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Epidemiology of SARS-CoV-2 infection in Karnataka State, South India: Transmission dynamics of symptomatic vs. asymptomatic infections
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20196501
ABSTRACT
Background:
In this report, we describe the epidemiology of SARS-CoV-2 infection, specifically examining how the symptomatic persons drove the transmission in the state of Karnataka, India, during the lockdown phase.Methods:
The study included all the cases reported from March 8 to May 31, 2020 in the state. Any person with history of international or domestic travel from high burden states, those presenting with Influenza-like or Severe Acute Respiratory Illness and high-risk contacts of COVID19 cases, who were SARS-CoV-2 RT-PCR positive were included. Detailed analysis based on contact tracing data available from line-list of the state surveillance unit was performed using cluster analysis software package.Findings:
Amongst the 3404 COVID-19 positive cases, 3096 (91%) were asymptomatic while 308 (9%) were symptomatic. Majority of the asymptomatic cases were in the age range of 16-50 years while symptomatic cases were between 31-65 years. Most of those affected were males. Cluster analysis of 822 cases indicated that the secondary attack rate, size of the cluster (dispersion) and occurrence of overt clinical illness is significantly higher when the index case in a cluster was symptomatic compared to an asymptomatic.Interpretation:
Our findings indicate that both asymptomatic and symptomatic SARS-CoV-2 cases transmit the infection; however, the main driving force behind the spread of infection within the state was significantly higher from symptomatic cases. This has major implications for policies related to testing. Active search for symptomatic cases, subjecting them to testing and treatment should be prioritized for containing the spread of COVID-19.
cc_by_nc_nd
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Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Observational_studies
/
Prognostic_studies
Idioma:
En
Año:
2020
Tipo del documento:
Preprint