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Modeling the positive testing rate of COVID-19 in South Africa using a semi-parametric smoother for binomial data

Owokotomo, Olajumoke Evangelina; Manda, Samuel; Cleasen, Jürgen; Kasim, Adetayo; Sengupta, Rudradev; Shome, Rahul; Subhra Paria, Soumya; Reddy, Tarylee; Shkedy, Ziv

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Authors

Olajumoke Evangelina Owokotomo

Samuel Manda

Jürgen Cleasen

Adetayo Kasim

Rudradev Sengupta

Rahul Shome

Soumya Subhra Paria

Tarylee Reddy

Ziv Shkedy



Abstract

Identification and isolation of COVID-19 infected persons plays a significant role in the control of COVID-19 pandemic. A country's COVID-19 positive testing rate is useful in understanding and monitoring the disease transmission and spread for the planning of intervention policy. Using publicly available data collected between March 5th, 2020 and May 31st, 2021, we proposed to estimate both the positive testing rate and its daily rate of change in South Africa with a flexible semi-parametric smoothing model for discrete data. There was a gradual increase in the positive testing rate up to a first peak rate in July, 2020, then a decrease before another peak around mid-December 2020 to mid-January 2021. The proposed semi-parametric smoothing model provides a data driven estimates for both the positive testing rate and its change. We provide an online R dashboard that can be used to estimate the positive rate in any country of interest based on publicly available data. We believe this is a useful tool for both researchers and policymakers for planning intervention and understanding the COVID-19 spread.

Journal Article Type Article
Acceptance Date Jan 13, 2023
Online Publication Date Feb 22, 2023
Publication Date 2023
Deposit Date Jun 5, 2023
Publicly Available Date Jun 5, 2023
Journal Frontiers in Public Health
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 11
Issue 2023
DOI https://doi.org/10.3389/fpubh.2023.979230
Public URL https://durham-repository.worktribe.com/output/1170760

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.






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