A Statistical Model of COVID-19 Infection Incidence in the Southern Indian State of Tamil Nadu

In this manuscript, we present an analysis of COVID-19 infection incidence in the Indian state of Tamil Nadu. We used seroprevalence survey data along with COVID-19 fatality reports from a six-month period (1 June 2020 to 30 November 2020) to estimate age- and sex-specific COVID-19 infection fatalit...

Full description

Saved in:
Bibliographic Details
Published in:International journal of environmental research and public health 2022-09, Vol.19 (17), p.11137
Main Authors: Devi, Tanmay, Gopalan, Kaushik
Format: Article
Language:English
Subjects:
Age groups
Coronaviruses
COVID-19
COVID-19 - epidemiology
COVID-19 vaccines
Estimates
Fatalities
Female
Humans
Immunization
Incidence
India - epidemiology
Infections
Male
Mathematical models
Model matching
Models, Statistical
Population
Public health
Seroepidemiologic Studies
Serology
Severe acute respiratory syndrome coronavirus 2
Statistical models
Surveys
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this manuscript, we present an analysis of COVID-19 infection incidence in the Indian state of Tamil Nadu. We used seroprevalence survey data along with COVID-19 fatality reports from a six-month period (1 June 2020 to 30 November 2020) to estimate age- and sex-specific COVID-19 infection fatality rates (IFR) for Tamil Nadu. We used these IFRs to estimate new infections occurring daily using the daily COVID-19 fatality reports published by the Government of Tamil Nadu. We found that these infection incidence estimates for the second COVID wave in Tamil Nadu were broadly consistent with the infection estimates from seroprevalence surveys. Further, we propose a composite statistical model that pairs a k-nearest neighbours model with a power-law characterisation for "out-of-range" extrapolation to estimate the COVID-19 infection incidence based on observed cases and test positivity ratio. We found that this model matched closely with the IFR-based infection incidence estimates for the first two COVID-19 waves for both Tamil Nadu as well as the neighbouring state of Karnataka. Finally, we used this statistical model to estimate the infection incidence during the recent "Omicron wave" in Tamil Nadu and Karnataka.
ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph191711137