Corpus overview


Overview

MeSH Disease

Human Phenotype

Falls (1)

Pneumonia (1)


Transmission

Seroprevalence
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    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 MESHD with comorbidities such as cardiovascular and cerebrovascular diseases MESHD and diabetes MESHD. 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. The model is simulated using data relevant to the dynamics of the diseases 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 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 MESHD 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 MESHD individuals, $\eta_1$ and $\eta_2$, as well as the recovery rate from COVID-19 for co-infected MESHD 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 MESHD with comorbidity) may be as high as 1000,000 cases by the end of November, 2020 if the re-infection rates for COVID-19 is 0.1 per day. It may be worse than this if the re-infection 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 MESHD individuals to 0.7 per day, then the reproduction number TRANS can be brought very low below one, and COVID-19 infection 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.

    Modelling COVID-19 cases in Nigeria: Forecasts, uncertainties, projections and the link with weather

    Authors: Adeyeri O.E.; Oyekan K.S.A.; Ige S.O.; Akinbobola A.; Okogbue E.C.

    doi:10.21203/rs.3.rs-41193/v1 Date: 2020-07-11 Source: ResearchSquare

    The World Health Organization (WHO) declared COVID-19 a global pandemic on 11 March 2020 due to its global spread. In Nigeria, the first case was documented on 27 February 2020. Since then, it has spread to most parts of the country. This study models, forecasts and projects COVID-19 incidence, cumulative incidence and death MESHD cases in Nigeria using six estimation methods i.e. the attack rate TRANS, maximum likelihood, exponential growth, Markov chain monte Carlo (MCMC), time-dependent and the sequential Bayesian approaches. A sensitivity SERO analysis with respect to the mean generation time is used to quantify the associated reproduction number TRANS uncertainties. The relationship between the COVID-19 incidence and five meteorological variables are further assessed. The result shows that the highest incidences are recorded in days with either religious activities or market days while the weekday trend decreases towards the weekend. It is also established that COVID-19 incidence significantly increases with increasing sea level pressure (0.7 correlation coefficient) and significantly decreases with increasing maximum temperature (-0.3 correlation coefficient). Also, selecting an optimal period for reproduction number TRANS estimates reduces the variability between estimates. As an example, in the EG approach, the epidemic curve that optimally fits the exponential growth is between 1- and 53-time units with reproduction number TRANS estimate of 1.60 [1.58; 1.62] at 95% confidence interval. However, this optimal reproduction number TRANS estimate is different from the default reproduction number TRANS estimate.  Using the MCMC approach, the correlation coefficients between the observed and forecasted incidence, cumulative death MESHD and cumulative confirmed cases TRANS are 0.66, 0.92 and 0.90 respectively. The projections till December shows values approaching 1,000,000, 120,000 and 3,000,000 respectively. Therefore, timely intervention and effective preventive measures are immediately needed to mitigate a full-scale epidemic in the country. 

    Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks

    Authors: Lior Rennert; Corey Andrew Kalbaugh; Lu Shi; Christopher McMahan

    doi:10.1101/2020.07.06.20147272 Date: 2020-07-07 Source: medRxiv

    Background: University campuses present an ideal environment for viral spread and are therefore at extreme risk of serving as a hotbed for a COVID-19 outbreak. While active surveillance throughout the semester such as widespread testing, contact tracing TRANS, and case isolation, may assist in detecting and preventing early outbreaks, these strategies will not be sufficient should a larger outbreak occur. It is therefore necessary to limit the initial number of active cases at the start of the semester. We examine the impact of pre-semester NAT testing on disease spread TRANS in a university setting. Methods: We implement simple dynamic transmission TRANS models of SARS-CoV-2 infection MESHD to explore the effects of pre-semester testing strategies on the number of active infections MESHD and occupied isolation beds throughout the semester. We assume an infectious period TRANS of 3 days and vary R0 TRANS to represent the effectiveness of disease mitigation strategies throughout the semester. We assume the prevalence SERO of active cases at the beginning of the semester is 5%. The sensitivity SERO of the NAT test is set at 90%. Results: If no pre-semester screening is mandated, the peak number of active infections occurs in under 10 days and the size of the peak is substantial, ranging from 5,000 active infections when effective mitigation strategies ( R0 TRANS = 1.25) are implemented to over 15,000 active infections for less effective strategies ( R0 TRANS = 3). When one NAT test is mandated within one week of campus arrival, effective ( R0 TRANS = 1.25) and less effective ( R0 TRANS = 3) mitigation strategies delay the onset of the peak to 40 days and 17 days, respectively, and result in peak size ranging from 1,000 to over 15,000 active infections. When two NAT tests are mandated, effective ( R0 TRANS = 1.25) and less effective ( R0 TRANS = 3) mitigation strategies delay the onset of the peak through the end of fall HP semester and 20 days, respectively, and result in peak size ranging from less than 1,000 to over 15,000 active infections. If maximum occupancy of isolation beds is set to 2% of the student population, then isolation beds would only be available for a range of 1 in 2 confirmed cases TRANS ( R0 TRANS = 1.25) to 1 in 40 confirmed cases TRANS ( R0 TRANS = 3) before maximum occupancy is reached. Conclusion: Even with highly effective mitigation strategies throughout the semester, inadequate pre-semester testing will lead to early and large surges of the disease and result in universities quickly reaching their isolation bed capacity. We therefore recommend NAT testing within one week of campus return. While this strategy is sufficient for delaying the timing of the outbreak, pre-semester testing would need to be implemented in conjunction with effective mitigation strategies to reduce the outbreak size.

    The effectiveness and perceived burden of nonpharmaceutical interventions against COVID-19 transmission TRANS: a modelling study with 41 countries

    Authors: Jan Markus Brauner; Sören Mindermann; Mrinank Sharma; Anna B Stephenson; Tomáš Gavenčiak; David Johnston; Gavin Leech; John Salvatier; George Altman; Alexander John Norman; Joshua Teperowski Monrad; Tamay Besiroglu; Hong Ge; Vladimir Mikulik; Meghan A. Hartwick; Yee Whye Teh; Leonid Chindelevitch; Yarin Gal; Jan Kulveit

    doi:10.1101/2020.05.28.20116129 Date: 2020-05-30 Source: medRxiv

    Background: Governments are attempting to control the COVID-19 pandemic with nonpharmaceutical interventions (NPIs). However, it is still largely unknown how effective different NPIs are at reducing transmission TRANS. Data-driven studies can estimate the effectiveness of NPIs while minimizing assumptions, but existing analyses lack sufficient data and validation to robustly distinguish the effects of individual NPIs. Methods: We collect chronological data on NPIs in 41 countries between January and May 2020, using independent double entry by researchers to ensure high data quality. We estimate NPI effectiveness with a Bayesian hierarchical model, by linking NPI implementation dates to national case and death counts. To our knowledge, this is the largest and most thoroughly validated data-driven study of NPI effectiveness to date. Results: We model each NPI's effect as a multiplicative (percentage) reduction in the reproduction number TRANS R. We estimate the mean reduction in R across the countries in our data for eight NPIs: mandating mask-wearing in (some) public spaces (2%; 95% CI: -14%-16%), limiting gatherings to 1000 people or less (2%; -20%-22%), to 100 people or less (21%; 1%-39%), to 10 people or less (36%; 16%-53%), closing some high-risk businesses (31%; 13%-46%), closing most nonessential businesses (40%; 22%-55%), closing schools and universities (39%; 21%-55%), and issuing stay-at-home orders (18%; 4%-31%). These results are supported by extensive empirical validation, including 15 sensitivity SERO analyses. Conclusions: Our results suggest that, by implementing effective NPIs, many countries can reduce R below 1 without issuing a stay-at-home order. We find a surprisingly large role for school and university closures in reducing COVID-19 transmission TRANS, a contribution to the ongoing debate about the relevance of asymptomatic TRANS carriers TRANS in disease spread TRANS. Banning gatherings and closing high-risk businesses can be highly effective in reducing transmission TRANS, but closing most businesses only has limited additional benefit.

