. PWH with asymptomatic and symptomatic Leishmania infection could potentially be highly infectious and constitute Leishmania superspreaders. Xenodiagnosis studies are required to confirm infectiousness.

Superspreading in the emergence of COVID-19 variants.

Superspreading and variants of concern (VOC) of the human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are the main catalyzers of the coronavirus disease 2019 (COVID-19) pandemic. However, measuring their individual impact is challenging. By examining the largest database of SARS-CoV-2 genomes The Global Initiative on Sharing Avian Influenza Data [GISAID; n >1.2 million high-quality (HQ) sequences], we present evidence suggesting that superspreading has had a key role in the epidemiological predominance of VOC. There are clear signatures in the database compatible with large superspreading events (SSEs) coinciding chronologically with the worst epidemiological scenarios triggered by VOC. The data suggest that, without the randomness effect of the genetic drift facilitated by superspreading, new VOC of SARS-CoV-2 would have had more limited chance of success.

Contact tracing & super-spreaders in the branching-process model.

In recent years, it became clear that super-spreader events play an important role, particularly in the spread of airborne infections. We investigate a novel model for super-spreader events, not based on a heterogeneous contact graph but on a random contact rate: Many individuals become infected synchronously in single contact events. We use the branching-process approach for contact tracing to analyze the impact of super-spreader events on the effect of contact tracing. Here we neglect a tracing delay. Roughly speaking, we find that contact tracing is more efficient in the presence of super-spreaders if the fraction of symptomatics is small, the tracing probability is high, or the latency period is distinctively larger than the incubation period. In other cases, the effect of contact tracing can be decreased by super-spreaders. Numerical analysis with parameters suited for SARS-CoV-2 indicates that super-spreaders do not decrease the effect of contact tracing crucially in case of that infection.

Exploring the dynamic variations of viral genomes via a novel genetic network.

Exploring the dynamic variations of viral genomes utilizing with a phylogenetic analysis is vital to control the pandemic and stop its waves. Genetic network can be applied to depict the complicated evolution relationships of viral genomes. However, current phylogenetic methods cannot handle the cases with deletions effectively. Therefore, the k-mer natural vector is employed to characterize the compositions and distribution features of k-mers occurring in a viral genome, and construct a one-to-one relationship between a viral genome and its k-mer natural vector. Utilizing the k-mer natural vector, we proposed a novel genetic network to investigate the variations of viral genomes in transmission among humans. With the assistance of genetic network, we identified the super-spreaders that were responsible for the pandemic outbreaks all over the world and chose the parental strains to evaluate the effectiveness of diagnostics, therapeutics, and vaccines. The obtaining results fully demonstrated that our genetic network can truly describe the relationships of viral genomes, effectively simulate virus spread tendency, and trace the transmission routes precisely. In addition, this work indicated that the k-mer natural vector has the ability to capture established hotspots of diversities existing in the viral genomes and understand how genomic contents change over time.

Contact tracing-induced Allee effect in disease dynamics.

Contact tracing, case isolation, quarantine, social distancing, and other non-pharmaceutical interventions (NPIs) have been a cornerstone in managing the COVID-19 pandemic. However, their effects on disease dynamics are not fully understood. Saturation of contact tracing caused by the increase of infected individuals has been recognized as a crucial variable by healthcare systems worldwide. Here, we model this saturation process with a mechanistic and a phenomenological model and show that it induces an Allee effect which could determine an infection threshold between two alternative states-containment and outbreak. This transition was considered elsewhere as a response to the strength of NPIs, but here we show that they may be also determined by the number of infected individuals. As a consequence, timing of NPIs implementation and relaxation after containment is critical to their effectiveness. Containment strategies such as vaccination or mobility restriction may interact with contact tracing-induced Allee effect. Each strategy in isolation tends to show diminishing returns, with a less than proportional effect of the intervention on disease containment. However, when combined, their suppressing potential is enhanced. Relaxation of NPIs after disease containment--e.g. because vaccination--have to be performed in attention to avoid crossing the infection threshold required to a novel outbreak. The recognition of a contact tracing-induced Allee effect, its interaction with other NPIs and vaccination, and the existence of tipping points contributes to the understanding of several features of disease dynamics and its response to containment interventions. This knowledge may be of relevance for explaining the dynamics of diseases in different regions and, more importantly, as input for guiding the use of NPIs, vaccination campaigns, and its combination for the management of epidemic outbreaks.

