Simon Bauer’s research while affiliated with Max Planck Institute for Dynamics and Self-Organization and other places

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Publications (13)


Bayesian inference enables individual assessment of the contribution of different SARS-CoV-2 variants to the spread of COVID-19. (a) Throughout 2021, five SARS-CoV-2 variants were identified as predominant in Chile, two considered Variants of Concern (VoC) by the WHO (Alpha, and Gamma), one Variant of Interest (Lambda), and two other unflagged lineages (B.1.1 and B.1.1.348). The total black line also included other non-predominant variants. Assuming that the contribution of each variant to the spreading dynamics (a–c) is proportional to their share (i.e., the fraction they represent of the total samples, d–h), we quantified their transmissibility compared to the Alpha variant (i–m). The Lambda and Gamma variants showed a 1.05 (95% CI [1.01,1.14]) and 1.16 (95% CI [1.11,1.21]) fold higher reproduction number than the Alpha variant. Other variants had a comparatively lower influence on the spread. Shaded areas in the b–h panels account for the 95% credible intervals of the model fit. Complementary parameters and variables are summarised in Supplementary Fig. S1.
Predominant variants are enriched with mutations in the Spike gene. (a) The Nextclade-based (https://clades.nextstrain.org/tree) phylogenetic tree of the SARS-CoV-2 variants isolated in Chile, visualised using Auspice online tool (https://auspice.us/ ) based on n = 2650 SARS-CoV-2 cases. The sequences are placed on a global reference tree (grey brunches and nodes), and clades are assigned to the nearest neighbour, while the branches with coloured circles represent lineages from Chile. (b) The normalised Total Mutational Load (nTML) indicates that the Spike gene is enriched in mutations compared to the entire genome for all analysed variants. The apparent discreteness of the Spike nTML traces is due to the shorter gene length. The white points denote the median, black boxes denote the interquartile ranges, and whiskers (thin black lines) extend until at most 1.5 times the length of the interquartile range, and dot opacity denotes the time when samples were collected (light →\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rightarrow$$\end{document} old, dark →\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rightarrow$$\end{document} recent). Significance levels were determined with an u-test, see Supplementary Table S2). c. The most predominant variants do not show a considerable drift in their average nTML over time. Dotted lines account for weeks when the variants were not observed. d. There is a marked and significant positive correlation between nTML in Spike and the variants’ relative transmissibility (median r = 0.923, p-value = 0.025). Vertical error bars are those reported in Figure 1, asterisks denote median values, and horizontal error bars were estimated through bootstrapping.
Signatures of the settlement, replacement, and selection of mutations in the different observed lineages of SARS-CoV-2. Throughout 2021, the set of mutations that are present in the analysed samples of the predominant lineages has changed. This temporal evolution of the mutational footprint of the lineages can be quantified by the proportion of the analysed samples which present a given mutation. We selected mutations with the largest temporal variability for each lineage, and we present their evolution as a heat map. (a–e) Evolution of the fraction of the samples presenting a given mutation for the B.1.1 (a), B.1.1.348 (b), Alpha (c), Gamma (d), and Lambda (e) variants, respectively, with their number of observations. Triangle markers at the lower end of each heat map account for the progress in vaccination.
Robustness check: linear correlation between nTML in spike and variant transmissibility. Probability-normalised histograms for the linear correlation coefficient (a) and the associated p-value (b) in the Monte Carlo-inspired experiment to test for robustness. We see that the correlation is statistically significant for most of the hypothetical curves.
Early mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants in Chile
  • Article
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July 2024

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55 Reads

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2 Citations

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Sebastian B. Mohr

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Jonas Dehning

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Genomic surveillance (GS) programmes were crucial in identifying and quantifying the mutating patterns of SARS-CoV-2 during the COVID-19 pandemic. In this work, we develop a Bayesian framework to quantify the relative transmissibility of different variants tailored for regions with limited GS. We use it to study the relative transmissibility of SARS-CoV-2 variants in Chile. Among the 3443 SARS-CoV-2 genomes collected between January and June 2021, where sampling was designed to be representative, the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. We found that Lambda and Gamma variants’ reproduction numbers were 5% (95% CI: [1%, 14%]) and 16% (95% CI: [11%, 21%]) larger than Alpha’s, respectively. Besides, we observed a systematic mutation enrichment in the Spike gene for all circulating variants, which strongly correlated with variants’ transmissibility during the studied period (r = 0.93, p-value = 0.025). We also characterised the mutational signatures of local samples and their evolution over time and with the progress of vaccination, comparing them with those of samples collected in other regions worldwide. Altogether, our work provides a reliable method for quantifying variant transmissibility under subsampling and emphasises the importance of continuous genomic surveillance.