    Forecasting COVID-19 Pandemic: A Data-Driven Analysis

    Authors: Khondoker Nazmoon Nabi

    doi:10.21203/rs.3.rs-30396/v1 Date: 2020-05-19 Source: ResearchSquare

    In this paper, a new Susceptible-Exposed-Symptomatic Infectious- Asymptomatic TRANS Infectious-Quarantined-Hospitalized-Recovered-Dead ( SEIDIUQHRD MESHD) deterministic compartmental model has been proposed and calibrated for interpreting the transmission TRANS dynamics of the novel coronavirus disease MESHD (COVID-19). The purpose of this study is to give a tentative prediction of the epidemic peak for Russia, Brazil, India and Bangladesh which could become the next COVID-19 hotspots in no time by using a Trust-region-reflective (TRR) algorithm which one of the well-known real data fitting techniques. Based on the publicly available epidemiological data from late January until 10 May, it has been estimated that the number of daily new symptomatic infectious cases for the above mentioned countries could reach the peak around the beginning of June with the peak size of 15, 774 (95% CI, 13,814-17,734) symptomatic infectious cases in Russia, 26, 449 (95% CI, 23,489-29,409) cases in Brazil, 9, 504 (95% CI, 8,378-10,630) cases in India and 2,209 (95% CI, 1,878-2,540) cases in Bangladesh. As of May 11, 2020, incorporating the infectiousness capability of asymptomatic TRANS carriers TRANS, our analysis estimates the value of the basic reproduction number TRANS ( R0 TRANS) as of May 11, 2020 was found to be 4.234 (95% CI, 3.764-4.7) in Russia, 5.347 (95% CI, 4.737-5.95) in Brazil, 5.218 (95% CI, 4.56-5.81)in India, 4.649 (95% CI, 4.17-5.12) in the United Kingdom and 3.53 (95% CI, 3.12-3.94) in Bangladesh. Moreover, Latin hypercube sampling-partial rank correlation coeffcient (LHS-PRCC) which is a global sensitivity SERO analysis (GSA) method is applied to quantify the uncertainty of our model mechanisms, which elucidates that for Russia, the recovery rate of undetected asymptomatic TRANS carriers TRANS, the rate of getting home-quarantined or self-quarantined and the transition rate from quarantined class to susceptible class are the most influential parameters, whereas the rate of getting home-quarantined or self-quarantined and the inverse of the COVID-19 incubation period TRANS are highly sensitive parameters in Brazil, India, Bangladesh and the United Kingdom which could signicantly affect the transmission TRANS dynamics of the novel coronavirus. Our analysis also suggests that relaxing social distancing restrictions too quickly could exacerbate the epidemic outbreak in the above-mentioned countries.

