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COVID-19 pandemic: The African paradox

AP reported this week that in spite of low vaccination rates, Africa has fared better than most of the world:

There is something “mysterious” going on in Africa that is puzzling scientists, said Wafaa El-Sadr, chair of global health at Columbia University. “Africa doesn’t have the vaccines and the resources to fight COVID-19 that they have in Europe and the U.S., but somehow they seem to be doing better,” she said …

Fewer than 6% of people in Africa are vaccinated. For months, the WHO has described Africa as “one of the least affected regions in the world” in its weekly pandemic reports.

With Low Vaccination Rates, Africa’s Covid Deaths Remain Far Below Europe and the US

Since COVID-19 became a pandemic, projection models were developed for Africa, with the assumption that SARS-CoV-2 has an exponential pattern of transmission.

Source: “Confirmed deaths per million, November 19, 2021“; “Share of people vaccinated against covid-19, November 19, 2021“.

Crowded social life and poor personal hygiene in Africa can be conducive for COVID-19 spread.

CLIMATE HYPOTHESIS

It has been argued since most human coronavirus infections associated with common cold symptoms peak in the winter months (December – April), and are undetectable during summer months in temperate regions of the world, SARS-CoV-2 infection will diminish as temperatures rise in the summer. Indeed, a recent study used a weather model to predict regions associated with a higher risk of COVID-19 community spread [*]. The high-risk temperate Western country zones and South Africa which have 5-11°C mean temperatures and 47%-79% relative humidity have more COVID-19 cases than tropical African countries (Figure 1, Panel A). In contrast, tropical Asian and Latin American countries are disproportionately infected by SARS-CoV-2 compared to tropical African countries (Figure 1, Panel A) suggesting other determinants than climate alone impact the spread of SARS-CoV-2. For example, living in high altitudes (less prone to hypoxia) appears to reduce transmission and death rates from COVID-19. So far, COVID-19 pandemic has shown a markedly low proportion of cases among young people, and this could be the reason why COVID-19 death rate is the lowest in African countries except South Africa. COVID-19 infections are rising sharply in South Africa which resembles the countries of South America more than those of its home continent (Figure 1, Panel A).

COVID-19 prevalence: Geographic variations and vaccination coverage. Panel A. Spread of COVID-19 in Africa vs countries in the temperate region.

There is significant different in cases including trajectories between the two regions. Numbers of total cases have been plotted against days since first reported case in respective countries (as of 5/15/2020). The spread of COVID-19 in Africa vs the rest of the tropical countries. The graph depicts different trajectories due to environmental variation. Numbers of total cases have been plotted against days since first reported case in respective countries (as of 7/07/2020). The COVID-19 pandemic has shown a markedly low proportion of cases among young people, and this could be the reason why COVID-19 infection rate is the lowest in African countries except South Africa. COVID-19 infections are rising sharply in South Africa. South Africa resembles the countries of South America more than those of its home continent. Panel B: Bacillus Calmette-Guérin (BCG) vaccination coverage map by country. Data from the World Health Organization about the BCG coverage in each country showing global status of the BCG vaccination program [**]. In contrast to the countries with no active BCG vaccination program (including the current COVID-19 epicenters such as the US, Italy, Spain, Ecuador), countries with active BCG vaccination program of African countries could be effective in the fight against COVID-19.

Source: NCBI –  COVID-19 pandemic: The African paradox

  • Published online 2020 Sep 11

References

[*] Sajadi MM, Habibzadeh P, Vintzileos A, Shokouhi S, Miralles-Wilhelm F, Amoroso A.Temperature, Humidity and Latitude Analysis to Predict Potential Spread and Seasonality for COVID-19. SSRN. 2020:3550308. PMC Analysis

[**] The BCG World Atlas 2nd Edition. Available: http://www.bcgatlas.org/index.php

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Daily Sceptic Accurately Predicts the Delta Surge in Seven Countries

Two months ago Anthony Brookes, Professor of Genomics and Health Data Science at the University of Leicester, wrote an important piece for the Daily Sceptic in which he assembled the “COVID jigsaw pieces into a complete pandemic picture”.

