By simply separating out weekly reporting variability, the long-term death rate profile becomes clear, and its peak can be located with confidence. Using the distribution of times from disease onset to death, it is possible to extend the model to infer the time course of fatal infections required to produce the later deaths. Because of the wide variability in onset to death times, a quite sharply peaked infection curve produces a death curve that declines only slowly. The inferred infection curve peaks a few days before lockdown, with fatal infections now likely to be occurring at a much-reduced rate.
Diagram shows the inferred time course of the number of fatal infections, where day 0 is March 13th. The continuous curve is the median estimate. The dashed curves delimit 80% and 95% credible intervals. The vertical grey line shows day of lock down. The overlaid scaled bar chart summarizes the probability distribution for the day of the infection peak.
However, new research from Johns Hopkins University (MD, USA) has found that the chance of these tests giving a false negative – stating no infection when the individual actually is infected – is greater than 1 in 5, at times being far higher. The study, which analyzed seven previously published studies that evaluated RT-PCR performance, calls into question the accuracy of the predictive value of such tests.
The way the data are analysed and presented currently gives them limited value for the first purpose [of understanding the epidemic]. The aim seems to be to show the largest possible number of tests, even at the expense of understanding. It is also hard to believe the statistics work to support the testing programme itself. The statistics and analysis serve neither purpose well.
Masks and respirators do not work. There have been extensive randomized controlled trial (RCT) studies, and meta-analysis reviews of RCT studies, which all show that masks and respirators do not work to prevent respiratory influenza-like illnesses, or respiratory illnesses believed to be transmitted by droplets and aerosol particles. Furthermore, the relevant known physics and biology, which I review, are such that masks and respirators should not work. It would be a paradox if masks and respirators worked, given what we know about viral respiratory diseases: The main transmission path is long-residence-time aerosol particles (< 2.5 μm), which are too fine to be blocked, and the minimum-infective-dose is smaller than one aerosol particle. The present paper about masks illustrates the degree to which governments, the mainstream media, and institutional propagandists can decide to operate in a science vacuum, or select only incomplete science that serves their interests. Such recklessness is also certainly the case with the current global lockdown of over 1 billion people, an unprecedented experiment in medical and political history.
While news headlines might still be dominated by the healthcare issues around coronavirus – when they’re not about Dominic Cummings – new YouGov tracker data reveals that economic concerns have been quietly rising among the population.
In fact, Britons are now almost as likely to say that ‘the economy’ is one of the top three issues facing the country (61%) as they are to say ‘health’ (66%).
We searched the literature for estimates of individual variation in propensity to acquire or transmit COVID-19 or other infectious diseases and overlaid the findings as vertical lines in Figure 3. Most CV estimates are comprised between 2 and 4, a range where naturally acquired immunity to SARS-CoV-2 may place populations over the herd immunity threshold once as few as 10-20% of its individuals are immune.
There was no exponential growth in Covid-19 infections the UK. From the first days of the outbreak growth rates were in decline.
The following chart produced by financial strategist Alistair Haimes should put the above question to rest (compare it with the above chart).
The left hand side starts in March 2020 when the UK had had its first 300 infections and then stops at 10 April when Europe as a whole had reached a growth rate of zero or less. The chart is analogous to the above chart of interest rates. If you cannot distinguish the different colours and European countries don’t worry too much (UK is dark blue) as they all show the same overall pattern. The trends are all downwards, from start to finish.
In summary, all the 455 contacts were excluded from SARS-CoV-2 infection and we conclude that the infectivity of some asymptomatic SARS-CoV-2 carriers might be weak.
Injected influenza vaccines probably have a small protective effect against influenza and ILI (moderate-certainty evidence), as 71 people would need to be vaccinated to avoid one influenza case, and 29 would need to be vaccinated to avoid one case of ILI. Vaccination may have little or no appreciable effect on hospitalisations (low-certainty evidence) or number of working days lost.
The observation that the greatest reduction in COVID-19 cases was achieved under the combined [social distancing] intervention is not surprising. However, the assessment of the additional benefit of each intervention, when implemented in combination, offers valuable insight. Since each approach individually will result in considerable societal disruption, it is important to understand the extent of intervention needed to reduce transmission and disease burden.
