### Overview

MeSH Disease

Disease (220)

Infections (191)

Death (113)

Human Phenotype

Falls (18)

Pneumonia (11)

Cough (7)

Fever (6)

Transmission

Seroprevalence
displaying 1 - 10 records in total 453
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### The effect of public health policies in the transmission TRANS of COVID-19 for South American countries

Authors: Bryan Valcarcel; Jose L Avilez; J. Smith Torres-Roman; Julio A Poterico; Janina Bazalar-Palacios; Carlo La Vecchia

doi:10.1101/2020.08.09.20149286 Date: 2020-08-12 Source: medRxiv

Objectives: The analysis of transmission TRANS dynamics is crucial to determine whether mitigation or suppression measures reduce the spread of Coronavirus disease MESHD 2019 (COVID-19). This study sought to estimate the basic ( R0 TRANS) and time-dependent (Rt) reproduction number TRANS of COVID-19 and contrast the public health measures for ten South American countries. Methods: Data was obtained from the European Centre for Disease MESHD Prevention and Control. Country-specific R0 TRANS estimates during the first two weeks of the outbreak and Rt estimates after 90 days were estimated. Results: Countries used a combination of isolation, social distancing, quarantine, and community-wide containment measures to contain the spread of COVID-19 at different points in time. R0 TRANS ranged from 1.52 (95% confidence interval: 1.13-1.99) in Venezuela, to 3.83 (3.04-4.75) in Chile, whereas Rt, after 90 days, ranged from 0.71 (95% credible interval: 0.39-1.05) in Uruguay to 1.20 (1.19-1.20) in Brazil. Different R0 TRANS and Rt values may be related to the testing capacity of each country. Conclusion: R0 TRANS in the early phase of the outbreak varied across the South American countries. The adopted public health measures in the initial period of the pandemic appear to have reduced Rt over time in each country.

### The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission TRANS across 130 countries and territories

Authors: Yang Liu; Christian Morgenstern; James Kelly; Rachel Lowe; - CMMID COVID-19 Working Group; Mark Jit

doi:10.1101/2020.08.11.20172643 Date: 2020-08-12 Source: medRxiv

Introduction: Non-pharmaceutical interventions (NPIs) are used to reduce transmission TRANS of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease MESHD 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel TRANS restrictions, economic measures, and health system actions on SARS-CoV-2 transmission TRANS in 130 countries and territories. Methods: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission TRANS with data from January - June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number TRANS (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g., restrictions on 1000+ people gathering were not effective, restrictions on <10 people gathering was). Evidence supporting the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel TRANS controls, testing, contact tracing TRANS) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Conclusion: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission TRANS is complicated by temporal clustering, time-dependent variation in effects and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications taking into account these effects, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many although not all the actions policy-makers are taking to respond to the COVID-19 pandemic.

### Effective reproduction number TRANS for COVID-19 in Aotearoa New Zealand

Authors: Rachelle N Binny; Audrey Lustig; Ann Brower; Shaun C Hendy; Alex James; Matthew Parry; Michael J Plank; Nicholas Steyn

doi:10.1101/2020.08.10.20172320 Date: 2020-08-11 Source: medRxiv

The effective reproduction number TRANS, Reff, is the average number of secondary cases TRANS infected by a primary case TRANS, a key measure of the transmission TRANS potential for a disease MESHD. Compared to many countries, New Zealand has had relatively few COVID-19 cases, many of which were caused by infections MESHD acquired overseas. This makes it difficult to use standard methods to estimate Reff. In this work, we use a stochastic model to simulate COVID-19 spread in New Zealand and report the values of Reff from simulations that gave best fit to case data. We estimate that New Zealand had an effective reproduction number TRANS Reff = 1.8 for COVID-19 transmission TRANS prior to moving into Alert Level 4 on March 25 2020 and that after moving into Alert level 4 this was reduced to Reff = 0.35. Our estimate Reff = 1.8 for reproduction number TRANS before Alert Level 4, is relatively low compared to other countries. This could be due, in part, to measures put in place in early- to mid-March, including: the cancellation of mass gatherings, the isolation of international arrivals, and employees being encouraged to work from home.

