Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 1 - 10 records in total 337
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    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.

    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.

    Optimal periodic closure for minimizing risk in emerging disease MESHD outbreaks

    Authors: Jason Hindes; Simone Bianco; Ira B. Schwartz

    id:2007.16151v1 Date: 2020-07-31 Source: arXiv

    Without vaccines and treatments, societies must rely on non-pharmaceutical intervention strategies to control the spread of emerging diseases MESHD such as COVID-19. Though complete lockdown is epidemiologically effective, because it eliminates infectious contacts, it comes with significant costs. Several recent studies have suggested that a plausible compromise strategy for minimizing epidemic risk is periodic closure, in which populations oscillate between wide-spread social restrictions and relaxation. However, no underlying theory has been proposed to predict and explain optimal closure periods as a function of epidemiological and social parameters. In this work we develop such an analytical theory for SEIR-like model diseases MESHD, showing how characteristic closure periods emerge that minimize the total outbreak, and increase predictably with the reproductive number TRANS and incubation periods TRANS of a disease MESHD, as long as both are within predictable limits. Using our approach we demonstrate a sweet-spot effect in which optimal periodic closure is maximally effective for diseases MESHD with similar incubation and recovery periods. Our results compare well to numerical simulations, including in COVID-19 models where infectivity and recovery show significant variability.

    The basic reproduction number TRANS of SARS-CoV-2: a scoping review of available evidence

    Authors: Ann Barber; John M Griffin; Miriam Casey; Aine Collins; Elizabeth A Lane; Quirine Ten Bosch; Mart De Jong; David Mc Evoy; Andrew W Byrne; Conor G McAloon; Francis Butler; Kevin Hunt; Simon J More

    doi:10.1101/2020.07.28.20163535 Date: 2020-07-30 Source: medRxiv

    Background: The transmissibility TRANS of SARS-CoV-2 determines both the ability of the virus to invade a population and the strength of intervention that would be required to contain or eliminate the spread of infection MESHD. The basic reproduction number TRANS, R0 TRANS, provides a quantitative measure of the transmission TRANS potential of a pathogen. Objective: Conduct a scoping review of the available literature providing estimates of R0 TRANS for SARS-CoV-2, provide an overview of the drivers of variation in R0 TRANS estimates and the considerations taken in the calculation of the parameter. Design: Scoping review of available literature between the 01 December 2019 and 07 May 2020. Data sources: Both peer-reviewed and pre-print articles were searched for on PubMed, Google Scholar, MedRxiv and BioRxiv. Selection criteria: Studies were selected for review if (i) the estimation of R0 TRANS represented either the initial stages of the outbreak or the initial stages of the outbreak prior to the onset of widespread population restriction (lockdown), (ii) the exact dates of the study period were provided and (iii) the study provided primary estimates of R0 TRANS. Results: A total of 20 R0 TRANS estimates were extracted from 15 studies. There was substantial variation in the estimates reported. Estimates derived from mathematical models fell HP within a wider range of 1.94-6.94 than statistical models which fell HP between the range of 2.2 to 4.4. Several studies made assumptions about the length of the infectious period TRANS which ranged from 5.8-20 days and the serial interval TRANS which ranged from 4.41-14 days. For a given set of parameters a longer duration of infectiousness or a longer serial interval TRANS equates to a higher R0 TRANS. Several studies took measures to minimise bias in early case reporting, to account for the potential occurrence of super-spreading events, and to account for early sub-exponential epidemic growth. Conclusions: The variation in reported estimates of R0 TRANS reflects the complex nature of the parameter itself, including the context (i.e. social/spatial structure), the methodology used to estimate the parameter, and model assumptions. R0 TRANS is a fundamental parameter in the study of infectious disease MESHD dynamics however it provides limited practical applicability outside of the context in which it was estimated, and should be calculated and interpreted with this in mind.

    Epidemic response to physical distancing policies and their impact on the outbreak risk

    Authors: Fabio Vanni; David Lambert; Luigi Palatella

    id:2007.14620v2 Date: 2020-07-29 Source: arXiv

    We introduce a theoretical framework that highlights the impact of physical distancing variables such as human mobility and physical proximity on the evolution of epidemics and, crucially, on the reproduction number TRANS. In particular, in response to the coronavirus disease MESHD (CoViD-19) pandemic, countries have introduced various levels of 'lockdown' to reduce the number of new infections MESHD. Specifically we use a collisional approach to an infection MESHD- age TRANS structured model described by a renewal equation for the time homogeneous evolution of epidemics. As a result, we show how various contributions of the lockdown policies, namely physical proximity and human mobility, reduce the impact of SARS-CoV-2 and mitigate the risk of disease MESHD resurgence. We check our theoretical framework using real-world data on physical distancing with two different data repositories, obtaining consistent results. Finally, we propose an equation for the effective reproduction number TRANS which takes into account types of interactions among people, which may help policy makers to improve remote-working organizational structure.

