Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 1 - 10 records in total 125
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    Extended SEIQR type model for COVID-19 epidemic and data analysis

    Authors: Swarnali Sharma; Vitaly Volpert; Malay Banerjee

    doi:10.1101/2020.08.10.20171439 Date: 2020-08-12 Source: medRxiv

    An extended SEIQR type model is considered in order to model the COVID-19 epidemic. It contains the classes of susceptible individuals, exposed, infected symptomatic and asymptomatic TRANS, quarantined, hospitalized and recovered. The basic reproduction number TRANS and the final size of epidemic are determined. The model is used to fit available data for some European countries. A more detailed model with two different subclasses of susceptible individuals is introduced in order to study the influence of social interaction HP social interaction TRANS on the disease progression MESHD. The coefficient of social interaction HP social interaction TRANS $K$ characterizes the level of social contacts in comparison with complete lockdown (K=0) and the absence of lockdown (K=1). The fitting of data shows that the actual level of this coefficient in some European countries is about 0.1, characterizing a slow disease progression MESHD. A slight increase of this value in the autumn can lead to a strong epidemic burst.

    The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission TRANS across 130 countries and territories

    Authors: Yang Liu; Christian Morgenstern; James Kelly; Rachel Lowe; - CMMID COVID-19 Working Group; Mark Jit

    doi:10.1101/2020.08.11.20172643 Date: 2020-08-12 Source: medRxiv

    Introduction: Non-pharmaceutical interventions (NPIs) are used to reduce transmission TRANS of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease MESHD 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel TRANS restrictions, economic measures, and health system actions on SARS-CoV-2 transmission TRANS in 130 countries and territories. Methods: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission TRANS with data from January - June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number TRANS (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g., restrictions on 1000+ people gathering were not effective, restrictions on <10 people gathering was). Evidence supporting the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel TRANS controls, testing, contact tracing TRANS) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Conclusion: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission TRANS is complicated by temporal clustering, time-dependent variation in effects and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications taking into account these effects, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many although not all the actions policy-makers are taking to respond to the COVID-19 pandemic.

    Epidemiological Characteristics of COVID-19 under Government-mandated Control Measures in Inner Mongolia, China

    Authors: Sha Du; Haiwen Lu; Yuenan Su; Shufeng Bi; Jing Wu; Wenrui Wang; Xinhui Yu; Min Yang; Huiqiu Zheng; Xuemei Wang

    doi:10.21203/rs.3.rs-57472/v1 Date: 2020-08-11 Source: ResearchSquare

    BackgroundThere were 75 local confirmed cases TRANS during the COVID-19 epidemic followed by an outbreak of Wuhan in Inner Mongolia. The aims of our study were to provide reference to control measures of COVID-19 and scientific information for supporting government decision-making for serious infectious disease MESHD, in remote regions with relatively insufficient medical resources like Inner Mongolia.MethodsThe data published by Internet were summarized in order to describe the epidemiological and clinical characteristics of patients with COVID-19. The basic reproductive number (R TRANS 0 ), incubation period TRANS, time from illness onset to confirmed and the duration of hospitalization were analyzed. The composition of imported and local secondary cases TRANS and the mild/common and severe/critical cases among different ages TRANS, genders TRANS and major clinical symptoms were compared.ResultsIn 2020, from January 23 to February 19 (less than 1 month), 75 local cases of COVID-19 were confirmed in Inner Mongolia. Among them, the median age TRANS was 45 years old (34.0, 57.0), and 61.1% were male TRANS and 33 were imported (44.0%). 29 (38.7%) were detected through close contact TRANS tracking, more than 80.0% were mild/common cases. The fatality rate was 1.3% and the basic reproductive number (R TRANS 0 ) was estimated to be 2.3. The median incubation period TRANS was 8.5 days (6.0~12.0) and the maximum incubation period TRANS reached 28 days. There was a statistically difference in the incubation period TRANS between imported and local secondary cases TRANS ( P <0.001). The duration of hospitalization of patients with incubation period TRANS <8.5 days was higher than that of patients with incubation period TRANS ≥8.5 days (30.0 vs. 24.0 days).ConclusionIn Inner Mongolia, an early and mandatory control strategy by government associated with the rapidly reduced incidence of COVID-19, by which the epidemic growth was controlled completely. And the fatality rate of COVID-19 was relatively low.

