Corpus overview


MeSH Disease

Human Phenotype

Pneumonia (4)

Falls (3)

Cough (2)

Fever (2)


    displaying 1 - 10 records in total 49
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    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 SARS-COV-2 in Myanmar

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

    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.

    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.

    Herd immunity thresholds for SARS-CoV-2 estimated from unfolding epidemics

    Authors: Ricardo Aguas; Rodrigo M. Corder; Jessica G. King; Guilherme Goncalves; Marcelo U. Ferreira; M. Gabriela M. Gomes

    doi:10.1101/2020.07.23.20160762 Date: 2020-07-24 Source: medRxiv

    As severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation declines causing the rate at which new infections MESHD occur to slow down. Variation in individual susceptibility or exposure to infection MESHD exacerbates this effect. Individuals that are more susceptible or more exposed tend to be infected and removed from the susceptible subpopulation earlier. This selective depletion of susceptibles intensifies the deceleration in incidence. Eventually, susceptible numbers become low enough to prevent epidemic growth or, in other words, the herd immunity threshold is reached. Here we fit epidemiological models with inbuilt distributions of susceptibility or exposure to SARS-CoV-2 outbreaks to estimate basic reproduction numbers TRANS ( R_0 TRANS) alongside coefficients of individual variation (CV) and the effects of containment strategies. Herd immunity thresholds are then calculated as 1-(1/ R_0 TRANS )^(1/((1+CV^2 ) )) or 1-(1/ R_0 TRANS )^(1/((1+2CV^2 ) )), depending on whether variation is on susceptibility or exposure. Our inferences result in herd immunity thresholds around 10-20%, considerably lower than the minimum coverage needed to interrupt transmission TRANS by random vaccination, which for R_0 TRANS higher than 2.5 is estimated above 60%. We emphasize that the classical formula, 1-1/ R_0 TRANS , remains applicable to describe herd immunity thresholds for random vaccination, but not for immunity induced by infection MESHD which is naturally selective. These findings have profound consequences for the governance of the current pandemic given that some populations may be close to achieving herd immunity despite being under more or less strict social distancing measures.

    Characterizing the Qatar advanced-phase SARS-CoV-2 epidemic

    Authors: Laith J Abu-Raddad; Hiam Chemaitelly; Houssein H Ayoub; Zaina Al Kanaani; Abdullatif Al Khal; Einas Al Kuwari; Adeel A Butt; Peter Coyle; Andrew Jeremijenko; Anvar Hassan Kaleeckal; Ali Nizar Latif; Robert C Owen; Hanan F Abdul Rahim; Samya A Al Abdulla; Mohamed G Al Kuwari; Mujeeb C Kandy; Hatoun Saeb; Shazia Nadeem N. Ahmed; Hamad Eid Al Romaihi; Devendra Bansal; Louise Dalton; Sheikh Mohammad Al Thani; Roberto Bertollini

