Corpus overview


Overview

MeSH Disease

Human Phenotype

Pneumonia (5)

Falls (3)

Fever (1)


Transmission

Seroprevalence
    displaying 1 - 10 records in total 40
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    COVID-19 outbreak and control in Kenya- Insights from a mathematical model

    Authors: Rachel Waema Mbogo; Titus Okellow Orwa

    doi:10.21203/rs.3.rs-77507/v1 Date: 2020-09-14 Source: ResearchSquare

    The coronavirus disease MESHD 2019 ( COVID -19) pandemic reached Kenya in March 2020 with the initial cases reported in the capital city Nairobi and in the coastal area Mombasa. As reported by the World Health Organization, the outbreak of COVID -19 has spread across the world, killed many, collapsed economies and changed the way people live since it was first reported in Wuhan, China, in the end of 2019. As of May 25,2020 It had led to over 100,000 confirmed cases TRANS in Africa with over 3000 deaths. The trend poses a huge threat to global public health. Understanding the early transmission TRANS dynamics of the infection MESHD and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission TRANS to occur in new areas. We employed a SEIHCRD mathematical transmission TRANS model with reported Kenyan data on cases of COVID -19 to estimate how transmission TRANS varies over time. The model is concise in structure, and successfully captures the course of the COVID -19 outbreak, and thus sheds light on understanding the trends of the outbreak. The next generation matrix approach was adopted to calculate the basic reproduction number TRANS ( $ R_0 TRANS$ ) from the model to assess the factors driving the infection . The results from the model analysis shows that non-pharmaceutical interventions over a relatively long period is needed to effectively get rid of the COVID -19 epidemic otherwise the rate of infection will continue to increase despite the increased rate of recovery.

    Epidemiological characteristics of SARS-COV-2 in Myanmar MESHD

    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 (COVID-19) is an infectious disease MESHD caused by a newly discovered severe acute respiratory syndrome coronavirus 2 MESHD (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 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 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 control strategy in Myanmar.

    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.

    Isolation Considered Epidemiological Model for the Prediction of COVID-19 Trend in Tokyo, Japan

    Authors: Motoaki Utamura; Makoto Koizumi; Seiichi Kirikami

    doi:10.1101/2020.07.31.20165829 Date: 2020-07-31 Source: medRxiv

    Background: Coronavirus Disease MESHD 2019 (COVID19) currently poses a global public health threat. Although no exception, Tokyo, Japan was affected at first by only a small epidemic. Medical collapse nevertheless nearly happened because no predictive method existed for counting patients. A standard SIR epidemiological model and its derivatives predict susceptible, infectious, and removed (recovered/deaths) cases but ignore isolation of confirmed cases TRANS. Predicting COVID19 trends with hospitalized and infectious people in field separately is important to prepare beds and develop quarantine strategies. Methods: Time-series COVID19 data from February 28 to May 23, 2020 in Tokyo were adopted for this study. A novel epidemiological model based on delay differential equation was proposed. The model can evaluate patients in hospitals and infectious cases in the field. Various data such as daily new cases, cumulative infections MESHD, patients in hospital, and PCR test positivity ratios were used to examine the model. This approach derived an alternative formulation equivalent to the standard SIR model. Its results were compared quantitatively with those of the present isolation model. Results: The basic reproductive number TRANS, inferred as 2.30, is a dimensionless parameter composed of modeling parameters. Effects of intervention to mitigate the epidemic spread were assessed a posteriori. An exit policy of how and when to release a statement of emergency was also assessed using the model. Furthermore, results suggest that the rapid isolation of infectious cases has a large potential to effectively mitigate the spread of infection MESHD and restores social and economic activities safely. Conclusions: A novel mathematical model was proposed and examined using COVID19 data for Tokyo. Results show that shortening the period from infection to hospitalization is effective against outbreak without rigorous public health intervention and control. Faster and precise case cluster detection and wider and quicker introduction of testing measures are strongly recommended.

    The effective reproductive number TRANS (Rt) of COVID-19 and its relationship with social distancing

    Authors: Lucas Jardim Sr.; Jose Alexandre Diniz-Filho Sr.; Thiago Fernando Rangel Sr.; Cristiana Maria Toscano II

    doi:10.1101/2020.07.28.20163493 Date: 2020-07-29 Source: medRxiv

    The expansion of the new coronavirus disease MESHD (COVID-19) triggered a renewed public interest in epidemiological models and on how parameters can be estimated from observed data. Here we investigated the relationship between average number of transmissions TRANS though time, the reproductive number TRANS Rt, and social distancing index as reported by mobile phone data service inloco, for Goias State, Brazil, between March and June 2020. We calculated Rt values using EpiEstim package in R-plataform for confirmed cases TRANS incidence curves. We found a correlation equal to -0.72 between Rt values for confirmed cases TRANS and isolation index at a time lag of 8 days. As the Rt values were paired with center of the moving window of 7 days, the delay matches the mean incubation period TRANS of the virus. Our findings reinforce that isolation index can be an effective surrogate for modeling and epidemiological analyses and, more importantly, can be an useful metrics for anticipating the need for early interventions, a critical issue in public health.

