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MeSH Disease


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    Demography, social contact patterns and the COVID-19 MESHD burden in different settings of Ethiopia: a modeling study

    Authors: Filippo Trentini; Giorgio Guzzetta; Margherita Galli; Agnese Zardini; Fabio Manenti; Giovanni Putoto; Valentina Marziano; Worku Gamshie Nigussa; Ademe Tsegaye; Alessandro Greblo; Alessia Melegaro; Marco Ajelli; Stefano Merler; Piero Poletti; Amit Joshi; Andrew Chan; Jakob Cramer; Tim Spector; Jonathan Wolf; Sebastien Ourselin; Claire Steves; Albert Loeliger; Henrik Kloverpris; Alex Sigal

    doi:10.1101/2020.11.24.20237560 Date: 2020-11-24 Source: medRxiv

    Background COVID-19 MESHD spread may have a dramatic impact in countries with vulnerable economies and limited availability of, and access to, healthcare resources and infrastructures. However, in sub-Saharan Africa a low prevalence SERO and mortality have been observed so far. Methods We collected data on individual social contacts in Ethiopia across geographical contexts characterized by heterogeneous population density, work and travel TRANS opportunities, and access to primary care. We assessed how socio-demographic factors and observed mixing patterns can influence the COVID-19 MESHD disease burden, by simulating SARS-CoV-2 transmission TRANS in remote settlements, rural villages, and urban neighborhoods MESHD, under the current school closure mandate. Results From national surveillance data, we estimated a net reproduction number TRANS of 1.62 (95%CI 1.55-1.70). We found that, at the end of an epidemic mitigated by school closure alone, 10-15% of the overall population would have been symptomatic and 0.3-0.4% of the population would require mechanical ventilation and/or possibly result in a fatal outcome. Higher infection attack rates TRANS are expected in more urbanized areas, but the highest incidence of critical disease MESHD is expected in remote subsistence farming settlements. Conclusions The relatively low burden of COVID-19 MESHD in Ethiopia can be explained by the estimated mixing patterns, underlying demography and the enacted school closures. Socio-demographic factors can also determine marked heterogeneities across different geographical contexts within the same country. Our findings can contribute to understand why sub-Saharan Africa is experiencing a relatively lower attack rate TRANS of severe cases compared to high income countries.

    Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19 MESHD

    Authors: Houssein H. Ayoub; Hiam Chemaitelly; Shaheen Seedat; Monia Makhoul; Zaina Al Kanaani; Abdullatif Al Khal; Einas Al Kuwari; Adeel A Butt; Peter Coyle; Andrew Jeremijenko; Anvar Hassan Kaleeckal; Ali Nizar Latif; Riyazuddin Mohammad Shaik; Hadi M. Yassine; Mohamed G. Al Kuwari; Hamad Eid Al Romaihi; Mohamed H. Al-Thani; Roberto Bertollini; Laith J Abu-Raddad

    doi:10.1101/2020.11.08.20184663 Date: 2020-11-10 Source: medRxiv

    Background: Mathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic MESHD. The study investigated the time course of the epidemic, forecasted healthcare needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions. Methods: An age TRANS-structured deterministic model was constructed to describe SARS-CoV-2 transmission TRANS dynamics and disease progression throughout the population. Results: The enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence SERO, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12,750 on May 23, and active-infection prevalence SERO was predicted to peak at 3.2% on May 25. Daily acute-care and ICU-care hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number TRANS R0 TRANS had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of Rt tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when Rt declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak. Conclusions: Use of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the healthcare system.

