Thongchai Thailand


Posted on: April 3, 2020

bandicam 2020-04-03 19-21-58-964




Emeritus of the Johannes-Gutenberg-University in Mainz and long time
director of the Institute for Medical Microbiology

MARCH 2020


Coronavirus Outbreak – Thai PBS World

MUST READ! More Cases Being Reported In China Of Recovered Covid-19 Patients  Dying Suddenly - Thailand Medical News

Overwhelming, lonely, stressful – life in a coronavirus COVID-19 unit in  Geneva | MSF


My concern is that unforeseeable socioeconomic consequences of the drastic containment measures which are currently being applied. We need to look at both the advantages and disadvantages of restricting public life in terms of its long term effects. To this end, I am confronted with FIVE UNANSWERED QUESTIONS.

ITEM #1: STATISTICS: In infectology, a distinction must be made made between infection and disease and so therefore, only patients with symptoms such as fever or cough should be included in the statistics as new cases. It is not sufficient to test positive for COVID-19 to be counted in the disease statistics.

ITEM #2: DANGER: A number of different coronaviruses have been with us for some time largely unnoticed by the media. If it should turn out that the COVID-19 virus should not be ascribed a significantly higher risk potential than the coronaviruses already circulating, all countermeasures now employed would obviously become unnecessary. The very credible International Journal of Antimicrobial Agents will soon publish a paper that addresses this issue. Preliminary results of the study lead to the conclusion that the new virus is NOT different from the corona viruses of the past in terms of danger. The title of the paper is “SARS-CoV-2: Fear versus Data“.

ITEM #3: DISSEMINATION: According to a report in the Süddeutsche Zeitung, not even the Robert Koch Institute knows exactly how many have tested positive for COVID-19. But there is no doubt that there has been a rapid increase in the number of cases in Germany as the volume of tests increases. It is possible therefore that the virus has already spread unnoticed into the whole of the population. If so, it means that the official death rate of 206 deaths from 37,300 infections by 26 March 2020, at a rate of 0.55%, is too high. This would also mean that it isn’t really possible to prevent the spread of this virus.

ITEM #4: MORTALITY: The fear of a rise in the death rate in Germany (currently 0.55 percent) currently carries an intense media interest. Many people are worried that it could go up to 7% or 10% as it had in Spain and Italy. This fear likely derives from the practice of attributing deaths to the virus only on the basis that patient had tested positive for Covid at the time of his death. This practice is flawed. To attribute death to an agent it must first be determined that the agent played a significant role in the death. The Association of the Scientific Medical Societies of Germany includes this principle in its guidelines saying that to declare a cause of death, the causal chain is more important than the underlying disease. A more critical analysis of medical records should be undertaken to determine how many deaths can be attributed to this virus.


The use of Italy as a reference scenario for evaluating the risk posed to our population by this virus is flawed because the role of the virus in the Italian fatality statistics is unclear. There are external factors at play unique to Italy that made Italy particularly vulnerable. It has not been determined that these factors also apply to Germany. A factor unique to Italy is a high level of air pollution in Northern Italy that would account for more than 8,000 fatalities even without the virus. Air pollution increases the risk of viral lung
diseases in very young and in the very old. A household feature of Italy is the cohabitation of the very young and the very old (27.4% of the population) such that the very young can pass the virus to the very old who are at a high risk of death from the virus. This social feature is also found in Spain at the higher percentage of 33.5%. But it is not found in Germany. Therefore these countries do not serve as a model for understanding the spread and fatality rate of the virus in Germany. Yet another factor that makes it difficult to compare Germany with Italy and Spain is the relatively better equipment in Germany’s health care facility.



López, Leonardo, and Xavier Rodó. “The end of social confinement and COVID-19 re-emergence risk.” Nature Human Behaviour 4.7 (2020): 746-755.  The lack of effective pharmaceutical interventions for SARS-CoV-2 raises the possibility of COVID-19 recurrence. We explore different post-confinement scenarios by using a stochastic modified SEIR (susceptible–exposed–infectious–recovered) model that accounts for the spread of infection during the latent period and also incorporates time-decaying effects due to potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of non-pharmaceutical interventions. Our results suggest that lockdowns should remain in place for at least 60 days to prevent epidemic growth, as well as a potentially larger second wave of SARS-CoV-2 cases occurring within months. The best-case scenario should also gradually incorporate workers in a daily proportion at most 50% higher than during the confinement period. We show that decaying immunity and particularly awareness and behaviour have 99% significant effects on both the current wave of infection and on preventing COVID-19 re-emergence. Social distancing and individual non-pharmaceutical interventions could potentially remove the need for lockdowns.