A seroepidemiologic study of a measles outbreak, Yamagata Prefecture, Japan, 2017: The estimation of spreaders using serological assays in a measles elimination setting.

INTRODUCTION: In regions where the endemic measles virus has been eliminated, early detection of contagious patients is important for preventing the spread of measles and sustaining elimination. To investigate whether serological assays can be used for the estimation of highly infectious patients with measles, we performed a seroepidemiologic study of a measles outbreak in Yamagata Prefecture, Japan, in 2017. METHODS: We tested plaque reduction neutralization (PRN), IgG avidity, and gelatin particle agglutination (PA) assays in 31 patients with measles, subdivided into two super-spreaders, three spreaders, and 26 non-spreaders. Simultaneously, these results were compared with the cycle threshold (Ct) of a semi-quantitative real-time reverse transcription PCR for the measles virus from throat swab specimens. RESULTS: In the PRN assay, one super-spreader and two spreaders lacked protective antibodies. The IgG avidity assay showed that two super-spreaders and one spreader had low avidity. The PA assay indicated that two super-spreaders and two spreaders lacked protective antibodies. Comparison of the results of the three serological assays and Ct revealed that patients whose antibody titers were judged as low in the IgG avidity and PA assays showed low Ct (i.e., high viral load), whereas non-spreaders tended to show low viral load. CONCLUSIONS: Our preliminary seroepidemiologic analysis of a population of 31 patients with measles suggests that PA and IgG avidity assays may be used for the identification of super-spreader/spreader candidates. However, further investigations are necessary to validate the robustness of these serological assays in detecting contagious measles cases.

Viral Load of Severe Acute Respiratory Syndrome Coronavirus 2 in Adults During the First and Second Wave of Coronavirus Disease 2019 Pandemic in Houston, Texas: The Potential of the Superspreader.

BACKGROUND: During the coronavirus disease 2019 pandemic, a minority of index cases are associated with a majority of secondary cases suggesting that superspreaders could drive the pandemic. We identified a phenotype in individuals with extremely high viral load who could act as superspreaders. METHODS: Data were analyzed from individuals tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from 18 March through 15 August 2020. Outcomes were compared using contingency table and quantile regression to test the equality of medians between the pandemic waves and by viral load groups. RESULTS: Of the 11 564 samples tested, 1319 (11.4%) were positive for SARS-CoV-2. An increase in weekly median viral load occurred in the second wave of the SARS-CoV2 pandemic. This population was more likely to be women, outpatients, and symptomatic and to have an extremely high or high viral load. In patients with multiple reverse-transcription polymerase chain reaction-positive test results, the durations of viral shedding were comparable between individuals with asymptomatic/mild and mild/moderate illness severity. CONCLUSIONS: We detected a small group of individuals with extremely high SARS-CoV-2 viral loads and mild illness. We believe that these individuals' characteristics could be consistent with the superspreader phenomenon and that greater awareness of the social dynamics of these individuals is needed to understand the spread of SARS-CoV-2.

First Reported Nosocomial Outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 in a Pediatric Dialysis Unit.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a life-threatening respiratory condition caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and was initially detected in China in December 2019. Currently, in Germany >140 000 cases of COVID-19 are confirmed. Here we report a nosocomial outbreak of SARS-CoV-2 infections in the pediatric dialysis unit of the University Hospital Münster (UHM). METHODS: Single-step real-time reverse-transcription polymerase chain reaction (rRT-PCR) from nasopharyngeal swabs was used to diagnose the index patient and identify infected contacts. Epidemiological links were analyzed by patient interviews and medical record reviews. In addition, each contact was assessed for exposure to the index case and monitored for clinical symptoms. Cycle threshold (Ct) values of all positive test results were compared between symptomatic and asymptomatic cases. RESULTS: Forty-eight cases were involved in this nosocomial outbreak. Nine contact cases developed laboratory-confirmed COVID-19 infections. Two SARS-CoV-2-positive cases remained clinically asymptomatic. Eleven cases reported flulike symptoms without positive results. Ct values were significantly lower in cases presenting typical COVID-19 symptoms, suggesting high viral shedding (P = .007). CONCLUSIONS: Person-to-person transmission was at the heart of a hospital outbreak of SARS-CoV-2 between healthcare workers (HCWs) and patients in the pediatric dialysis unit at UHM. Semiquantitative rRT-PCR results suggest that individuals with high viral load pose a risk to spread SARS-CoV-2 in the hospital setting. Our epidemiological observation highlights the need to develop strategies to trace and monitor SARS-CoV-2-infected HCWs to prevent COVID-19 outbreaks in the hospital setting.