    Time is of the essence: containment of the SARS-CoV-2 epidemic in Switzerland from February to May 2020

    Authors: Christian L Althaus; Daniel Probst; Anthony Hauser; Julien L Riou

    doi:10.1101/2020.07.21.20158014 Date: 2020-07-25 Source: medRxiv

    AIM: In late February and early March 2020, Switzerland experienced rapid growth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections MESHD with 30,243 confirmed cases TRANS and 1,860 deaths as of 10 May 2020. The sequential introduction of non-pharmaceutical interventions (NPIs) resulted in successful containment of the epidemic. A better understanding of how the timing of implementing NPIs influences the dynamics and outcome of SARS-CoV-2 epidemics will be crucial for the management of a potential resurgence in Switzerland. METHODS: We developed a dynamic transmission TRANS model that describes infection MESHD, hospitalization, recovery and death MESHD due to SARS-CoV-2 in Switzerland. Using a maximum likelihood framework, we fitted the model to aggregated daily numbers of hospitalized patients, ICU occupancy MESHD and death MESHD from 25 February to 10 May 2020. We estimated critical parameters of SARS-CoV-2 transmission TRANS in Switzerland and explored counterfactual scenarios of an earlier and later implementation of NPIs. RESULTS: We estimated the basic reproduction number TRANS R0 TRANS = 2.61 (95% compatibility interval, CI: 2.51-2.71) during the early exponential phase of the SARS-CoV-2 epidemic MESHD in Switzerland. After the implementation of NPIs, the effective reproduction number TRANS approached Re = 0.64 (95% CI: 0.61-0.66). Based on the observed doubling times of the epidemic before and after the implementation of NPIs, we estimated that one week of early exponential spread required 3.1 weeks (95% CI: 2.8-3.3 weeks) of 'lockdown' to reduce the number of infections to the same level. Introducing the same sequence of NPIs one week earlier or later would have resulted in substantially lower (399, 95% prediction interval, PI: 347-458) and higher (8,683, 95% PI: 8,038-9,453) numbers of deaths, respectively. CONCLUSIONS: The introduction of NPIs in March 2020 prevented thousands of SARS-CoV-2-related deaths in Switzerland. Early implementation of NPIs during SARS-CoV-2 outbreaks can reduce the number of deaths MESHD and the necessary duration of strict control measures considerably.

    The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial cities

    Authors: Ting Tian; Wenxiang Luo; Yukang Jiang; Minqiong Chen; Wenliang Pan; Jiashu Zhao; Songpan Yang; Heping Zhang; Xueqin Wang

    doi:10.1101/2020.06.22.20137380 Date: 2020-06-23 Source: medRxiv

    Background The outbreak of novel coronavirus disease MESHD (COVID-19) has spread around the world since it was detected in December 2019. As the starting place of COVID-19 pandemic, the Chinese government executed a series of interventions to curb the pandemic. The "battle" against COVID-19 in Shenzhen, China is valuable because populated industrial cities are the epic centers of COVID-19 in many regions. Methods We used synthetic control methods to compare the spread of COVID-19 between Shenzhen and its counterpart regions that didn't implement interventions for the total duration of 16 days starting from the day of the first reported case in compared locations. The hypothetical epidemic situations in Shenzhen were inferred by using time-varying reproduction numbers TRANS, assuming the interventions were delayed by 0 day to 5 days. Results The expected cumulative confirmed cases TRANS would be 1307, is which 4.86 times of 269 observed cumulative confirmed cases TRANS in Shenzhen on February 3, 2020, based on the data from the counterpart counties (mainly from Broward, New York, Santa Clara, Westchester and Orange) in the United States. If the interventions were delayed 5 days from the day when the interventions started, the expected cumulative confirmed cases TRANS of COVID-19 in Shenzhen on February 3, 2020 would be 676 with 95% CI (303,1959). Conclusions Early implementation of mild interventions can subdue the epidemic of COVID-19. The later the interventions were implemented, the more severe the epidemic was in the hard-hit areas. Mild interventions are less damaging to the society but can be effective when implemented early.