To recap, this was his summary of his argument:

  • A series of SARS-CoV-2 variants have arisen, many of which possessed a transient selective advantage that led to a wave of infection that peaked some three-to-four months later. Several such variants have spread globally, though different successful variants have arisen simultaneously in a number of countries. The result is a three-to-four month wave pattern per country, which is also apparent globally.
  • Seasonality affects variant transmissibility. Colder seasons accelerate the growth and increase the size of waves, but the continually changing environment may also differentially affect the relative transmissibility of competing variants (i.e., negatively as well as positively), thereby helping to terminate previously dominant variants and promote the growth of new ones.
  • Overall there is a minimal positive impact from quarantine policy, isolation requirements, Test and Trace regimes, social distancing, masking or other non-pharmaceutical interventions. Initially, these were the only tools in the tool-box of interventionist politicians and scientists. At best they slightly delayed the inevitable, but they also caused considerable collateral harms.
  • Immunity created by SARS-CoV-2 infection, layered on top of pre-existing immunity due to cross-immunity to other coronaviruses, provides good protection against infection, severe disease/death, and being infectious. Immunity created by vaccination also helps protect against serious disease and death, but does little or nothing to provide protection against infection or being infectious (which completely negates the case for vaccine ID cards).
  • Population immunity stems mainly from natural infections, with vaccines adding only slightly to this (and only in recent months). Population immunity is created by societal waves of infection and is somewhat variant-specific. An emerging new variant is able to infect (or re-infect) some fraction of individuals and this serves to top up and broaden the scope of our population immunity to also protect against the new variant.
  • This empirical and data-driven understanding of the pandemic allows us to make predictions. Such predictions don’t look good for some of the U.K.’s new Green List countries. But in these and all other places the ongoing arms-race between viral mutations and growing human immunity will always eventually be won by the human immune system. The virus then becomes a low-level endemic pathogen in equilibrium with its human host species. If this were not the case all humans would have been wiped out by viruses eons ago!

In the piece he made some very specific predictions about what would happen over the following months, and we’re now in a position to see how close he got to the target. He wrote:

With an essentially complete COVID jigsaw picture now assembled using an empirical data-driven approach, we can offer up some testable predictions. The first is that current Delta waves unfolding in different countries will reach natural peaks around three-to-four months after this variant arrived in each location. For example, considering countries recently added to the U.K.’s Green List, we would expect: Slovenia, Slovakia and Romania (where Delta arrived little more than one month ago) will see their nascent summer waves grow further and peak in about two months’ time; Latvia (where Delta has only just arrived) will face a multi-month wave starting very soon; and Austria, Germany and Norway (where Delta has already been present for several months) will likely see their summer waves peak around the end of August. NPIs will do little to change this, and neither will vaccines (see Israel for evidence of this).

So the specific predictions were:

Reported cases in Slovenia, Slovakia and Romania peaking around about now.

Latvia to currently be on the up-slope.

Germany, Austria and Norway to peak around the end of August.

Let’s have a look.

Latvia is currently on the up-slope, as predicted, while Slovenia peaked on September 18th, a little early but close enough.

Slovakia and Romania haven’t yet peaked but presumably will soon; in any case their nascent summer waves have certainly grown as predicted.

Norway peaked on September 5th and Germany on September 4th, right on cue. Austria was a little late on September 15th, but not far off.

These are some of the most accurate predictions made by anyone in the pandemic to date, and underline the accuracy of the jigsaw pieces Prof. Brookes has assembled to explain the inner dynamics of the COVID-19 pandemic.

On noting the success of his predictions, Prof. Brookes commented:

The basis for the growth and decline of waves of COVID infection now seems clear and predictable. But not by computer modelling! Instead, the main pre-requisite seems to be the emergence of a new variant that partially evades existing immunity against infection. The resulting wave then (re)infects about 10-15% of the population and thereby restores sufficient herd immunity to stop the wave growing. A degree of fading of population immunity, along with some mechanism(s) by which winters promote viral spread, can also strengthen the growth of a new variant wave – but these are ancillary phenomena and not main drivers.

The really great news is that Delta has now spread worldwide and been around for many months, without there being any evidence in any country of any major new variants emerging that would cause new waves to occur. It therefore looks increasingly likely that Delta-related variants, in practical terms, mark the end of the pandemic. Delta is, as expected, resolving into a low-level endemic pathogen. Its prevalence may rise and fall somewhat as the seasons change, but the overall Infection Fatality Rate (IFR) in populations where those who are vulnerable to severe illness (i.e., the old and those with comorbidities) have been vaccinated, is now tolerable and of the same order as that of influenza. Vaccination of all others (i.e., the young and the healthy) is no longer medically required or justified, given what we now know about the significant rate of vaccine harms, and the fact that vaccines at best only slightly delay rather than prevent infections.