The effectiveness and societal impact of quarantine and social distancing will depend on the credibility of public health authorities, political leaders, and institutions. It is important that policy makers maintain the public’s trust through use of evidence-based interventions and fully transparent, fact-based communication.
Doctors have told The BMJ they are deeply concerned at the number of patients becoming infected with covid-19 in NHS hospitals in England and have called for more stringent infection control measures to combat its spread.
Introduction: An important unknown during the COVID-19 pandemic has been the infection-fatality rate (IFR). This differs from the case-fatality rate (CFR) as an estimate of the number of deaths as a proportion of the total number of cases, including those who are mild and asymptomatic. While the CFR is extremely valuable for experts, IFR is increasingly being called for by policy-makers and the lay public as an estimate of the overall mortality from COVID-19.
Results: After exclusions, there were 13 estimates of IFR included in the final meta-analysis, from a wide range of countries, published between February and April 2020. The meta-analysis demonstrated a point-estimate of IFR of 0.75% (0.49-1.01%) with significant heterogeneity (p<0.001).
Conclusion: Based on a systematic review and meta-analysis of published evidence on COVID-19 until the end of April, 2020, the IFR of the disease across populations is 0.75% (0.49-1.01%). However, due to very high heterogeneity in the meta-analysis, it is difficult to know if this represents the “true” point estimate.
We randomized 115 children to trivalent inactivated influenza vaccine (TIV) or placebo. Over the following 9 months, TIV recipients had an increased risk of virologically-confirmed non-influenza infections (relative risk: 4.40; 95% confidence interval: 1.31-14.8). Being protected against influenza, TIV recipients may lack temporary non-specific immunity that protected against other respiratory viruses.
In the prepandemic period of our study, we did not observe a statistically significant reduction in confirmed seasonal influenza virus infections in the TIV recipients (Table 3), although serological evidence (Supplementary Appendix) and point estimates of vaccine efficacy based on confirmed infections were consistent with protection of TIV recipients against the seasonal influenza viruses that circulated from January through March 2009 [16]. We identified a statistically significant increased risk of noninfluenza respiratory virus infection among TIV recipients (Table 3), including significant increases in the risk of rhinovirus and coxsackie/echovirus infection, which were most frequently detected in March 2009, immediately after the peak in seasonal influenza activity in February 2009 (Figure 1).
The key findings are that <50% of participants were adherent with mask use and that the intention-to-treat analysis showed no difference between arms. Although our study suggests that community use of face masks is unlikely to be an effective control policy for seasonal respiratory diseases, adherent mask users had a significant reduction in the risk for clinical infection. Another recent study that examined the use of surgical masks and handwashing for the prevention of influenza transmission also found no significant difference between the intervention arms.
The virus is thought to spread mainly from person-to-person.
Between people who are in close contact with one another (within about 6 feet).
Through respiratory droplets produced when an infected person coughs, sneezes, or talks.
These droplets can land in the mouths or noses of people who are nearby or possibly be inhaled into the lungs.
COVID-19 may be spread by people who are not showing symptoms.
The virus spreads easily between people
How easily a virus spreads from person-to-person can vary. Some viruses are highly contagious, like measles, while other viruses do not spread as easily. Another factor is whether the spread is sustained, which means it goes from person-to-person without stopping.
The virus that causes COVID-19 is spreading very easily and sustainably between people. Information from the ongoing COVID-19 pandemic suggest that this virus is spreading more efficiently than influenza, but not as efficiently as measles, which is highly contagious.
The virus does not spread easily in other ways
COVID-19 is a new disease and we are still learning about how it spreads. It may be possible for COVID-19 to spread in other ways, but these are not thought to be the main ways the virus spreads.
From touching surfaces or objects. It may be possible that a person can get COVID-19 by touching a surface or object that has the virus on it and then touching their own mouth, nose, or possibly their eyes. This is not thought to be the main way the virus spreads, but we are still learning more about this virus.
From animals to people. At this time, the risk of COVID-19 spreading from animals to people is considered to be low. Learn about COVID-19 and pets and other animals.
From people to animals. It appears that the virus that causes COVID-19 can spread from people to animals in some situations. CDC is aware of a small number of pets worldwide, including cats and dogs, reported to be infected with the virus that causes COVID-19, mostly after close contact with people with COVID-19. Learn what you should do if you have pets.
Letter dated 17 March 2020 to Chief executives of all NHS trusts and foundation trusts.
ANNEX: CORONAVIRUS COST REIMBURSEMENT This guidance sets out the amended financial arrangements for the NHS for the period between 1 April and 31 July. These changes will enable the NHS and partner organisations (including Local Authorities and the Independent Sector) to respond to COVID-19. We will continue to revise this guidance to reflect operational changes and feedback from the service as the response develops.
We will shortly be making a payment on account to all acute and ambulance providers to cover the costs of COVID-19-related work done so far this year, with final costs for the current financial year being confirmed as part of the year end processes. This initial payment will be based on information already submitted by providers. Future payments will be based on further cost submissions.
All NHS providers and commissioners must carefully record the costs incurred in responding to the outbreak and will be required to report actual costs incurred on a monthly basis. Accurate record keeping during this time is crucial – record keeping must meet the requirements of external audit, and public and Parliamentary scrutiny.
To support reimbursement and track expenditure we will in due course be asking all relevant organisations to provide best estimates of expected costs from now until the expected end of the peak outbreak. We will provide further guidance with relevant assumptions in order to support you in making these estimates.
Covid-19 appearance and fast spreading took by surprise the international community. Collaboration between researchers, public health workers and politicians has been established to deal with the epidemic. One important contribution from researchers in epidemiology is the analysis of trends so that both current state and short-term future trends can be carefully evaluated. Gompertz model has shown to correctly describe the dynamics of cumulative confirmed cases, since it is characterized by a decrease in growth rate that is able to show the effect of control measures. Thus, it provides a way to systematically quantify the Covid-19 spreading velocity. Moreover, it allows to carry out short-term predictions and long-term estimations that may facilitate policy decisions and the revision of in-place confinement measures and the development of new protocols. This model has been employed to fit the cumulative cases of Covid-19 from several Chinese provinces and from other countries with a successful containment of the disease. Results show that there are systematic differences in spreading velocity between countries. In countries that are in the initial stages of the Covid-19 outbreak, model predictions provide a reliable picture of its short-term evolution and may permit to unveil some characteristics of the long-term evolution. These predictions can also be generalized to short-term hospital and Intensive Care Units (ICU) requirements, which together with the equivalent predictions on mortality provide key information for health officials.
When faced with danger, humans draw closer together. Social distancing thwarts this impulse. Professor Ophelia Deroy from Ludwigs-Maximilians Universitaet in Munich (LMU) and colleagues argue that this dilemma poses a greater threat to society than overtly antisocial behavior.
Although R0 might appear to be a simple measure that can be used to determine infectious disease transmission dynamics and the threats that new outbreaks pose to the public health, the definition, calculation, and interpretation of R0 are anything but simple. R0 remains a valuable epidemiologic concept, but the expanded use of R0 in both the scientific literature and the popular press appears to have enabled some misunderstandings to propagate. R0 is an estimate of contagiousness that is a function of human behavior and biological characteristics of pathogens. R0 is not a measure of the severity of an infectious disease or the rapidity of a pathogen’s spread through a population. R0 values are nearly always estimated from mathematical models, and the estimated values are dependent on numerous decisions made in the modeling process. The contagiousness of different historic, emerging, and reemerging infectious agents cannot be fairly compared without recalculating R0 with the same modeling assumptions. Some of the R0 values commonly reported in the literature for past epidemics might not be valid for outbreaks of the same infectious disease today.
R0 can be misrepresented, misinterpreted, and misapplied in a variety of ways that distort the metric’s true meaning and value. Because of these various sources of confusion, R0 must be applied and discussed with caution in research and practice. This epidemiologic construct will only remain valuable and relevant when used and interpreted correctly.
Don’t Forget The Bubbles — a blog for medical professionals specializing in pediatrics — partnered with the UK Royal College of Pediatrics and Child Health to track and review studies on COVID-19 in children, according to its website. Using research from 78 of those studies, it released a 45-page report on April 22 that extracts early findings on the epidemiology, transmission and symptoms of the coronavirus in children.
Conclusion:
The role of children in transmission is unclear, but it seems likely they do not play a significant role.
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