Corpus overview


MeSH Disease

Human Phenotype

Falls (10)

Pneumonia (6)

Hypertension (1)

Fever (1)


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    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.

    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 MESHD) 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 MESHD 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 MESHD 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 MESHD coronavirus 2 (SARS-CoV-2) infections MESHD with 30,243 confirmed cases TRANS and 1,860 deaths MESHD 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 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 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 MESHD 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 MESHD, respectively. CONCLUSIONS: The introduction of NPIs in March 2020 prevented thousands of SARS-CoV-2-related deaths MESHD 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.

    An Analysis of Outbreak Dynamics and Intervention Effects for COVID-19 Transmission TRANS in Europe

    Authors: Wei Wang

    doi:10.1101/2020.07.21.20158873 Date: 2020-07-25 Source: medRxiv

    As of March 13, 2020, Europe became the center of COVID-19 pandemic. In order to prevent further spread and slow down the increase in confirmed cases TRANS and deaths MESHD, many countries in European Union have taken some interventions since mid-March. In this study, a metapopulation model was used to model the outbreak of COVID-19 in Europe and the effectiveness of these interventions were also estimated. The findings suggested that many countries successfully kept the reproduction number TRANS R_t less than 1 (e.g., Belgium, Germany, Spain, and France) while other countries exhibited R_t greater than 1 (e.g., United Kingdom, Cyprus). Based on the assumed reopen strategy, this study also revealed that a 2-week delay in response predicted approximately 2,000 deaths MESHD and 200,000 cases (daily peak value), while a 3-week delay predicted approximately 5,000 deaths MESHD and 600,000 cases (daily peak value). Therefore, a quick response upon signs of a re-emerging pandemic in the world is highly imperative to mitigate potential loss of life and to keep transmission TRANS of Covid-19 under control.

    The COVID-19 outbreak in Sichuan, China: epidemiology and impact of interventions

    Authors: Quanhui Liu; Ana I Bento; Kexin Yang; Hang Zhang; Xiaohan Yang; Stefano Merler; Alessandro Vespignani; Jiancheng Lv; Hongjie Yu; Wei Zhang; Tao Zhou; Marco Ajelli

    doi:10.1101/2020.07.20.20157602 Date: 2020-07-21 Source: medRxiv

    In January 2020, a COVID19 outbreak was detected in Sichuan Province of China. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of the performed interventions. We analyzed patient records for all laboratory confirmed cases TRANS reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers TRANS, we used a Bayesian framework. In addition, we estimate the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases TRANS, lasted less than two months, and no further local transmission TRANS was detected after February 27. The median age TRANS of local cases was 8 years older than that of imported cases. Severity of symptoms increased with age TRANS. We estimated R0 TRANS at 2.4 (95% CI: 1.6-3.7). The epidemic was self sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency MESHD by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95%CI: 31-68 days), causing 9,216 (95%CI: 1,317-25,545) more cases and possibly overwhelming Sichuan healthcare system.

    Epidemiological Profile and Transmission TRANS Dynamics of COVID-19 in the Philippines

    Authors: Nel Jason Ladiao Haw; Jhanna Uy; Karla Therese L. Sy

    doi:10.1101/2020.07.15.20154336 Date: 2020-07-20 Source: medRxiv

    The Philippines confirmed local transmission TRANS of COVID-19 on 7 March 2020. We described the characteristics and epidemiological time-to-event distributions for laboratory- confirmed cases TRANS in the Philippines. The median age TRANS of 8,212 cases was 46 years (IQR: 32-61), with 46.2% being female TRANS and 68.8% living in the National Capital Region. Health care workers represented 24.7% of all detected infections MESHD. Mean length of hospitalization for those who were discharged or died were 16.00 days (95% CI: 15.48, 16.54) and 7.27 days (95% CI: 6.59, 8.24). Mean duration of illness was 26.66 days (95% CI: 26.06, 27.28) and 12.61 days (95% CI: 11.88, 13.37) for those who recovered or died. Mean serial interval TRANS was 6.90 days (95% CI: 5.81, 8.41). Epidemic doubling time pre-quarantine (11 February and 19 March) was 4.86 days (95% CI: 4.67, 5.07) and the reproductive number TRANS was 2.41 (95% CI: 2.33, 2.48). During quarantine (March 20 to April 9), doubling time was 12.97 days (95% CI: 12.57, 13.39) and the reproductive number TRANS was 0.89 (95% CI: 0.78, 1.02).

    Modeling the Impact of Lock-down on COVID-19 Spread in Malaysia

    Authors: Altahir A. Altahir; Nirbhay Mathur; Loshini Thiruchelvam; Ghulam E. Mustafa Abro; Syaimaa S. M. Radzi; Sarat C Dass; Balvinder Singh Gill; Patrick Sebastian; Saiful A. Zulkifli; Vijanth S. Asirvadam