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Figure 1: Model overview a) The SIRSsm model: An extended SIRS model including periodic seasonality (s,
Figure 8: Various mitigation-hazard feedbacks trigger a Hopf bifurcation. The onset of oscillations due to a Hopf bifurcation is not unique to one specific example for the functional form of m(h). Instead, for different functional shapes of m(h) oscillations emerge when maximal mitigation mmax and mitigation delay τ are large enough (a,d for a logistic feedback, b,e for an exponential feedback). c,f) Mitigation alertness α is the other free variable of the exponential feedback. If it is large enough, namely mitigation increases fast enough with hazard, oscillations emerge. Model parameters used are found in Tab. 1. For b,e α = 1500 was used. For c,f mmax = 0.83 was used.
Parameters of the SIRSsm model.
Data sources for Influenza and COVID-19 timeseries
Societal feedback induces complex and chaotic dynamics in endemic infectious diseases

May 2023

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259 Reads

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2 Citations

Classically, endemic diseases are expected to display relatively stable, predictable infection dynamics. Indeed, diseases like influenza show yearly recurring infection waves that can be anticipated accurately enough to develop and distribute new vaccines. In contrast, newly-emerging diseases may cause more complex, unpredictable dynamics, like COVID-19 has demonstrated. Here we show that complex infection dynamics can also occur in the endemic state of seasonal diseases when including human behaviour. We implement human behaviour as a feedback between incidence and disease mitigation and study the system as an epidemiological oscillator driven by seasonality. When behaviour and seasonality have a comparable impact, we find a rich structure in parameter and state space with Arnold tongues, co-existing attractors, and chaos. Moreover, we demonstrate that if a disease requires active mitigation, balancing costs of mitigation and infections can lead societies right into this complex regime. We observe indications of this when comparing past COVID-19 and influenza data to model simulations. Our results challenge the intuition that endemicity implies predictability and seasonal waves, and show that complex dynamics can dominate even in the endemic phase.