    High prevalence SERO of SARS-CoV-2 swab positivity and increasing R number in England during October 2020: REACT-1 round 6 interim report

    Authors: Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Nicole E. Quigley; Andrew Cummings; Alizée McLorg; Kaelene LoMonaco; Sarah Schlossberg; Drew W. Barron-Kraus; Harrison C. Shrock; - UFCOVID Interventions Team; Justin Lessler; Carl D. Laird; Derek A.T. Cummings

    doi:10.1101/2020.10.30.20223123 Date: 2020-11-03 Source: medRxiv

    Background REACT-1 measures prevalence SERO of SARS-CoV-2 infection MESHD in representative samples of the population in England using PCR testing from self-administered nose and throat swabs. Here we report interim results for round 6 of observations for swabs collected from the 16th to 25th October 2020 inclusive. Methods REACT-1 round 6 aims to collect data and swab results from 160,000 people aged TRANS 5 and above. Here we report results from the first 86,000 individuals. We estimate prevalence SERO of PCR-confirmed SARS-CoV-2 infection MESHD, reproduction numbers TRANS (R) and temporal trends using exponential growth or decay models. Prevalence SERO estimates are presented both unweighted and weighted to be representative of the population of England, accounting for response rate, region, deprivation and ethnicity. We compare these interim results with data from round 5, based on swabs collected from 18th September to 5th October 2020 inclusive. Results Overall prevalence SERO of infection in the community in England was 1.28% or 128 people per 10,000, up from 60 per 10,000 in the previous round. Infections were doubling every 9.0 (6.1, 18) days with a national reproduction number TRANS (R) estimated at 1.56 (1.27, 1.88) compared to 1.16 (1.05, 1.27) in the previous round. Prevalence SERO of infection was highest in Yorkshire and The Humber at 2.72% (2.12%, 3.50%), up from 0.84% (0.60%, 1.17%), and the North West at 2.27% (1.90%, 2.72%), up from 1.21% (1.01%, 1.46%), and lowest in South East at 0.55% (0.45%, 0.68%), up from 0.29% (0.23%, 0.37%). Clustering of cases was more prevalent in Lancashire, Manchester, Liverpool and West Yorkshire, West Midlands and East Midlands. Interim estimates of R were above 2 in the South East, East of England, London and South West, but with wide confidence intervals. Nationally, prevalence SERO increased across all age groups TRANS with the greatest increase in those aged TRANS 55-64 at 1.20% (0.99%, 1.46%), up 3-fold from 0.37% (0.30%, 0.46%). In those aged TRANS over 65, prevalence SERO was 0.81% (0.58%, 0.96%) up 2-fold from 0.35% (0.28%, 0.43%). Prevalence SERO remained highest in 18 to 24-year olds at 2.25% (1.47%, 3.42%). Conclusion The co-occurrence of high prevalence SERO and rapid growth means that the second wave of the epidemic in England has now reached a critical stage. Whether via regional or national measures, it is now time-critical to control the virus and turn R below one if further hospital admissions and deaths from COVID-19 MESHD are to be avoided.

    Implications of the COVID-19 MESHD pandemic on eliminating trachoma MESHD as a public health problem

    Authors: Seth Blumberg; Anna Borlase; Joaquin M Prada; Anthony W Solomon; Paul Emerson; Pamela J Hooper; Michael S. Deiner; Benjamin Amoah; Deirdre S. Hollingsworth; Travis C Porco; Thomas M Lietman; Sarah Caddy; Anna Yakovleva; Grant Hall; Fahad A Khokhar; Theresa Feltwell; Malte Pinckert; Iliana Georgana; Yasmin Chaudhry; Martin Curran; Surendra Parmar; Dominic Sparkes; Lucy Rivett; Nick K Jones; Sushmita Sridhar; Sally Forest; Tom Dymond; Kayleigh Grainger; Chris Workman; Effrossyni Gkrania-Klotsas; Nicholas M Brown; Michael Weekes; Stephen Baker; Sharon J Peacock; Theodore Gouliouris; Ian G. Goodfellow; Daniela de Angelis; M. Estee Torok

    doi:10.1101/2020.10.26.20219691 Date: 2020-10-27 Source: medRxiv

    Background: Progress towards elimination of trachoma MESHD as a public health problem has been substantial, but the COVID-19 MESHD pandemic has disrupted community-based control efforts. Methods: We use a susceptible-infected model to estimate the impact of delayed distribution of azithromycin treatment on the prevalence SERO of active trachoma MESHD. Results: We identify three distinct scenarios for geographic districts depending on whether the basic reproduction number TRANS and the treatment-associated reproduction number TRANS are above or below a value of one. We find that when the basic reproduction number TRANS is below one, no significant delays in disease control will be caused. However, when the basic reproduction number TRANS is above one, significant delays can occur. In most districts a year of COVID-related delay can be mitigated by a single extra round of mass drug administration. However, supercritical districts require a new paradigm of infection control because the current strategies will not eliminate disease. Conclusion: If the pandemic can motivate judicious, community-specific implementation of control strategies, global elimination of trachoma MESHD as a public health problem could be accelerated.

