Read on Twitter
Viral loads (& age but not symptoms) influences transmission probability, incubation period & symptomatic/asymptomatic outcome.
Fantastic new study @dr_michaelmarks. Tons to learn & haven't seen any detailed thread yet, so here's one. https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30985-3/fulltext
Fantastic new study @dr_michaelmarks. Tons to learn & haven't seen any detailed thread yet, so here's one. https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30985-3/fulltext
Background
We know that transmission of SARS-CoV-2 is highly heterogeneous, with most cases infecting no one & minority of cases infecting 1 to many. How much of this is due to variation in infectiousness vs...
@_akiraendo @AdamJKucharski @sbfnk @seabbs
https://doi.org/10.12688/wellcomeopenres.15842.1
We know that transmission of SARS-CoV-2 is highly heterogeneous, with most cases infecting no one & minority of cases infecting 1 to many. How much of this is due to variation in infectiousness vs...
@_akiraendo @AdamJKucharski @sbfnk @seabbs
https://doi.org/10.12688/wellcomeopenres.15842.1
differences in # & type of contacts including setting & activity (indoors, singing, temp/RH, etc.), & susceptibility of contacts? We have evidence that all of these things likely matter, but evidence linking viral loads of index patient to infection of their contacts was missing.
Why does this matter? Lots of reasons. A few key ones:
If viral loads predicts transmission, then:
-vaccines that reduce viral loads will likely reduce transmission
-individual traits that influence viral loads would also influence transmission
-we can map loads to infectiousness
If viral loads predicts transmission, then:
-vaccines that reduce viral loads will likely reduce transmission
-individual traits that influence viral loads would also influence transmission
-we can map loads to infectiousness
Methods
This study (part of RCT on hydrox. reducing transmsission) took swabs from symptomatic people (median 4d since onset), measured viral loads & followed contacts for infection/disease w/ repeated swabs & symptom monitoring.
This study (part of RCT on hydrox. reducing transmsission) took swabs from symptomatic people (median 4d since onset), measured viral loads & followed contacts for infection/disease w/ repeated swabs & symptom monitoring.
Results
- (left fig) Only 32% of index cases w/ 1+ contact transmitted to 1-5 contacts.
- (right fig) Prob trans inc. w/ viral load of index case from 12% to 24% (but I would like to see more than 3 bins of loads; is pattern linear? asymptomatic? sigmoid?)
- (left fig) Only 32% of index cases w/ 1+ contact transmitted to 1-5 contacts.
- (right fig) Prob trans inc. w/ viral load of index case from 12% to 24% (but I would like to see more than 3 bins of loads; is pattern linear? asymptomatic? sigmoid?)
Prob transmission increased w/ age of index & contact, household (vs healthcare/nursing home) contact (likely duration higher) but NOT w/ symptoms (cough, runny nose) or mask use by contact.
Interestingly, viral load was higher for index patients w/ cough, fever, loss of smell, runny nose (some on edge of significance but 0.05 is arbitrary & P = 0.019 & 0.087 aren't that different), but not difficult breathing (dyspnoea).
Despite this, as noted above, symptoms (& mask) didn't influence transmission, either in univariate or multivariate analysis. This contrasts w/ another study suggesting cough influenced transmission: https://academic.oup.com/cid/article/71/16/2099/5835845
Initial viral loads of contacts influenced whether they went on to develop symptoms & incub period. Not clear if this was b/c some contacts were tested later in infection & had more time to develop higher loads & shorter subsequent incub period (exact time of infection not known)
A link b/w viral loads & disease severity was also found by @VirusesImmunity w/ saliva loads being stronger predictor than NP (nasal)
https://www.medrxiv.org/content/10.1101/2021.01.04.21249236v2
https://www.medrxiv.org/content/10.1101/2021.01.04.21249236v2
Viral load of index patient was not strongly correlated w/ load in infected contacts (paper says P=0.10 but relationship looks weaker than that; full stats of analysis not given).
Bonus result: Fraction of contacts that never became symptomatic w/in 14d was only 56% (230/429). Not sure why, but this is very high compared to similar studies in meta-analysis by @nicolamlow @dianacarbg
Ideas?
https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003346
Ideas?
https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003346
Big Conclusions
-Viral loads in index patients, even 4d post onset are predictor of actual infectiousness. This has long been discussed in context of interpreting viral loads vs age, infectiousness & other patterns. @angie_rasmussen @apsmunro @DrZoeHyde @michaelmina_lab
-Viral loads in index patients, even 4d post onset are predictor of actual infectiousness. This has long been discussed in context of interpreting viral loads vs age, infectiousness & other patterns. @angie_rasmussen @apsmunro @DrZoeHyde @michaelmina_lab
To make use of this relationship quantitatively would require raw data to re-analyze (see above) & we'd need to map viral loads into common unit from diff studies (no easy matter for many of us who have tried this). @michaelmina_lab @MackayIM @bennyborremans
Regardless, it means viral load values have value in assessing infectiousness & could be used to assess effects of vaccination in reducing infectiousness (with caveats above). Unfortunately these data haven't been presented yet (link if I missed them): https://twitter.com/DiseaseEcology/status/1339093180151603202
Additional analyses needed: does index patient viral load predict Y/N symptomatic illness in contact? Not analyzed directly, but lack of relationship b/w loads of index & contact & link b/w contact loads & symptoms suggests no.
This would mean that shedding from index case influences prob of infection in contact but that other traits/factors determine subsequent viral dynamics/loads & symptom development in infected contacts.
It is now possible to determine relative importance of infectiousness & # contacts in determining secondary infections using data on # of household & other contacts w/ assumptions about contact types in this study (health care & nursing homes) & others.
Addition: another paper w/ a very large dataset also found a relationship b/w viral load, age & attack rates.
h/t @LucaFerrettiEvo
http://modmedmicro.nsms.ox.ac.uk/wp-content/uploads/2021/01/infectivity_manuscript_20210119_merged.pdf
h/t @LucaFerrettiEvo
http://modmedmicro.nsms.ox.ac.uk/wp-content/uploads/2021/01/infectivity_manuscript_20210119_merged.pdf
It also showed that rapid tests were quite effective in detecting the more infectious viral loads. @michaelmina_lab
