Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 11 - 20 records in total 823
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    The impact of relaxing interventions on human contact patterns and SARS-CoV-2 transmission TRANS in China

    Authors: Juanjuan Zhang; Maria Litvinova; Yuxia Liang; Wen Zheng; Huilin Shi; Alessandro Vespignani; Cecile Viboud; Marco Ajelli; Hongjie Yu

    doi:10.1101/2020.08.03.20167056 Date: 2020-08-04 Source: medRxiv

    Non-pharmaceutical interventions to control COVID-19 spread have been implemented in several countries with different intensity, timing, and impact on transmission TRANS. As a result, post-lockdown COVID-19 dynamics are heterogenous and difficult to interpret. Here we describe a set of contact surveys performed in four Chinese cities (Wuhan, Shanghai, Shenzhen, and Changsha) during the pre-pandemic, lockdown, and post-lockdown period to quantify the transmission TRANS impact of relaxing interventions via changes in age TRANS-specific contact patterns. We estimate that the mean number of contacts increased 5%-17% since the end of the lockdown but are still 3-7 times lower than their pre-pandemic levels. We find that post-lockdown contact patterns in China are still sufficiently low to keep SARS-CoV-2 transmission TRANS under control. We also find that the impact of school interventions depends non-linearly on the share of other activities being resumed. When most community activities are halted, school closure leads to a 77% decrease in the reproductive number TRANS; in contrast, when social mixing outside of schools is at pre-pandemic level, school closure leads to a 5% reduction in transmission TRANS. Moving forward, to control COVID-19 spread without resorting to a lockdown, it will be key to dose relaxation in social mixing in the community and strengthen targeted interventions.

    The Silent Partners

    Authors: Gal Almogy

    id:10.20944/preprints202007.0475.v2 Date: 2020-08-04 Source: Preprints.org

    Despite great advances in understanding the dynamics of viral epidemics, the emergence of rapidly spreading, highly pathogenic viruses remains a realistic and catastrophic possibility, which current health systems may not be able to fully contain. An intriguing feature in many recent zoonotic viral outbreaks is the presence of superspreaders, which are infected individuals that cause dramatically more new cases than the average. Here I study the effect of superspreaders on the early dynamics of emerging viruses that have not gained the capacity for efficient human-to-human transmission TRANS, i.e viruses with R0 TRANS < 1. I show that superspreaders have a higher chance of rapid extinction, but under crowded conditions can lead to outbreaks, causing far more cases than regular viruses. I suggest that outbreaks of highly pathogenic superspreaders are more likely when they coincide in time and space with an unrelated outbreak leading to increased hospital admission rates. These superspreader outbreaks may be difficult to detect, especially in the context of a different epidemic in progress, and can significantly affect mortality patterns observed in affected areas.

    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.

    Analysis of COVID-19 and comorbidity co- infection MESHD Model with Optimal Control

    Authors: Dr. Andrew Omame; Nometa Ikenna

    doi:10.1101/2020.08.04.20168013 Date: 2020-08-04 Source: medRxiv

    The new coronavirus disease MESHD 2019 (COVID-19) infection MESHD is a double challenge for people infected with comorbidities such as cardiovascular and cerebrovascular diseases MESHD and diabetes. Comorbidities have been reported to be risk factors for the complications of COVID-19. In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 infection MESHD in order to assess the impacts of prior comorbidity on COVID-19 complications and COVID-19 re- infection MESHD. The model is simulated using data relevant to the dynamics of the diseases MESHD in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection MESHD by comorbid susceptibles as well as the rate of re- infection MESHD by those who have recovered from a previous COVID-19 infection MESHD. Sensitivity SERO analysis of the model when the population of individuals co-infected with COVID-19 and comorbidity is used as response function revealed that the top ranked parameters that drive the dynamics of the co- infection MESHD model are the effective contact rate for COVID-19 transmission TRANS, $\beta\sst{cv}$, the parameter accounting for increased susceptibility to COVID-19 by comorbid susceptibles, $\chi\sst{cm}$, the comorbidity development rate, $\theta\sst{cm}$, the detection rate for singly infected and co-infected individuals, $\eta_1$ and $\eta_2$, as well as the recovery rate from COVID-19 for co-infected individuals, $\varphi\sst{i2}$. Simulations of the model reveal that the cumulative confirmed cases TRANS (without comorbidity) may get up to 180,000 after 200 days, if the hyper susceptibility rate of comorbid susceptibles is as high as 1.2 per day. Also, the cumulative confirmed cases TRANS (including those co-infected with comorbidity) may be as high as 1000,000 cases by the end of November, 2020 if the re- infection MESHD rates for COVID-19 is 0.1 per day. It may be worse than this if the re- infection MESHD rates increase higher. Moreover, if policies are strictly put in place to step down the probability of COVID-19 infection MESHD by comorbid susceptibles to as low as 0.4 per day and step up the detection rate for singly infected individuals to 0.7 per day, then the reproduction number TRANS can be brought very low below one, and COVID-19 infection MESHD eliminated from the population. In addition, optimal control and cost-effectiveness analysis of the model reveal that the the strategy that prevents COVID-19 infection MESHD by comorbid susceptibles has the least ICER and is the most cost-effective of all the control strategies for the prevention of COVID-19.