Maybe ministers should be asking Prof Brookes to advise them on the future course of the pandemic, rather than the perennially predictively-challenged Professor Neil Ferguson?

Source: Will Jones / 8 October 2021 • 07.00 – DAILY SCEPTIC

Note

Anthony Brookes on 10 August 2021:

With an essentially complete COVID jigsaw picture now assembled using an empirical data-driven approach, we can offer up some testable predictions.

The first is that current Delta waves unfolding in different countries will reach natural peaks around three-to-four months after this variant arrived in each location.

For example, considering countries recently added to the U.K.’s Green List, we would expect: Slovenia, Slovakia and Romania (where Delta arrived little more than one month ago) will see their nascent summer waves grow further and peak in about two months’ time; Latvia (where Delta has only just arrived) will face a multi-month wave starting very soon; and Austria, Germany and Norway (where Delta has already been present for several months) will likely see their summer waves peak around the end of August. NPIs will do little to change this, and neither will vaccines (see Israel for evidence of this).

The really big question, however, is whether or not Delta is the last major variant we will all have to deal with.

SARS-CoV-2 and the human immune system are basically in an arms race.

Population immunity increases and targets the latest variant, causing new variants with different immunological profiles and transmission advantages to rise in abundance, which in turn further strengthens and broadens our population immunity. Vaccines merely help accelerate this arms race. But the end of the war is always the same – the virus runs out of strategies a long time before the highly adaptable immune system runs out of defences. The virus then gives up and resigns itself to becoming a low-level endemic pathogen in equilibrium with its human host species. If this were not the case all humans would have been wiped out by viruses eons ago.

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SAGE COVID-19 models need a reality check

The transmission of respiratory viruses is poorly understood.

However, the models used by SAGE to justify draconian restrictions are far too simplistic – they are based on a handful of assumptions that have not been adjusted in the light of real world evidence, despite numerous forecasting failures.

First, they assume that every individual is equally susceptible to every variant. SAGE therefore assumes that each outbreak will lead to uncontrolled, exponential viral spread unless there is a material reduction in human interactions.

Why haven’t lockdowns worked?

There are broadly two types of respiratory virus.

There are those that spread person to person – like measles – in a continuous chain of transmission, uninterrupted by season and with every susceptible contact falling ill. Then there are those we do not understand so well, like influenza, which are much more complex. Instead of the simplistic close contact model, which assumes COVID spreads like measles, we should perhaps consider an alternative more sophisticated model based on influenza.

The influenza virus model is unusual – it is predicated on the majority being exposed to a particular airborne virus but, oddly, only a minority appear to be susceptible to each year’s variant. To complicate matters further, influenza can also spread person to person.

The spread of influenza is difficult to model and the cause of the surges in transmission seen each winter is not fully understood.

However, influenza has been measured for centuries, enabling interesting patterns to be discerned. Spread does appear to occur person-to-person but only a trickle of cases occur in the summer months before there is sudden exponential growth leading to a winter surge. This annual surge also happens in autumn in milder climates like Australia and California.

Each winter between 5 per cent and 15 per cent of the population somehow become susceptible to the new circulating influenza ‘variant’ (aka strain) – and to date no one can explain why the percentage is so small. Spending an hour in indoor environments in winter is sufficient to expose everyone inside to an infectious dose of influenza, but the majority remain uninfected – perhaps because they are not susceptible.

After the 5-15 per cent cohort of susceptible individuals in a particular year are infected, a temporary quasi-herd immunity is reached. Cases therefore fall, reaching negligible levels until the next winter. Clear Gompertz curves are seen, although only affecting part of the population.

The following winter, those who were previously infected remain immune but a further 5-15 per cent become susceptible, somehow. No-one understands what exactly causes these people to become susceptible in winter when they were not the previous winter nor in the summer.

A novel influenza virus can take up to eleven winters before full herd immunity is reached for that particular type of influenza virus.

