IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i17p11137-d907343.html
   My bibliography  Save this article

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

Author

Listed:
  • Tanmay Devi

    (Department of Computing and Data Sciences, FLAME University, Pune 412115, India
    Current address: Department of Social Sciences, Rice University, Houston, TX 77005, USA.
    These authors contributed equally to this work.)

  • Kaushik Gopalan

    (Department of Computing and Data Sciences, FLAME University, Pune 412115, India
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • Tanmay Devi & Kaushik Gopalan, 2022. "A Statistical Model of COVID-19 Infection Incidence in the Southern Indian State of Tamil Nadu," IJERPH, MDPI, vol. 19(17), pages 1-10, September.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:11137-:d:907343
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/17/11137/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/17/11137/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew T. Levin & William P. Hanage & Nana Owusu-Boaitey & Kensington B. Cochran & Seamus P. Walsh & Gideon Meyerowitz-Katz, 2020. "Assessing the Age Specificity of Infection Fatality Rates for COVID-19: Systematic Review, Meta-analysis, & Public Policy Implications," NBER Working Papers 27597, National Bureau of Economic Research, Inc.
    2. Hani Amir Aouissi & Ahmed Hamimes & Mostefa Ababsa & Lavinia Bianco & Christian Napoli & Feriel Kheira Kebaili & Andrey E. Krauklis & Hafid Bouzekri & Kuldeep Dhama, 2022. "Bayesian Modeling of COVID-19 to Classify the Infection and Death Rates in a Specific Duration: The Case of Algerian Provinces," IJERPH, MDPI, vol. 19(15), pages 1-18, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fattahi, Mohammad & Keyvanshokooh, Esmaeil & Kannan, Devika & Govindan, Kannan, 2023. "Resource planning strategies for healthcare systems during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 192-206.
    2. Ali Athamena & Aissam Gaagai & Hani Amir Aouissi & Juris Burlakovs & Selma Bencedira & Ivar Zekker & Andrey E. Krauklis, 2022. "Chemometrics of the Environment: Hydrochemical Characterization of Groundwater in Lioua Plain (North Africa) Using Time Series and Multivariate Statistical Analysis," Sustainability, MDPI, vol. 15(1), pages 1-28, December.
    3. Anna Scherbina, 2021. "Assessing the Optimality of a COVID Lockdown in the United States," Economics of Disasters and Climate Change, Springer, vol. 5(2), pages 177-201, July.
    4. Antonio Diez de los Rios, 2022. "A macroeconomic model of an epidemic with silent transmission and endogenous self‐isolation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 581-625, February.
    5. Saskia Morwinsky & Natalie Nitsche & Enrique Acosta, 2021. "COVID-19 fatality in Germany: Demographic determinants of variation in case-fatality rates across and within German federal states during the first and second waves," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(45), pages 1355-1372.
    6. Neha Deopa & Piergiuseppe Fortunato, 2022. "Language and the cultural markers of COVID-19," Post-Print hal-03665755, HAL.
    7. Miguel Casares & Paul Gomme & Hashmat Khan, 2022. "COVID‐19 pandemic and economic scenarios for Ontario," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 503-539, February.
    8. Lin Ma & Gil Shapira & Damien de Walque & Quy‐Toan Do & Jed Friedman & Andrei A. Levchenko, 2022. "The Intergenerational Mortality Trade‐Off Of Covid‐19 Lockdown Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1427-1468, August.
    9. Michalski Tomasz & Stępień Joanna, 2021. "Ageing in European post-communist countries – is it a threat to the welfare system?," Environmental & Socio-economic Studies, Sciendo, vol. 9(2), pages 63-71, June.
    10. Egor Malkov, 2021. "Spousal Occupational Sorting and COVID-19 Incidence: Evidence from the United States," Papers 2107.14350, arXiv.org, revised Sep 2021.
    11. Paul Labonne & Leif Anders Thorsrud, 2023. "Risky news and credit market sentiment," Working Papers No 14/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    12. Jan Krzysztof Solarz & Krzysztof Waliszewski, 2020. "Holistic Framework for COVID-19 Pandemic as Systemic Risk," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 340-351.
    13. Ferdinand von Siemens, 2021. "Motivated Beliefs and the Elderly's Compliance With Covid-19 Measures," CESifo Working Paper Series 8832, CESifo.
    14. Andrew Perrault & Marie Charpignon & Jonathan Gruber & Milind Tambe & Maimuna Majumder, 2020. "Designing Efficient Contact Tracing Through Risk-Based Quarantining," NBER Working Papers 28135, National Bureau of Economic Research, Inc.
    15. Quang Dang Nguyen & Mikhail Prokopenko, 2022. "A general framework for optimising cost-effectiveness of pandemic response under partial intervention measures," Papers 2205.08996, arXiv.org, revised Nov 2022.
    16. Christina Bohk-Ewald & Enrique Acosta & Timothy Riffe & Christian Dudel & Mikko Myrskylä, 2021. "Magnitude, global variation, and temporal development of the COVID-19 infection fatality burden," MPIDR Working Papers WP-2021-024, Max Planck Institute for Demographic Research, Rostock, Germany.
    17. Kordonis, Ioannis & Lagos, Athanasios-Rafail & Papavassilopoulos, George P., 2022. "Nash social distancing games with equity constraints: How inequality aversion affects the spread of epidemics," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    18. Claudius Gros & Thomas Czypionka & Daniel Gros, 2021. "When to end a lock down? How fast must vaccination campaigns proceed in order to keep health costs in check?," Papers 2103.15544, arXiv.org, revised Jan 2022.
    19. Fulvio Lauretani & Marco Salvi & Irene Zucchini & Crescenzo Testa & Chiara Cattabiani & Arianna Arisi & Marcello Maggio, 2023. "Relationship between Vitamin D and Immunity in Older People with COVID-19," IJERPH, MDPI, vol. 20(8), pages 1-19, April.
    20. Mouré, Christopher, 2022. "Costly Efficiencies: Health Care Spending, COVID-19, and the Public/Private Health Care Debate," Review of Capital as Power, Capital As Power - Toward a New Cosmology of Capitalism, vol. 2(2), pages 17-45.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:11137-:d:907343. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.