Transmissibility of coronavirus between symptomatic and asymptomatic patients: reanalysis of the Ningbo COVID-19 data
Transmissibility of coronavirus between symptomatic and asymptomatic patients: reanalysis of the Ningbo COVID-19 data. Spencer EA, Heneghan C.
Published on July 27, 2020
Transmission Dynamics of COVID-19
||Yin G, Jin H. Comparison of transmissibility of coronavirus between symptomatic and asymptomatic patients: reanalysis of the Ningbo COVID-19 data. JMIR Public Health Surveill 2020;6(2):e19464 DOI: 10.2196/19464
||Community and hospital
||Community, close contacts, person to person
This reanalysis of data from Ningbo, China, showed no difference in the transmission rates of coronavirus between symptomatic and asymptomatic cases.
After excluding the cases related to the super-spreader there was no difference in the transmission rates from symptomatic and asymptomatic cases; Fisher exact test P value of = 0.84.
The odds ratio of coronavirus transmission rates between the symptomatic and asymptomatic patients = 1.2 (95% CI 0.5 to 2.8). The conclusion does not differ from the original analysis by Chen Y et al, that there is no statistically significant difference in the transmissibility of the coronavirus between symptomatic and asymptomatic patients.
What did they do?
This is a reanalysis of transmission from symptomatic and asymptomatic COVID-19 cases, summarised in Chen Y 2020. In the original analysis, the usual chi-square tests were unduly used for some contingency tables with small cell counts including zero, which may violate the assumptions for the chi-square test.
This study used a permutation test to determine the difference in the average numbers of contacts by the symptomatic and asymptomatic cases. Fisher exact tests were used to investigate the difference in the transmission rates between the symptomatic and asymptomatic patients wherever small cell counts were present (eg, less than 5 as a rule of thumb). Odds ratios for symptomatic and asymptomatic groups were also calculated.
The sample size is small. The study attempts to remove certain problems with a previous analysis but the data available remain the same, i.e. a moderately small sample size, so the study needs replication.
|Clearly defined setting
||Demographic characteristics described
||Follow-up length was sufficient
||Transmission outcomes assessed
||Main biases are taken into consideration
What else should I consider?
This is a reanalysis of:
Chen Y, Wang A, Yi B, Keqin D, Haibo W, Jianmei W, et al. The epidemiological characteristics of infection in close contacts of COVID-19 in Ningbo city. Chin J Epidemiol 2020;41(5):668-672. doi: 10.3760/cma.j.cn112338-20200304-00251
based on the fact that in the original analysis, chi-square tests were inappropriately used for some contingency tables with small cell counts including zero, which may violate the assumptions for the chi-square test.
Also, Chen Y et al included the cases associated with a “superspreader” who attended a Buddhist gathering, but the authors here (Yin and Jin) think these are non-generalisable and should be removed as outliers.
About the authors
Carl is Professor of EBM & Director of CEBM at the University of Oxford. He is also a GP and tweets @carlheneghan. He has an active interest in discovering the truth behind health research findings
Dr Elizabeth Spencer; MMedSci, PhD. Epidemiologist, Nuffield Department for Primary Care Health Sciences, University of Oxford.