Corpus overview


Overview

MeSH Disease

Human Phenotype

Falls (13)

Pneumonia (10)

Fever (4)

Cough (3)

Confusion (2)


Transmission

Seroprevalence
    displaying 1 - 10 records in total 354
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    A "Tail" of Two Cities: Fatality-based Modeling of COVID-19 Evolution in New York City and Cook County, IL

    Authors: Joshua Frieman

    doi:10.1101/2020.08.10.20170506 Date: 2020-08-12 Source: medRxiv

    I describe SIR modeling of the COVID-19 pandemic in two U.S. urban environments, New York City (NYC) and Cook County, IL, from onset through the month of June, 2020. Since testing was not widespread early in the pandemic in the U.S., I do not use data on confirmed cases TRANS and rely solely on public fatality data to estimate model parameters. Fits to the first 20 days of data determine a degenerate combination of the basic reproduction number TRANS, R0 TRANS, and the mean time to removal from the infectious population, 1/{gamma} with {gamma}( R0 TRANS - 1) = 0.25(0.21) inverse days for NYC (Cook County). Equivalently, the initial doubling time was td = 2.8(3.4) days for NYC (Cook). The early fatality data suggest that both locations had infections MESHD in early February. I model the mitigation measures implemented in mid-March in both locations (distancing, quarantine, isolation, etc) via a time-dependent reproduction number TRANS Rt that declines monotonically from R0 TRANS to a smaller asymptotic TRANS value, with a parameterized functional form. The timing (mid-March) and duration (several days) of the transitions in Rt appear well determined by the data. However, the fatality data determine only a degenerate combination of the parameters R0 TRANS, the percentage reduction in social contact due to mitigation measures, X, and the infection MESHD fatality rate (IFR), f . With flat priors, based on simulations the NYC model parameters have 95.45% credible intervals of R0 TRANS = 3.0 - 5.4, X = 80 - 99.9% and f = 2 - 6%, with 5 - 13% of the population asymptotically infected. A strong external prior indicating a lower value of f or of 1/{gamma} would imply lower values of R0 TRANS and X and higher percentage infection MESHD of the population. For Cook County, the evolution was qualitatively different: after mitigation measures were implemented, the daily fatality counts reached a plateau for about a month before tailing off. This is consistent with an SIR model that exhibits "critical slowing-down", in which Rt plateaus at a value just above unity. For Cook County, the 95.45% credible intervals for the model parameters are much broader and shifted downward, R0 TRANS = 1.4 - 4.7, X = 26 - 54%, and f = 0.1 - 0.6% with 15 - 88% of the population asymptotically infected. Despite the apparently lower efficacy of its social contact reduction measures, Cook County has had significantly fewer fatalities per population than NYC, D{infty}/N = 100 vs. 270 per 100,000. In the model, this is attributed to the lower inferred IFR for Cook; an external prior pointing to similar values of the IFR for the two locations would instead chalk up the difference in D/N to differences in the relative growth rate of the disease MESHD. I derive a model-dependent threshold, Xcrit, for "safe" re-opening, that is, for easing of contact reduction that would not trigger a second wave; for NYC, the models predict that increasing social contact by more than 20% from post-mitigation levels will lead to renewed spread, while for Cook County the threshold value is very uncertain, given the parameter degeneracies. The timing of 2nd-wave growth will depend on the amplitude of contact increase relative to Xcrit and on the asymptotic TRANS growth rate, and the impact in terms of fatalities will depend on the parameter f .

    The effect of public health policies in the transmission TRANS of COVID-19 for South American countries

    Authors: Bryan Valcarcel; Jose L Avilez; J. Smith Torres-Roman; Julio A Poterico; Janina Bazalar-Palacios; Carlo La Vecchia

    doi:10.1101/2020.08.09.20149286 Date: 2020-08-12 Source: medRxiv

    Objectives: The analysis of transmission TRANS dynamics is crucial to determine whether mitigation or suppression measures reduce the spread of Coronavirus disease MESHD 2019 (COVID-19). This study sought to estimate the basic ( R0 TRANS) and time-dependent (Rt) reproduction number TRANS of COVID-19 and contrast the public health measures for ten South American countries. Methods: Data was obtained from the European Centre for Disease MESHD Prevention and Control. Country-specific R0 TRANS estimates during the first two weeks of the outbreak and Rt estimates after 90 days were estimated. Results: Countries used a combination of isolation, social distancing, quarantine, and community-wide containment measures to contain the spread of COVID-19 at different points in time. R0 TRANS ranged from 1.52 (95% confidence interval: 1.13-1.99) in Venezuela, to 3.83 (3.04-4.75) in Chile, whereas Rt, after 90 days, ranged from 0.71 (95% credible interval: 0.39-1.05) in Uruguay to 1.20 (1.19-1.20) in Brazil. Different R0 TRANS and Rt values may be related to the testing capacity of each country. Conclusion: R0 TRANS in the early phase of the outbreak varied across the South American countries. The adopted public health measures in the initial period of the pandemic appear to have reduced Rt over time in each country.