Epidemiology and Clinical Course of First Wave Coronavirus Disease Cases, Faroe Islands.

The Faroe Islands was one of the first countries in the Western Hemisphere to eliminate coronavirus disease (COVID-19). During the first epidemic wave in the country, 187 cases were reported between March 3 and April 22, 2020. Large-scale testing and thorough contact tracing were implemented early on, along with lockdown measures. Transmission chains were mapped through patient history and knowledge of contact with prior cases. The most common reported COVID-19 symptoms were fever, headache, and cough, but 11.2% of cases were asymptomatic. Among 187 cases, 8 patients were admitted to hospitals but none were admitted to intensive care units and no deaths occurred. Superspreading was evident during the epidemic because most secondary cases were attributed to just 3 infectors. Even with the high incidence rate in early March, the Faroe Islands successfully eliminated the first wave of COVID-19 through the early use of contact tracing, quarantine, social distancing, and large-scale testing.

Clinical characteristics and outcomes of patients with haematologic malignancies and COVID-19 suggest that prolonged SARS-CoV-2 carriage is an important issue.

Specificities of COVID-19 disease course in patients with haematologic malignancies are still poorly studied. So, we aimed to compare patients with haematologic malignancies to patients without malignancies, matched by sex and age and hospitalised for COVID-19 at the same time and in the same centre. Among 25 patients with haematologic malignancies, we found that mortality (40% versus 4%, p < 0.01), number of days with RT-PCR positivity (21.2 ± 15.9 days [range, 3-57] versus 7.4 ± 5.6 days [range, 1-24], p < 0.01), maximal viral load (mean minimal Ct, 17.2 ± 5.2 [range, 10-30] versus 26.5 ± 5.1 [range, 15-33], p < 0.0001) and the delay between symptom onset and clinical worsening (mean time duration between symptom onset and first day of maximum requirement in inspired oxygen fraction, 14.3 ± 10.7 days versus 9.6 ± 3.7 days, p = 0.0485) were higher than in other patients. COVID-19 course in patients with haematologic malignancies has a delayed onset and is more severe with a higher mortality, and patients may be considered as super-spreaders. Clinicians and intensivists need to be trained to understand the specificity of COVID-19 courses in patients with haematological malignancies.

Global stability analysis of the role of multi-therapies and non-pharmaceutical treatment protocols for COVID-19 pandemic.

In this paper, we sought and presented an 8-Dimensional deterministic mathematical COVID-19 dynamic model that accounted for the global stability analysis of the role of dual-bilinear treatment protocols of COVID-19 infection. The model, which is characterized by human-to-human transmission mode was investigated using dual non-pharmaceutical (face-masking and social distancing) and dual pharmaceutical (hydroxylchloroquine and azithromycin) as control functions following the interplay of susceptible population and varying infectious population. First, we investigated the model state-space and then established and computed the system reproduction number for both off-treatment ℜ 0 ( 1 ) = 10.94 and for onset-treatment ℜ 0 ( 2 ) = 3.224 . We considered the model for off-treatment and thereafter by incorporating the theory of LaSalle's invariant principle into the classical method of Lyapunov functions, we presented an approach for global stability analysis of COVID-19 dynamics. Numerical verification of system theoretical predictions was computed using in-built Runge-Kutta of order of precision 4 in a Mathcad surface. The set approach produces highly significant results in the main text. For example, while rapid population extinction was observed by the susceptible under off-treatment scenario in the first t f ≤ 18 days, the application of non-pharmaceuticals at early stage of infection proved very effective strategy in curtailing the spread of the virus. Moreso, the implementation of dual pharmacotherapies in conjunction with non-pharmaceuticals yields tremendous rejuvenation of susceptible population ( 0.5 ≤ S p ( t ) ≤ 3.143 c e l l s / m l 3 ) with maximal reduction in the rates of isolation, super spreaders and hospitalization of the infectives. Thus, experimental results of investigation affirm the suitability of proposed model for the control and treatment of the deadly disease provided individuals adheres to treatment protocols.

