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1.
Infect Dis Model ; 8(4): 1138-1150, 2023 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-38023490

RESUMO

Background: The public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems. The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19. We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data. Methods: Using county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties, we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29, 2020 to June 30, 2022. We included covariates such as COVID-19 vaccine coverage in the county, comorbidities, demographic variables, and holiday gatherings. Findings: Wastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission. Models that included wastewater had higher predictive power than models that included clinical cases only, increasing the accuracy of the model by 15%. Predicted hospital admissions correlated highly with observed admissions (r = 0.77) with an average difference of 0.013 hospitalizations per 100,000 (95% CI = [0.002, 0.025]). Interpretation: Using wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone. The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.

2.
J Public Health Manag Pract ; 29(6): 854-862, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37566797

RESUMO

CONTEXT: The COVID-19 pandemic sparked efforts across the globe to implement wastewater surveillance for SARS-CoV-2. PROGRAM: New York State (NYS) established the NYS Wastewater Surveillance Network to estimate the levels of COVID-19 community risk and to provide an early indication of SARS-CoV-2 transmission trends. The network is designed to provide a better understanding of public health burdens and to assist health departments to respond effectively to public health threats. IMPLEMENTATION: Wastewater surveillance across NYS increased from sporadic and geographically spare in 2020 to routine and widespread in 2022, reaching all 62 counties in the state and covering 74% of New Yorkers. The network team focused on engaging local health departments and wastewater treatment plants to provide wastewater samples, which are then analyzed through a network-affiliated laboratory. Both participating local health departments and wastewater treatment plants receive weekly memos on current SARS-CoV-2 trends and levels. The data are also made publicly available at the state dashboard. EVALUATION: Using standard indicators to evaluate infectious disease surveillance systems, the NYS Wastewater Surveillance Network was assessed for accuracy, timeliness, and completeness during the first year of operations. We observed 96.5% sensitivity of wastewater to identify substantial/high COVID-19 transmission and 99% specificity to identify low COVID-19 transmission. In total, 80% of results were reported within 1 day of sample collection and were published on the public dashboard within 2 days of sample collection. Among participating wastewater treatment plants, 32.5% provided weekly samples with zero missing data, 31% missed 1 or 2 weeks, and 36.5% missed 3 or more weeks. DISCUSSION: The NYS Wastewater Surveillance Network continues to be a key component of the state and local health departments' pandemic response. The network fosters prompt public health actions through real-time data, enhancing the preparedness capability for both existing and emerging public health threats.


Assuntos
COVID-19 , Humanos , COVID-19/epidemiologia , Saúde Pública , Águas Residuárias , SARS-CoV-2 , Pandemias , Vigilância Epidemiológica Baseada em Águas Residuárias
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