Can someone more familiar with the virology comment on the meaning of this statistic? I keep hearing it, but I don't really know how to interpret it. Delta's obviously more infections than the original strain, but could one simply have a virus that "weighs more" than another virus, without being more contagious, and have it have 1000x more "viral mass" or "viral load?"
How should this stat be interpreted epidemiologically? Should we care more about R0 than viral load?
Viral load refers to quantity of viral particles, not weight. A greater viral load suggests faster replication, which can be consequential to disease progression; and it also suggests easier transmission as transmission probability tends to be a function of number of viral particles shed (among other characteristics).
The publication referenced by this news article has not undergone peer-review yet, but it contains additional detail that may be useful to others who already have a basic understanding of the topic [1].
Highlights from [1]:
- "On May 21, 2021 the first local infection of the Delta variant in Guangzhou, Guangdong, China was identified"
- "A total of 167 local infections were identified during the outbreak ..."
- "All cases could be epidemiologically or genetically traced back to the first index case ... for 111 transmission events, the donor and recipient cases were known"
- "Daily sequential PCR testing of the quarantined subjects indicated that the viral loads of Delta infections, when they first become PCR+, were on average ~1000 times greater compared to A/B lineage infections during initial epidemic wave in China in early 2020"
- "The transmission of minor intra-host single nucleotide variants resulted in at least 4 of the 30 substitutions identified in the outbreak, highlighting the contribution of intra-host variants to population level viral diversity during rapid spread"
While the linked news article provides a somewhat shallow overview of the situation, it does pose a crucial question: "Why is the delta variant more contagious?"
If you're curious to learn more about the evolutionary dynamics behind SARS-CoV-2 variants, one accessible resource is this peer reviewed paper from 2017 [2].
Some notes from [2]:
- "A growing body of evidence suggests that the targets of several human vaccines are evolving"
- "For example, resistance to influenza and herpes-virus drugs emerged within a few years of FDA approval, and resistance to antivirals rapidly arises within human immunodeficiency virus (HIV) and hepatitis C virus (HCV)-infected patients"
- "The best documented example of vaccine resistance evolution occurred in Marek’s disease, a commercially important disease of chickens caused by Marek’s disease virus (Gallid herpesvirus II). There, two generations of vaccines were undermined by viral evolution. Those vaccines prevented disease, but even before the pathogen evolved, they did not prevent viral infection, replication, or transmission. Instead, Marek’s disease virus reached large population sizes even within vaccinated hosts and was able to transmit to new hosts. As a result, the virus was likely able to generate genetic diversity within vaccinated hosts, and vaccine-induced selection was able to act during transmission between hosts. The benefits of prophylaxis were thus missing."
- "We have argued that drug resistance has tended to evolve faster than vaccine resistance (figure 1) because, for the most part, drugs are used therapeutically whereas vaccines are used prophylactically, and drugs attack far fewer target sites than do vaccines. This means that drug resistance is more likely to arise in the first place and then spread more rapidly once it has arisen (table 1). By contrast, vaccines prevent infection and transmission and induce immunity against many pathogen target sites, making it hard for vaccine resistance to evolve. ... The few examples of vaccine-associated evolution detected in human and animal pathogens have occurred against vaccines that lack the benefits of one or both of these features."
For even more reading see these peer reviewed publications [3][4].
How should this stat be interpreted epidemiologically? Should we care more about R0 than viral load?