    How Efficient is Contact Tracing TRANS in Mitigating the Spread of Covid-19? A Mathematical Modeling Approach

    Authors: T. A. Biala; Y. O. Afolabi; A. Q. M. Khaliq

    id:2008.03859v1 Date: 2020-08-10 Source: arXiv

    Contact Tracing TRANS (CT) is one of the measures taken by government and health officials to mitigate the spread of the novel coronavirus. In this paper, we investigate its efficacy by developing a compartmental model for assessing its impact on mitigating the spread of the virus. We describe the impact on the reproduction number TRANS $\mathcal{R}_c$ of Covid-19. In particular, we discuss the importance and relevance of parameters of the model such as the number of reported cases, effectiveness of tracking and monitoring policy, and the transmission TRANS rates to contact tracing TRANS. We describe the terms ``perfect tracking'', ``perfect monitoring'' and ``perfect reporting'' to indicate that traced contacts TRANS will be tracked while incubating, tracked contacts are efficiently monitored so that they do not cause secondary infections MESHD, and all infected persons are reported, respectively. We consider three special scenarios: (1) perfect monitoring and perfect tracking of contacts of a reported case, (2) perfect reporting of cases and perfect monitoring of tracked reported cases and (3) perfect reporting and perfect tracking of contacts of reported cases. Furthermore, we gave a lower bound on the proportion of contacts to be traced TRANS to ensure that the effective reproduction, $\mathcal{R}_c$, is below one and describe $\mathcal{R}_c$ in terms of observable quantities such as the proportion of reported and traced TRANS cases. Model simulations using the Covid-19 data obtained from John Hopkins University for some selected states in the US suggest that even late intervention of CT may reasonably reduce the transmission TRANS of Covid-19 and reduce peak hospitalizations and deaths MESHD. In particular, our findings suggest that effective monitoring policy of tracked cases and tracking of traced contacts TRANS while incubating are more crucial than tracing TRANS more contacts.

    Phylodynamics reveals the role of human travel TRANS and contact tracing TRANS in controlling COVID-19 in four island nations

    Authors: Jordan Douglas; Fabio K Mendes; Remco Bouckaert; Dong Xie; Cinthy L Jimenez-Silva; Christiaan Swanepoel; Joep de Ligt; Xiaoyun Ren; Matt Storey; James Hadfield; Colin R Simpson; Jemma L Geoghegan; David Welch; Alexei J Drummond

    doi:10.1101/2020.08.04.20168518 Date: 2020-08-06 Source: medRxiv

    Most populated corners of the planet have been exposed to SARS-CoV-2, the coronavirus behind the COVID-19 pandemic. We examined the progression of COVID-19 in four island nations that fared well over the first three months of the pandemic: New Zealand, Australia, Iceland, and Taiwan. Using Bayesian phylodynamic methods, we estimated the effective reproduction number TRANS of COVID-19 in the four islands as 1-1.4 during early stages of the pandemic, and show that it declined below 1 as human movement was restricted. Our reconstruction of COVID-19's phylogenetic history indicated that this disease MESHD was introduced many times into each island, and that introductions slowed down markedly when the borders closed. Finally, we found that New Zealand clusters identified via standard health surveillance largely agreed with those defined by genomic data. Our findings can assist public health decisions in countries with circulating SARS-CoV-2, and support efforts to mitigate any second waves or future epidemics.

    COVID-19 pandemic in Djibouti: epidemiology and the response strategy followed to contain the virus during the first two months, 17 March to 16 May 2020