    Detecting COVID-19 MESHD infection hotspots in England using large-scale self-reported data from a mobile application

    Authors: Thomas Varsavsky; Mark S Graham; Liane S Canas; Sajaysurya Ganesh; Joan Capdevila Puyol; Carole H Sudre; Benjamin Murray; Marc Modat; M. Jorge Cardoso; Christina M Astley; David A Drew; Long H Nguyen; Tove Fall; Maria F Gomez; Paul W Franks; Andrew T Chan; Richard Davies; Jonathan Wolf; Claire J Steves; Tim D Spector; Sebastien Ourselin

    doi:10.1101/2020.10.26.20219659 Date: 2020-10-27 Source: medRxiv

    Background As many countries seek to slow the spread of COVID-19 MESHD without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. Methods We performed modelling on longitudinal, self-reported data from users of the COVID Symptom Study app in England between 24 March and 29 September, 2020. Combining a symptom-based predictive model for COVID-19 MESHD positivity and RT-PCR tests provided by the Department of Health we were able to estimate disease incidence, prevalence SERO and effective reproduction number TRANS. Geographically granular estimates were used to highlight regions with rapidly increasing case numbers, or hotspots. Findings More than 2.6 million app users in England provided 115 million daily reports of their symptoms, and recorded the results of 170,000 PCR tests. On a national level our estimates of incidence and prevalence SERO showed similar sensitivity SERO to changes as two national community surveys: the ONS and REACT studies. On a geographically granular level, our estimates were able to highlight regions before they were subject to local government lockdowns. Between 12 May and 29 September we were able to flag between 35-80% of regions appearing in the Government's hotspot list. Interpretation Self-reported data from mobile applications can provide a cost-effective and agile resource to inform a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance.

    High and increasing prevalence SERO of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report

    Authors: Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott

    doi:10.1101/2020.10.12.20211227 Date: 2020-10-14 Source: medRxiv

    Background REACT-1 is quantifying prevalence SERO of SARS-CoV-2 infection MESHD among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report. Methods Representative samples of the population aged TRANS 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence SERO of PCR-confirmed SARS-CoV-2 infection MESHD, estimation of reproduction number TRANS (R) and time trends between and within rounds using exponential growth or decay models. Results 175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence SERO of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence SERO is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands. Conclusion Rapid growth has led to high prevalence SERO of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence SERO has increased in all age groups TRANS, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19 MESHD.

    Evaluating the impact of curfews and other measures on SARS-CoV-2 transmission TRANS in French Guiana

    Authors: Alessio Andronico; Cecile Tran Kiem; Juliette Paireau; Tiphanie Succo; Paolo Bosetti; Noemie Lefrancq; Mathieu Nacher; Felix Djossou; Alice Sanna; Claude Flamand; Henrik Salje; Cyril Rousseau; Simon Cauchemez; James Kinross; Zoltan Takats; Siham Seid Ali

    doi:10.1101/2020.10.07.20208314 Date: 2020-10-12 Source: medRxiv

    While general lockdowns have proven effective to control SARS-CoV-2 epidemics, they come with enormous costs for society. It is therefore essential to identify control strategies with lower social and economic impact. Here, we report and evaluate the control strategy implemented during a large SARS-CoV-2 epidemic in June-July 2020 in French Guiana that relied on curfews, targeted lockdowns and other measures. We find that the combination of these interventions reduced the basic reproduction number TRANS of SARS-CoV-2 from 1.7 to 1.1, which was sufficient to avoid saturation of hospitals. We estimate that thanks to the young demographics across the territory, the risk of hospitalisation following infection was 0.3 times that of metropolitan France and that about 20% of the population was infected by July. Our model projections are consistent with a recent seroprevalence SERO study. The study showcases how mathematical modeling can be used to support healthcare planning and decision making in a context of high uncertainty.

