Seroprevalence and infection attack rate of COVID-19 in Indian cities.
Infect Dis Model
; 7(2): 25-32, 2022 Jun.
Article
in English
| MEDLINE | ID: covidwho-1796731
ABSTRACT
Objectives:
Serological surveys were used to infer the infection attack rate in different populations. The sensitivity of the testing assay, Abbott, drops fast over time since infection which makes the serological data difficult to interpret. In this work, we aim to solve this issue.Methods:
We collect longitudinal serological data of Abbott to construct a sensitive decay function. We use the reported COVID-19 deaths to infer the infections, and use the decay function to simulate the seroprevalence and match to the reported seroprevalence in 12 Indian cities.Results:
Our model simulated seroprevalence matchs the reported seroprevalence in most of the 12 Indian cities. We obtain reasonable infection attack rate and infection fatality rate for most of the 12 Indian cities.Conclusions:
Using both reported COVID-19 deaths data and serological survey data, we infer the infection attack rate and infection fatality rate with increased confidence.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Observational study
/
Prognostic study
Language:
English
Journal:
Infect Dis Model
Year:
2022
Document Type:
Article
Affiliation country:
J.idm.2022.03.001
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