Peto, Julian, et al. “Universal weekly testing as the UK COVID-19 lockdown exit strategy.” The Lancet 395.10234 (2020): 1420-1421. 

The British public have been offered alternating periods of lockdown and relaxation of restrictions as part of the coronavirus disease 2019 (COVID-19) lockdown exit strategy.  Extended periods of lockdown will increase economic and social damage, and each relaxation will almost certainly trigger a further epidemic wave of deaths. These cycles will kill tens of thousands, perhaps hundreds of thousands, of people before a vaccine becomes available, with the most disadvantaged groups experiencing the greatest suffering.  There is an alternative strategy: universal repeated testing.  We recommend evaluation of weekly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen testing of the whole population in an entire city as a demonstration site (preferably several towns and cities, if possible), with strict household quarantine after a positive test. Quarantine would end when all residents of the household test negative at the same time; everyone else in the city can resume normal life, if they choose to. This testing programme should be assessed for feasibility in one or more cities with 200 000–300 000 people. Such a feasibility study should begin as soon as possible and continue after the current lockdown ends, when the infection rate will be fairly low but rising. The rate at which the number of infections then rises or falls, compared with the rest of the UK, will be apparent within a few weeks. A decision to proceed with national roll-out can then be made, beginning in high-risk areas and limited only by reagent supplies. If the epidemic is controlled, hundreds of thousands of lives could be saved, intensive care units will no longer be overloaded, and the adverse effects of lockdown on mental ill health and unemployment will end.
Block, Per, et al. “Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world.” Nature Human Behaviour (2020): 1-9. 
Social distancing and isolation have been widely introduced to counter the COVID-19 pandemic. Adverse social, psychological and economic consequences of a complete or near-complete lockdown demand the development of more moderate contact-reduction policies. Adopting a social network approach, we evaluate the effectiveness of three distancing strategies designed to keep the curve flat and aid compliance in a post-lockdown world. These are: limiting interaction to a few repeated contacts akin to forming social bubbles; seeking similarity across contacts; and strengthening communities via triadic strategies. We simulate stochastic infection curves incorporating core elements from infection models, ideal-type social network models and statistical relational event models. We demonstrate that a strategic social network-based reduction of contact strongly enhances the effectiveness of social distancing measures while keeping risks lower. We provide scientific evidence for effective social distancing that can be applied in public health messaging and that can mitigate negative consequences of social isolation.
Rawson, Thomas, et al. “How and when to end the COVID-19 lockdown: an optimization approach.” Frontiers in Public Health 8 (2020): 262.
Countries around the world are in a state of lockdown to help limit the spread of SARS-CoV-2. However, as the number of new daily confirmed cases begins to decrease, governments must decide how to release their populations from quarantine as efficiently as possible without overwhelming their health services. We applied an optimal control framework to an adapted Susceptible-Exposure-Infection-Recovery (SEIR) model framework to investigate the efficacy of two potential lockdown release strategies, focusing on the UK population as a test case. To limit recurrent spread, we find that ending quarantine for the entire population simultaneously is a high-risk strategy, and that a gradual re-integration approach would be more reliable. Furthermore, to increase the number of people that can be first released, lockdown should not be ended until the number of new daily confirmed cases reaches a sufficiently low threshold. We model a gradual release strategy by allowing different fractions of those in lockdown to re-enter the working non-quarantined population. Mathematical optimization methods, combined with our adapted SEIR model, determine how to maximize those working while preventing the health service from being overwhelmed. The optimal strategy is broadly found to be to release approximately half the population 2–4 weeks from the end of an initial infection peak, then wait another 3–4 months to allow for a second peak before releasing everyone else. We also modeled an “on-off” strategy, of releasing everyone, but re-establishing lockdown if infections become too high. We conclude that the worst-case scenario of a gradual release is more manageable than the worst-case scenario of an on-off strategy, and caution against lockdown-release strategies based on a threshold-dependent on-off mechanism. The two quantities most critical in determining the optimal solution are transmission rate and the recovery rate, where the latter is defined as the fraction of infected people in any given day that then become classed as recovered. We suggest that the accurate identification of these values is of particular importance to the ongoing
Ruktanonchai, Nick Warren, et al. “Assessing the impact of coordinated COVID-19 exit strategies across Europe.” Science (2020).
As rates of new COVID-19 cases decline across Europe due to non-pharmaceutical interventions such as social distancing policies and lockdown measures, countries require guidance on how to ease restrictions while minimizing the risk of resurgent outbreaks. Here, we use mobility and case data to quantify how coordinated exit strategies could delay continental resurgence and limit community transmission of COVID-19. We find that a resurgent continental epidemic could occur as many as 5 weeks earlier when well-connected countries with stringent existing interventions end their interventions prematurely. Further, we found that appropriate coordination can greatly improve the likelihood of eliminating community transmission throughout Europe. In particular, synchronizing intermittent lockdowns across Europe meant half as many lockdown periods were required to end community transmission continent-wide.