    Estimating the reproduction number TRANS and forecasting the impact of COVID-19 in Kuwait using a modified compartmental epidemiological model 

    Authors: Mohammad AlHamli

    doi:10.21203/rs.3.rs-49773/v1 Date: 2020-07-27 Source: ResearchSquare

    A modified compartmental epidemic model was developed to simulate the state of Kuwait protocol in fighting COVID-19 pandemic. The next generation matrix method was used to drive an expression for the basic reproduction number TRANS, R0. Basic and effective reproduction numbers TRANS were calculated using data from the intrinsic growth rate of the  confirmed COVID-19 cases. R0  was found to be 2.18. Three scenarios that varied by effective reproduction number TRANS were used to estimate the future course of the disease MESHD: a high value of R = 1.98, a middle value of R = 1.62, and a low value of R = 1.2. The maximum number of beds required in general hospitals in each scenario were estimated at 141 184, 85 341, and 16 412, respectively. For intensive care units, the estimated numbers of beds required were 16 461, 9 645, and 1788. Maximum deaths MESHD also varied and were estimated to be 29 202, 23 973, and 11 565. For the maximum value of R, it is estimated to peak on August 27, 2020. For the middle value of R, it is estimated to peak on September 20, 2020. For the minimum value of R, it is estimated to peak on December 21, 2020. 

    SEIHCRD Model for COVID-19 spread scenarios, disease MESHD predictions and estimates the basic reproduction number TRANS, case fatality rate, hospital, and ICU beds requirement

    Authors: Avaneesh Singh; Manish Kumar Bajpai

    doi:10.1101/2020.07.24.20161752 Date: 2020-07-27 Source: medRxiv

    We have proposed a new mathematical method, SEIHCRD-Model that is an extension of the SEIR-Model adding hospitalized and critical twocompartments. SEIHCRD model has seven compartments: susceptible (S), exposed (E), infected (I), hospitalized (H), critical (C), recovered (R), and deceased or death MESHD (D), collectively termed SEIHCRD. We have studied COVID- 19 cases of six countries, where the impact of this disease MESHD in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. SEIHCRD model is estimating COVID-19 spread and forecasting under uncertainties, constrained by various observed data in the present manuscript. We have first collected the data for a specific period, then fit the model for death MESHD cases, got the values of some parameters from it, and then estimate the basic reproduction number TRANS over time, which is nearly equal to real data, infection MESHD rate, and recovery rate of COVID-19. We also compute the case fatality rate over time of COVID-19 most affected countries. SEIHCRD model computes two types of Case fatality rate one is CFR daily and the second one is total CFR. We analyze the spread and endpoint of COVID-19 based on these estimates. SEIHCRD model is time-dependent hence we estimate the date and magnitude of peaks of corresponding to the number of exposed cases, infected cases, hospitalized cases, critical cases, and the number of deceased cases of COVID-19 over time. SEIHCRD model has incorporated the social distancing parameter, different age groups TRANS analysis, number of ICU beds, number of hospital beds, and estimation of how much hospital beds and ICU beds are required in near future.

