Antonia Ho Profile picture
Jan 24, 2020 5 tweets 4 min read
Early modelling estimates of epidemiological parameters and epidemic predictions of the #Wuhan #coronovirus #nCoV2019 outbreak - our preprint is out now! @JonRead15 @JessicaBridgen @datcummings @chrism0dwk @LancasterUni @UF @CVRinfo
livelancsac-my.sharepoint.com/personal/readj… Image
Another link for paper: drive.google.com/file/d/1fz7Ewl…
Summary estimates:
- early basic reproduction number (R0), i.e. the average number of persons that a new case will infect in a fully susceptible population, is 3.6-4.0. This is higher than the @WHO
estimate of 1.4-2.5, but within the range reported for #SARS in 2002/3 (R0 2-5)
@WHO - Majority (95%) of infections in Wuhan are unidentified, suggesting a large number of infections in the community.
- Assuming no control interventions or change in transmission, further outbreaks in Chinese cities outside of Wuhan and increasing rates of exported cases to other countries are likely. >250,000 infected cases predicted in 2 weeks’ time.

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More from @DrToniHo

Jun 3, 2021
Our paper on co-infections, secondary infections & antimicrobial use in patients hospitalised with #COVID19 in UK during the 1st wave is out in @LancetMicrobe!

@ISARIC1 @CCPUKstudy @CVRinfo @UofGlasgow @EdinburghUni @LivUni @imperialcollege

thelancet.com/journals/lanmi…

A🧵
2/ Of 48,902 hospitalised Covid19 patients enrolled in CCP-UK study (6 Feb - 8 June 20):
- 8,649 (17.7%) had >=1 microbiological investigation
- 1,107 had Covid19-related bacterial infection (blood or respiratory); 70.6% (n=762) were secondary infection (>48 hrs from admission)
3/ Most frequently identified organisms:
- Respiratory co-infection: Staph aureus & Haemophilus influenzae (differ from flu)
- Respiratory 2ry infection: Gram negative organisms & Staph aureus (similar to non-Covid HAI)
- Bloodstream co-/2ry infections: E Coli & Staph aureus
Read 9 tweets
Sep 10, 2020
Delighted to share our paper out in @bmj_latest today.

Risk stratification of hospitalised patients with #COVID19: development and validation of the 4C Mortality Score

bmj.com/content/370/bm…

@ISARIC1 @CCPUKstudy @CVRinfo @UofGlasgow @EdinburghUni @LivUni @imperialcollege
2/ We developed & validated an easy-to-use 8-variable risk stratification score to predict inpatient mortality in hospitalised adults with #COVID19

The 4C Mortality Score uses patient demographics, clinical & blood parameters commonly available at the time of hospital admission: Image
3/ The 4C Mortality Score (range 0-21 pt) stratifies hospitalised patients into 4 risk groups, which can help clinicians optimise treatment:
- Low (<3) - 1% inhospital death
- Intermediate (4-8) - 10%
- High (9-14) - 31%
- Very high (15-21) - 62% Image
Read 8 tweets

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