FIGURE 2 | Data-derived formulation of behavioral feedback loops. (A): Reported contact reductions follow intensive care unit (ICU) occupancy in Germany. Survey participants were asked how likely they were to avoid private parties over the course of the pandemic on a discrete scale from 1 (never) to 5 (always) [4]. To decouple the effect of vaccination availability, we present 2020 (red) and 2021 (yellow) data separately. Ticks indicate the middle of the month. (B): The survey data on contact reduction and the ICU occupancy are related. The piece-wise linear relationship shows the reduction of contacts with increasing ICU occupancy, and for even higher ICU occupancy a saturation. Red, yellow, and black represent fits to the data from 2020, 2021, and overall, respectively. (C): In the model, the contact reduction and its dependency on ICU occupancy is implemented as a multiplicative reduction factor k that weighs the age-dependent contextual contact matrices (Figure 1B). (D): Vaccine uptake increases with ICU occupancy in Romania (shown here) and other European countries (Supplementary Figure S4). (E): Willingness to accept a vaccine offer is modeled using an exponentially-saturating function, ranging between a lower and upper bound of acceptance depending on ICU occupancy. The bounds represent that a fraction of people is willing to be vaccinated even at no immediate threat (no ICU occupancy), and another fraction is not willing or able to get vaccinated no matter the threat. (F): Vaccines are delivered at a rate proportional to the number of people seeking a vaccine, i.e., the difference between the number of people willing to be vaccinated and those already vaccinated. Thus, when the number of already vaccinated equals the number of people willing to get vaccinated, no more vaccinations are carried out. The same functional shape describes the booster uptake.
FIGURE 3 | Incorporating behavioral feedback loops in compartmental models broadens the dynamic range of the solutions and yields more realistic results. Different variations of a compartmental model are displayed to show the effect of the two feedback loops used in our model: When ICU occupancy increases, individuals increase their health-protective behavior and are more willing to be vaccinated. This dynamical adaptation can break a wave at lower case numbers and lead to extended infection plateaus (blue curves), which a classic compartment model is unable to reproduce as it does not incorporate the population's reaction to the disease (red curve).
FIGURE 4 | Maintaining moderate contact restrictions throughout winter outperforms extreme scenarios in balancing the burden on ICUs by allowing people the freedom to act according to their risk perception. The level of mandatory NPIs sustained throughout winter 2021/2022, together with people's voluntary preventive actions, determines case numbers and ICU occupancy over winter and beyond. Ticks are set on the first day of the month. (A): The three displayed scenarios of mandatory NPI stringency in winter reflect "freedom-day" with only basic hygiene measures (black), considerable contact reduction and protective measures (e.g., mandatory masks) in school, at the workplace and in the community (blue), and strong contact reduction and partial school closure (mint). All measures are gradually lifted centred around 1 March 2022, over the course of 4 weeks. (B): The seasonality of the basic reproduction number R 0 . (C,D): Scenario 1 (black): Without mandatory restrictions, incidence and ICU occupancy increase steeply; this increases voluntary health-protective behavior and vaccine uptake in the population (E,F), and leads to higher rates of naturally acquired immunity (G), but also high mortality and morbidity in winter (H). Note that disproportionally more vaccinated individuals die after March 2022 because, at this point, most of the population is vaccinated. A "full wave" is added in (C,D) (red dotted line), depicting the development of case numbers and ICU occupancy in the absence of behavioral feedback mechanisms. Scenario 3 (blue): Maintaining moderate restrictions would prevent overwhelming ICUs while allowing for higher vaccine uptakes and rates of post-infection immunity. Scenario 5 (mint): Maintaining strong restrictions would minimize COVID-19 cases and hospitalizations in winter, generating a perception of safety across the population. However, this perceived safety is expected to lower the incentives to get vaccinated. Furthermore, immunity of all kinds will wane over winter. Altogether, this can cause a severe rebound wave if restrictions are completely lifted in March. Furthermore, in all scenarios where ICU capacity is exceeded, we would in reality expect either disproportionally higher mortality due to the burden on the health system or a change in mandatory NPIs.
Interplay Between Risk Perception, Behavior, and COVID-19 Spread

February 2022

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180 Reads

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30 Citations

Frontiers in Physics

Pharmaceutical and non-pharmaceutical interventions (NPIs) have been crucial for controlling COVID-19. They are complemented by voluntary health-protective behavior, building a complex interplay between risk perception, behavior, and disease spread. We studied how voluntary health-protective behavior and vaccination willingness impact the long-term dynamics. We analyzed how different levels of mandatory NPIs determine how individuals use their leeway for voluntary actions. If mandatory NPIs are too weak, COVID-19 incidence will surge, implying high morbidity and mortality before individuals react; if they are too strong, one expects a rebound wave once restrictions are lifted, challenging the transition to endemicity. Conversely, moderate mandatory NPIs give individuals time and room to adapt their level of caution, mitigating disease spread effectively. When complemented with high vaccination rates, this also offers a robust way to limit the impacts of the Omicron variant of concern. Altogether, our work highlights the importance of appropriate mandatory NPIs to maximise the impact of individual voluntary actions in pandemic control.


The benefits, costs and feasibility of a low incidence COVID-19 strategy

February 2022

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230 Reads

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29 Citations

The Lancet Regional Health - Europe

In the summer of 2021, European governments removed most NPIs after experiencing prolonged second and third waves of the COVID-19 pandemic. Most countries failed to achieve immunization rates high enough to avoid resurgence of the virus. Public health strategies for autumn and winter 2021 have ranged from countries aiming at low incidence by re-introducing NPIs to accepting high incidence levels. However, such high incidence strategies almost certainly lead to the very consequences that they seek to avoid: restrictions that harm people and economies. At high incidence, the important pandemic containment measure ‘test-trace-isolate-support’ becomes inefficient. At that point, the spread of SARS-CoV-2 and its numerous harmful consequences can likely only be controlled through restrictions. We argue that all European countries need to pursue a low incidence strategy in a coordinated manner. Such an endeavour can only be successful if it is built on open communication and trust.