Severe Acute Respiratory Syndrome Coronavirus 2 Outbreak Related to a Nightclub, Germany, 2020.

We report an outbreak of coronavirus disease with 74 cases related to a nightclub in Germany in March 2020. Staff members were particularly affected (attack rate 56%) and likely caused sustained viral transmission after an event at the club. This outbreak illustrates the potential for superspreader events and corroborates current club closures.

A super-spreader of SARS-CoV-2 in incubation period among health-care workers.

Since the coronavirus disease 2019 (COVID-19) identified in Wuhan, Hubei, China in December 2019, it has been characterized as a pandemic by World Health Organization (WHO). It was reported that asymptomatic persons are potential sources of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We present an outbreak among health-care workers incited by a doctor who cared a patient with COVID-19 in a Hospital in Wuhan, Hubei, China, which indicates existence of super-spreader even during incubation period.

Drawing transmission graphs for COVID-19 in the perspective of network science.

When we consider a probability distribution about how many COVID-19-infected people will transmit the disease, two points become important. First, there could be super-spreaders in these distributions/networks and second, the Pareto principle could be valid in these distributions/networks regarding estimation that 20% of cases were responsible for 80% of local transmission. When we accept that these two points are valid, the distribution of transmission becomes a discrete Pareto distribution, which is a kind of power law. Having such a transmission distribution, then we can simulate COVID-19 networks and find super-spreaders using the centricity measurements in these networks. In this research, in the first we transformed a transmission distribution of statistics and epidemiology into a transmission network of network science and second we try to determine who the super-spreaders are by using this network and eigenvalue centrality measure. We underline that determination of transmission probability distribution is a very important point in the analysis of the epidemic and determining the precautions to be taken.

[Covid-19, september 2020: fall storm warning]. / Covid-19, septembre 2020 : avis de tempête automnale.

The resurgence of the Covid-19 epidemic in the fall of 2020 in France and in many countries around the world raises many questions. The situation of SARS-CoV-2 infection in France after the first epidemic wave in spring 2020 approximatively indicates more than 30,000 deaths, 3 to 4 millions people infected, 50% asymptomatic infections. These data encourage us to modify the initial perception of this infection, which was imagined to be benign, with massive, homogeneous and rapid distribution ("tsunamic"), and comprising a large majority of asymptomatic forms. This invites us to reassess the hypothesis of a major role of superspreaders in the spread of the infection, which would be more limited and discontinuous ("saltatory") than expected, as for SARS-CoV-1 and MERS-CoV. The role of viral load in the transmission and clinical expression of infection also needs to be assessed. To fight against the spread of the epidemic, generalized confinement a posteriori appears to have a disproportionate cost compared to its effectiveness, whereas the application of barrier gestures (breathing mask, hand hygiene, social distancing) should be promoted without any restriction, along with the diagnosis and temporary isolation of infected persons. While the Covid-19 epidemic is a medical challenge for human societies, it is also a moral challenge that they may not ignore.

Wildlife disease ecology from the individual to the population: Insights from a long-term study of a naturally infected European badger population.

