Willem G. van Panhuis

Infectious, Allergic, and Immune-Mediated Disease Data Resources: a Landscape Overview and Subset Assessment

Darya Pokutnaya, Sydney Foote, Sepideh Mazrouee, Willem G. van Panhuis et autres

The Data Management and Sharing (DMS) Policy issued by the National Institutes of Health (NIH) requires most grant applications to include a DMS Plan, detailing data type(s), resources (e.g., data repositories, knowledgebases, portals) for data sharing, and a dissemination timeline. Researchers face …

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Infectious, Allergic, and Immune-Mediated Disease Data Resources: A Landscape Overview and Subset Assessment

Darya Pokutnaya, Willem G. van Panhuis, Reed S. Shabman

Abstract Background The Data Management and Sharing (DMS) Policy issued by the National Institutes of Health (NIH) requires most grant applications to include a DMS Plan, detailing data type(s), resources (e.g., data repositories, knowledgebases, portals) for data sharing, and a dissemination timeline. …

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OpenDengue: source data

Joe Clarke, Ahyoung Lim, Pratik Rajan Gupte, David M. Pigott et autres

Source data relevant to the original data source category that was searched, located and extracted was stored in a corresponding version-specific “.csv” file. This includes date accessed, url of main landing page, steps taken through website/sitemap navigation, relevant search terms used, and …

OpenDengue: data from the OpenDengue database

Joe Clarke, Ahyoung Lim, Pratik Rajan Gupte, David M. Pigott et autres

The OpenDengue project aims to build and maintain a database of dengue case counts for every dengue-affected country worldwide since 1990 or earlier. We collate data from a range of publicly available sources including ministry of health websites, peer-reviewed publications and other …

A global dataset of publicly available dengue case count data

Joseph Clarke, Ahyoung Lim, P S Gupte, David M. Pigott et autres

OpenDengue is a global database of dengue case data collated from public sources and standardised and formatted to facilitate easy reanalysis. Dataset version 1.2 of this database contains information on over 56 million dengue cases from 102 countries between 1924 and 2023, …

gb, us (code pays fourni par la source)

The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy

Sara L. Loo, Emily Howerton, Lucie Contamin, Claire P. Smith et autres

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt …

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Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Emily Howerton, Lucie Contamin, Luke C. Mullany, Michelle Qin et autres

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. …

us, ca (code pays fourni par la source)

Inter-rater reliability of the infectious disease modeling reproducibility checklist (IDMRC) as applied to COVID-19 computational modeling research

Darya Pokutnaya, Willem G. van Panhuis, Bruce R. Childers, Marquis Hawkins et autres

BACKGROUND: Infectious disease computational modeling studies have been widely published during the coronavirus disease 2019 (COVID-19) pandemic, yet they have limited reproducibility. Developed through an iterative testing process with multiple reviewers, the Infectious Disease Modeling Reproducibility Checklist (IDMRC) enumerates the minimal elements …

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Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub

Emily Howerton, Lucie Contamin, Luke C. Mullany, Michelle Qin et autres

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic …

us, Kenya, ca, tr (code pays fourni par la source)

Multiple models for outbreak decision support in the face of uncertainty

Katriona Shea, Rebecca K. Borchering, William J. M. Probert, Emily Howerton et autres

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened …

us, gb, cn, Afrique du Sud, au (code pays fourni par la source)

Inter-rater reliability of the Infectious Disease Modeling Reproducibility Checklist (IDMRC) as applied to COVID-19 computational modeling research

Darya Pokutnaya, Willem G. van Panhuis, Bruce R. Childers, Marquis Hawkins et autres

Background: Infectious disease computational modeling studies have been widely published during the coronavirus disease 2019 (COVID-19) pandemic, yet they have limited reproducibility. Developed through an iterative testing process with multiple reviewers, the Infectious Disease Modeling Reproducibility Checklist (IDMRC) enumerates the minimal elements …

us, au (code pays fourni par la source)

An implementation framework to improve the transparency and reproducibility of computational models of infectious diseases

Darya Pokutnaya, Bruce R. Childers, Alice E. Arcury‐Quandt, Harry Hochheiser et autres

Computational models of infectious diseases have become valuable tools for research and the public health response against epidemic threats. The reproducibility of computational models has been limited, undermining the scientific process and possibly trust in modeling results and related response strategies, such …

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