    Authors: Mohamed Elhakim; Saleh Banoita Tourab; Ahmed Zouiten

    doi:10.1101/2020.08.03.20167692 Date: 2020-08-04 Source: medRxiv

    Background: First cases of COVID-19 were reported from Wuhan, China, in December 2019, and it progressed rapidly. On 30 January, WHO declared the new disease MESHD as a PHEIC, then as a Pandemic on 11 March. By mid-March, the virus spread widely; Djibouti was not spared and was hit by the pandemic with the first case detected on 17 March. Djibouti worked with WHO and other partners to develop a preparedness and response plan, and implemented a series of intervention measures. MoH together with its civilian and military partners, closely followed WHO recommended strategy based on four pillars: testing, isolating, early case management, and contact tracing TRANS. From 17 March to 16 May, Djibouti performed the highest per capita tests in Africa and isolated, treated and traced the contacts TRANS of each positive case, which allowed for a rapid control of the epidemic. Methods: COVID-19 data included in this study was collected through MoH Djibouti during the period from 17 March to 16 May 2020. Results: A total of 1,401 confirmed cases TRANS of COVID-19 were included in the study with 4 related deaths MESHD (CFR: 0.3%) and an attack rate TRANS of 0.15%. Males TRANS represented (68.4%) of the cases, with the age group TRANS 31-45 years old (34.2%) as the most affected. Djibouti conducted 17,532 tests, and was considered as a champion for COVID-19 testing in Africa with 18.2 tests per 1000 habitant. All positive cases were isolated, treated and had their contacts traced TRANS, which led to early and proactive diagnosis of cases and in turn yielded up to 95-98% asymptomatic TRANS cases. Recoveries reached 69% of the infected cases with R0 TRANS (0.91). The virus was detected in 4 regions in the country, with the highest percentage in the capital (83%). Conclusion: Djibouti responded to COVID-19 pandemic following an efficient and effective strategy, using a strong collaboration between civilian and military health assets that increased the response capacities of the country. Partnership, coordination, solidarity, proactivity and commitment were the pillars to confront COVID-19 pandemic.

    Early transmission TRANS dynamics, spread, and genomic characterization of SARS-CoV-2 in Panama.

    Authors: Danilo Franco; Claudia Gonzalez; Leyda E Abrego; Jean P Carrera; Yamilka Diaz; Yaset Caisedo; Ambar Moreno; Oris Chavarria; Jessica Gondola; Marlene Castillo; Elimelec Valdespino; Melissa Gaitan; Jose Martinez-Mandiche; Lizbeth Hayer; Pablo Gonzalez; Carmen Lange; Yadira Molto; Dalis Mojica; Ruben Ramos; Maria Mastelari; Lizbeth Cerezo; Lourdes Moreno; Christl A Donnelly; Nuno R. Faria; Juan M Pascale; Sandra Lopez-Verges; Alexander A Martinez

    doi:10.1101/2020.07.31.20160929 Date: 2020-08-04 Source: medRxiv

    Background With more than 50000 accumulated cases, Panama has one of the highest incidences of SARS-CoV-2 in Central America, despite the fast implementation of disease MESHD control strategies. We investigated the early transmission TRANS patterns of the virus and the outcomes of mitigation measures in the country. Methods We collected information from epidemiological surveillance, including contact tracing TRANS, and genetic data from SARS-CoV-2 whole genomes, of the first five weeks of the outbreak. These data were used to estimate the exponential growth rate, doubling time and the time-varying effective reproductive number TRANS (Rt) using date of symptom onset TRANS in a Bayesian framework. The time of most recent ancestor for the introduced and circulating lineages was estimated by Bayesian analysis. Findings A total of 4210 subjects were SARS-CoV-2 positive during the period evaluated, of them we sequenced 313 cases, detecting the circulation of 10 SARS-CoV-2 lineages. Whole genomes analysis identified the local transmission TRANS of one cryptic lineage as early as 2 weeks before it was detected by surveillance systems. Analysis of transmission TRANS dynamics showed that lockdown reduced Rt and increased the doubling time, however, these measures did not stop the circulation of this lineage in the country. Interpretation These results demonstrate the value of epidemiological modeling and genome surveillance to assess mitigation strategies. At the same time, an active search for cryptic transmission TRANS clusters is crucial to interrupt local transmission TRANS of SARS-CoV-2 in a region.

    Using social contact data TRANS to predict and compare the impact of social distancing policies with implications for school re-opening

    Authors: Ellen Brooks-Pollock; Jonathan M Read; Angela R McLean; Matt J Keeling; Leon Danon