    Successive Waves of COVID 19: Confinement Effects on Virus- Prevalence SERO with a Mathematical Model

    Authors: Soliman Abdalla; Duaa Bakhshwain; Waleed Shirbeeny; Ahmad Bakhshwain; Fatema Bahabri; Abdulaziz Bakhshwin; Samar Alsagaf

    doi:10.21203/ Date: 2020-10-05 Source: ResearchSquare

    Background A pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (COVID 19) incidence data are largely available online. Until August 17, COVID 19 has hit more than 22 million individuals all over the globe. So, it is urged to get clear information about the prevalence SERO of the virus. Therefore, one can manipulate easily a suitable mathematical model to fit these published data. Methods We propose a mathematical model that considers the total population, in 25 countries, either infected by COVID-19 MESHD or confined (safe) during the period from November 17, 2019, to August 17, 2020. The model considers the total population as a complex number; the imaginary part is the number of infected individuals and the real part is the number of confined individuals. This classification combined with mathematical treatments leads to a transmission TRANS dynamics of the virus to be as wave-like motion. The virus can hit any country either by one wave or by successive waves (up to eleven waves). Findings We find net discrimination between the twenty-five countries investigated in this report. The immediate response to the first attack is a substantial parameter to determine whether the epidemic attack will be in one wave or it can be in successive waves. For example, the best case such as individuals in China was hit by one wave while the individuals in the USA were attacked by nine waves; it the worst case all over the globe. In addition, the model differentiates between the daily reproduction numbers TRANS (Rd0) and the median reproduction number TRANS ( R0 TRANS). We have found that Rd0 decreases exponentially with time from high values down to zero at the wave maximum point; and R0 TRANS varies from a country to another. For example, the virus hit individuals in Germany in R0 TRANS = 1·39 (96% CI 1·01–3·87) and in the USA R0 TRANS = 3·81 (91% CI 1·71–5·15). We have found that twice the virus has hit both the USA and Iran. The great protestation of black matter lives in the USA and the great assemblage of the new Iranian year, on March 21, 2020, have been the cause of the second epidemic attack in both countries.Interpretation Our results show that COVID-19 MESHD transmission TRANS depends on the prompt reaction against the first viral-wave. The reaction depends on both the social behaviour of individuals and on the swift system-decision by the governmental decision maker (s). The Chinese strictly follow the decision-maker and therefore the virus hit by only one wave; while in the USA, the system-decision was different and the American-responses were different, therefore ten waves followed the first wave.

    High prevalence SERO of SARS-CoV-2 swab positivity in England during September 2020: interim report of round 5 of REACT-1 study

    Authors: Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E. Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott

    doi:10.1101/2020.09.30.20204727 Date: 2020-10-02 Source: medRxiv

    Background: REACT-1 is a community survey of PCR confirmed swab-positivity for SARS-CoV-2 among random samples of the population in England. This interim report includes data from the fifth round of data collection currently underway for swabs sampled from the 18th to 26th September 2020. Methods: Repeated cross-sectional surveys of random samples of the population aged TRANS 5 years and over in England with sample size ranging from 120,000 to 160,000 people in each round of data collection. Collection of self-administered nose and throat swab for PCR and questionnaire data. Prevalence SERO of swab-positivity by round and by demographic variables including age TRANS, sex, region, ethnicity. Estimation of reproduction number TRANS (R) between and within rounds, and time trends using exponential growth or decay model. Assessment of geographical clustering based on boundary-free spatial model. Results: Over the 9 days for which data are available, we find 363 positives from 84,610 samples giving a weighted prevalence SERO to date of 0.55% (0.47%, 0.64%) in round 5. This implies that 411,000 (351,000, 478,000) people in England are virus-positive under the assumption that the swab assay is 75% sensitive. Using data from the most recent two rounds, we estimate a doubling time of 10.6 (9.4, 12.0) days covering the period 20th August to 26th September, corresponding to a reproduction number TRANS R of 1.47 (1.40, 1.53). Using data only from round 5 we estimate a reproduction number TRANS of 1.06 (0.74, 1.46) with probability of 63% that R is greater than 1. Between rounds 4 and 5 there was a marked increase in unweighted prevalence SERO at all ages TRANS. In the most recent data, prevalence SERO was highest in the 18 to 24 yrs age group TRANS at 0.96% (0.68%, 1.36%). At 65+ yrs prevalence SERO increased ~7-fold between rounds 4 and 5 from 0.04% (0.03%, 0.07%) to 0.29% (0.23%, 0.37%). Prevalence SERO increased in all regions between rounds 4 and 5, giving the highest unweighted prevalence SERO in round 5 in the North West at 0.86% (0.69%, 1.06%). In London, prevalence SERO increased ~5-fold from 0.10% (0.06%, 0.17%) to 0.49% (0.36%, 0.68%). Regional R values TRANS ranged from 1.32 (1.16,1.50) in Yorkshire and the Humber to 1.63 (1.42, 1.88) in the East Midlands over the same period. In the most recent data, there was extensive clustering in the North West, Midlands and in and around London with pockets of clustering in other regions including the South West, North East and East of England. Odds of swab-positivity were ~2-fold higher in people of Asian and Black ethnicity compared with white participants. Conclusion: Rapid growth has led to high prevalence SERO of SARS-CoV-2 virus in England among all regions and age groups TRANS, including those age groups TRANS at highest risk. Although there is evidence of a recent deceleration in the epidemic, current levels of prevalence SERO will inevitably result in additional hospitalisations and mortality in coming weeks. A re-doubling of public health efforts is needed to return to a declining phase of the epidemic.

    Exploring COVID-19 MESHD Daily Records of Diagnosed Cases and Fatalities Based on Simple Non-parametric Methods

    Authors: Hans H. Diebner; Nina Timmesfeld

    id:10.20944/preprints202009.0628.v1 Date: 2020-09-26 Source:

    Based on comprehensible non-parametric methods, estimates of crucial parameters that characterise the COVID-19 MESHD pandemic with a focus on the German epidemic are presented. Where appropriate, the estimates for Germany are compared with the results for six other countries (FR, IT, US, UK, ES, CH) to get an idea of the breadth of applicability and a relational understanding. Thereby, only prevalence SERO data of daily reported new counts of diagnosed cases and fatalities provided by the ECDC are used. Where appropriate, the results are compared with conclusions drawn from using the dataset provided by the RKI. Drawing on uncertain a priori knowledge is avoided. Specifically, we present estimates for the duration from diagnosis to death MESHD being 13 days for Germany and about 2 days for Italy as the extremes. Furthermore, based on the knowledge of this time lag between diagnoses and deaths, properly delayed asymptotic TRANS as well as instantaneous fatality-case ratios are calculated having superiority compared to the commonly published case-fatality rate. The median of the time series of the instantaneous fatality-case ratio with proper delay of 13-days between cases and deaths for Germany turns out to be 0.024. Asymptotic TRANS values are presented for other countries with France ranking highest with a fatality-case ratio of almost 0.2 at its peak. The basic reproduction number TRANS, R_0 TRANS, for Germany is estimated to be between 2.4 and 3.4. The uncertainty stems from uncertain knowledge of the generation time. A delay autocorrelation shows resonances at about 4 days and 7 days, where the latter resonance is at least partially attributable to the sampling process with weekly periodicity. The calculation of the basic reproduction number TRANS is based on an evaluation of cumulative numbers of cases yielding time-dependent doubling times as an intermediate step. This allows to infer to the reproduction number TRANS during the early phase of onset of the epidemic. In a second approach, the instantaneous basic reproduction number TRANS is derived from the incident (counts of new) cases and allows, in contrast to the first version, to infer to the temporal behaviour of the reproduction number TRANS during the later epidemic course. To conclude, by avoiding complicated parametric models we provide insights into basic features of the COVID-19 MESHD epidemic in an utmost transparent and comprehensible way.

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MeSH Disease

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