Interplay between risk perception, behaviour, and COVID-19 spread

December 2021

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165 Reads

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1 Citation

Pharmaceutical and non-pharmaceutical interventions (NPIs) have been crucial for controlling COVID-19. This is complemented by voluntary preventive behaviour, thereby building a complex interplay between risk perception, behaviour, and disease spread. We studied how voluntary health-protective behaviour and vaccination willingness impact the long-term dynamics combining COVID-19 data and modelling. We analysed how different levels of mandatory NPIs determine how individuals use their leeway for voluntary actions. If mandatory NPIs are too weak, COVID-19 incidence will surge, implying high morbidity and mortality before individuals can act; if they are too strong, one expects a rebound wave once restrictions are lifted, challenging the transition to endemicity. Conversely, with moderate mandatory NPIs, individuals effectively adapt their behaviour following their risk perception, mitigating disease spread effectively. Furthermore, together with high vaccination rates, these scenarios offer a robust way to mitigate the impacts of the Omicron Variant of Concern. Altogether, our work highlights the importance of appropriate mandatory NPIs to maximise the impact of individual voluntary actions in pandemic control.


Fig. 1. Spreading dynamics depend on the balance between destabilizing and stabilizing contributions and on the level of case numbers. (A) Among the factors that destabilize the spread, we find the basic reproduction number R 0 and the external influx of infections (and, possibly, seasonality). On the other hand, increased hygiene, TTI strategies, contact reduction, and immunity contribute to stability. We specifically investigated how reductions in the contact level k t and limited TTI capacity determine the stabilization of case numbers. (B) At mild contact reduction (k t = 80% compared to pre-COVID-19 times), TTI is not sufficient; case numbers would grow even when TTI capacity is available. (C) At moderate contact reduction (k t = 60%), a metastable equilibrium emerges (gray dots) to which case numbers converge, if they were below the TTI capacity. However, destabilizing events (e.g., a sudden influx of infections) can push a previously stable system above the TTI capacity and lead to an uncontrolled spread (black line as an example). (D) Assuming strong contact reduction (k t = 40%), case numbers decrease even if the TTI capacity is exceeded. (E) Near to the critical level of contacts k t crit , small changes in the contact level will lead to a considerable increase in observed cases in equilibriumˆNequilibriumˆ equilibriumˆN ∞ obs . (F) Reducing the influx of infections  t (by closing borders or deploying extensive testing at arrival) reduces the number of infections. (G) Increasing the efficiency of manual contact tracing and additional measures such as increased hygiene and compulsory use of face masks will increase the maximum allowed level of contacts k t crit .
Fig. 3. The effectiveness of a lockdown depends on three primary parameters: its duration, stringency (strength), and starting time. (A to C) Observed daily new cases for a lockdown (LD.), enacted after exceeding the TTI capacity. Reference parameters are a lockdown duration of 4 weeks, reducing contact level to k t = 25%, and a start time at 4 weeks after exceeding TTI capacity. We vary lockdown duration from 1 to 5 weeks (A), lockdown strength (B), and lockdown starting time (C) to investigate whether stable case numbers can be reached. (D to F) Total cases after 3 months, if the lockdown is parameterized as described in (A) to (C), respectively. (G and H) The minimal required duration of lockdown to reach equilibrium depends both on strength and start time. (G) Heavy contact reduction (leading to lower values of k t ) and timely lockdown enacting can create effective short lockdowns (≤2 weeks, lower left, dark region). Whereas with mild contact reduction and very late start times, lockdowns become ineffective even when they last indefinitely (upper right, bright area). (H) Horizontal slices through the color map (G). Here, colors match (C) and (F) and correspond to the lockdown start time.
Fig. 7. Flowchart of the complete model. The solid blocks in the diagram represent different SEIR compartments for both hidden and quarantined individuals. Hidden compartments account for both symptomatic and asymptomatic carriers (as described in Methods). Solid lines represent the natural progression of the infection (contagion, latent period, and recovery). On the other hand, dashed lines account for imperfect quarantine and limited compliance, external factors, and TTI policies.
Model parameters.
Model variables.
Low case numbers enable long-term stable pandemic control without lockdowns