    doi:10.1101/2020.07.16.20155317 Date: 2020-07-19 Source: medRxiv

    ABSTRACT Background: Qatar has a population of 2.8 million, over half of whom are expatriate craft and manual workers (CMW). We aimed to characterize the severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) epidemic in Qatar. Methods: A series of epidemiologic studies were conducted including analysis of the national SARS-CoV-2 PCR testing and hospitalization database, community surveys assessing current infection MESHD, ad-hoc PCR testing campaigns in workplaces and residential areas, serological testing SERO for antibody SERO on blood SERO specimens collected for routine clinical screening/management, national Coronavirus Diseases MESHD 2019 (COVID-19) death MESHD registry, and a mathematical model. Results: By July 10, 397,577 individuals had been PCR tested for SARS-CoV-2, of whom 110,986 were positive, a positivity cumulative rate of 27.9% (95% CI: 27.8-28.1%). PCR positivity of nasopharyngeal swabs in a national community survey (May 6-7) including 1,307 participants was 14.9% (95% CI: 11.5-19.0%); 58.5% of those testing positive were asymptomatic TRANS. Across 448 ad-hoc PCR testing campaigns in workplaces and residential areas including 26,715 individuals, pooled mean PCR positivity was 15.6% (95% CI: 13.7-17.7%). SARS-CoV-2 antibody SERO prevalence SERO was 24.0% (95% CI: 23.3-24.6%) in 32,970 residual clinical blood SERO specimens. Antibody SERO prevalence SERO was only 47.3% (95% CI: 46.2-48.5%) in those who had at least one PCR positive result, but it was 91.3% (95% CI: 89.5-92.9%) among those who were PCR positive >3 weeks before serology testing. There were substantial differences in exposure to infection MESHD by nationality and sex, reflecting risk differentials between the craft/manual workers and urban populations. As of July 5, case severity rate, based on the WHO severity classification, was 3.4% and case fatality rate was 1.4 per 1,000 persons. Model-estimated daily number of infections MESHD and active- infection MESHD prevalence SERO peaked at 22,630 and 5.7%, respectively, on May 21 and May 23. Attack rate TRANS (ever infection MESHD) was estimated at 53.5% on July 12. R0 TRANS ranged between 1.45-1.68 throughout the epidemic. Rt was estimated at 0.70 on June 15, which was hence set as onset date for easing of restrictions. Age TRANS was by far the strongest predictor of severe, critical, or fatal infection MESHD. Conclusions: Qatar has experienced a large SARS-CoV-2 epidemic that is rapidly declining, apparently due to exhaustion of susceptibles. The epidemic demonstrated a classic susceptible-infected-recovered 'SIR' dynamics with a rather stable R0 TRANS of about 1.6. The young demographic structure of the population, in addition to a resourced public health response, yielded a milder disease MESHD burden and lower mortality than elsewhere.

    COVID-19 transmission TRANS in the U.S. before vs. after relaxation of social distancing measures

    Authors: Alexander C Tsai; Guy Harling; Zahra C Reynolds; Rebecca F Gilbert; Mark J Siedner

    doi:10.1101/2020.07.15.20154534 Date: 2020-07-16 Source: medRxiv

    Background: All fifty U.S. states and the District of Columbia implemented social distancing measures that interrupted transmission TRANS of severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) and reduced morbidity and mortality from coronavirus disease MESHD 2019 (COVID-19). All 51 jurisdictions have since begun to relax these measures, albeit in an uncoordinated fashion. Methods: We obtained state-level data on implementation and relaxation of social distancing measures. We fitted mixed-effects linear regression models with a random effect for state, specifying the time-varying, state-specific effective reproduction number TRANS (Rt, the expected number of secondary infections TRANS infections MESHD generated by each index case given date-specific population susceptibility and risk behavior). Explanatory variables included time in days, implementation period (1-21 days prior to first relaxation of any statewide social distancing measure vs. time from relaxation through May 28, 2020), and a time-by-period product term. Results: During the three weeks prior to relaxation, the estimated Rt was declining by an average of 0.0016 units per day (95% confidence interval [CI], -0.0025 to -0.0008). At the time of initial relaxation, states had reported a median 7,628 cases (range, 337-361,313) and 289 COVID-attributable deaths MESHD (range, 7-28,663), and the median estimated Rt was 1.0 (range, 0.8-1.3) (i.e., the median rate of epidemic growth across states was estimated to be zero). After the first relaxation of statewide social distancing measures, the estimated Rt began increasing by an average of 0.0047 units per day (95% CI, 0.0037 to 0.0058) compared with the pre-relaxation period. If these trends continue, the estimated state-level Rt would reach an average value of 1.05 (95% CI, 1.03-1.07) by 30 days after relaxation and 1.15 (95% CI, 1.11-1.18) by 60 days. A similar upward trajectory in the estimated Rt was observed after relaxation of statewide restrictions on internal movement. Conclusions: Relaxation of U.S. statewide social distancing measures was associated with a subsequent reversal of an earlier downward trend in transmission TRANS of SARS-CoV-2, particularly in states with less active epidemics at the time of relaxation.

    Estimating the Effect of Social Distancing Interventions on COVID-19 in the United States

    Authors: Andrew M. Olney; Jesse Smith; Saunak Sen; Fridtjof Thomas; H. Juliette T. Unwin

    doi:10.1101/2020.07.10.20151001 Date: 2020-07-11 Source: medRxiv

    Since its global emergence in 2020, severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) has caused multiple epidemics in the United States. Because medical treatments for the virus are still emerging and a vaccine is not yet available, state and local governments have sought to limit its spread by enacting various social distancing interventions such as school closures and lockdown, but the effectiveness of these interventions is unknown. We applied an established, semi-mechanistic Bayesian hierarchical model of these interventions on SARS-CoV-2 spread in Europe to the United States. We estimated the effect of interventions across all states, contrasted the estimated reproduction number TRANS, Rt , for each state before and after lockdown, and contrasted predicted future fatalities with actual fatalities as a check on the model's validity. Overall, school closures and lockdown are the only interventions modeled that have a reliable impact on Rt , and lockdown appears to have played a key role in reducing Rt below 1.0. We conclude that reversal of lockdown, without implementation of additional, equally effective interventions, will enable continued, sustained transmission TRANS of SARS-CoV-2 in the United States.