    Effective reproduction number TRANS for COVID-19 in Aotearoa New Zealand

    Authors: Rachelle N Binny; Audrey Lustig; Ann Brower; Shaun C Hendy; Alex James; Matthew Parry; Michael J Plank; Nicholas Steyn

    doi:10.1101/2020.08.10.20172320 Date: 2020-08-11 Source: medRxiv

    The effective reproduction number TRANS, Reff, is the average number of secondary cases TRANS infected by a primary case TRANS, a key measure of the transmission TRANS potential for a disease MESHD. Compared to many countries, New Zealand has had relatively few COVID-19 cases, many of which were caused by infections MESHD acquired overseas. This makes it difficult to use standard methods to estimate Reff. In this work, we use a stochastic model to simulate COVID-19 spread in New Zealand and report the values of Reff from simulations that gave best fit to case data. We estimate that New Zealand had an effective reproduction number TRANS Reff = 1.8 for COVID-19 transmission TRANS prior to moving into Alert Level 4 on March 25 2020 and that after moving into Alert level 4 this was reduced to Reff = 0.35. Our estimate Reff = 1.8 for reproduction number TRANS before Alert Level 4, is relatively low compared to other countries. This could be due, in part, to measures put in place in early- to mid-March, including: the cancellation of mass gatherings, the isolation of international arrivals, and employees being encouraged to work from home.

    Application of Optimal Control to Long Term Dynamics of COVID-19 Disease MESHD in South Africa

    Authors: Farai Nyabadza; Williams Chukwu; Faraimunashe Chirove; fatmawati fatmawati; Princess Gatyeni

    doi:10.1101/2020.08.10.20172049 Date: 2020-08-11 Source: medRxiv

    SARS-CoV-2 (COVID-19) belongs to the beta-coronavirus family, these include; the severe acute respiratory syndrome MESHD coronavirus (SARS-CoV) and the Middle East respiratory syndrome MESHD coronavirus (MERS-CoV). Since its resurgence in South Africa in March 2020, it has lead to high mortality and thousands of people contracting the virus. In this study, we use a set of five differential equations to analyse the effects on long term dynamics of COVID-19 pandemic with optimal control measures. Mathematical analyses of the model without control were done and the basic reproduction number TRANS ( R0 TRANS) of the COVID-19 for the South African epidemic determined. The model steady states were also determined, and their analyses presented based on R0 TRANS: We introduced permissible control measures and formulated an optimal control problem using the Pontraygain Maximum Principle. Our numerical findings suggest that joint implementation of effective mask usage, physical distancing and active screening and testing are effective measures to curtail the spread of the disease TRANS disease on undiagnosed MESHD humans. The results obtained in this paper are of public health importance in the control and management of the spread for the novel coronavirus, SARS-CoV-2, in South Africa.

    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.

    Mathematical Modelling of COVID-19 Pandemic with Demographic Effects

    Authors: Abdul Alimamy Kamara; Lagès N. Mouanguissa; Godfrey Barasa

    doi:10.21203/rs.3.rs-56595/v1 Date: 2020-08-10 Source: ResearchSquare

    In this paper, an asymptomatic infection MESHD asymptomatic TRANS transmission TRANS Susceptible-Exposed-Infectious-Recovered (SEIR) model with demographic effects is used to understand the dynamics of the COVID-19 pandemics. We calculate the basic reproduction number TRANS ( R0 TRANS), and prove the global stability of the model by solving the differential equations of the model using the disease MESHD-free equilibrium (DFE) and endemic equilibrium (EE) equations, respectively. We showed that when the R0 TRANS less than one or less than and equal to one, and greater than one or greater than and equal to one the DFE and EE asymptotic TRANS stability exist theoretically and numerically, respectively. We also demonstrate the detrimental impact of the direct and asymptomatic infections MESHD asymptomatic TRANS for the COVID-19 pandemic. 