    FORECASTING COVID-19 PANDEMIC: A DATA-DRIVEN ANALYSIS

    Authors: Khondoker Nazmoon Nabi

    doi:10.1101/2020.05.12.20099192 Date: 2020-05-17 Source: medRxiv

    In this paper, a new Susceptible-Exposed-Symptomatic Infectious- Asymptomatic TRANS Infectious-Quarantined-Hospitalized-Recovered-Dead ( SEIDIUQHRD MESHD) deterministic compartmental model has been proposed and calibrated for describing the transmission TRANS dynamics of the novel coronavirus disease MESHD (COVID-19). A calibration process is executed through the solution of an inverse problem with the help of a Trust-Region-Reflective algorithm, used to determine the best parameter values that would fit the model response. The purpose of this study is to give a tentative prediction of the epidemic peak for Russia, Brazil, India and Bangladesh which could become the next COVID-19 hotspots in no time. Based on the publicly available epidemiological data from late January until 10 May, it has been estimated that the number of daily new symptomatic infectious cases for the above mentioned countries could reach the peak around the beginning of June with the peak size of {approx}15,774 symptomatic infectious cases in Russia, {approx}26,449 cases in Brazil, {approx}9,504 cases in India and {approx}2,209 cases in Bangladesh. Based on our analysis, the estimated value of the basic reproduction number TRANS ( R0 TRANS) as of May 11, 2020 was found to be {approx}4.234 in Russia, {approx}5.347 in Brazil, {approx}5.218 in India, {approx}4.649 in the United Kingdom and {approx}3.5 in Bangladesh. Moreover, with an aim to quantify the uncertainty of our model parameters, Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) which is a global sensitivity SERO analysis (GSA) method is applied which elucidates that, for Russia, the recovery rate of undetected asymptomatic TRANS carriers TRANS, the rate of getting home-quarantined or self-quarantined and the transition rate from quarantined class to susceptible class are the most influential parameters, whereas the rate of getting home-quarantined or self-quarantined and the inverse of the COVID-19 incubation period TRANS are highly sensitive parameters in Brazil, India, Bangladesh and the United Kingdom which could significantly affect the transmission TRANS dynamics of the novel coronavirus. Our analysis also suggests that relaxing social distancing restrictions too quickly could exacerbate the epidemic outbreak in the above mentioned countries.

    Transmission TRANS in Latent Period Causes A Large Number of Infected People in the United States

    Authors: Qinghe Liu; Junkai Zhu; Zhicheng Liu; Yuhao Zhu; Liuling Zhou; Zefei Gao; Deqiang Li; Yuanbo Tang; Xiang Zhang; Junyan Yang; Qiao Wang

    doi:10.1101/2020.05.07.20094086 Date: 2020-05-11 Source: medRxiv

    The cumulative number of confirmed cases TRANS in the United States exceeded one million on 29 April 2020, becoming the country of the most serious pandemic in the world. We proposed a model to analyze the real situation and follow-up trend of the epidemic in the US. The proposed model divides the epidemic period into two phases, and includes three different categories of transmitters: the latent population, the documented infectious population, and the undocumented infectious population. We use metapopulation network to simulate the spread of the COVID-19 in the US, and apply the Bayesian inference to estimate the key parameters of the model. We also perform component analysis and sensitivity SERO analysis, researching the compositions of the people with COVID-19. The results show that the basic reproduction number TRANS in the early period of propagation is 4.06. As of April 13, 2020, only 45% (95% CI: 35% - 73%) of symptom onset TRANS cases in the United States were documented. The incubation period TRANS of COVID-19 is 10.69 days (95% CI: 10.02-11.74). If the current level of interventions is continued, the cumulative number of confirmed cases TRANS is expected to reach more than 1.7 million in July and continue to grow.