    Epidemiological characteristics of SARS-COV-2 in Myanmar

    Authors: Aung Min Thway; Htun Tayza; Tun Tun Win; Ye Minn Tun; Moe Myint Aung; Yan Naung Win; Kyaw M Tun

    doi:10.1101/2020.08.02.20166504 Date: 2020-08-04 Source: medRxiv

    Coronavirus disease MESHD (COVID-19) is an infectious disease MESHD caused by a newly discovered severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2). In Myanmar, first COVID-19 reported cases were identified on 23rd March 2020. There were 336 reported confirmed cases TRANS, 261 recovered and 6 deaths MESHD through 13th July 2020. The study was a retrospective case series and all COVID-19 confirmed cases TRANS from 23rd March to 13th July 2020 were included. The data series of COVID-19 cases were extracted from the daily official reports of the Ministry of Health and Sports (MOHS), Myanmar and Centers for Disease MESHD Control and Prevention (CDC), Myanmar. Among 336 confirmed cases TRANS, there were 169 cases with reported transmission TRANS events. The median serial interval TRANS was 4 days (IQR 3, 2-5) with the range of 0 - 26 days. The mean of the reproduction number TRANS was 1.44 with (95% CI = 1.30-1.60) by exponential growth method and 1.32 with (95% CI = 0.98-1.73) confident interval by maximum likelihood method. This study outlined the epidemiological characteristics and epidemic parameters of COVID-19 in Myanmar. The estimation parameters in this study can be comparable with other studies and variability of these parameters can be considered when implementing disease MESHD control strategy in Myanmar.

    Modified SIR-model applied to covid-19, similarity solutions and projections to further development

    Authors: Eckhard Rebhan

    doi:10.1101/2020.07.30.20165035 Date: 2020-08-03 Source: medRxiv

    The SIR-model is adapted to the covid-19 pandemic through a modification that consists in making the basic reproduction number TRANS variable. Independent of it, another reproduction number TRANS is introduced, which is defined similarly to the usual net reproduction number TRANS. Due to its simple analytic form, it enables a clear interpretation for all values. A further parameter, provisionally called acceleration parameter, is introduced and applied, which enables a more differentiated characterization of the infection MESHD number dynamics. By a variable transformation the 3 equations of the modified SIR-model can be reduced to 2. The latter are solved up to ordinary integrations. The solutions are evaluated for current situations, yielding a pretty good match with the data reported. Encouraged by this, a variety of possible future developments is examined, including linear and exponential growth of the infection MESHD numbers as well as sub- and super-exponential growth. In particular, the behavior of the two reproduction numbers TRANS and the acceleration parameter is studied, which in some cases leads to surprising results. With regard to the number of unreported infections MESHD it is shown, that from the solution for a special one solutions for others can be derived by similarity transformations.

    A Compartmental Epidemic Model Incorporating Probable Cases to Model COVID-19 Outbreak in Regions with Limited Testing Capacity

    Authors: Agus Hasan; Yuki Nasution

    doi:10.1101/2020.07.30.20165282 Date: 2020-08-02 Source: medRxiv

    We propose a new compartmental epidemic model taking into account people who has symptoms with no confirmatory laboratory testing (probable cases). We prove well-posedness of the model and provide an explicit expression for the basic reproduction number TRANS R0 TRANS. We use the model together with an extended Kalman filter (EKF) to estimate the time-varying effective reproduction number TRANS Rt of COVID-19 in West Java province, Indonesia, where laboratory testing capacity is limited. Based on our estimation, the value of Rt is higher when the probable cases are taken into account. This correction can be used by decision and policy makers when considering re-opening policy and evaluation of measures.

