Semiparametric inference of effective reproduction number dynamics from wastewater pathogen surveillance data DOI
Isaac Goldstein, Daniel M. Parker, Sunny C. Jiang

et al.

Biometrics, Journal Year: 2024, Volume and Issue: 80(3)

Published: July 1, 2024

Concentrations of pathogen genomes measured in wastewater have recently become available as a new data source to use when modeling the spread infectious diseases. One promising for this is inference effective reproduction number, average number individuals newly infected person will infect. We propose model where infections arrive according time-varying immigration rate which can be interpreted compound parameter equal product proportion susceptibles population and transmission rate. This allows us estimate from concentrations while avoiding difficult verify assumptions about dynamics susceptible population. As byproduct our primary goal, we also produce estimating case using same framework. test framework an agent-based simulation study with realistic generating mechanism accounts shedding. Finally, apply SARS-CoV-2 Los Angeles, California, RNA collected large treatment facility.

Language: Английский

A flexible framework for local-level estimation of the effective reproductive number in geographic regions with sparse data DOI Creative Commons

Md Sakhawat Hossain,

RK Goyal, Natasha K. Martin

et al.

BMC Medical Research Methodology, Journal Year: 2025, Volume and Issue: 25(1)

Published: March 18, 2025

Our research focuses on local-level estimation of the effective reproductive number, which describes transmissibility an infectious disease and represents average number individuals one person infects at a given time. The ability to accurately estimate in geographically granular regions is critical for disaster planning resource allocation. However, not all have sufficient outcome data; this lack data presents significant challenge accurate estimation. To overcome challenge, we propose two-step approach that incorporates existing $$\:{R}_{t}$$ procedures (EpiEstim, EpiFilter, EpiNow2) using from geographic with (step 1), into covariate-adjusted Bayesian Integrated Nested Laplace Approximation (INLA) spatial model predict sparse or missing 2). flexible framework effectively allows us implement any procedure coarse entirely data. We perform external validation simulation study evaluate proposed method assess its predictive performance. applied our $$\:{R}_{t}\:$$ South Carolina (SC) counties ZIP codes during first COVID-19 wave ('Wave 1', June 16, 2020 – August 31, 2020) second 2', December March 02, 2021). Among three methods used step, EpiNow2 yielded highest accuracy prediction Median county-level percentage agreement (PA) was 90.9% (Interquartile Range, IQR: 89.9–92.0%) 92.5% (IQR: 91.6–93.4%) Wave 1 2, respectively. zip code-level PA 95.2% 94.4–95.7%) 96.5% 95.8–97.1%) Using EpiEstim, ensemble-based median ranging 81.9 90.0%, 87.2-92.1%, 88.4-90.9%, respectively, across both waves granularities. These findings demonstrate methodology useful tool small-area , as yields high

Language: Английский

Citations

0
Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide DOI Creative Commons
Ekaterina Krymova, Benjamı́n Béjar, Dorina Thanou

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2022, Volume and Issue: 119(32)

Published: Aug. 3, 2022

Since the beginning of COVID-19 pandemic, many dashboards have emerged as useful tools to monitor its evolution, inform public, and assist governments in decision-making. Here, we present a globally applicable method, integrated daily updated dashboard that provides an estimate trend evolution number cases deaths from reported data more than 200 countries territories, well 7-d forecasts. One significant difficulties managing quickly propagating epidemic is details dynamic needed forecast are obscured by delays identification irregular reporting. Our forecasting methodology substantially relies on estimating underlying observed time series using robust seasonal decomposition techniques. This allows us obtain forecasts with simple yet effective extrapolation methods linear or log scale. We results assessment our discuss application production global regional risk maps.

Language: Английский

Citations

16
Estimating the effect of mobility on SARS-CoV-2 transmission during the first and second wave of the COVID-19 epidemic, Switzerland, March to December 2020 DOI Creative Commons
Adrian Lison, Joel Persson, Nicolas Banholzer

et al.

Eurosurveillance, Journal Year: 2022, Volume and Issue: 27(10)

Published: March 10, 2022

IntroductionHuman mobility was considerably reduced during the COVID-19 pandemic. To support disease surveillance, it is important to understand effect of on transmission.AimWe compared role first and second wave in Switzerland by studying link between daily travel distances effective reproduction number (

Language: Английский

Citations

15
Analyzing the emerging patterns of SARS‐CoV‐2 Omicron subvariants for the development of next‐gen vaccine: An observational study DOI Creative Commons
Ranjan K. Mohapatra, Snehasish Mishra,

Venkataramana Kandi

et al.

Health Science Reports, Journal Year: 2023, Volume and Issue: 6(10)

Published: Oct. 1, 2023

Understanding the prevalence and impact of SARS-CoV-2 variants has assumed paramount importance. This study statistically analyzed to effectively track emergence spread highlights importance such investigations in developing potential next-gen vaccine combat continuously emerging Omicron subvariants.

Language: Английский

Citations

9
Semiparametric inference of effective reproduction number dynamics from wastewater pathogen surveillance data DOI
Isaac Goldstein, Daniel M. Parker, Sunny C. Jiang

et al.

Biometrics, Journal Year: 2024, Volume and Issue: 80(3)

Published: July 1, 2024

Concentrations of pathogen genomes measured in wastewater have recently become available as a new data source to use when modeling the spread infectious diseases. One promising for this is inference effective reproduction number, average number individuals newly infected person will infect. We propose model where infections arrive according time-varying immigration rate which can be interpreted compound parameter equal product proportion susceptibles population and transmission rate. This allows us estimate from concentrations while avoiding difficult verify assumptions about dynamics susceptible population. As byproduct our primary goal, we also produce estimating case using same framework. test framework an agent-based simulation study with realistic generating mechanism accounts shedding. Finally, apply SARS-CoV-2 Los Angeles, California, RNA collected large treatment facility.

Language: Английский

Citations

3