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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. COMMUNICATIONS MEDICINE 2024; 4:143. [PMID: 39009723 PMCID: PMC11250817 DOI: 10.1038/s43856-024-00570-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 07/04/2024] [Indexed: 07/17/2024] Open
Abstract
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.
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Affiliation(s)
- Leighton M Watson
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand.
| | - Michael J Plank
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
| | | | - Joanne R Chapman
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Joanne Hewitt
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Helen Morris
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Alvaro Orsi
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Michael Bunce
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Christl A Donnelly
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom
| | - Nicholas Steyn
- Department of Statistics, University of Oxford, Oxford, United Kingdom
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Perry WB, Chrispim MC, Barbosa MRF, de Souza Lauretto M, Razzolini MTP, Nardocci AC, Jones O, Jones DL, Weightman A, Sato MIZ, Montagner C, Durance I. Cross-continental comparative experiences of wastewater surveillance and a vision for the 21st century. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170842. [PMID: 38340868 DOI: 10.1016/j.scitotenv.2024.170842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/12/2024]
Abstract
The COVID-19 pandemic has brought the epidemiological value of monitoring wastewater into sharp focus. The challenges of implementing and optimising wastewater monitoring vary significantly from one region to another, often due to the array of different wastewater systems around the globe, as well as the availability of resources to undertake the required analyses (e.g. laboratory infrastructure and expertise). Here we reflect on the local and shared challenges of implementing a SARS-CoV-2 monitoring programme in two geographically and socio-economically distinct regions, São Paulo state (Brazil) and Wales (UK), focusing on design, laboratory methods and data analysis, and identifying potential guiding principles for wastewater surveillance fit for the 21st century. Our results highlight the historical nature of region-specific challenges to the implementation of wastewater surveillance, including previous experience of using wastewater surveillance, stakeholders involved, and nature of wastewater infrastructure. Building on those challenges, we then highlight what an ideal programme would look like if restrictions such as resource were not a constraint. Finally, we demonstrate the value of bringing multidisciplinary skills and international networks together for effective wastewater surveillance.
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Affiliation(s)
| | - Mariana Cardoso Chrispim
- Environmental and Biosciences Department, School of Business, Innovation and Sustainability, Halmstad University, Kristian IV:s väg 3, 30118 Halmstad, Sweden
| | - Mikaela Renata Funada Barbosa
- Environmental Analysis Department, Environmental Company of the São Paulo State (CETESB), Av. Prof. Frederico Hermann Jr., 345, São Paulo CEP 05459-900, Brazil; NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Marcelo de Souza Lauretto
- NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil; School of Arts, Sciences and Humanities, University of Sao Paulo, Rua Arlindo Bettio, 1000, São Paulo CEP 03828-000, Brazil
| | - Maria Tereza Pepe Razzolini
- NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil; School of Public Health, University of Sao Paulo, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Adelaide Cassia Nardocci
- NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil; School of Public Health, University of Sao Paulo, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Owen Jones
- School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK
| | - Davey L Jones
- Environment Centre Wales, Bangor University, Bangor LL57 2UW, UK; Food Futures Institute, Murdoch University, Murdoch WA 6105, Australia
| | | | - Maria Inês Zanoli Sato
- Environmental Analysis Department, Environmental Company of the São Paulo State (CETESB), Av. Prof. Frederico Hermann Jr., 345, São Paulo CEP 05459-900, Brazil; NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Cassiana Montagner
- Environmental Chemistry Laboratory, Institute of Chemistry, University of Campinas, Campinas, São Paulo 13083970, Brazil
| | - Isabelle Durance
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK.
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Tran DPH, You BC, Liu CW, Chen YN, Wang YF, Chung SN, Lee JJ, You SJ. Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: from the perspective of upstream and downstream wastewater-based epidemiology (WBE). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:11576-11590. [PMID: 38221556 DOI: 10.1007/s11356-023-31769-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 12/25/2023] [Indexed: 01/16/2024]
Abstract
Recently, many efforts have been made to address the rapid spread of newly identified COVID-19 virus variants. Wastewater-based epidemiology (WBE) is considered a potential early warning tool for identifying the rapid spread of this virus. This study investigated the occurrence of SARS-CoV-2 in eight wastewater treatment plants (WWTPs) and their sewerage systems which serve most of the population in Taoyuan City, Taiwan. Across the entire study period, the wastewater viral concentrations were correlated with the number of COVID-19 cases in each WWTP (Spearman's r = 0.23-0.76). In addition, it is confirmed that several treatment technologies could effectively eliminate the virus RNA from WWTP influent (> 90%). On the other hand, further results revealed that an inverse distance weighted (IDW) interpolation and hotspot model combined with the geographic information system (GIS) method could be applied to analyze the spatiotemporal variations of SARS-CoV-2 in wastewater from the sewer system. In addition, socio-economic factors, namely, population density, land use, and income tax were successfully identified as the potential drivers which substantially affected the onset of the COVID-19 outbreak in Taiwan. Finally, the data obtained from this study can provide a powerful tool in public health decision-making not only in response to the current epidemic situation but also to other epidemic issues in the future.
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Affiliation(s)
- Duyen Phuc-Hanh Tran
- Department of Civil Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Bo-Cheng You
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
- Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Chen-Wuing Liu
- Department of Water Resource, Taoyuan City Government, Taoyuan City, 320, Taiwan, Republic of China
| | - Yi-Ning Chen
- Department of Bioscience Technology, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Ya-Fen Wang
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
- Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Shu-Nu Chung
- Department of Water Resource, Taoyuan City Government, Taoyuan City, 320, Taiwan, Republic of China
| | - Jin-Jing Lee
- Department of Water Resource, Taoyuan City Government, Taoyuan City, 320, Taiwan, Republic of China
| | - Sheng-Jie You
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China.
- Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China.
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