October 2021

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830 Reads

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35 Citations

Science Advances

The traditional long-term solutions for epidemic control involve eradication or population immunity. Here, we analytically derive the existence of a third viable solution: a stable equilibrium at low case numbers, where test-trace-and-isolate policies partially compensate for local spreading events and only moderate restrictions remain necessary. In this equilibrium, daily cases stabilize around ten or fewer new infections per million people. However, stability is endangered if restrictions are relaxed or case numbers grow too high. The latter destabilization marks a tipping point beyond which the spread self-accelerates. We show that a lockdown can reestablish control and that recurring lockdowns are not necessary given sustained, moderate contact reduction. We illustrate how this strategy profits from vaccination and helps mitigate variants of concern. This strategy reduces cumulative cases (and fatalities) four times more than strategies that only avoid hospital collapse. In the long term, immunization, large-scale testing, and international coordination will further facilitate control.


Figure 1: COVID-19 restrictions planning through winter: a long-term dilemma. The interplay of non-pharmaceutical interventions (NPI), that are sustained through winter 2021/2022, with people's protection-seeking behavior will determine case numbers and ICU occupancy over winter and beyond. A: We explored three scenarios of mandatory NPI stringency in winter, gradually lifting all restrictions in March 2022. B, C: Scenario 1: having no restrictions causes a steep increase in case numbers and ICU occupancy that triggers protection-seeking behavior among the population. In this situation, the self-regulation of contacts, growing vaccine uptake, and higher rates of natural immunization would contribute to stabilizing case numbers (D, E), bearing, however, high mortality and morbidity in winter (F). Scenario 2: Maintaining mild restrictions would curb the overwhelming of ICUs while allowing for higher vaccine uptakes and natural immunity rates. Scenario 3: Maintaining moderate restrictions throughout winter will minimize COVID-19 cases and hospitalizations in winter, generating a shared perception of safety across the population. However, low vaccine uptake and rates of naturally acquired immunity through winter together with waned immunity will cause a severe rebound wave when restrictions are completely lifted in March (D--F)
The winter dilemma

October 2021

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208 Reads

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1 Citation

As summer in the northern hemisphere comes to an end, changes in daylight, temperature, and weather -- and people's reaction to them -- will be the drivers of a disadvantageous seasonality of SARS-CoV-2. With the seasonal odds against us, stabilization of new COVID-19 cases and hospitalizations requires high immunity levels in the population or sufficient non-pharmaceutical interventions (NPIs). However, compliance with mandatory NPIs, vaccine uptake, and individual protective measures depend on individual opinions and decisions. This in turn depends on the individuals' communication network, as well as access to and personal consumption of information, e.g., about vaccine safety or current infection levels. Therefore, understanding how individual protection-seeking behavior affects disease spread is crucial to prepare for the upcoming winter and future challenges.


Relaxing restrictions at the pace of vaccination increases freedom and guards against further COVID-19 waves