The ongoing experience with the SARS-CoV-2 virus and its companion disease, COVID-19, is a matter of balancing health and medical aspects of the associated pandemic against economic costs and consequences of policy responses. Alarmed by estimates from models predicting high morbidity rates (e.g., Edinburgh model), politicians and health bureaucrats imposed lockdowns, mandated social distancing or required citizens to shelter-in-place. As it turned out, worst-case scenarios of healthcare systems and hospitals being overwhelmed were exaggerated with hotspots like Wuhan, Lombardy and NYC bearing the brunt of the wave of illnesses and treatments. The policy responses to this pandemic provide several important lessons.

First, policy makers must understand that estimates derived from models can never be treated as reflecting objective reality of Besides the subjective nature of the assumptions within these models, it is as misguided as it is misleading to treat data sets as if they are devoid of subjectivity. What this means is that claims that public policy is guided by “science and evidence” rings hollow. Science is about testing and questioning what we see around us, not about establishing a consensus.

Second, policy makers should understand and undertake cost-benefit analysis of their decisions before jumping in over their heads. In large measure, the material harm and human costs of the economic collapse are the outcome of what now seems to have been rash judgements based upon faulty modelling.

Third, the goals of policies must be tempered by reality rather than rhetoric or political impulses. For example, Illinois Governor J.B. Pritzker announced economic reopening plan would wait “until we’re able to eradicate” the novel coronavirus.

But to imagine a world that is 100% free of corona or any other virus is an unrealistic goal. As it turns out, moving the number of cases closer to zero will cause the economic and human costs of the collateral damage to rise asymptotically. The way that epidemics or pandemics end is when a large enough proportion of the population acquires immunity either from the antibodies in reaction to infections or the development of a vaccine or treatment.

Vaccines must not be thought of as a magic bullet. On the one hand, vaccines for influenza that have been developed and used for decades are effective in the range of 35% to 45%. On the other hand, the RNA nature of coronaviruses makes them harder to pin down due to more rapid mutations. As it is, there are no vaccines for HIV, Zika, or Ebola despite so much having been invested over such a long period. Indeed, there are no “cures” for these deadly pathogens, only treatments.

Insisting that restrictions should only be lifted only after a vaccine is discovered is also misguided. Discovery of the vaccine is only one part of the puzzle. Even with a miraculous discovery of a vaccine within a few months, it will take considerable time to develop the capacity to produce medically acceptable scales that guarantee purity and safety. Then there is the matter of distributing and inoculating a large enough population. All of this will extend the time horizon into the distant future.

In all events, a question arises concerning the appropriate target ratio is that we should be tracking all the way to zero. Is it the case fatality rate, the infection fatality rate, or the crude mortality rate? None of these ratios are objective ratios determined purely from the data because their interpretation in immunology and virology have a subjective component; but once published these numbers are treated as objective data.

Yet, even the published number for the total number of deaths from COVID-19 is subject to interpretation because the death of persons known to have been infected by the virus creates a strong bias to record the cause of death as COVID-19. In the US, hospitals were guided by a incentive whereby they receive higher financial assistance for such patients that is likely to contribute to an upward bias on reported cases. Similarly, regardless of co-morbidity, instructions were given that all deaths of individuals infected with COV-19 were to be counted as COV-19 fatalities, even if they died with it rather than from it.