    Estimation of Effective Reproduction Number TRANS for COVID-19 in Bangladesh and its districts

    Authors: Al-Ekram Elahee Hridoy; Mohammad Naim; Edris Alam; Nazim Uddin Emon; Imrul Hasan Tipo; Shekh Md. Shajid Hasan Tusher; Safaet Alam; Mohammad Safiqul Islam

    doi:10.1101/2020.08.04.20168351 Date: 2020-08-06 Source: medRxiv

    Background Bangladesh is going through an unprecedented crisis since the onset of the COVID-19 pandemic. Throughout the COVID-19 pandemic, the reproduction number TRANS of COVID-19 swarmed in the scientific community and public media due to its simplicity in explaining an infectious disease MESHD dynamic. This paper aims to estimate the effective reproduction number TRANS (Rt) for COVID-19 over time in Bangladesh and its districts using reported cases. Methods Adapted methods derived from Bettencourt and Ribeiro (2008), which is a sequential Bayesian approach using the compartmental Susceptible-Infectious-Recovered (SIR) model, have been used to estimate Rt. Findings As of July 21, the mean Rt is 1.32(0.98-1.70, 90% HDI), with a median of 1.16(0.99-1.34 90% HDI). The initial Rt of Bangladesh was 3, whereas the Rt on the day of imposing nation-wide lockdown was 1.47, at the end of lockdown phase 1 was 1.06, at the end of lockdown phase 2 was 1.33. Each phase of nation-wide lockdown has contributed to the decline of effective reproduction number TRANS (Rt) for Bangladesh by 28.44%, and 26.70%, respectively, implying moderate effectiveness of the epidemic response strategies. Interpretation and Conclusion The mean Rt fell HP by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh. The Rt continued to fall HP below the threshold value one steadily from the beginning of July and sustained around 1. The mean Rt fell HP by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh. As of July 21, the current estimate of Rt is 1.07(0.92-1.15: 90% HDI), meaning that an infected individual is spreading the virus to an average of one other, with 0.07 added chance of infecting a second individual. This whole research recommends two things- broader testing and careful calibration of measures to keep Rt a long way below the crucial threshold one.

    Groundbreaking predictions about COVID-19 pandemic duration, number of infected and dead: A novel mathematical approach never used in epidemiology

    Authors: Javier Garcia Garcia de Alcaniz; Victoria Lopez-Rodas; Eduardo Costas

    doi:10.1101/2020.08.05.20168781 Date: 2020-08-06 Source: medRxiv

    Hundreds of predictions about the duration of the pandemic and the number of infected and dead have been carried out using traditional epidemiological tools (i.e. SIR, SIRD models, etc.) or new procedures of big-data analysis. However, the extraordinary complexity of the disease MESHD and the lack of knowledge about the pandemic (i.e. R value TRANS, mortality rate, etc.) create uncertainty about the accuracy of these estimates. However, several elegant mathematical approaches, based on physics and probability principles, like the Delta-t argument, Lindy's Law or the Doomsday principle-Carter's catastrophe, which have been successfully applied by scientists to unravel complex phenomena characterized by their great uncertainty (i.e. Human race's longevity; How many more humans will be born before extinction) allow predicting parameters of the Covid-19 pandemic. These models predict that the COVID-19 pandemic will hit us until at least September-October 2021, but will likely last until January-September 2022, causing a minimum of 36,000,000 infected and most likely 60,000,000, as well as 1,400,000 dead at best and most likely 2,333,000.

    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.

    Genomic epidemiology reveals transmission TRANS patterns and dynamics of SARS-CoV-2 in Aotearoa New Zealand

    Authors: Jemma L Geoghegan; Xiaoyun Ren; Matthew Storey; James Hadfield; Lauren Jelley; Sarah Jefferies; Jill Sherwood; Shevaun Paine; Sue Huang; Jordan Douglas; Fabio K L Mendes; Andrew Sporle; Michael G Baker; David R Murdoch; Nigel French; Colin R Simpson; David Welch; Alexei J Drummond; Edward C Holmes; Sebastian Duchene; Joep de Ligt

    doi:10.1101/2020.08.05.20168930 Date: 2020-08-06 Source: medRxiv

    New Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nation-wide lockdown of all non-essential services to curb the spread of COVID-19. New Zealand has now effectively eliminated the virus, with low numbers of new cases limited to new arrivals in managed quarantine facilities at the border. Here, we generated 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected between 26 February and 22 May 2020, representing 56% of all confirmed cases TRANS in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. The proportion of D614G variants in the virus spike protein increased over time due to an increase in their importation frequency, rather than selection within New Zealand. These data also helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number TRANS, Re, of New Zealand's largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in a transmission TRANS lineage of more than one additional case. Most of the cases that resulted in a transmission TRANS lineage originated from North America, rather than from Asia where the virus first emerged or from the nearest geographical neighbour, Australia. Genomic data also helped link more infections MESHD to a major transmission TRANS cluster than through epidemiological data alone, providing probable sources of infections MESHD for cases in which the source was unclear. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease MESHD mitigation.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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