September 2021

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216 Reads

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65 Citations

Mass vaccination offers a promising exit strategy for the COVID-19 pandemic. However, as vaccination progresses, demands to lift restrictions increase, despite most of the population remaining susceptible. Using our age-stratified SEIRD-ICU compartmental model and curated epidemiological and vaccination data, we quantified the rate (relative to vaccination progress) at which countries can lift non-pharmaceutical interventions without overwhelming their healthcare systems. We analyzed scenarios ranging from immediately lifting restrictions (accepting high mortality and morbidity) to reducing case numbers to a level where test-trace-and-isolate (TTI) programs efficiently compensate for local spreading events. In general, the age-dependent vaccination roll-out implies a transient decrease of more than ten years in the average age of ICU patients and deceased. The pace of vaccination determines the speed of lifting restrictions; Taking the European Union (EU) as an example case, all considered scenarios allow for steadily increasing contacts starting in May 2021 and relaxing most restrictions by autumn 2021. Throughout summer 2021, only mild contact restrictions will remain necessary. However, only high vaccine uptake can prevent further severe waves. Across EU countries, seroprevalence impacts the long-term success of vaccination campaigns more strongly than age demographics. In addition, we highlight the need for preventive measures to reduce contagion in school settings throughout the year 2021, where children might be drivers of contagion because of them remaining susceptible. Strategies that maintain low case numbers, instead of high ones, reduce infections and deaths by factors of eleven and five, respectively. In general, policies with low case numbers significantly benefit from vaccination, as the overall reduction in susceptibility will further diminish viral spread. Keeping case numbers low is the safest long-term strategy because it considerably reduces mortality and morbidity and offers better preparedness against emerging escape or more contagious virus variants while still allowing for higher contact numbers (freedom) with progressing vaccinations.


Predominant variants are enriched with mutations in the Spike gene. a. When analyzing their normalized total mutational load (TML), namely, the number of mutations divided by the size of the gene x1000 (1 kbp), we observe that the number of mutations in the Spike gene (yellow) is above the average (red) for all variants herein analyzed. Furthermore, variants with higher normalized TML are consistent with those contributing more
strongly to the transmission. The discreteness of the Spike gene mutational load is due to the shorter gene length. The white points denote the median, black boxes denote the interquartile ranges, and whiskers (thin black lines)
extend until at most 1.5 times the length of the interquartile range. b. The most predominant variants do not show a considerable drift in their average TML over time. However, the TML could not account for the replacement of mutations, or other genetic dynamics, thus suggesting that it should not be used as a stand-alone measure of
variability. Dotted lines account for weeks where the variants were not observed. c. The normalized TML in the Spike gene correlates positively with the relative contribution to the spread of the analyzed lineages. Furthermore,
the discrepancy between observed TML and the linear regression is quite low, i.e., R2 = 0.83. Errorbars denote 95%. Vertical errorbars are those reported in Figure 1, and horizontal errorbars were estimated through bootstrapping.
Bayesian inference enables individual assessment of the contribution of different SARS-CoV-2 variants to the spread of COVID-19. a. Throughout 2021, five SARS-CoV-2 variants were identified as
predominant in Chile, two considered Variants of Concern (VOC) by the WHO (Alpha, and Gamma), one Variant of Interest (Lambda), and two other unflagged lineages (B.1.1 and B.1.1.348). Assuming that the contribution of each variant to the spreading dynamics (a–c) is proportional to their share (i.e., the fraction they represent of the total samples, d–h), we quantified their transmissibility compared to the Alpha variant (i–m). The Lambda and Gamma variants showed a 1.05 (95% CI [1.01,1.14]) and 1.16 (95% CI [1.11,1.21]) fold higher reproduction number than the Alpha variant. Other variants had a comparatively lower influence on the spread. Shaded areas in the b–h panels account for the 95% credible intervals of the model fit. Complementary parameters and variables are summarized in Supplementary Figure S1.
Mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants

August 2021

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816 Reads

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1 Citation

The emergence of SARS-CoV-2 variants of concern endangers the long-term control of COVID-19, especially in countries with limited genomic surveillance. In this work, we explored genomic drivers of contagion in Chile. We sequenced 3443 SARS-CoV-2 genomes collected between January and July 2021, where the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. Using a Bayesian model tailored for limited genomic surveillance, we found that Lambda and Gamma variants' reproduction numbers were about 5% and 16% larger than Alpha's, respectively. We observed an overabundance of mutations in the Spike gene, strongly correlated with the variant's transmissibility. Furthermore, the variants' mutational signatures featured a breakpoint concurrent with the beginning of vaccination (mostly CoronaVac, an inactivated virus vaccine), indicating an additional putative selective pressure. Thus, our work provides a reliable method for quantifying novel variants' transmissibility under subsampling (as newly-reported Delta, B.1.617.2) and highlights the importance of continuous genomic surveillance.