Details on the human transmissibility and age-specific impacts of the Coronavirus were reported during an earlier SARS pandemic in 2002-03. Details can be found in this 2009 paper [LINK] by Chris Ka-fai Li and Xiaoning Xu where we learn that “The reemergence of the Coronavirus in humans remains high due to the large animal reservoirs of coronavirus and the genome instability of coronaviruses RNA.”

It is extremely difficult to make accurate estimates of the true risks arising from human encounters with SARS-CoV-2 or any other disease during the initial stages of an epidemic, making it difficult to formulate appropriate policy responses. In all events, pandemics and epidemics first require medical rather than political responses.

In assessing the risk of death from the virus, there are several indicators, i.e., the “case fatality rate”, the “crude mortality rate”, and the “infection fatality rate”.

The Case Fatality Rate (CFR) is the ratio between confirmed deaths and confirmed cases, but it is a poor measure of the overall mortality risk of the disease. As it is, CFR relies on a clear assessment of the number of confirmed cases, something that is very fluid. This is worsened by the fact that the total number of deaths from COVID-19 is subject to interpretation. Anyone testing positive for SARS-CoV-2 will be known to clinical staff, so if they should die, it will be recorded on the death certificate as Covid-19 even if it was not the cause of death.

As such, it is very likely that deaths from COVID-19 are being recorded will tend to give the appearance that Covid-19 is causing an excess number of deaths. Data from the CDC & WHO indicate the CFR for the USA rate is about 5.9%, France 15%, UK 14.4%, Italy 14%, Netherlands 12.75%, Sweden 12.2%, Spain 10%, Mexico 10%, Canada 7.1%, Brazil 6.8%, Ireland 6.3%, & Switzerland 6.1%.

While the negative impact of lockdowns and similar restrictions on movements on economic activity is very clear, it is difficult to know the health impacts. Even so, it is likely that they may also make matters worse for several reasons. First, by simply delaying an inevitable spread of a highly contagious disease from the wide community. Second, keeping people indoors, away from sunshine, fresh(er) air, confined in close quarters with other people, especially if third, they are confined with other people suffering from other communicable diseases like TB that will not be diagnosed so it could have been treated or for infected to be isolated (NB: the “poor” are likely to be hit the hardest, especially in Third World countries). Fourth, extending the timeline of moving towards “herd immunity” might actually lead to a higher overall long-term death rate.

Numbers 1 and 2 will almost surely contribute to a “2nd wave” while number 3 leads to avoidable deaths from otherwise treatable diseases. So, it is not the lifting of a lockdown so much as instituting it in the first place that leads to another round of infections.

In light of the slow progress towards & low probability of discovering, producing and administering an effective vaccine on a large scale, the immediate path towards “herd immunity” is the natural development of antibodies against the SARS-CoV-2 virus. As it is, the evidence from an earlier iteration of the SARS virus suggests that the antibodies formed in that case were effective for up to 12 months & in some cases perhaps as much as 48 months.

For its part, this novel virus does not care about the choice of timing; either accept an initial short, sharp shock or suffer through a series of lockdowns in response to successive waves. Public Choice theory as a subset of economics predicts that politicians and bureaucrats tend to avoid political costs of immediate events inducing them to follow what is in their own best interest, which they believe is to engage in more interventions rather than less. So it is better for them to claim they are being guided by “science and evidence” to issue policy declaration that really reflect their own personal incentives as political agents. In all events, they have no “skin-in-the-game” of the lockdowns since neither they nor most public sector employees will face job losses as have occurred in the private sector.

“Successful” lockdowns will almost certainly be followed by a nasty 2nd wave. In turn, this will almost surely lead to more economic damage while undermining institutional and Constitutional restraints on the democratic process that would impose greater limits on human liberty. Another concern about lockdowns, social distancing mandates, and shelter-in-place orders is if they involve heavy-handed enforcement, there are likely to be heavy impacts on racial minorities, the poor, and those less able to defend themselves.

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  • chaamjamal: Thank you for your valuable input. The carbon footprint of climate science is a reference to carbon dioxide emissions but denominated in tons of carbo
  • chaamjamal: Yes sir. Well said. Thank you.
  • jamesmatkinwritings: Here is a reference about your fake carbon footprint -Caring about sound science: Carbon is not carbon dioxide Wiki Commons photo October 25,
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