    doi:10.1101/2020.07.25.20156471 Date: 2020-07-27 Source: medRxiv

    Background Social distancing measures, including school closures, are being used to control SARS-CoV-2 transmission TRANS in many countries. Once "lockdown" has driven incidence to low levels, selected activities are being permitted. Re-opening schools is a priority because of the welfare and educational impact of closures on children TRANS. However, the impact of school re-opening needs to be considered within the context of other measures. Methods We use social contact data TRANS from the UK to predict the impact of social distancing policies on the reproduction number TRANS. We calibrate our tool to the COVID-19 epidemic in the UK using publicly available death MESHD data and Google Community Mobility Reports. We focus on the impact of re-opening schools against a back-drop of wider social distancing easing. Results We demonstrate that pre-collected social contact data TRANS, combined with incidence data and Google Community Mobility Reports, is able to provide a time-varying estimate of the reproduction number TRANS (R). From an pre-control setting when R=2.7 (95%CI 2.5, 2.9), we estimate that the minimum reproduction number TRANS that can be achieved in the UK without limiting household contacts TRANS is 0.45 (95%CI:0.41-0.50); in the absence of other changes, preventing leisure contacts has a smaller impact (R=2.0,95%CI:1.8-2.4) than preventing work contacts (R=1.5,95%CI:1.4-1.7). We find that following lockdown (when R=0.7 (95% CI 0.6, 0.8)), opening primary schools in isolation has a modest impact on transmission TRANS R=0.83 (95%CI:0.77-0.90) but that high adherence to other measures is needed. Opening secondary schools as well as primary school is predicted to have a larger overall impact (R=0.95,95%CI:0.85-1.07), however transmission TRANS could still be controlled with effective contact tracing TRANS. Conclusions Our findings suggest that primary school children TRANS can return to school without compromising transmission TRANS, however other measures, such as social distancing and contract tracing TRANS, are required to control transmission TRANS if all age groups TRANS are to return to school. Our tool provides a mapping from policies to the reproduction number TRANS and can be used by policymakers to compare the impact of social-easing measures, dissect mitigation strategies and support careful localized control strategies.

    Analyzing the dominant SARS-CoV-2 transmission TRANS routes towards an ab-initio SEIR model

    Authors: Swetaprovo Chaudhuri; Saptarshi Basu; Abhishek Saha

    id:2007.13596v2 Date: 2020-07-27 Source: arXiv

    Identifying the relative importance of the different transmission TRANS routes of the SARS-CoV-2 virus is an urgent research priority. To that end, the different transmission TRANS routes, and their role in determining the evolution of the Covid-19 pandemic are analyzed in this work. Probability of infection MESHD caused by inhaling virus-laden droplets (initial, ejection diameters between $0.5-750\mu m$) and the corresponding desiccated nuclei that mostly encapsulate the virions post droplet evaporation, are individually calculated. At typical, air-conditioned yet quiescent indoor space, for average viral loading, cough MESHD cough HP droplets of initial diameter between $10-50 \mu m$ have the highest infection MESHD probability. However, by the time they are inhaled, the diameters reduce to about $1/6^{th}$ of their initial diameters. While the initially near unity infection MESHD probability due to droplets rapidly decays within the first $25s$, the small yet persistent infection MESHD probability of desiccated nuclei decays appreciably only by $\mathcal{O} (1000s)$, assuming the virus sustains equally well within the dried droplet nuclei as in the droplets. Combined with molecular collision theory adapted to calculate frequency of contact TRANS frequency of contact SERO between the susceptible population and the droplet/nuclei cloud, infection MESHD rate constants are derived ab-initio, leading to a SEIR model applicable for any respiratory event - vector combination. Viral load, minimum infectious dose, sensitivity SERO of the virus half-life to the phase of its vector and dilution of the respiratory jet/puff by the entraining air are shown to mechanistically determine specific physical modes of transmission TRANS and variation in the basic reproduction number TRANS $\mathcal{R}_0$, from first principle calculations.

    Dynamics of SARS-CoV-2 with Waning Immunity in the UK Population

    Authors: Thomas Crellen; Li Pi; Emma Davis; Timothy M Pollington; Tim C D Lucas; Diepreye Ayabina; Anna Borlase; Jaspreet Toor; Kiesha Prem; Graham F Medley; Petra Klepac; T Deirdre Hollingsworth

    doi:10.1101/2020.07.24.20157982 Date: 2020-07-25 Source: medRxiv

    The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. While the duration and strength of immunity to SARS-CoV-2 is currently unknown, specific antibody SERO titres to related coronaviruses SARS-CoV and MERS-CoV have been shown to wane in recovered individuals, and immunity to seasonal circulating coronaviruses is estimated to be shorter than one year. Using an age TRANS-structured, deterministic model, we explore different potential immunity dynamics using contact data TRANS from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalised individuals, a year for hospitalised individuals, and the effective reproduction number TRANS (Rt) after lockdown is 1.2 (our worst case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 409,000 infectious individuals; almost three-fold greater than in a scenario with permanent immunity. Our models suggests that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 SERO is expected to increase due to the secondary peak. Overall, our analysis presents considerations for policy makers on the longer term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection MESHD if immunity to re- infection MESHD is not permanent.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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