Citations (8)


... An important example is the genomic surveillance of infectious diseases, where the mutational dynamics of a particular pathogen (and variants thereof) are tracked and quantified [5]. In the context of the COVID-19 pandemic, genomic surveillance has unveiled the rapid evolution of SARS-CoV-2 and signalled the emergence of variants with increased transmissibility and partial immune escape (e.g., those labelled as Variants of Concern VoC) [6][7][8][9][10][11]. ...

Reference:

Model-based assessment of sampling protocols for infectious disease genomic surveillance
Early mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants in Chile

... Consequently, the analysis of infectious diseases comprises data at multiple scales, from bio-molecular to global social dynamics, thus making epidemic data rather specific [9] in the era of big data science. In this respect, theoretical concepts developed in complex systems physics can help to recognise properties that emerge at a larger scale [10,11]. In particular, collective dynamic effects occurring in the nonlinear systems under different constraints, driving modes and self-organisation often lead to certain regularities and typical patterns that can be revealed using a complex systems perspective in analysing pertinent empirical data. ...

Societal feedback induces complex and chaotic dynamics in endemic infectious diseases

... Canadian policy makers need to be cognizant of cooperating within international frameworks that will serve Canadians and other countries well and remain aware of issues regarding vaccine availability, systemic disadvantages, and daily individual struggles that are commonplace in other countries (55). Moderate policies that are not too strong or too weak optimize desired health outcomes (56). For instance, policies that reduce social contacts to a moderate level and avoid full lockdowns may achieve outcomes that protect the healthcare system and avoid economic consequences (57) while avoiding severe conditions that exacerbate psychological distress. ...

Interplay Between Risk Perception, Behavior, and COVID-19 Spread

Frontiers in Physics

... Mass vaccination is necessary to protect the populace from disease and build herd immunity (APIC 2021). Moreover, in the opinion of Czypionka et al. (2022) the current rate of completely vaccinated individuals in most European nations is insufficient to break transmission chains and lower infection rates especially among young population. In order to acquire herd immunity against viral diseases like the measles and polio, a research found that around 90% and 80% of the population, respectively, needed to be immunized (WHO 2020). ...

The benefits, costs and feasibility of a low incidence COVID-19 strategy

The Lancet Regional Health - Europe

... Moderate policies that are not too strong or too weak optimize desired health outcomes (56). For instance, policies that reduce social contacts to a moderate level and avoid full lockdowns may achieve outcomes that protect the healthcare system and avoid economic consequences (57) while avoiding severe conditions that exacerbate psychological distress. This relationship between psychological distress and adherence to public health directives warrants continued monitoring as the effects of prolonged mitigation may evolve into serious pathology and adherence behaviors deteriorate due to psychological fatigue. ...

Low case numbers enable long-term stable pandemic control without lockdowns

Science Advances

... Over the last years, a large number of authors has made contributions to predict the development of SARS-CoV-2. Simple ordinary differential equation (ODE)-based SIR (Susceptible-Infected-Removed)-type models [3,4] have been used for their efficiency in time-critical moments. More flexible integro-differential equation-based models can be used to allow for more realistic disease stage transitions; see, e.g., [5]. ...

Relaxing restrictions at the pace of vaccination increases freedom and guards against further COVID-19 waves

... Therefore it is crucial to quickly increase the distribution of immunisations and booster shots, while also becoming ready for any new variants (BMJ 2022). To boost vaccination rates among the masses, factors such as vaccine reluctance, misinformation about vaccinations, motivation, and health literacy play a crucial role (Priesmann et al. 2021). ...

Towards a European strategy to address the COVID-19 pandemic
  • Citing Article
  • August 2021

The Lancet

... For example, potential cross-immunity from exposure to other coronaviruses may be playing a role in reducing the severity of COVID-19 in African populations. In addition, the widespread use of insecticide-treated bed nets for malaria control may have also contributed to a lower incidence of COVID-19 in Africa [6][7][8][9][10][11][12]. ...

A look into the future of the COVID-19 pandemic in Europe: an expert consultation

The Lancet Regional Health - Europe