This analysis of #covid19 clusters in Japan in the first two and a half months of the epidemic there presents some really interesting data. It reinforces many points I and others have made in the last weeks re clusters and superspreading events wwwnc.cdc.gov/eid/article/26…
The researchers identified 61 clusters where five or more people were infected at once (they did not count onward transmission from these people that happened later):
largest cluster was more than 100 cases, most were 5-10 cases.
largest cluster was more than 100 cases, most were 5-10 cases.
The places where they found clusters:
18 healthcare facilities
10 care facilities such as nursing homes or daycare centers
10 restaurants or bars
8 workplaces
7 music events, such as concerts or karaoke parties
5 gyms
2 ceremonial functions
1 transport-related (airplane)
18 healthcare facilities
10 care facilities such as nursing homes or daycare centers
10 restaurants or bars
8 workplaces
7 music events, such as concerts or karaoke parties
5 gyms
2 ceremonial functions
1 transport-related (airplane)
“many #COVID19 clusters were associated with heavy breathing in close proximity, such as singing at karaoke parties, cheering at clubs, having conversations in bars, and exercising in gymnasiums.”
3Cs: closed spaces with poor ventilation, crowded places, close-contact settings
3Cs: closed spaces with poor ventilation, crowded places, close-contact settings
The researchers also identified the people that likely started 22 of these clusters and made two interesting observations:
1. Half of them were between 20 and 39 years old, so younger than expected from the age distribution of #covid19 cases.
“We do not know whether social, biological, or both factors play a role in the difference in transmission patterns between the younger and older persons.”
“We do not know whether social, biological, or both factors play a role in the difference in transmission patterns between the younger and older persons.”
That’s to say: Maybe this is simply because young people tend to go more often to the kinds of events that play a role here (the researchers did not analyze primary cases for health care clusters). Or there may be some other biological factor as well.
2. 9 of the 22 cases that probably touched off clusters had no symptoms or no symptoms yet at the time of transmission:
"probable primary #COVID19 case-patients appear to transmit the virus and generate clusters even in the absence of apparent respiratory symptoms, such as cough"
"probable primary #COVID19 case-patients appear to transmit the virus and generate clusters even in the absence of apparent respiratory symptoms, such as cough"
As noted before these kinds of studies come with a lot of caveats: Memory is imperfect, all kinds of biases play a role, cases can be missed, etc. But clearly data like this is crucial and I would love to see more studies like this (digital contact tracing might help with that).
That’s to say: Maybe this is simply because young people tend to go more often to the kinds of events that play a role here (the researchers did not analyze primary cases for health care clusters). Or there may be some other biological factor as well.
2. 9 of the 22 cases that probably touched off clusters had no symptoms or no symptoms yet at the time of transmission:
"probable primary #COVID19 case-patients appear to transmit the virus and generate clusters even in the absence of apparent respiratory symptoms, such as cough"
"probable primary #COVID19 case-patients appear to transmit the virus and generate clusters even in the absence of apparent respiratory symptoms, such as cough"
As noted before these kinds of studies come with a lot of caveats: Memory is imperfect, all kinds of biases play a role, cases can be missed, etc. But clearly data like this is crucial and I would love to see more studies like this (digital contact tracing might help with that).
