Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand
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 testi...
| Main Authors: | , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Nature Research
2024
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| _version_ | 1811140222012882944 |
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| author | Watson, LM Plank, MJ Armstrong, BA Chapman, JR Hewitt, J Morris, H Orsi, A Bunce, M Donnelly, CA Steyn, N |
| author_facet | Watson, LM Plank, MJ Armstrong, BA Chapman, JR Hewitt, J Morris, H Orsi, A Bunce, M Donnelly, CA Steyn, N |
| author_sort | Watson, LM |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-09-25T04:18:33Z |
| format | Journal article |
| id | oxford-uuid:34f95083-c4b6-494b-9b59-eb47970330c6 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:18:33Z |
| publishDate | 2024 |
| publisher | Nature Research |
| record_format | dspace |
| spelling | oxford-uuid:34f95083-c4b6-494b-9b59-eb47970330c62024-07-24T19:33:46ZJointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New ZealandJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:34f95083-c4b6-494b-9b59-eb47970330c6EnglishJisc Publications RouterNature Research2024Watson, LMPlank, MJArmstrong, BAChapman, JRHewitt, JMorris, HOrsi, ABunce, MDonnelly, CASteyn, NBackground: 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. |
| spellingShingle | Watson, LM Plank, MJ Armstrong, BA Chapman, JR Hewitt, J Morris, H Orsi, A Bunce, M Donnelly, CA Steyn, N Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand |
| title | Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand |
| title_full | Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand |
| title_fullStr | Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand |
| title_full_unstemmed | Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand |
| title_short | Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand |
| title_sort | jointly estimating epidemiological dynamics of covid 19 from case and wastewater data in aotearoa new zealand |
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