SARS-CoV-2: Cross-scale Insights from Ecology and Evolution

Snedden, Celine E.; Makanani, Sara K.; Schwartz, Shawn T.; Gamble, Amandine; Blakey, Rachel V.; Borremans, Benny; Helman, Sarah K; Espericueta, Luisa; Valencia, Alondra; Endo, Andrew; Alfaro, Michael E.; Lloyd‐Smith, James O.

doi:10.1016/j.tim.2021.03.013

Cited by 19 publications

(14 citation statements)

References 113 publications

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“…Attempts to quantify an individual’s airborne infectiousness from swab measurements - even of infectious virus titer - should thus be interpreted with caution. Similarly, viral load should not be treated as a single quantity that rises and falls synchronously throughout the host; spatial models of infection may be required to identify the best correlates of infectiousness [42]. Crucially, there is a period early in infection (around 24 h post-infection in inoculated hamsters) when oral swabs show high viral titers, but air samples exhibit low or undetectable levels of virus.…”

Section: Discussionmentioning

confidence: 99%

Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster

Port

Morris

Yinda

et al. 2022

Preprint

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Airborne transmission is one of the major routes contributing to the spread of SARS-CoV-2. Successful aerosol transmission occurs when people release respiratory particles carrying infectious virus in the fine aerosol size range. It remains poorly understood how infection influences the physiological host factors that are integral to this process. Here we assessed the changes in breathing, exhaled droplets, and released virus early after infection with the Alpha and Delta variants in the Syrian hamster. Infection with the two variants led to only nuanced differences in viral tissue titers, disease severity, or shedding magnitude. Both variants led to a short window of detectable virus in the air between 24 h and 48 h, which was poorly reflected by upper respiratory shedding measured in oropharyngeal swabs. The loss of viable air samples coincided with changes in airway constriction as measured by whole body plethysmography, and a decrease of fine aerosols produced in the 1-10 μm aerodynamic diameter range. We found that male sex was associated with greater viral replication in the upper respiratory tract and virus shedding in the air. This coincided with an exhaled particle profile shifted towards smaller droplets, independent of variant. Transmission efficiency of Alpha and Delta did not differ on average but exhibited clear variation among donor individuals, including a superspreading event. Transmission leading to substantial dual infections only occurred when both viruses were shed by the same donor and exposure was prolonged. These findings provide direct experimental evidence that quantitative and qualitative assessment of exhaled aerosols may be critical for understanding the limitations and determinants of efficient airborne transmission, thus allowing us to control the pandemic with non-pharmaceutical interventions.

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Section: Discussionmentioning

confidence: 99%

Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster

Port

Morris

Yinda

et al. 2022

Preprint

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“…Thus, the selection pressures these pathogens experience from public health interventions, and non-pharmaceutical interventions in particular, have the potential to be very different from the selection pressures operating on endemic pathogens. Third, several novel variants of SARS-CoV-2 with distinct epidemiological profiles have readily emerged [ 49 , 93 , 113 , 115 ]. This speaks to the considerable evolvability of the virus, making it an attractive case study for evolutionary epidemiology.…”

Section: Methodsmentioning

confidence: 99%

When might host heterogeneity drive the evolution of asymptomatic, pandemic coronaviruses?

et al. 2022

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Controlling many infectious diseases, including SARS-Coronavirus-2 (SARS-CoV-2), requires surveillance followed by isolation, contact-tracing and quarantining. These interventions often begin by identifying symptomatic individuals. However, actively removing pathogen strains causing symptomatic infections may inadvertently select for strains less likely to cause symptomatic infections. Moreover, a pathogen’s fitness landscape is structured around a heterogeneous host pool; uneven surveillance efforts and distinct transmission risks across host classes can meaningfully alter selection pressures. Here, we explore this interplay between evolution caused by disease control efforts and the evolutionary consequences of host heterogeneity. Using an evolutionary epidemiology model parameterized for coronaviruses, we show that intense symptoms-driven disease control selects for asymptomatic strains, particularly when these efforts are applied unevenly across host groups. Under these conditions, increasing quarantine efforts have diverging effects. If isolation alone cannot eradicate, intensive quarantine efforts combined with uneven detections of asymptomatic infections (e.g., via neglect of some host classes) can favor the evolution of asymptomatic strains. We further show how, when intervention intensity depends on the prevalence of symptomatic infections, higher removal efforts (and isolating symptomatic cases in particular) more readily select for asymptomatic strains than when these efforts do not depend on prevalence. The selection pressures on pathogens caused by isolation and quarantining likely lie between the extremes of no intervention and thoroughly successful eradication. Thus, analyzing how different public health responses can select for asymptomatic pathogen strains is critical for identifying disease suppression efforts that can effectively manage emerging infectious diseases. Supplementary Information The online version contains supplementary material available at 10.1007/s11071-022-07548-7.

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“…Transmission of all infections occurs at different spatial scales [18,19] that depend on the pathogen, host movement patterns, immunity, and other factors. Genomic data can help to identify how pathogens are related through space and time (Figure 1A) and thereby track outbreaks across all spatial scales, from within-hospital outbreaks to international pandemics [20,21].…”

Section: Uncovering the Spatial Scales Of Transmission And Interventionsmentioning

confidence: 99%

Progress and challenges in virus genomic epidemiology

Hill

Ruis

Bajaj

et al. 2021

Trends in Parasitology

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Genomic epidemiology, which links pathogen genomes with associated metadata to understand disease transmission, has become a key component of outbreak response. Decreasing costs of genome sequencing and increasing computational power provide opportunities to generate and analyse large viral genomic datasets that aim to uncover the spatial scales of transmission, the demographics contributing to transmission patterns, and to forecast epidemic trends. Emerging sources of genomic data and associated metadata provide new opportunities to further unravel transmission patterns. Key challenges include how to integrate genomic data with metadata from multiple sources, how to generate efficient computational algorithms to cope with large datasets, and how to establish sampling frameworks to enable robust conclusions. Virus genomic epidemiology for public healthThe decreasing cost of genomic sequencing combined with increasing computational power has led to an explosion of interest in the application of whole-genome sequencing to public health [1,2]. This is facilitated by genomic epidemiology (see Glossary), the use of pathogen genomes to study the spread of infectious diseases through populations. Together with the field of phylodynamicsthe combination of epidemiology, evolution, and immunodynamics [3]this rapidly growing field has tackled key questions regarding epidemic preparedness and control, increasingly in real-time. HighlightsGenomic epidemiology enables tracking of pathogen transmission over all spatial scales, from local outbreaks to global pandemics, thereby highlighting the scale of interventions required.Combining genomic data with individuallevel metadata can identify demographic factors driving transmission patterns.The power of genomic epidemiology is increasing due to better models, methods, and novel technologies, including new sample-collection protocols and metadata.Future integration of virus genomic data may enable forecasting of the spatial spread and ignition/decline of epidemics.

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SARS-CoV-2: Cross-scale Insights from Ecology and Evolution

Cited by 19 publications

References 113 publications

Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster

Host and viral determinants of airborne transmission of SARS-CoV-2 in the Syrian hamster

When might host heterogeneity drive the evolution of asymptomatic, pandemic coronaviruses?

Progress and challenges in virus genomic epidemiology

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