The poorly understood winter trigger that precipitates an influenza surge actually occurs twice each winter and usually the second half sees a different ‘variant’ surge and predominate. Influenza was present for the first half of winter 2019/20 but disappeared globally for the second half at the exact time that SARS-CoV-2 surged, 3 weeks earlier in Italy than in Sweden and the UK. Although these are quite different viruses, the fact that SARS-CoV-2 surged at the exact time that we would have expected a new influenza variant to rise suggests that the influenza transmission model is a viable candidate to examine further for COVID.

The critical point is that many more people are exposed to influenza every year than are infected, because it is airborne and infuses throughout indoor enclosed spaces.

The majority are protected by their immune system and the remainder succumb. Vaccination is generally thought to have had an impact on influenza associated hospitalisations and mortality but the evidence it has significantly reduced transmission and infection is weak.

Comparing the transmission of SARS-CoV-2 to influenza is not the equivalent of dismissing COVID as being like ‘flu.

In a certain subset, COVID causes more hospitalisations than influenza and results in greater demand for intensive care. However, how we respond to it is predicated on understanding how it transmits, so considering the influenza model is important.

Although we do have evidence of significant person-to-person close contact transmission of SARS-CoV-2, there are many areas of ambiguity such that this cannot be the only route of transmission, once again supporting the ‘influenza spread’ hypothesis to explain the spread of COVID.

The person-to-person close contact model cannot explain certain oddities of influenza transmission.

For hundreds of years there have been reports of outbreaks of influenza in boats that have been at sea for weeks with no human contact. It is now clear that SARS-CoV-2 can be transmitted as aerosols through the air, like influenza, and it has been isolated from hospital ventilation systems. In addition, there is a growing body of evidence of numerous viruses present in the troposphere (four to 12 miles above us) which fall to ground level under the right environmental conditions. For decades the simultaneous appearance of genetically identical influenza virus around the world could not be explained, but tropospheric spread may explain this phenomenon.

The simplistic person-to-person close contact model cannot explain certain oddities of COVID either. There was an outbreak of a thousand cases diagnosed within two days of each other in a garment factory in Sri Lanka, without a super-spreader, at a time when there was minimal community Covid. An Argentinian fishing vessel had an outbreak after five weeks at sea, despite everyone testing negative before setting sail. There have been several occasions when Australian authorities have struggled to understand the source of Delta variant infections in the community at times of very low prevalence. Canada publish their test and trace data and 40 per cent of COVID cases in Canada, even at low prevalence, never have an identified source of transmission.

SAGE has never explained how key workers, including hospital staff, who have been continually exposed, could remain unaffected by the original and Alpha variants only to succumb to the Delta variant months later.

The household transmission rate for SARS-CoV-2 is around one in 10 – is this because of good luck, or because the other nine in 10 people sharing living quarters with an infected person are not susceptible to that particular variant?

The influenza model of transmission is a hypothesis that requires testing, which could start by interviewing those on the Diamond Princessto see how many have been infected with subsequent variants.

Real world evidence has repeatedly shown that the simplistic approach adopted by SAGE – and others – has failed.

No explanations have been offered for the lack of correlation between changes in human behaviour and viral prevalence.

Early models were always more likely to be inaccurate but as more data has appeared the refusal to adjust the models becomes less forgivable. Numerous scientists have been pointing out the faults in the SAGE models for well over a year.

Rather than SAGE listening, debating and adjusting their hypothesis, in a scientific way, dissenting voices have been quashed. The latest failures of the SAGE models must be a reality check.

Other hypotheses, including the influenza model, need to be given due consideration and overly simplistic models, which fail to explain the patterns in real world data, must be discarded for good.

Source: Clare Craig – Reaction

Note

Header image:

Universality in COVID-19 spread in view of the Gompertz function

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Study claims virus thrives in temperate climate band across globe

A study published […] suggested that COVID-19 thrives in cooler, drier weather, the latest volley in an ongoing scientific debate over whether the coronavirus is affected by seasonal changes.

The analysis, published by a team out of the University of Maryland, found that hard-hit cities around the globe were within a band between 30 and 50 degrees North, while 42 other cities that seemed to avoid the worst of the pandemic were to the north or south of them.