### 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.

### Mathematical Modelling of COVID-19 Pandemic with Demographic Effects

Authors: Abdul Alimamy Kamara; Lagès N. Mouanguissa; Godfrey Barasa

doi:10.21203/rs.3.rs-56595/v1 Date: 2020-08-10 Source: ResearchSquare

In this paper, an asymptomatic infection MESHD asymptomatic TRANS transmission TRANS Susceptible-Exposed-Infectious-Recovered (SEIR) model with demographic effects is used to understand the dynamics of the COVID-19 pandemics. We calculate the basic reproduction number TRANS ( R0 TRANS), and prove the global stability of the model by solving the differential equations of the model using the disease MESHD-free equilibrium (DFE) and endemic equilibrium (EE) equations, respectively. We showed that when the R0 TRANS less than one or less than and equal to one, and greater than one or greater than and equal to one the DFE and EE asymptotic TRANS stability exist theoretically and numerically, respectively. We also demonstrate the detrimental impact of the direct and asymptomatic infections MESHD asymptomatic TRANS for the COVID-19 pandemic.

### How Efficient is Contact Tracing TRANS in Mitigating the Spread of Covid-19? A Mathematical Modeling Approach

Authors: T. A. Biala; Y. O. Afolabi; A. Q. M. Khaliq

id:2008.03859v1 Date: 2020-08-10 Source: arXiv

Contact Tracing TRANS (CT) is one of the measures taken by government and health officials to mitigate the spread of the novel coronavirus. In this paper, we investigate its efficacy by developing a compartmental model for assessing its impact on mitigating the spread of the virus. We describe the impact on the reproduction number TRANS $\mathcal{R}_c$ of Covid-19. In particular, we discuss the importance and relevance of parameters of the model such as the number of reported cases, effectiveness of tracking and monitoring policy, and the transmission TRANS rates to contact tracing TRANS. We describe the terms perfect tracking'', perfect monitoring'' and perfect reporting'' to indicate that traced contacts TRANS will be tracked while incubating, tracked contacts are efficiently monitored so that they do not cause secondary infections MESHD, and all infected persons are reported, respectively. We consider three special scenarios: (1) perfect monitoring and perfect tracking of contacts of a reported case, (2) perfect reporting of cases and perfect monitoring of tracked reported cases and (3) perfect reporting and perfect tracking of contacts of reported cases. Furthermore, we gave a lower bound on the proportion of contacts to be traced TRANS to ensure that the effective reproduction, $\mathcal{R}_c$, is below one and describe $\mathcal{R}_c$ in terms of observable quantities such as the proportion of reported and traced TRANS cases. Model simulations using the Covid-19 data obtained from John Hopkins University for some selected states in the US suggest that even late intervention of CT may reasonably reduce the transmission TRANS of Covid-19 and reduce peak hospitalizations and deaths MESHD. In particular, our findings suggest that effective monitoring policy of tracked cases and tracking of traced contacts TRANS while incubating are more crucial than tracing TRANS more contacts.

### COVID-19 in South Asia: Real-time monitoring of reproduction and case fatality rate

Authors: Fakhar Mustafa; Rehan Ahmed Khan Sherwani; Syed Salman Saqlain; Muhammad Asad Meraj; Haseeb ur Rehman; Rida Ayyaz

id:2008.04347v1 Date: 2020-08-10 Source: arXiv

As the ravages caused by COVID-19 pandemic are becoming inevitable with every moment, monitoring and understanding of transmission TRANS and fatality rate has become even more paramount for containing its spread. The key purpose of this analysis is to report the real-time effective reproduction rate ($R_t$ ) and case fatality rates (CFR) of COVID-19 in South Asia region. Data for this study are extracted from JHU CSSE COVID-19 Data source up to July 31, 2020. $R_t$ is estimated using exponential growth and time-dependent methods. R0 TRANS package in R-language is employed to estimate $R_t$ by fitting the existing epidemic curve. Case fatality rate is estimated by using Naive and Kaplan-Meier methods. Owing to exponential increase in cases of COVID-19, the pandemic will ensue in India, Maldives and in Nepal as $R_t$ was estimated greater than 1 for these countries. Although case fatality rates are found lesser as compared to other highly affected regions in the world, strict monitoring of deaths MESHD for better health facilities and care of patients is emphasized. More regional level cooperation and efforts are the need of time to minimize the detrimental effects of the virus.

### Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission TRANS and super-spreading events

Authors: Ashish Goyal; Daniel B Reeves; E. Fabian Cardozo-Ojeda; Joshua T Schiffer; Bryan T. Mayer

doi:10.1101/2020.08.07.20169920 Date: 2020-08-07 Source: medRxiv

SARS-CoV-2 is difficult to contain because most transmissions TRANS occur during the pre-symptomatic phase of infection MESHD. Moreover, in contrast to influenza, while most SARS-CoV-2 infected people do not transmit the virus to anybody, a small percentage secondarily infect large numbers of people. We designed mathematical models of SARS-CoV-2 and influenza which link observed viral shedding patterns with key epidemiologic features of each virus, including distributions of the number of secondary cases TRANS attributed to each infected person (individual R0 TRANS) and the duration between symptom onset TRANS in the transmitter and secondarily infected person ( serial interval TRANS). We identify that people with SARS-CoV-2 or influenza infections MESHD are usually contagious for fewer than two days congruent with peak viral load several days after infection MESHD, and that transmission TRANS is unlikely below a certain viral load. SARS-CoV-2 super-spreader events with over 10 secondary infections MESHD occur when an infected person is briefly shedding at a very high viral load and has a high concurrent number of exposed contacts. The higher predisposition of SARS-CoV-2 towards super-spreading events is not due to its 1-2 additional weeks of viral shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks than a person infected with influenza, likely due to aerosolization of virus. Our results support policies that limit crowd size in indoor spaces and provide viral load benchmarks for infection MESHD control and therapeutic interventions intended to prevent secondary transmission TRANS.

### Genomic epidemiology reveals transmission TRANS patterns and dynamics of SARS-CoV-2 in Aotearoa New Zealand

Authors: Jemma L Geoghegan; Xiaoyun Ren; Matthew Storey; James Hadfield; Lauren Jelley; Sarah Jefferies; Jill Sherwood; Shevaun Paine; Sue Huang; Jordan Douglas; Fabio K L Mendes; Andrew Sporle; Michael G Baker; David R Murdoch; Nigel French; Colin R Simpson; David Welch; Alexei J Drummond; Edward C Holmes; Sebastian Duchene; Joep de Ligt

doi:10.1101/2020.08.05.20168930 Date: 2020-08-06 Source: medRxiv

New Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nation-wide lockdown of all non-essential services to curb the spread of COVID-19. New Zealand has now effectively eliminated the virus, with low numbers of new cases limited to new arrivals in managed quarantine facilities at the border. Here, we generated 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected between 26 February and 22 May 2020, representing 56% of all confirmed cases TRANS in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. The proportion of D614G variants in the virus spike protein increased over time due to an increase in their importation frequency, rather than selection within New Zealand. These data also helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number TRANS, Re, of New Zealand's largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in a transmission TRANS lineage of more than one additional case. Most of the cases that resulted in a transmission TRANS lineage originated from North America, rather than from Asia where the virus first emerged or from the nearest geographical neighbour, Australia. Genomic data also helped link more infections MESHD to a major transmission TRANS cluster than through epidemiological data alone, providing probable sources of infections MESHD for cases in which the source was unclear. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease MESHD mitigation.

### Inhomogeneous mixing and asynchronic transmission TRANS between local outbreaks account for the spread of COVID-19 epidemics

Authors: Carlos I Mendoza

doi:10.1101/2020.08.04.20168443 Date: 2020-08-06 Source: medRxiv

The ongoing epidemic of COVID-19 originated in China has reinforced the need to develop epidemiological models capable of describing the progression of the disease MESHD to be of use in the formulation of mitigation policies. Here, this problem is addressed using a metapopulation approach to show that the delay in the transmission TRANS of the spread between different subsets of the total population, can be incorporated into a SIR framework through a time-dependent transmission TRANS rate. Thus, the reproduction number TRANS decreases with time despite the population dynamics remains uniform and the depletion of susceptible individuals is small. The obtained results are consistent with the early subexponential growth observed in the cumulated number of confirmed cases TRANS even in the absence of containment measures. We validate our model by describing the evolution of the COVID-19 using real data from different countries with an emphasis in the case of Mexico and show that it describes correctly also the long-time dynamics of the spread. The proposed model yet simple is successful at describing the onset and progression of the outbreak and considerably improves accuracy of predictions over traditional compartmental models. The insights given here may probe be useful to forecast the extent of the public health risks of epidemics and thus improving public policy-making aimed at reducing such risks.

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 All None MeSH Disease Human Phenotype Transmission Seroprevalence

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