    Diagnostics and spread of SARS-CoV-2 in Western Africa: An observational laboratory-based study from Benin

    Authors: Anges Yadouleton; Anna-Lena Sander; Andres Moreira-Soto; Carine Tchibozo; Gildas Hounkanrin; Yvette Badou; Carlo Fischer; Nina Krause; Petas Akogbeto; Edmilson F. de Oliveira Filho; Anges Dossou; Sebastian Bruenink; Melchior AIssi; Mamoudou Harouna Djingarey; Benjamin Hounkpatin; Michael Nagel; Jan felix Drexler

    doi:10.1101/2020.06.29.20140749 Date: 2020-07-08 Source: medRxiv

    Information on severe acute respiratory syndrome MESHD coronavirus-2 (SARS-CoV-2) spread in Africa is limited by fragile 2 surveillance systems and insufficient diagnostic capacity. 3 We assessed the coronavirus disease MESHD-19 (COVID-19)-related diagnostic workload in Benin, Western Africa, 4 characterized SARS-CoV-2 genomes from 12 acute cases of COVID-19, used those together with public data to 5 estimate SARS-CoV-2 transmission TRANS dynamics in a Bayesian framework, validated a widely used diagnostic dual target 6 RT-PCR kit donated to African countries, and conducted serological analyses in 68 sera from confirmed COVID-19 7 cases and from febrile patients sampled before the predicted SARS-CoV-2 introduction. 8 We found a 15-fold increase in the monthly laboratory workload due to COVID-19. Genomic surveillance showed 9 introductions of three distinct SARS-CoV-2 lineages. SARS-CoV-2 genome-based analyses yielded an R0 TRANS estimate of 10 4.4 (95% confidence interval: 2.0-7.7), suggesting intense spread of SARS-CoV-2 in Africa. RT-PCR-based tests 11 were highly sensitive but showed variation of internal controls and between diagnostic targets. Commercially available 12 SARS-CoV-2 ELISAs SERO showed up to 25% false-positive results depending on antigen and antibody SERO types, likely due 13 to unspecific antibody SERO responses elicited by acute malaria MESHD according to lack of SARS-CoV-2-specific neutralizing 14 antibody SERO responses and relatively higher parasitemia MESHD in those sera. 15 We confirm an overload of the diagnostic capacity in Benin and provide baseline information on the usability of 16 genome-based surveillance in resource-limited settings. Sero-epidemiological studies SERO Sero-epidemiological studies SERO needed to assess SARS-CoV-2 17 spread may be put at stake by low specificity of tests in tropical settings globally. The increasing diagnostic challenges 18 demand continuous support of national and supranational African stakeholders.

    An SEIR Model with Contact Tracing TRANS and Age TRANS-Structured Social Mixing for COVID-19 outbreak

    Authors: Ali Teimouri

    doi:10.1101/2020.07.05.20146647 Date: 2020-07-07 Source: medRxiv

    In December 2019 a severe acute respiratory syndrome MESHD now known as SARS-CoV-2 began to surge in Wuhan, China. The virus soon spread throughout the world to become a pandemic. Since the outbreak various measures were put in place to contain and control the spread, these interventions were mostly based on compartmental models in epidemiology with the main goal of controlling and monitoring the rate of the basic and effective reproduction number TRANS. In this paper, we propose an SEIR model where we incorporate contact tracing TRANS and age TRANS-structured social mixing. We show the explicit relation between contact tracing TRANS and social mixing and other relevant parameters of the proposed model. We derive a formula for the effective reproduction number TRANS which is expressed in terms of reported cases, tracing TRANS quantities and social mixing. We use this formula to determine the expectation value of the effective reproduction number TRANS in London, UK.

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MeSH Disease
Human Phenotype

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