Estimates of serial interval for COVID-19: A systematic review and meta-analysis
| Autor: | Laxmi Kant Dwivedi, Balram Rai, Anandi Shukla |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Microbiology (medical)
medicine.medical_specialty Epidemiology Disease Article 03 medical and health sciences 0302 clinical medicine Serial interval Statistics Medicine 030212 general & internal medicine Statistic 030219 obstetrics & reproductive medicine business.industry Public Health Environmental and Occupational Health Outbreak COVID-19 Random effects model Meta-analysis Infectious Diseases Systematic review Public aspects of medicine RA1-1270 business Contact tracing |
| Zdroj: | Clinical Epidemiology and Global Health, Vol 9, Iss, Pp 157-161 (2021) Clinical Epidemiology and Global Health |
| ISSN: | 2213-3984 |
| Popis: | Background On 11th March 2020, the World Health Organization declared COVID-19 as Pandemic. The estimation of transmission dynamics in the initial days of the outbreak of any infectious disease is crucial to control its spread in a new area. The serial interval is one of the significant epidemiological measures that determine the spread of infectious disease. It is the time interval between the onset of symptoms in the primary and secondary case. Objective The present study aimed at the qualitative and quantitative synthesis of the currently available evidence for the serial interval of COVID-19. Methodology Data on serial intervals were extracted from 11 studies following a systematic review. A meta-analysis was performed to estimate the pooled estimate of the serial interval. The heterogeneity and bias in the included studies were tested by various statistical measures and tests, including I2 statistic, Cochran's Q test, Egger's test, and Beggs's test. Result The pooled estimate for the serial interval was 5.40 (5.19, 5.61) and 5.19 (4.37, 6.02) days by the fixed and random effects model, respectively. The heterogeneity between the studies was found to be 89.9% by I2 statistic. There is no potential bias introduced in the meta-analysis due to small study effects. Conclusion The present review provides sufficient evidence for the estimate of serial interval of COVID-19, which can help in understanding the epidemiology and transmission of the disease. The information on serial interval can be useful in developing various policies regarding contact tracing and monitoring community transmission of COVID-19. |
| Databáze: | OpenAIRE |
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