Journal article
Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand
- Abstract:
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Background Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported as cases, is typically much less than one and varies with testing practices and behaviours, making reported cases unreliable as the sole source of data. The concentration of viral RNA in wastewater samples provides an alternate measure of infection prevalence that is not affected by clinical testing, healthcare-seeking behaviour or access to care.
Methods We construct a state-space model with observed data of levels of SARS-CoV-2 in wastewater and reported case incidence and estimate the hidden states of the effective reproduction number, R, and CAR using sequential Monte Carlo methods.
Results We analyse data from 1 January 2022 to 31 March 2023 from Aotearoa New Zealand. Our model estimates that R peaks at 2.76 (95% CrI 2.20, 3.83) around 18 February 2022 and the CAR peaks around 12 March 2022. We calculate that New Zealand’s second Omicron wave in July 2022 is similar in size to the first, despite fewer reported cases. We estimate that the CAR in the BA.5 Omicron wave in July 2022 is approximately 50% lower than in the BA.1/BA.2 Omicron wave in March 2022.
Conclusions Estimating R, CAR, and cumulative number of infections provides useful information for planning public health responses and understanding the state of immunity in the population. This model is a useful disease surveillance tool, improving situational awareness of infectious disease dynamics in real-time.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.4MB, Terms of use)
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(Preview, Supplementary materials, pdf, 11.6MB, Terms of use)
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- Publisher copy:
- 10.1038/s43856-024-00570-3
Authors
- Publisher:
- Springer Nature
- Journal:
- Communications Medicine More from this journal
- Volume:
- 4
- Issue:
- 1
- Article number:
- 143
- Publication date:
- 2024-07-15
- Acceptance date:
- 2024-07-04
- DOI:
- EISSN:
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2730-664X
- Language:
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English
- Pubs id:
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2012828
- Local pid:
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pubs:2012828
- Deposit date:
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2024-07-05
- ARK identifier:
Terms of use
- Copyright holder:
- Watson et al.
- Copyright date:
- 2024
- Rights statement:
- © The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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