    The role of mathematical model in curbing COVID-19 in Nigeria

    Authors: Chinwendu Emilian Madubueze; Nkiru M. Akabuike; Dachollom Sambo

    doi:10.1101/2020.07.22.20159210 Date: 2020-07-25 Source: medRxiv

    The role of mathematical models in controlling infectious diseases MESHD cannot be overemphasized. COVID-19 is a viral disease MESHD that is caused by Severe Acute Respiratory Syndrome MESHD coronavirus 2 (SARS-CoV-2) which has no approved vaccine. The available control measures are non-pharmacological interventions like wearing face masks, social distancing, and lockdown which are being advocated for by the WHO. This work assesses the impact of non-pharmaceutical control measures (social distancing and use of face-masks) and mass testing on the spread of COVID-19 in Nigeria. A community-based transmission TRANS model for COVID-19 in Nigeria is formulated with observing social distancing, wearing face masks in public and mass testing. The model is parameterized using Nigeria data on COVID-19 in Nigeria. The basic reproduction number TRANS is found to be less than unity( R_0 TRANS<1) when the compliance with intervention measures is moderate (50%[≤]<70%) and the testing rate per day is moderate (0.5[≤]{sigma}_2<0.7) or when the compliance with intervention measures is strict ([≥]70%) and the testing rate per day is poor ({sigma}_2=0.3). This implies that Nigeria will be able to halt the spread of COVID-19 under these two conditions. However, it will be easier to enforce strict compliance with intervention measures in the presence of poor testing rate due to the limited availability of testing facilities and manpower in Nigeria. Hence, this study advocates that Nigerian governments (Federal and States) should aim at achieving a testing rate of at least 0.3 per day while ensuring that all the citizens strictly comply with wearing face masks and observing social distancing in public.

    A Framework for SARS-CoV-2 Testing on a Large University Campus: Statistical Considerations

    Authors: Paul J Rathouz; Catherine A Calder

    doi:10.1101/2020.07.23.20160788 Date: 2020-07-24 Source: medRxiv

    We consider testing strategies for active SARS-CoV-2 infection MESHD for a large university community population, which we define. Components of such a strategy include individuals tested because they self-select or are recommended for testing by a health care provider for their own health care; individuals tested because they belong to a high-risk group where testing serves to disrupt transmission TRANS; and, finally, individuals randomly selected for testing from the university community population as part of a proactive community testing, or surveillance, program. The proactive community testing program is predicated on a mobile device application that asks individuals to self-monitor COVID-like symptoms daily. The goals of this report are (i) to provide a framework for estimating prevalence SERO of SARS-CoV-2 infection MESHD in the university community wherein proactive community testing is a major component of the overall strategy, (ii) to address the issue of how many tests should be performed as part of the proactive community testing program, and (iii) to consider how effective proactive community testing will be for purposes of detection of new disease MESHD clusters. We argue that a comprehensive prevalence SERO estimate informed by all testing done of the university community is a good metric to obtain a global picture of campus SARS-CoV-2 infection MESHD rates at a particular point in time and to monitor the dynamics of infection MESHD over time, for example, estimating the population-level reproductive number TRANS, R0 TRANS). Importantly, the prevalence SERO metric can be useful to campus leadership for decision making. One example involves comparing campus prevalence SERO to that in the broader off-campus community. We also show that under some reasonable assumptions, we can obtain valid statements about the comprehensive prevalence SERO by only testing symptomatic persons in the proactive community testing component. The number of tests performed for individual-level and high-risk group-level needs will depend on the disease MESHD dynamics, individual needs, and testing availability. For purposes of this report, we assume that, for these groups of individuals, inferential precision --- that is, the accuracy with which we can estimate the true prevalence SERO from testing a random sample of individuals --- does not drive decisions on the number of tests. On the other hand, for proactive community testing, the desired level of inferential precision {in a fixed period of time can be used to justify the number of tests to perform {in that period. For example, our results show that, if we establish a goal of ruling out with 98\% confidence a background prevalence SERO of 2\% {in a given week, and the actual prevalence SERO is 1\% among those eligible for proactive community testing, we would need to test 835 randomly-selected symptomatics (i.e., those presenting with COVID-like symptoms) per week via the proactive community testing program in a campus of 80k individuals. In addition to justifying decisions about the number of tests to perform, inferential precision can formalize the intuition that testing of symptomatic individuals should be prioritized over testing asymptomatic TRANS individuals in the proactive community testing program.

    Mathematical Modeling and Optimal Control Analysis of COVID-19 in Ethiopia

    Authors: Haileyesus Tessema Alemneh; Getachew Teshome Telahun

    doi:10.1101/2020.07.23.20160473 Date: 2020-07-24 Source: medRxiv

    In this paper we developed a deterministic mathematical model of the pandemic COVID-19 transmission TRANS in Ethiopia, which allows transmission TRANS by exposed humans. We proposed an SEIR model using system of ordinary differential equations. First the major qualitative analysis, like the disease MESHD free equilibruim point, endemic equilibruim point, basic reproduction number TRANS, stability analysis of equilibrium points and sensitivity SERO analysis was rigorously analysed. Second, we introduced time dependent controls to the basic model and extended to an optimal control model of the disease MESHD. We then analysed using Pontryagins Maximum Principle to derive necessary conditions for the optimal control of the pandemic. The numerical simulation indicated that, an integrated strategy effective in controling the epidemic and the gvernment must apply all control strategies in combating COVID-19 at short period of time.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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