Long-term individual-based datasets on host-pathogen systems are a rare and valuable resource for understanding the infectious disease dynamics in wildlife. A study of European badgers (Meles meles) naturally infected with bovine tuberculosis (bTB) at Woodchester Park in Gloucestershire (UK) has produced a unique dataset, facilitating investigation of a diverse range of epidemiological and ecological questions with implications for disease management. Since the 1970s, this badger population has been monitored with a systematic mark-recapture regime yielding a dataset of >15,000 captures of >3,000 individuals, providing detailed individual life-history, morphometric, genetic, reproductive and disease data. The annual prevalence of bTB in the Woodchester Park badger population exhibits no straightforward relationship with population density, and both the incidence and prevalence of Mycobacterium bovis show marked variation in space. The study has revealed phenotypic traits that are critical for understanding the social structure of badger populations along with mechanisms vital for understanding disease spread at different spatial resolutions. Woodchester-based studies have provided key insights into how host ecology can influence infection at different spatial and temporal scales. Specifically, it has revealed heterogeneity in epidemiological parameters; intrinsic and extrinsic factors affecting population dynamics; provided insights into senescence and individual life histories; and revealed consistent individual variation in foraging patterns, refuge use and social interactions. An improved understanding of ecological and epidemiological processes is imperative for effective disease management. Woodchester Park research has provided information of direct relevance to bTB management, and a better appreciation of the role of individual heterogeneity in disease transmission can contribute further in this regard. The Woodchester Park study system now offers a rare opportunity to seek a dynamic understanding of how individual-, group- and population-level processes interact. The wealth of existing data makes it possible to take a more integrative approach to examining how the consequences of individual heterogeneity scale to determine population-level pathogen dynamics and help advance our understanding of the ecological drivers of host-pathogen systems.

Age-specific infectious period shapes dynamics of pneumonia in bighorn sheep.

Superspreading, the phenomenon where a small proportion of individuals contribute disproportionately to new infections, has profound effects on disease dynamics. Superspreading can arise through variation in contacts, infectiousness or infectious periods. The latter has received little attention, yet it drives the dynamics of many diseases of critical public health, livestock health and conservation concern. Here, we present rare evidence of variation in infectious periods underlying a superspreading phenomenon in a free-ranging wildlife system. We detected persistent infections of Mycoplasma ovipneumoniae, the primary causative agent of pneumonia in bighorn sheep (Ovis canadensis), in a small number of older individuals that were homozygous at an immunologically relevant genetic locus. Interactions among age-structure, genetic composition and infectious periods may drive feedbacks in disease dynamics that determine the magnitude of population response to infection. Accordingly, variation in initial conditions may explain divergent population responses to infection that range from recovery to catastrophic decline and extirpation.

Using Social Network Measures in Wildlife Disease Ecology, Epidemiology, and Management.

Contact networks, behavioral interactions, and shared use of space can all have important implications for the spread of disease in animals. Social networks enable the quantification of complex patterns of interactions; therefore, network analysis is becoming increasingly widespread in the study of infectious disease in animals, including wildlife. We present an introductory guide to using social-network-analytical approaches in wildlife disease ecology, epidemiology, and management. We focus on providing detailed practical guidance for the use of basic descriptive network measures by suggesting the research questions to which each technique is best suited and detailing the software available for each. We also discuss how using network approaches can be used beyond the study of social contacts and across a range of spatial and temporal scales. Finally, we integrate these approaches to examine how network analysis can be used to inform the implementation and monitoring of effective disease management strategies.

A dynamic compartmental model for the Middle East respiratory syndrome outbreak in the Republic of Korea: A retrospective analysis on control interventions and superspreading events.

The 2015 Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea has provided an opportunity to improve our understanding of the spread of MERS linked to healthcare settings. Here we designed a dynamic transmission model to analyze the MERS outbreak in the Republic of Korea based on confirmed cases reported during the period May 20-July 4, 2015. Our model explicitly incorporates superspreading events and time-dependent transmission and isolation rates. Our model was able to provide a good fit to the trajectory of the outbreak and was useful to analyze the role of hypothetical control scenarios. Specifically, we assessed the impact of the timing of control measures, especially associated with a reduction of the transmission rate and diagnostic delays on outbreak size and duration. Early interventions within 1week after the epidemic onset, for instance, including the initial government announcement to the public about the list of hospitals exposed to MERS coronavirus (MERS-CoV), show a promising means to reduce the size (>71%) and duration (>35%) of the MERS epidemic. Finally, we also present results of an uncertainty analysis focused on the role of superspreading events.

Behavioural phenotypes predict disease susceptibility and infectiousness.

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans.