Summaries by Irina Yakutenko
Writer and Science Journalist
https://m.facebook.com/irina.yakutenko

Episode 62
Released 27 October 2020

Complete transcript is here

  1. Number of incidences is not the best parameter to control the epidemics. It makes much more sense to keep track of the number of incidents among people who are older than 50 or 60. They are the ones who most often end up in hospital, therefore this parameter most reliably predicts the dynamics of filling the wards.
  2. It is believed that only few people get infected in public transport and supermarkets. But this idea can be deceiving. In fact, if someone caught the virus in a bus, in a supermarket or in a restaurant, it’s very hard to determine that. Such cases are counted as infections from an unknown source – in Germany these unknown cases sum up to three thirds of all cases.
  3. As COVID-19 spreads predominantly in clusters, “classic” contact tracing could be inefficient. Each infected individual with a probability of 80% does not infect anyone; trying to reach all his or her contacts we waste time and money – especially considering that this procedure does not work very well altogether. But there is another approach – namely, to try to determine the clusters in which the infection occurred. By doing this, we will immediately identify many more people who could be infected. These are the people who belong to this cluster and they should be immediately isolated.
  4. Cluster tracing, however, faces a lot of technical problems. To prevent virus spreading healthcare officers have to isolate the whole cluster immediately (for example, the whole office) – but they do not always have the authority to do this. Especially considering that most people who belong to this cluster would likely feel good and refuse to isolate. It seems logical to send them all for testing – but this is the wrong strategy as testing takes time. And in the case of infectious cluster we don’t have it. These people can be contagious right now and they need to be isolated right now, not in three to five days, when tests are ready. Luckily, at the moment we have a solution to this problem, and that solution is rapid antigen tests. Even if a couple of people have positive results, this will be a reason to consider this office a cluster and send everyone to self-isolation.
  5. Prof. Drosten and radio hostess discussed a small interesting research from RKI physics Dirk Brockmann (http://rocs.hu-berlin.de/contact-reduction-tutorial/#/). He made a model to count how many variants of infectious chains could exist in a group of 36 people depending on the size of the subgroups which it will be divided into. In a whole group of 36 people there are 1260 ways of infection transmission. If we divide it in half, there are 51,4% less variants. If we divide the big group into nine parts of four people, number of possible transmission ways is reduced by 91,4%. In other words, if there is a superspreader in a group – for example a yoga class – when all the people train together, he can infect all 36 of them. When we divide this class into parts, he can infect only the people in his subgroup. This example shows once again that strategies that involve separation of large groups of people into smaller ones work. Even if it’s a plastic screen between tables in school class or dividing the class in halves when one of them study in the morning and another one – in the afternoon.
  6. Another working strategy that emerges from this work is dividing people into so called social bubbles. It’s impossible to prevent people from communication completely, but each family can choose which other familyor a couple of families it wants to constantly communicate with. People belonging to these families form a social bubble and can freely communicate with each other during the whole quarantine time. They can go out together, help to look after kids etc. The obvious weakness of this approach is that it does not work when schools are open.
  7. Another concept Prof. Drosten and radio hostess discussed is preventive lockdown (“circuit breaker”, or precautionary breaks). This concept implies that when number of new cases rises dangerously but not yet critically, the government announces a time-limited lockdown. It makes the announcement sufficient time in advance to give people and economy time to prepare. And such lockdown always has a predetermined duration. Time-limited lockdown works like a short press on the brake and can be applied regularly to slow down the spread of the epidemic. It’s very important to press the brake early enough because of the two to three weeks delay between contagion and hospitalization. Moreover, when the number of new cases is rather big, such short respite won’t be enough. And at all accounts circuit breaker is not a radical solution, but only a way to mitigate with less losses. Here is a preprint that describes strategies when precautionary breaks provide the biggest gains (https://www.medrxiv.org/content/10.1101/2020.10.13.20211813v1).
  8. Number of new cases in Germany is lower than in neighboring countries due to early restrictive measures implied in spring. 
  9. Another topic touched by Prof. Drosten was ADE. Recently there has been a new wave of discussions about this phenomenon stimulated by this paper (https://www.medrxiv.org/content/10.1101/2020.10.08.20209114v1). Using pseudovirus, authors investigated whether plasma taken from recovered COVID-19 patients can stimulate virus entry into cells in cultures. They showed that plasma from severe patients stimulated such a scenario in 76% of cells, and the one from mild cases – only in 8%. Authors worked with Raji cells, K562 cells and primary B cells that have a lot of receptors for Fc antibody fragment. However, the primary goal for SARS-CoV-2 is epithelial cells which don’t have such receptors. Macrophages and other immune cells do have them, but additional experiments are needed to prove if this effect takes place in these cells as well. Fears that ADE may appear as a result of vaccination also do not have good evidence as in this case a patient has antibodies before the SARS-CoV-2 would multiply enough and these antibodies won’t let the virus to do so.
  10. Another consideration regarding ADE: it is predominantly observed in vaccine experiments on animal models, and to be sure that vaccine really protects against the pathogen, researches give animals much more virus than they can get in reality. In this situation virus infects many more immune cells than in the case of natural disease.
  11. As in the early stages of infection SARS-CoV-2 enters mainly in the cells of the mucous membrane in nose and throat, to obtain sterilizing immunity we should possibly use a vaccine that is applied directly to mucous membrane to stimulate local immunity including IgA production. Vaccines that are injected in the muscle will probably protect more from severe disease but not from infection itself. And this means that at the first place they should be given to the people who belong to risk groups (people over 60, with diabetes, chronic lung diseases, high pressure etc.).

Episode 60
Released 14 October 2020

Complete transcript is here

  1. Prof. Drosten and radio hostess started with the discussion about epidemiological situation in Germany. When comparing to many other European countries we are going much better but anyway the number of new cases is growing rather fast. The dynamics is somewhat two weeks behind Germany’s neighbors. The bad sign is that we see new infection clusters in federal states where there are no big cities. That means that virus has spread all over and is not limited by places with high population density. Such situation makes it hard for politicians to implement restrictive measures as local actions are no more effective. To cope with the virus now government should implement measures that are obligatory for all citizens. That’s hard task by itself and now it’s even harder as population compliance has declined. People are tired of restrictions and don’t want to comply with them anymore. From the other hand, it’s very important to restrict virus spreading early. If politicians hesitate for too long, it will be too late, and situation will get out of control.
  2. Contact tracing statistics tells us two things. First – we have no idea where half of the infected people caught the virus. Possibly they did it on parties and meetings with friends and acquaintances. Second – we see that a lot of infections happened in clusters. That lead us to the idea of “contact diary”, that Prof. Drosten suggested in the episode 54. At the time of symptoms onset people simply don’t remember which possibly dangerous places they visited ten days ago. Writing down every evening the list of situations when many people were in limited space for a long period of time would not only make it easier to remember. Prof. Drosten hopes that with “contact diary” people will learn to avoid such situations. 
  3. Prof. Drosten also commented on the popular argument of the proponents of the Swedish model. There are two main counterarguments. First – it’s an illusion that we can effectively protect vulnerable groups without restrictive measures for the population as a whole. And second – among people without comorbidities and other risk factors there are those who would have severe disease. There are few of them, but without restrictive measures a lot of people will catch the virus simultaneously – including those unlucky guys. As a consequence, a lot of severely ill patients will get to ICU simultaneously and overwhelm health care capacities.
  4. Talking about appropriate testing strategy, Prof. Drosten also supported the scheme that includes rapid tests. This is especially important given that PCR tests will soon be in short supply (and in many places they already are).
  5. In episode 58 Prof. Drosten discussed a paper where authors concluded that pre-existing memory T-cells against SARS-CoV-2 could determine whether a patient would have severe COVID-19 (https://www.medrxiv.org/content/10.1101/2020.09.15.20188896v1.full.pdf). As these memory T-cells have low specificity and low avidity they could possibly worsen the course of the disease (because severe COVID-19 is associated with imbalanced and simultaneously too violent immune response). Now he told about another paper published in Science (https://science.sciencemag.org/content/370/6512/89) where authors came to somehow opposite conclusions. Like in the first paper, they also found out that many individuals who never met the new coronavirus nevertheless have SARS-CoV-2-reactive CD4+ T-cells. But here authors demonstrated that these T-cells are cross-reactive with comparable affinity to antigens of SARS-CoV-2 and common cold coronaviruses. This could possibly mean that common colds give us a protection against SARS-CoV-2, but additional experiments are necessary to state this for sure – especially considering that a different interpretation of these findings is also possible.
  6. Indian and American researchers published a paper where they described tracing of more than 400 thousand index patients and more than one million of their contacts (https://science.sciencemag.org/content/early/2020/09/29/science.abd7672). Main attention was paid to 85 thousand individuals and their close contacts for whom detailed documentation was available. On average, every infected person contacted with 7,3 other people, but 0,2% of index patients have more than 80 contacts. However, it was found that more than 70% of contacts didn’t end up with infections. These results demonstrated that in India, where implementation of restrictive measures is very limited and virus behaves more “naturally”, COVID-19 also spreads in clusters. In the study there was a sort of internal control that makes it possible to translate results from India to western countries. Authors assessed secondary attack rates for risky contacts (more than 15 minutes on close distance) and not so risky ones. They were found to be 11% and 5% respectively – and these values are more or less the same as in Europe. Another interesting finding from this study: in most cases, contagious individuals will infect people belonging to the same age group. That means that a lot of risky contacts occur not within the households but between them. People infect those with whom they contact during their social activities and not family life.
  7. At the very end Prof. Drosten discussed this famous D614G mutation that has spread very widely. It is very attractive to assume that D614G make it easier for coronavirus to be transmitted. However, it was shown that this mutation changes tissue specificity of the virus. Mutated virus replicated better in nose and upper respiratory tissues than in lungs. Furthermore, Ralph Baric group used hamster model to show that early after infection D614G variant transmits in droplets much faster than wild type virus (https://www.biorxiv.org/content/10.1101/2020.09.28.317685v1.full.pdf). Since the transmission of the SARS-CoV-2 mainly occurs with droplets from the upper respiratory tract, these results explain why D614G variant is so widespread.

Episode 59
Released 7 October 2020

Complete transcript is here

In this episode Prof. Ciesek and radio host discussed medical strategies, that were used to treat President Trump. Frau Ciesek expressed surprise by the choice of drugs and the timing they were prescribed. For example, remdesivir should be used early in the course of the disease and dexamethasone on the other hand is the drug for the cytokine stage. However, these two drugs were used almost simultaneously and moreover right after taking dexamethasone President Trump was discharged. But as you have thoroughly discussed all these issues on TWiV, I’ll mention only couple of things that you haven’t touched. 

  1. Regeneron. A mixture of two different monoclonal antibodies against two different spike epitopes. Prof. Ciesek emphasized that using a mixture could be beneficial as SARS-CoV-2 can mutate but it’s highly unlikely that mutation would alter both epitopes (here I dare to make a little comment: it depends on the mutual arrangement of epitopes and the mutation itself. The mutation can alter conformation of rather big protein fragment (in this case it’s RBD) and if epitopes are located in this particular region, they both could be changed. Cocktails are pretty good to prevent viral ‘escape’, but if the mutation is already there, they are not as effective. But, fortunately, at the moment we don’t see mutations that radically change RBD conformation). Such treatment can be successful, but it should be done early.
  2. Famotidin. It’s an H2-receptor inhibitor used against heartburn, gastrointestinal ulcers or reflux. Computer simulation showed that this substance could possibly inhibit SARS-CoV-2 protease (https://www.mdpi.com/2218-273X/10/6/954). It is also assumed that it can somehow modulate the immune system via histamine signaling pathway, although the exact mechanism is not clear. In one retrospective low-quality (10 patients on various disease stages without control group) study it was shown that famotidine improved condition of patients with COVID-19.
  3. Lopinavir/Ritonavir. This combination is used as anti-HIV drug. A lot of research demonstrated that it has no effect against COVID-19.
  4. Vitamin D. Several studies and at least one metaanalys (https://pubmed.ncbi.nlm.nih.gov/30675873/https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0239252) showed that vitamin D can possibly protect people from acute respiratory infections although the effect is not that big. Most likely explanation: if someone has vitamin D deficiency, supplements with this substance theoretically could help to prevent infection. If a person receives enough vitamin D, additional administration is unnecessary. The correlation found between lower vitamin D levels and the risk of severe illness can also be explained by the overlap of various risk factors (https://www.thelancet.com/journals/landia/article/PIIS2213-8587(20)30268-0/fulltext). For example, older people and people with obesity are more likely to have lower vitamin D levels than younger ones. And although some researchers hypothesize that vitamin D could have a direct effect on COVID-19 disease, at the moment there are no reliable studies to support this hypothesis. But some are planned now.
  5. Zinc. In experiments using animal models it has been shown, that zinc deficiency can impair the functioning of the immune system and particularly antiviral immunity. There are evidence, that zinc-deficient people are at higher risk of acquiring viral infections (https://academic.oup.com/advances/article/10/4/696/5476413). But zinc deficiency typically is not a problem in western countries as people there have (more or less) balanced diet. Moreover, it seems doubtful that zinc could be used directly as an antiviral due to concentration problems. In cell cultures zinc was effective in micromolar concentrations, whereas in human body zinc levels vary from picomolar to low nanomolar.
  6. Animal models for COVID-19. There are two of them: rhesus macaque for studying light course of the disease and manipulations in that time point and golden hamsters for studying severe cases.
  7. Frasu Ciesek mentioned, how many drug candidates fall out in the process of clinical trials. On average there are from 5000 to 10 000 unsuccessful attempts per one registered drug. And that means that average cost of developing one drug is somewhere between 300 million to one billion euro.

Episode 58
Released 30 September 2020

Complete transcript is here

  1. This episode can be named “Why do we die of coronavirus?” And the main answer to this question is “Because of age”. We already have a whole bunch of arguments for this assumption, but Prof. Drosten told about new and very good one. It is presented in preprint “Assessing the Age Specificity of Infection Fatality Rates for COVID-19: Systematic Review, Meta-Analysis, and Public Policy Implications” (https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v5.full.pdf). Authors collected, rated and investigated in detail all available papers that deal with COVID-19 deaths and age. They used very strict criteria for the research and national statistics left in final survey (just to mention, they threw away 948 papers from initial 962). Authors wanted to be sure that included patients that died of COVID-19 are the same patients that were counted as COVID-positive 3-5 weeks earlier. Usually in such types of research that is not the case and scientists count positives and died “in bulk”. Using data from remaining 14 research, authors calculated relationship between age and IFR (infection fatality rate) for COVID-19 and found out they are exponential. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.2% at age 75, and 14% at age 85. Authors also compare IFR for COVID-19 and for influenza and the results are astonishing: 0.8% versus 0.05%, 16 times more. Authors conclude that differences in the age structure of the population and the age-specific prevalence of COVID-19 explain nearly 90% of the geographical variation in population IFR – the question you discussed with Prof. Drosten on TWiV.
  2. The second reason why some people have greater chances to die of COVID-19 is their so called immunological age. And namely the proportion of activated memory T-cells in their total T-cells pool. The basis for such a conclusion described in preprint named “Pre-existing T cell memory as a risk factor for severe COVID-19 in the elderly” (https://www.medrxiv.org/content/10.1101/2020.09.15.20188896v1.full.pdf). It’s a huge immunological paper, but shortly they showed that a) people who were never exposed to SARS-CoV-2, nevertheless harbor specific memory T-cells against it. These cell have low avidity and react to broad spectrum of targets (they are also slightly cross-reactive to common cold coronaviruses as well as to other unrelated viruses). From the other hand, in severe COVID-19 cases we observe inadequately enhanced but “erratic” and non-specific T-cell response. Authors suggest, that these two things could be interconnected and people with a large number of such pre-existing memory T cells (immunologically old) are at greater risk of developing severe COVID-19 than those who have fewer pre-existing memory T cells (immunologically young). Because this pathological cellular immune response possibly originated from these pool of pre-existing memory T cells with low functional avidity. Older people tend to have more pre-existing memory T-cells, as they were exposed to more different antigens than younger ones during their longer life. But immunological age doesn’t always directly correlate with biological and such discrepancy could explain why young and otherwise healthy people sometimes develop sever COVID-19 complications and even die of them.
  3. In the beginning Prof. Drosten explained, that SARS-CoV-2 PCR tests are very specific, and it is impossible to obtain positive signal that comes, for example, from influenza virus genome. He emphasized, that all tests were specially checked to see if they give a signal when there are genome fragments of other most popular respiratory viruses in the specimen. This is, of course, trivial issue about test specificity, but a lot of people tend to think, that COVID-19 tests are not accurate. And these suspicions intensified with the onset of cold season.

Episode 57
Released 24 September 2020

Complete transcript is here

Radio host of the podcast mostly spoke with Prof. Ciesek not about the latest news but predominantly about the current situation in different corona fields. This time they discussed various aspects of testing. Here are a couple of interesting issues that you didn’t mention much in TWiV.

  1. About C(t) values that determine whether we could consider positive PCR signal as reliable. People used to say something like “C(t) values higher than 25 are true positives and higher than 35 are probably false positives”, but actually these limits should be established for each PCR machine and/or testing kit on an individual basis. The kits for example can be based on different SARS-CoV-2 genes and gene fragments and that means different primers and different amplification dynamics. Minimum and maximum threshold C(t) values from one lab are not necessarily comparable with such values from another one. It’s especially important to keep this in mind when we are talking about population testing and interpreting the results. In an ideal world every lab should obtain a standard sample with a known number of virus particles, make serial dilutions and determine to which C(t) corresponds each one.
  2. Talking about rapid tests Prof. Ciesek noted that for this tool to be effective it’s necessary to develop clear algorithms of what is to be done in the case of positive test result. Namely – what number to call, how many days to stay home etc. The best would be if every person who had positive rapid test result could make PCR test on the same day.
  3. LAMP rapid tests are good in theory but there are still a lot of obstacles that prevent their implementation in clinical practice. Here are some of them. LAMP tests are not validated, this process takes time and no one is ready at the moment to get into that mess. Also there is a lack of trained staff – and to start a clinical lab that performs testing based on any new method you have to train all the people appropriately. And finally, LAMP uses the same reagents as convenient PCR does. And in the situation of high demand there are simply not enough suppliers who can produce them.
  4. There are also issues with saliva tests. Protocols that are affordable now demand a lot of saliva. For example in a method described here (https://www.nejm.org/doi/full/10.1056/NEJMc2016359) patients were asked to collect one third of standard urine glass of saliva upon waking without eating or drinking. Urine glass volume is typically from 125 to 150 ml. That means that a patient should spit up to 50 ml of saliva. That’s not easy for adults and almost impossible for kids. Moreover, saliva collecting this way is very viscous and it’s very hard to aspirate, dispense and mix it.
  5. Prof. Ciesek told a little bit about using stool samples for SARS-CoV-2 testing. Stool samples can be useful as people definitely shed virus in the stool far longer than in the throat, so one can test stool samples to confirm COVID-19 in patients who are ill for two or three weeks. But handling such type of material is not easy and some components in feces can inhibit PCR. To sum up, though doctors and scientists can sometimes use stool samples testing as an additional tool, they are not suitable for wide use.

Episode 56
Released 16 September 2020

Complete transcript is here

  1. The main topic of the conversation was epidemiological situation in Africa. To make long story short: no one knows for sure what’s going on there. There are several papers that make us think that they are approaching herd immunity – at least in clusters. However it’s impossible to make any robust conclusions as there are a lot of methodological flaws and lack of good data. 
  2. One of the best papers came from Kenia (https://www.medrxiv.org/content/10.1101/2020.07.27.20162693v1.full.pdf). Researchers assessed seroprevalence in Kenyan blood donors and found that 5% of donors had antibodies as early as in May. In big cities such as Nairobi and Mombasa seroprevalence was even higher – up to 9,3%. But in that research they used self-made ELISA tests – probably because commercial tests were not available in Kenya at that time. And with such tests no one can be sure that the results are really sound.
  3. From the other hand, even if commercial tests would be available in Africa, we can not fully trust them. These tests were made and validated in countries with much lower infection prevalence and when using in African population, their PPV (positive predictive value) is low. Drosten’s colleague Felix Drexler determined that commercially available 12 SARS-CoV-2 ELISAs showed up to 25% false-positive results depending on antigen and antibody types (https://www.researchgate.net/publication/342792434_Diagnostics_and_spread_of_SARS-CoV-2_in_Western_Africa_An_observational_laboratory-based_study_from_Benin). (Study was made in Benin).
  4. Data about deaths are also scarce. It seems that there are less deaths in cities than we would expect. But urban population in Africa is much younger than in the country – that’s the first reason. The second – they don’t test enough in the country. Testing is poor even in the biggest cities. For example since SARS-CoV-2 came in Kenya in March there have been done 320 000 tests. It’s comparable with the number of tests Germany did in March weekly.
  5. We don’t know whether immune system of people who live in Africa reacts to the virus the same way as ours. In that region there are a lot of infections, parasites etc. Immune cells are trained to recognize different pathogen patterns – and much more of them than can recognize immune cells of people in the Western world. May be that “pathogen immune library” could help to combat coronavirus. 
  6. Drosten mentioned that he had private communications with virologist from South Africa who told him that seroprevalence in pregnant women from poorest districts of Cape Town is 40%. Drosten didn’t specify which test did health workers use there but anyway it’s a huge number. At the same time excess mortality in Cape Town was 3900 people. Using these numbers one can calculate that IFR here is 0,28. Given that not all Cape Town residents are poor (and richer citizens have lesser chance to catch virus so total seroprevalence is lower), adjusted IFR is somewhere about 0,6 – more or less the same is European countries.
  7. At the end of the episode Prof. Drosten told a little bit about this letter to NEJM about masks having a potential for sort of variolation (https://www.nejm.org/doi/full/10.1056/NEJMp2026913). He regarded this hypothesis as an interesting academic speculation but noticed that it would be very hard to translate it into any practical guidelines.

Episode 55
Released 9 September 2020

Complete transcript is here

  1. We still don’t know how many people have asymptomatic COVID-19. But we know that there could be a lot more cases that we find out with PCR testing. Frau Ciesek told about influenza research (pity there is no link) when people investigated how many people have virus in the time of outbreak using PCR test and after that using antibody test. During the outbreak they found virus in 16% of patients and their contacts. After the outbreak it turned out that 85% of people they’ve checked for influenza antibodies had them.
  2. One more hypothesis explaining how it could be that asymptomatic have the same amount of virus as symptomatic but differ so much in the disease course. The idea is as follows: though we detect the same viral RNA concentration on the peak, in people who don’t exhibit any symptoms it fades much faster than in symptomatic. By the time there are no reliable proof of that assumption and some research showed that asymptomatic shed virus even longer. But it could be that after the peak is passed total amount of virus particles is much smaller in them as opposed to people with symptoms.
  3. In autumn and winter we will have both influenza and COVID-19. The symptoms are more or less similar and it could be hard to distinguish which virus a patient has. Frau Ciesek mentioned a method to do that – multiplex PCR. I’ve read about this method in COVID-19 research but only as a way to detect it more precisely (for example https://www.sciencedirect.com/science/article/pii/S1386653220302419?via%3Dihub). The idea of using it with primers to influenza and SARS-CoV-2 sounds new to me.
  4. A proposal how we can change airport testing. At the moment we make tests right after people return from red zones. But using this testing strategy we possibly miss a lot of cases as people could get infected in the last days of their journey or right in the foreign airport. To prevent the spread of infection we should oblige all travelers who were in red zones to quarantine for five days (mean incubation period) and make test after that.
  5. An interesting notice about running nose and COVID-19 in kids. Researchers from Robert Koch institute (https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Projekte_RKI/KiTAStudie_Juli.pdf?__blob=publicationFile) found out that a single symptom we see it in 3,5% of cases. But along with other symptoms it is detected in good 18% of cases.

Episode 54
Released 1 September 2020

Complete transcript is here

  1. There are many variants of SARS-CoV-2. There are relatively weak data that some of them can infect cells in cell culture better than others. But it’s too early to say whether these results are real and whether they could be directly translated to humans.
  2. Robert Koch Institute does very good job and numbers of new incidents in Germany are more or less correct. Apparently, the true numbers are bigger then what we have, but not too much. We can say that because we see these jumps in daily statistics – if there were a constant increase, we would see more stable behavior of the graph. And the reason for low incidence is not test scarcity –we are doing a lot of tests.
  3. We already know that SARS-CoV-2 tends to spread in clusters. And while the total number of incidences is low the situation looks stable. But there is a threshold and when number of incidences overpasses it, we can suddenly get a rapid increase in numbers and new cases all over the population. Christian tried to describe the model that explains that phenomenon on TWiV. In his podcast he used a couple of metaphors. The first is coffee filter metaphor. When you start pouring water at coffee filter, at the beginning there comes no water from the bottom of the filter – though the filter itself becomes more and more wet. And suddenly the amount of water becomes too big, and a lot of drops start to fall constantly. Another metaphor is more complicated. Drosten described this Connect Four game in which you drop red and yellow discs into the grid (and to win you have to form a horizontal, vertical, or diagonal line of four discs). When the ratio between red and yellow discs is 50 to 50, we will almost always have a connection between clusters of for example red color – but not through the whole grid. When the ratio changes to 80 to 20, the probability that red discs would be connected to each other throughout the whole grid is almost 100%. The same pattern we observe with the incidence numbers in clusters. And if our grid has two electrodes in two angles and red disks are from metal and yellow disks are from wood, with rising number of reds we will suddenly have a current – rapid increase in case number.
  4. At the moment Germany performs enough tests, but it will be hard to do simultaneously school and airport testing. Labs are now almost overwhelmed.
  5. Drosten offers chip method to stop community spreading without additional testing. Every week people should write down, whether they were in “cluster situations”. When someone gets infected, he can tell healthcare worker about all these potentially dangerous situations. This method should ease contact tracing. Also it would be useful if local healthcare authorities make a list of typical “cluster situations” to help people to remember.
  6. Drosten offers to make decision about isolation more flexible. If someone has symptoms and becomes positive PCR-test results four days after that happened, there is no sense in 14-days isolation. All research results point out that after 4-7 days after symptoms ongoing virus carrier can not infect other people.
  7. Labs in Germany are working to make rapid test (antigen test). If everything will go smoothly, it could be certified in December.