    Data-driven modeling and forecasting of COVID-19 outbreak for public policy making

    Authors: Agus Hasan; Endah Putri; Hadi Susanto; Nuning Nuraini

    doi:10.1101/2020.07.30.20165555 Date: 2020-08-02 Source: medRxiv

    This paper presents a data-driven approach for COVID-19 outbreak modeling and forecasting, which can be used by public policy and decision makers to control the outbreak through Non-Pharmaceutical Interventions (NPI). First, we apply an extended Kalman filter (EKF) to a discrete-time stochastic augmented compartmental model to estimate the time-varying effective reproduction number TRANS Rt. We use daily confirmed cases TRANS, active cases, recovered cases, deceased cases, Case-Fatality-Rate (CFR), and infectious time as inputs for the model. Furthermore, we define a Transmission TRANS Index (TI) as a ratio between the instantaneous and the maximum value of the effective reproduction number TRANS. The value of TI shows the disease MESHD transmission TRANS in a contact between a susceptible and an infectious individual due to current measures such as physical distancing and lock-down relative to a normal condition. Based on the value of TI, we forecast different scenarios to see the effect of relaxing and tightening public measures. Case studies in three countries are provided to show the practicability of our approach.

    Covid-19 mortality rates in Northamptonshire UK: initial sub-regional comparisons and provisional SEIR model of disease MESHD disease spread TRANS spread

    Authors: Nick Petford; Jackie Campbell

    doi:10.1101/2020.07.30.20165399 Date: 2020-08-02 Source: medRxiv

    We analysed mortality rates in a non-metropolitan UK subregion (Northamptonshire) to understand SARS-CoV-2 disease MESHD fatalities at sub 1000000 population levels. A numerical (SEIR) model was then developed to predict the spread of Covid-19 in Northamptonshire. A combined approach using statistically-weighted data to fit the start of the epidemic to the mortality record. Parameter estimates were then derived for the transmission TRANS rate and basic reproduction number TRANS. Age TRANS standardised mortality rates are highest in Northampton (urban) and lowest in semi-rural districts. Northamptonshire has a statistically higher Covid-19 mortality rate than for the East Midlands and England as a whole. Model outputs suggest the number of infected individuals exceed official estimates, meaning less than 40 percent of the population may require immunisation. Combining published (sub-regional) mortality rate data with deterministic models on disease MESHD disease spread TRANS spread has the potential to help public health practitioners develop bespoke mitigations, guided by local population demographics.

    Mathematical modeling of the transmission TRANS of SARS-CoV-2 '' Evaluating the impact of isolation in Sao Paulo State (Brazil) and lockdown in Spain associated with protective measures on the epidemic of covid-19

    Authors: Hyun Mo Yang; Luis Pedro Lombardi Jr.; Fabio Fernandes Morato Castro; Ariana Campos Yang

    doi:10.1101/2020.07.30.20165191 Date: 2020-08-01 Source: medRxiv

    Coronavirus disease MESHD 2019 (covid-19), with the fatality rate in elder (60 years old or more) being much higher than young (60 years old or less) patients, was declared a pandemic by the World Health Organization on March 11, 2020. Taking into account this age TRANS-dependent fatality rate, a mathematical model considering young and elder subpopulations was formulated based on the natural history of covid-19 to study the transmission TRANS of the SARS-CoV-2. This model can be applied to study the epidemiological scenario resulting from the adoption of isolation or lockdown in many countries to control the rapid propagation of covid-19. We chose as examples the isolation adopted in Sao Paulo State (Brazil) in the early phase but not at the beginning of the epidemic, and the lockdown implemented in Spain when the number of severe covid-19 cases was increasing rapidly. Based on the data collected from Sa o Paulo State and Spain, the model parameters were evaluated and we obtained higher estimation for the basic reproduction number TRANS R0 TRANS (9.24 for Sao Paulo State, and 8 for Spain) compared to the currently accepted estimation of R0 TRANS around 3. The model allowed to explain the flattening of the epidemic curves by isolation in Sao Paulo State and lockdown in Spain when associated with the protective measures (face mask and social distancing) adopted by the population. However, a simplified mathematical model providing lower estimation for R0 TRANS did not explain the flattening of the epidemic curves. The implementation of the isolation in Sa o Paulo State before the rapidly increasing phase of the epidemic enlarged the period of the first wave of the epidemic and delayed its peak, which are the desirable results of isolation to avoid the overloading in the health care system.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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