    doi:10.1101/2020.07.17.208371 Date: 2020-07-17 Source: bioRxiv

    After a breakdown notified in Wuhan, China in December 2019, COVID-19 is declared as pandemic diseases MESHD. To the date more than 13 million confirmed cases TRANS and more than half a million are dead around the world. This virus also attached Malaysia in its immature stage where 8718 cases were confirmed TRANS and 122 were declared as death MESHD. Malaysia responsibly controlled the spread by enforcing MCO. Hence, it is required to visualize the pattern of Covid-19 spread. Also, it is necessary to estimate the impact of the enforced prevention measures. In this paper, an infectious disease MESHD dynamic modeling (SEIR) is used to estimate the epidemic spread in Malaysia. The main assumption is to update the reproduction number TRANS Rt with respect to the implemented prevention measures. For a time-frame of five month, the Rt was assumed to vary between 2.9 and 0.3. Moreover, the manuscript includes two possible scenarios: the first will be the extension of the stricter measures all over the country, and the second will be the gradual lift of the lock-down. After implementing several stages of lock-down we have found that the estimated values of the Rt with respect to the strictness degree varies between 0.2 to 1.1. A continuous strict lock-down may reduce the Rt to 0.2 and accordingly the estimated active cases will be reduced to 20 by the beginning of September 2020. In contrast, the second scenario considers a gradual lift of the enforced prevention measures by the end of June 2020, here we have considered three possible outcomes according to the MCO relaxation. Thus, the estimated values of Rt = 0.7, 0.9, 1.1, which shows a rapid increase in the number of active cases. The implemented SEIR model shows a close resemblance with the actual data recorded from 10, March till 7, July 2020. Author summaryConceptualization, A.A.A; methodology, A.A.A, N.M; validation, A.A.A, N.M; formal analysis, A.A.A; investigation, N.M, A.A.A; resources, G.E.M.A, L.T; data collection, L.T, N.M; writing--original draft preparation, A.A.A, L.T, G.E.M.A, N.M; writing--review and editing, V.S.A, S.C.D, B.S.G, P.S, S.A.B.M.Z, N.M; visualization, N.M; supervision, V.S.A; project administration, V.S.A. All authors have read and agreed to the published version of the manuscript

    Epidemiological aspects of COVID-19 disease MESHD in India during nationwide lockdown phase- An empirical data-based analysis and its implications on interrupting the transmission TRANS


    doi:10.1101/2020.07.16.20155903 Date: 2020-07-17 Source: medRxiv

    Background: Covid-19 disease MESHD is pandemic in more than 85% of the countries in the world, with about 10 million cases and 0.5 million deaths MESHD as on July 2, 2020. In India reporting of the first case was on January 30, 2020, and to prevent rapid community spread of the disease TRANS disease MESHD nationwide lockdown phase was imposed from March 25- June 1, 2020. Our objective was to assess various epidemiological measures during the lockdown phase. Methods: We used daily reporting of confirmed cases TRANS by the Ministry of Health and Family Welfare, Government of India during the period March 19-June 1, 2020. Using statistical packages STATA version 16.0 and R-packages in R-version 4.0, we fitted statistical distributions, estimated generation time and Basic Reproduction numbers TRANS. Results: During the lockdown phase, the daily per cent increase in the cumulative number of cases showed negative exponential growth with 0.022 as an instantaneous rate of decrease. Day specific incidence rate per million revealed the exponential pattern with 0.069 as the instantaneous rate of increase per day, which accounted for the doubling time of the disease MESHD (10 days; 95% CI: 9.25-10.93). Case fatality rate (2.92%; 95% CI: 2.82% -3.02%) and overall death MESHD rate was 1.14 (95% CI: 0.87-1.41) per million. were abysmally low. Statistical distribution fitting of new cases found to be satisfactory with Gamma distribution. Basic reproduction numbers TRANS 1.83 (95% CI: 1.82-1.83) was less. Conclusion: In India, with a population density of about 450 per Km2, the virulent of COVID-19 transmission TRANS was interrupted significantly with 70 days lockdown during the early transmission TRANS stage. A great decline could be seen in all the epidemiological indices compared to the index noted during the same period in the severely affected countries.

    A comprehensive analysis of R0 TRANS with different lockdown phase during covid-19 in India

    Authors: Mayank Chhabra; Tushant Agrawal

    doi:10.1101/2020.07.10.20150631 Date: 2020-07-11 Source: medRxiv

    Background: World Health organization declared Covid-19 as an outbreak, hence preventive measure like lockdown should be taken to control the spread of infection MESHD. This study offers an exhaustive analysis of the reproductive number TRANS ( R0 TRANS) in India with major intervention for COVID-19 outbreaks and analysed the lockdown effects on the Covid-19. Methodology: Covid-19 data extracted from Ministry of Health and Family Welfare, Government of India. Then, a novel method implemented in the incidence and Optimum function in desolve package to the data of cumulative daily new confirmed cases TRANS for robustly estimating the reproduction number TRANS in the R software. Result: Analysis has been seen that the lockdown was really quite as effective, India has already shown a major steady decline. The growth rate has fluctuated about 20 percent with trend line projections in various lockdown. A comparative analysis gives an idea of decline in value of R0 TRANS from 1.73 to 1.08. Annotation plot showing the predicted R0 TRANS values based on previous lockdown in month of June and July. Conclusion: Without lockdown, the growth might not have been contained in India and may have gone into the exponential zone. We show that, the lockdown in India was fairly successful. The effect partial lifting of the lockdown (unlock) is also seen in the results, in terms of increment in R0 TRANS values. Hence this study provides a platform for policy makers and government authorities for implementing the strategies to prevent the spread of infection MESHD.

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MeSH Disease
Human Phenotype

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