    A first study on the impact of containment measure on COVID-19 spread in Morocco

    Authors: Aayah Hammoumi; Redouane Qesmi

    doi:10.1101/2020.04.26.20080770 Date: 2020-05-01 Source: medRxiv

    Background: Since the appearance of the first case of COVID-19 in Morocco, the cumulative number of reported infectious cases continues to increase and, consequently, the government imposed the containment measure within the country. Our aim is to predict the impact of the compulsory containment on COVID-19 spread. Earlier knowledge of the epidemic characteristics of COVID-19 transmission TRANS related to Morocco will be of great interest to establish an optimal plan-of-action to control the epidemic. Method: Using a Susceptible- Asymptomatic TRANS-Infectious model and the data of reported cumulative confirmed cases TRANS in Morocco from March 2nd to April 9, 2020, we determined the basic and control reproduction numbers TRANS and we estimated the model parameter values. Furthermore, simulations of different scenarios of containment are performed. Results: Epidemic characteristics are predicted according to different rates of containment. The basic reproduction number TRANS is estimated to be 2.9949, with CI(2.6729-3.1485). Furthermore, a threshold value of containment rate, below which the epidemic duration is postponed, is determined. Conclusion: Our findings show that the basic reproduction number TRANS reflects a high speed of spread of the epidemic. Furthermore, the compulsory containment can be efficient if more than 73% of population are confined. However, even with 90% of containment, the end-time is estimated to happen on July 4th which can be harmful and lead to consequent social-economic damages. Thus, containment need to be accompanied by other measures such as mass testing to reduce the size of asymptomatic TRANS population. Indeed, our sensitivity SERO analysis investigation shows that the COVID-19 dynamics depends strongly on the asymptomatic TRANS duration as well as the contact and containment rates. Our results can help the Moroccan government to anticipate the spread of COVID-19 and avoid human loses and consequent social-economic damages as well.

    A novel Monte Carlo simulation procedure for modelling COVID-19 spread over time

    Authors: Gang Xie

    doi:10.21203/rs.3.rs-26308/v1 Date: 2020-04-30 Source: ResearchSquare

    The coronavirus disease MESHD 2019 (COVID-19) has now spread throughout most countries in the world causing heavy life losses and damaging social-economic impacts. Following a stochastic point process modelling approach, a Monte Carlo simulation model was developed to represent the COVID-19 spread dynamics.  First the simulation study was to examine various expected properties of the simulation model performance SERO based on a number of arbitrarily defined scenarios. Then the simulation studies were performed in analysis of the real COVID-19 data reported for Australia and United Kingdom (UK). Given the initial number of active cases before 1 March were around 10 for both countries, the model estimated that the number of active COVID-19 cases was to peak around 30 March in Australia (≈ 1630 cases) and around 11 April in UK (≈ 24600 cases); ultimately the total confirmed cases TRANS could sum to 6610 for Australia in about 70 days and 136000 for UK in about 90 days. The analysis results also confirmed the reproduction number TRANS ranges as reported in the literature. This simulation model was considered as an effective and adaptable decision making/what-if analysis tool in battling COVID-19 in the immediate need, and in battling any other infectious diseases in the future.

    Shortages of hospital beds exacerbate severity of COVID-19 outbreaks

    Authors: Weike Zhou; Aili Wang; Xia Wang; Robert A Cheke; Sanyi Tang

    doi:10.21203/rs.3.rs-24862/v1 Date: 2020-04-23 Source: ResearchSquare

    Background: The global outbreak of COVID-19 has caused worrying concern amongst the public and health authorities. The first and foremost problem that many countries face is a shortage of medical resources. The experience of Wuhan, China, in fighting against COVID-19 provides a model for other countries to learn from. Methods: We formulated a piecewise smooth model to describe the limitation of hospital beds, based on the transmission TRANS progression of COVID-19, and the strengthening prevention and control strategies implemented in Wuhan, China. We used data of the cumulative numbers of confirmed cases TRANS, cured cases and deaths MESHD in Wuhan city from 10 January to 20 March, 2020 to estimate unknown parameters and the effective reproduction number TRANS. Sensitivity SERO analysis was conducted to investigate the impact of a shortage of hospital beds on the COVID-19 outbreak. Results: Even with strong prevention and control measures in Wuhan, slowing down of the supply rate, reducing the maximum capacity and delaying the intervention time of supplementing hospital beds aggravated the outbreak severity by magnifying the cumulative numbers of confirmed cases TRANS and deaths MESHD, prolonging the period of the outbreak in Wuhan, enlarging the value of the effective reproduction number TRANS during the outbreak and postponing the time when the threshold value is reduced to 1. Conclusions: The quick establishment of the Huoshenshan and Leishenshan Hospitals in a short time and the deployment of mobile cabin hospitals played important roles in containing the COVID-19 outbreak in Wuhan, providing a model for other countries to provide more hospital beds for COVID-19 patients faster and earlier. 

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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