“The distribution of substantial community outbreaks of COVID-19 along restricted latitude, temperature, and humidity measurements was consistent with the behavior of a seasonal respiratory virus,” the authors wrote in the study, published online by the Journal of the America Medical Association.

The eight cities examined within the band were Wuhan, China; Tokyo, Japan; Daegu, South Korea; Qom, Iran; Milan, Italy; Paris, France; Seattle, Washington; and Madrid, Spain. All of them had temperatures between 41 to 51 degrees Fahrenheit and relative humidity between 44 and 84 percent when the virus was spreading most rapidly.

“We think the SARS-CoV-2 virus has a more difficult time spreading in conditions with higher temperature and humidity,” study co-author Dr. Mohammad Sajadi told UPI.

He added that researchers could use climate modeling to predict where the virus might break out next, but cautioned that more work needed to be done.

Some experts have suggested that hotter temperatures can affect the spread of the virus, though others say the climate is not a major factor. In Israel, Prime Minister Benjamin Netanyahu has insisted that heat does not affect the virus.

The authors noted in the study that coronaviruses that cause the common cold in humans “have been shown to display strong winter seasonality between December and April and are undetectable in summer months in temperate regions of the northern hemisphere.”

Maps produced by the research team showed a green band of moderate weather across the northern hemisphere that forms a sort of Goldilocks Zone for the virus, and which all eight cities fell into. Israel is just to the south of the zone.

It claimed that cities near virus centers but outside the temperate zone appeared to have fared better than those within it, though the study only includes data up to March 10. Among the cities listed as not having major outbreaks is Jerusalem, though Israel’s worst-hit city saw most of its infections only starting in late March and April.

The model conforms with major outbreaks in several cities in March and April based on the climate data, including London, Berlin, New York and Beijing.

Source: TOI Staff

Notes:

Discussion on Temperature, Humidity, and Latitude Analysis to Estimate Potential Spread and Seasonality of Coronavirus Disease 2019 (COVID-19)

The distribution of the substantial community outbreaks of COVID-19 along restricted latitude, temperature, and humidity measurements were consistent with the behavior of a seasonal respiratory virus.

The association between temperature and humidity in the cities affected by COVID-19 deserves special attention.

There is a similarity in the measures of mean temperature (ie, 5-11 °C) and RH (ie, 44%-84%) in the affected cities and known laboratory conditions that are conducive to coronavirus survival (4 °C and 20%-80% RH).[…]

In the time we have written up these results, new centers of substantial community outbreaks include parts of Germany and England, all of which had seen mean temperatures between 5 and 11 °C in January and February 2020 and were included in either the January to February 2020 map […] or the March to April risk map […].

Temperature and humidity are known factors in SARS-CoV, MERS-CoV, and influenza survival.[…] Furthermore, new outbreaks occurred during prolonged periods at these temperatures, perhaps pointing to increased risk of outbreaks with prolonged conditions in this range.

Besides potentially prolonging half-life and viability of the virus, other potential mechanisms associated with cold temperature and low humidity include stabilization of the droplet, enhanced propagation in nasal mucosa, and impaired localized innate immunity, as has been demonstrated with other respiratory viruses.[…] It is important to note that even colder areas in the more northern latitudes have been relatively free of COVID-19, pointing to a potential minimum range for temperature, which could be because of avoidance of freeze-thaw cycles that could affect virus viability or other factors (given that at least 1 human coronavirus tested is freeze-thaw resistant).

Human coronaviruses (HCoV 229E, HCoV HKU1, HCoV NL63, and HCoV OC43), which usually cause common cold symptoms, have been shown to display strong winter seasonality between December and April and are undetectable in summer months in temperate regions of the northern hemisphere.[…] Some studies have shown that the alphacoronavirus HCoV 229E peaks in the fall, while HCoV OC43 (a betacoronavirus in the same genera as SARS-CoV-2) has a winter predominance.[…] Although it would be even more difficult to make a long-term estimation at this stage, it is possible that COVID-19 will diminish considerably in affected areas (above 30° N) in the coming months and into the summer. However, given that SARS-CoV-2 is only recently introduced to humans, there is presumably no preexisting immunity. In such cases, whether the 2009 H1N1 influenza pandemic or the first whooping cough pandemics documented in Persia and France in the 1400s and 1500s, the initial epidemic acted unpredictably, so in addition to their recognizable seasonal peak, they had additional peaks outside their later seasonal patterns.

