IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v24y2021i2d10.1007_s10729-020-09525-1.html
   My bibliography  Save this article

Aligning SARS-CoV-2 indicators via an epidemic model: application to hospital admissions and RNA detection in sewage sludge

Author

Listed:
  • Edward H. Kaplan

    (Yale School of Management
    Yale University
    Yale University)

  • Dennis Wang

    (Yale School of Medicine)

  • Mike Wang

    (Yale University)

  • Amyn A. Malik

    (Yale University)

  • Alessandro Zulli

    (Yale University)

  • Jordan Peccia

    (Yale University)

Abstract

Ascertaining the state of coronavirus outbreaks is crucial for public health decision-making. Absent repeated representative viral test samples in the population, public health officials and researchers alike have relied on lagging indicators of infection to make inferences about the direction of the outbreak and attendant policy decisions. Recently researchers have shown that SARS-CoV-2 RNA can be detected in municipal sewage sludge with measured RNA concentrations rising and falling suggestively in the shape of an epidemic curve while providing an earlier signal of infection than hospital admissions data. The present paper presents a SARS-CoV-2 epidemic model to serve as a basis for estimating the incidence of infection, and shows mathematically how modeled transmission dynamics translate into infection indicators by incorporating probability distributions for indicator-specific time lags from infection. Hospital admissions and SARS-CoV-2 RNA in municipal sewage sludge are simultaneously modeled via maximum likelihood scaling to the underlying transmission model. The results demonstrate that both data series plausibly follow from the transmission model specified and provide a 95% confidence interval estimate of the reproductive number R0 ≈ 2.4 ± 0.2. Sensitivity analysis accounting for alternative lag distributions from infection until hospitalization and sludge RNA concentration respectively suggests that the detection of viral RNA in sewage sludge leads hospital admissions by 3 to 5 days on average. The analysis suggests that stay-at-home restrictions plausibly removed 89% of the population from the risk of infection with the remaining 11% exposed to an unmitigated outbreak that infected 9.3% of the total population.

Suggested Citation

  • Edward H. Kaplan & Dennis Wang & Mike Wang & Amyn A. Malik & Alessandro Zulli & Jordan Peccia, 2021. "Aligning SARS-CoV-2 indicators via an epidemic model: application to hospital admissions and RNA detection in sewage sludge," Health Care Management Science, Springer, vol. 24(2), pages 320-329, June.
    • Handle: RePEc:kap:hcarem:v:24:y:2021:i:2:d:10.1007_s10729-020-09525-1
    DOI: 10.1007/s10729-020-09525-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-020-09525-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10729-020-09525-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Edward H. Kaplan, 2020. "Containing 2019-nCoV (Wuhan) coronavirus," Health Care Management Science, Springer, vol. 23(3), pages 311-314, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alec Morton & Ebru Bish & Itamar Megiddo & Weifen Zhuang & Roberto Aringhieri & Sally Brailsford & Sarang Deo & Na Geng & Julie Higle & David Hutton & Mart Janssen & Edward H Kaplan & Jianbin Li & Món, 2021. "Introduction to the special issue: Management Science in the Fight Against Covid-19," Health Care Management Science, Springer, vol. 24(2), pages 251-252, June.
    2. Xuan Li & Huan Liu & Li Gao & Samendra P. Sherchan & Ting Zhou & Stuart J. Khan & Mark C. M. Loosdrecht & Qilin Wang, 2023. "Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    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. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    2. Gillis, Melissa & Urban, Ryley & Saif, Ahmed & Kamal, Noreen & Murphy, Matthew, 2021. "A simulation–optimization framework for optimizing response strategies to epidemics," Operations Research Perspectives, Elsevier, vol. 8(C).
    3. Anna Nagurney & Pritha Dutta, 2021. "A Multiclass, Multiproduct Covid-19 Convalescent Plasma Donor Equilibrium Model," SN Operations Research Forum, Springer, vol. 2(3), pages 1-30, September.
    4. Joseph T. Chang & Forrest W. Crawford & Edward H. Kaplan, 2021. "Repeat SARS-CoV-2 testing models for residential college populations," Health Care Management Science, Springer, vol. 24(2), pages 305-318, June.
    5. Atul Pokharel & Robert Soulé & Avi Silberschatz, 2021. "A case for location based contact tracing," Health Care Management Science, Springer, vol. 24(2), pages 420-438, June.
    6. Matthias Klumpp & Dominic Loske & Silvio Bicciato, 2022. "COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(8), pages 1263-1285, November.
    7. Eugenio F. Sánchez-Úbeda & Pedro Sánchez-Martín & Macarena Torrego-Ellacuría & Ángel Del Rey-Mejías & Manuel F. Morales-Contreras & José-Luis Puerta, 2021. "Flexibility and Bed Margins of the Community of Madrid’s Hospitals during the First Wave of the SARS-CoV-2 Pandemic," IJERPH, MDPI, vol. 18(7), pages 1-22, March.
    8. Sarbast Moslem & Tiziana Campisi & Agnieszka Szmelter-Jarosz & Szabolcs Duleba & Kh Md Nahiduzzaman & Giovanni Tesoriere, 2020. "Best–Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    9. Chang, Joseph T. & Kaplan, Edward H., 2023. "Modeling local coronavirus outbreaks," European Journal of Operational Research, Elsevier, vol. 304(1), pages 57-68.
    10. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2020. "Testing, Voluntary Social Distancing and the Spread of an Infection," NBER Working Papers 27483, National Bureau of Economic Research, Inc.

    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:kap:hcarem:v:24:y:2021:i:2:d:10.1007_s10729-020-09525-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.