    Transmission TRANS Potential and Forecasting The Number of Coronavirus Disease MESHD 2019 in Hubei Province, China

    Authors: Ke-wei Wang; Jie Gao; Hua Wang; Xiao-long Wu; Qin-fang Yuan; Yang Cheng

    doi:10.21203/rs.3.rs-36755/v1 Date: 2020-06-19 Source: ResearchSquare

    Background: Coronavirus disease 2019 (COVID-19) was first reported in Wuhan, Hubei province, China. We aimed to describe the temporal and spatial distribution and the transmission TRANS dynamics of COVID-19 and to assess whether a hybrid model can forecast the trend of COVID-19 in Hubei Province, China. Method: The data of COVID-19 cases were obtained from the websites of Chinese Center for Disease Control and Prevention, whereas the data on the resident population were obtained from the websites of Hubei Provincial Bureau of Statistics. The temporal and spatial distribution and the transmission TRANS dynamics of COVID-19 were described. A combination of autoregressive integrated moving average (ARIMA) and support vector machine was constructed to forecast the trend of COVID-19. Results: A total of 56,062 confirmed COVID-19 cases, which were mainly concentrated in Wuhan, were reported from January 16 to March 16, 2020 in Hubei Province, China. The daily number of confirmed cases TRANS exponentially increased to 3,156 before February 4, 2020, fluctuated to 4,823 before February 13, 2020, and then markedly decreased to 1 after March 16, 2020. The highest mean reproduction number TRANS R(t) of 9.48 was recorded on January 16, 2020, after which it decreased to 2.15 on February 2, 2020 and further decreased to less than 1 on February 13, 2020. In the modeling stage, the mean square error, mean absolute error, and mean absolute percentage error of the hybrid ARIMA–SVM model decreased by 98.59%, 89.19% and 89.68%, and those of SVM decreased by 98.58%, 87.71%, and 88.94%, respectively, compared with the ARIMA model. Similar results were obtained in the forecasting stage.Conclusion: Public health interventions resulted in the terminal phase of COVID-19 in Hubei province. The hybrid ARIMA–SVM model may be a reliable tool for forecasting the trend of the COVID-19 epidemic.

    A model for COVID-19 with isolation, quarantine and testing as control measures

    Authors: Maria Soledad Aronna; Roberto Guglielmi; Lucas Machado Moschen

    doi:10.1101/2020.05.29.20116897 Date: 2020-05-29 Source: medRxiv

    In this article we propose a compartmental model for the dynamics of Coronavirus Disease MESHD 2019 (COVID-19). We take into account the presence of asymptomatic TRANS infections MESHD and the main policies that have been adopted so far to contain the epidemic: isolation (or social distancing) of a portion of the population, quarantine for confirmed cases TRANS and testing. We model isolation by separating the population in two groups: one composed by key-workers that keep working during the pandemic and have a usual contact rate, and a second group consisting of people that are enforced/recommended to stay at home. We refer to quarantine as strict isolation, and it is applied to confirmed infected cases. In the proposed model, the proportion of people in isolation, the level of contact reduction and the testing rate are control parameters that can vary in time, representing policies that evolve in different stages. We obtain an explicit expression for the basic reproduction number TRANS R0 TRANS in terms of the parameters of the disease and of the control policies. In this way we can quantify the effect that isolation and testing have in the evolution of the epidemic. We present a series of simulations to illustrate different realistic scenarios. From the expression of R0 TRANS and the simulations we conclude that isolation (social distancing) and testing among asymptomatic TRANS cases are fundamental actions to control the epidemic, and the stricter these measures are and the sooner they are implemented, the more lives can be saved. Additionally, we show that people that remain in isolation significantly reduce their probability of contagion, so risk groups should be recommended to maintain a low contact rate during the course of the epidemic.

    Transmission TRANS Dynamics of COVID-19 in Bangladesh- A Compartmental Modeling Approach 

    Authors: Abul Mukid Md. Mukaddes; Mridul Sannyal

    doi:10.21203/rs.3.rs-31194/v1 Date: 2020-05-23 Source: ResearchSquare

    The c oronavirus disease MESHD(COVID-19) was first identified in Bangldesh, on March 8, 2020. As of May 15, there are 20065 confirmed COVID-19 cases, including 3882 patients who have recovered and 298 related deaths. The objective of this study is to examine the transmission TRANS dynamics of COVID-19 and predict the growth of the i nfection MESHDin Bangladesh using the publicly available data though a mathematical model. The suscected-exposed-infectious-recoverd-dead (SEIRD) model is employed to describe the dynamics based on the kinematic parameters fitted on the data for the outbreak in Bangladesh up to May 15. The expression of basic reproduction number TRANS  using the next generating matrix is derived and estimated. The kinematic parameters that describe transmission TRANS rate (0.045), recovery rate (0.03) and death rate (0.01) seems to be lower, respective of other countries. Based on the official counts for confirmed cases TRANS, the simulations suggest that the cumulative number of active infected follows an exponential trend. The mean reproduction number TRANS 2.25 (95% CI: 1.90-2.40) and transmission TRANS trends clearly indicates the outbreak of COVID-19 in Bangladesh. There is now breakneck concern regarding the capacity to respond to needs of i nfected MESHDpatients effectively and to prevent this pandemic from further spreading in Bangladesh, one of the densest countries in the world. 

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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