The spread of the SARS-CoV-2 virus in the upcoming years could follow different patterns; it could prevail at low levels or cause several seasonal peaks in tropical regions like influenza,[…] cause outbreaks in the southern hemisphere at the same time, and begin to rise again in late fall and winter in temperate regions in the upcoming year. Another possibility is that, combined with intensive public health efforts, it will not be able to sustain itself in the summer in the tropics and southern hemisphere and disappear, just as SARS-CoV did in 2003; however, the ever-increasing number of cases worldwide make this increasingly less likely. MERS-CoV has been pointed to as a betacoronavirus that can spread in all seasons. However, it should be remembered that most cases of MERS-CoV were in the Arabian Peninsula and that influenza infection there does not follow the same pattern as in more temperate climates.[…] In the upcoming summer months in the northern hemisphere, surveillance efforts for SARS-CoV-2 in currently affected areas will be important to determine whether there is a viral reservoir (eg, prolonged stool shedding). Similarly, surveillance efforts in the tropics as well as in New Zealand, Australia, South Africa, Argentina, and Chile between the months of June and September may be of value in determining its establishment in the human population.

An avenue for further research involves the use of integrated or coupled epidemiological-earth-human systems models, which can incorporate climate and weather processes and variables (eg, dynamics of temperature, humidity) and their spatiotemporal changes as well as simulate scenarios of human interactions (eg, travel, transmission due to population density). Such models can assimilate data currently being collected to accelerate the improvements of model estimations on short time scales (ie, daily to seasonally). This approach would allow researchers to explore questions such as which population centers are most at risk and for how long; where to intensify large-scale surveillance and tighten control measures to prevent spreading; how to better understand limiting factors for virus spreading in the southern hemisphere; and how to make estimations for the 2021 to 2022 virus season. A better understanding of the cause of seasonality for coronaviruses and other respiratory viruses would undoubtedly aid in better treatments and/or prevention and be useful in determining which areas need heightened surveillance.

Limitations

This study has limitations. The reported data for number of cases and mortality are invariably different in different countries, owing to differences in availability of testing, the sensitivity and specificity of each test, and reporting. Other potential factors that influence transmission (eg, other climate factors, public health interventions, travel, population density, air pollution, population demographic characteristics, viral factors) were not included in this study.

Conclusions

In this study, the distribution of substantial community outbreaks along restricted latitude, temperature, and humidity measurements were consistent with the behavior of a seasonal respiratory virus. Additionally, we have proposed a simplified model that shows a zone that may be at increased risk for COVID-19 spread. Using weather modeling, it may be possible to estimate the regions most likely to be at higher risk of substantial community spread of COVID-19 in the upcoming weeks and months, allowing for a concentration of public health efforts on surveillance and containment.

Comment:

Daylight May Drive Seasonal Variation in SARS-CoV-2 Infectivity

  • Andy Goren, MD | Clinical Hospital Center Sestre Milosrdnice Zagreb, Croatia

SARS-CoV-2 infectivity is dependent on proteolysis of its spike protein by the TMPRSS2 enzyme expressed on the surface of type II pneumocytes (…).

In humans, the only known promoter of the TMPRSS2 gene is an androgen response element; therefore, androgen receptor expression is likely to determine COVID-19 disease severity (…).

In support of the androgen driven COVID-19 hypothesis, a recent study from Italy (…) demonstrated a significant protective effect of androgen depravation therapy in COVID-19 prostate cancer patients OR 4.05 (95% CI: 1.55-10.59). Androgen receptor expression is mediated by the period circadian protein homolog 1 (Per1). Per1 overexpression inhibits the transactivation of the androgen receptor(…). Per1 expression follows a circadian cycle determined by the length of the daylight. Rats exposed to a longer photoperiod (16 hours light and 8 hours darkness) exhibit higher expression of Per1 compared to rats exposed to a shorter photoperiod (8 hours light and 16 hours darkness) (…).

In conclusion, during the fall and the winter months when daylight is short, TMPRSS2 expression is likely to be increased which may lead to increased SARS-CoV-2 infectivity.

Header: A map showing the temperate zone, highlighted in red, where the virus had climate conditions to thrive, according to a study published June 11, 2020. (CC-BY Sajadi MM et al. JAMA Network Open)