Collaborative modeling key to improving outbreak response

Reich, Nicholas G.; Ray, Evan L.

doi:10.1073/pnas.2200703119

Cited by 6 publications

(2 citation statements)

References 13 publications

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“…To inform mitigation and control measures and provide local situational awareness, public health agencies have produced real-time reports on emerging variants and local variant prevalence [26][27][28][29][30] . An understanding of variant properties (e.g., immune evasion, transmissibility, and therapeutic efficacy) combined with accurate regional estimates of each variant's prevalence has been applied to optimize public health strategies to mitigate transmission and disease 14,16,21,[31][32][33][34][35][36] .…”

Section: Introductionmentioning

confidence: 99%

Leveraging global genomic sequencing data to estimate local variant dynamics

Susswein

Johnson

Kassa

et al. 2023

Preprint

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Accurate, reliable, and timely estimates of pathogen variant risk are essential for informing effective public health responses to infectious diseases. Despite decades of use for influenza vaccine strain selection and PCR-based molecular diagnostics, data on pathogen variant prevalence and growth advantage has only risen to its current prominence during the SARS-CoV-2 pandemic. However, such data are still often sparse: novel variants are initially rare or a region has limited sequencing. To ensure real-time estimates of risk are available in these types of data-sparse conditions, we develop a hierarchical modeling approach that estimates variant fitness advantage and prevalence by pooling data across geographic regions. We apply this method to estimate SARS-CoV-2 variant dynamics at the country-level and assess its stability with retrospective validation. Our results show that more stable and robust estimates can be obtained even when sequencing data are sparse, as compared to established, single-country estimation approaches. We discuss how this method can inform risk assessment of novel emerging variants and provide situational awareness on currently circulating variants, for a range of pathogens and use-cases.

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Section: Introductionmentioning

confidence: 99%

Leveraging global genomic sequencing data to estimate local variant dynamics

Susswein

Johnson

Kassa

et al. 2023

Preprint

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“…This shift was made because of changes in outpatient care seeking associated with the pandemic, the continued cocirculation of SARS-CoV-2 and RSV, which complicated the interpretation of influenza-like illness data, and the new availability of laboratory-confirmed influenza hospital admission data through NHSN for all 50 states. This centralized source of virus-specific hospitalization data may provide actionable and reliable information moving forward [ 28 , 29 ]. Experience from using the NHSN hospital admission indicator for influenza forecasting during the 2021-2022 and 2022-2023 influenza seasons [ 30 ], as well as during other forecasting and modeling efforts during the COVID-19 pandemic, indicates that the NHSN hospital admission data [ 13 ], which became available during the COVID-19 pandemic, are a robust source of timely information about the impact of influenza in US hospitals.…”

Section: Collaborative Forecasting Efforts Hosted By the Cdc Use Surv...mentioning

confidence: 99%

Responding to the Return of Influenza in the United States by Applying Centers for Disease Control and Prevention Surveillance, Analysis, and Modeling to Inform Understanding of Seasonal Influenza

Borchering,

Biggerstaff,

Brammer

et al. 2024

JMIR Public Health Surveill

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We reviewed the tools that have been developed to characterize and communicate seasonal influenza activity in the United States. Here we focus on systematic surveillance and applied analytics, including seasonal burden and disease severity estimation, short-term forecasting, and longer-term modeling efforts. For each set of activities, we describe the challenges and opportunities that have arisen because of the COVID-19 pandemic. In conclusion, we highlight how collaboration and communication have been and will continue to be key components of reliable and actionable influenza monitoring, forecasting, and modeling activities.

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Counterpoint: Preprints and the Future of Scientific Publishing—In Favor of Relevance

Glymour¹,

Charpignon²,

Chen³

et al. 2023

American Journal of Epidemiology

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Peer-reviewed journals provide an invaluable but inadequate vehicle for scientific communication. Preprints are now an essential complement to peer-reviewed publications. Eschewing preprints will slow scientific progress and reduce the public health impact of epidemiologic research. The COVID-19 pandemic highlighted long-standing limitations of the peer-review process. Preprint servers, such as bioRxiv and medRxiv, served as crucial venues to rapidly disseminate research and provide detailed backup to sound-bite science that is often communicated through the popular press or social media. The major criticisms of preprints arise from an unjustified optimism about peer-review. Peer-review provides highly imperfect sorting and curation of research and only modest improvements in research conduct or presentation for most individual papers. The advantages of peer-review come at the expense of months to years of delay in sharing research methods or results. For time-sensitive evidence, these delays can lead to important missteps and ill-advised policies. Even with research that is not intrinsically urgent, preprints expedite debate, expand engagement, and accelerate progress. The risk that poor quality papers will have undue influence because they are posted on a preprint server is low. If epidemiology aims to deliver evidence relevant for public health, we need to embrace strategic uses of preprint servers.

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Collaborative modeling key to improving outbreak response

Cited by 6 publications

References 13 publications

Leveraging global genomic sequencing data to estimate local variant dynamics

Leveraging global genomic sequencing data to estimate local variant dynamics

Responding to the Return of Influenza in the United States by Applying Centers for Disease Control and Prevention Surveillance, Analysis, and Modeling to Inform Understanding of Seasonal Influenza

Counterpoint: Preprints and the Future of Scientific Publishing—In Favor of Relevance

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