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Lee JS, Tyler ARB, Veinot TC, Yakel E. Now Is the Time to Strengthen Government-Academic Data Infrastructures to Jump-Start Future Public Health Crisis Response. JMIR Public Health Surveill 2024; 10:e51880. [PMID: 38656780 PMCID: PMC11079773 DOI: 10.2196/51880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/24/2024] [Accepted: 03/05/2024] [Indexed: 04/26/2024] Open
Abstract
During public health crises, the significance of rapid data sharing cannot be overstated. In attempts to accelerate COVID-19 pandemic responses, discussions within society and scholarly research have focused on data sharing among health care providers, across government departments at different levels, and on an international scale. A lesser-addressed yet equally important approach to sharing data during the COVID-19 pandemic and other crises involves cross-sector collaboration between government entities and academic researchers. Specifically, this refers to dedicated projects in which a government entity shares public health data with an academic research team for data analysis to receive data insights to inform policy. In this viewpoint, we identify and outline documented data sharing challenges in the context of COVID-19 and other public health crises, as well as broader crisis scenarios encompassing natural disasters and humanitarian emergencies. We then argue that government-academic data collaborations have the potential to alleviate these challenges, which should place them at the forefront of future research attention. In particular, for researchers, data collaborations with government entities should be considered part of the social infrastructure that bolsters their research efforts toward public health crisis response. Looking ahead, we propose a shift from ad hoc, intermittent collaborations to cultivating robust and enduring partnerships. Thus, we need to move beyond viewing government-academic data interactions as 1-time sharing events. Additionally, given the scarcity of scholarly exploration in this domain, we advocate for further investigation into the real-world practices and experiences related to sharing data from government sources with researchers during public health crises.
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Affiliation(s)
- Jian-Sin Lee
- School of Information, University of Michigan, Ann Arbor, MI, United States
| | | | - Tiffany Christine Veinot
- School of Information, University of Michigan, Ann Arbor, MI, United States
- Department of Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Department of Learning Health Sciences, School of Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Elizabeth Yakel
- School of Information, University of Michigan, Ann Arbor, MI, United States
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van Roode MY, Dos S Ribeiro C, Farag E, Nour M, Moustafa A, Ahmed M, Haringhuizen G, Koopmans MPG, van de Burgwal LHM. Six dilemmas for stakeholders inherently affecting data sharing during a zoonotic (re-)emerging infectious disease outbreak response. BMC Infect Dis 2024; 24:185. [PMID: 38347527 PMCID: PMC10863217 DOI: 10.1186/s12879-024-09054-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 01/24/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Timely access to outbreak related data, particularly in the early events of a spillover, is important to support evidence based control measures in response to outbreaks of zoonotic Emerging Infectious Diseases (EID). Yet, this is impeded by several barriers that need to be understood to promote timely sharing of data. Using the MERS epidemic as a model for a zoonotic EID outbreak, this study sought to provide an in-depth understanding of data sharing practices. METHODS Semi-structured interviews with 25 experts were conducted, along with Focus Group Discussions with 15 additional experts. A root-cause analysis was performed to examine the causal relationships between barriers. Enablers were mapped to the root-cause analysis to understand their influence on the barriers. Finally, root causes were placed in context of core dilemmas identified from the qualitative analysis. FINDINGS Eight barriers to data sharing were identified, related to collaboration, technical preparedness, regulations, and (conflict of) interests, and placed in the context of six dilemmas inherent to the multi-stakeholder collaboration required for a zoonotic outbreak response. Fourteen identified enablers showed the willingness of stakeholders to overcome or circumvent these barriers, but also indicated the inherent trial and error nature of implementing such enablers. INTERPRETATION Addressing the barriers requires solutions that must consider the complexity and interconnectedness of the root causes underlying them, and should consider the distinct scopes and interests of the different stakeholders. Insights provided by this study can be used to encourage data sharing practices for future outbreaks FUNDING: Wellcome Trust and UK Aid; EU-H2020 Societal Challenges (grant agreement no. 643476), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Veni.201S.044).
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Affiliation(s)
- Martine Y van Roode
- Department of Viroscience, Erasmus University Medical Center (Erasmus MC), Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
| | - Carolina Dos S Ribeiro
- Center for Infectious Disease Control, The Netherlands National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Vrije Universiteit Amsterdam (VU Amsterdam), Faculty of Science, Athena Institute for Research On Innovation and Communication in Health and Life Sciences, Amsterdam, The Netherlands
| | - Elmoubasher Farag
- Department of Health Protection & Communicable Diseases, Ministry of Public Health, Doha, Qatar
| | - Mohamed Nour
- Department of Health Protection & Communicable Diseases, Ministry of Public Health, Doha, Qatar
| | - Aya Moustafa
- Department of Health Protection & Communicable Diseases, Ministry of Public Health, Doha, Qatar
| | - Minahil Ahmed
- Department of Health Protection & Communicable Diseases, Ministry of Public Health, Doha, Qatar
| | - George Haringhuizen
- Center for Infectious Disease Control, The Netherlands National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Marion P G Koopmans
- Department of Viroscience, Erasmus University Medical Center (Erasmus MC), Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Pandemic and Disaster Preparedness Center (PDPC), Rotterdam, The Netherlands
| | - Linda H M van de Burgwal
- Vrije Universiteit Amsterdam (VU Amsterdam), Faculty of Science, Athena Institute for Research On Innovation and Communication in Health and Life Sciences, Amsterdam, The Netherlands
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Christoffels A, Mboowa G, van Heusden P, Makhubela S, Githinji G, Mwangi S, Onywera H, Nnaemeka N, Amoako DG, Olawoye I, Diallo A, Mbala-Kingebeni P, Oyola SO, Adu B, Mvelase C, Ondoa P, Dratibi FA, Sow A, Gumede N, Tessema SK, Ouma AO, Tebeje YK. A pan-African pathogen genomics data sharing platform to support disease outbreaks. Nat Med 2023; 29:1052-1055. [PMID: 37161068 DOI: 10.1038/s41591-023-02266-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Affiliation(s)
- Alan Christoffels
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia.
- South African National Bioinformatics Institute, SAMRC Bioinformatics Unit, University of the Western Cape, Cape Town, South Africa.
| | - Gerald Mboowa
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia
| | - Peter van Heusden
- South African National Bioinformatics Institute, SAMRC Bioinformatics Unit, University of the Western Cape, Cape Town, South Africa
| | | | - George Githinji
- KEMRI-Wellcome Trust Research Programme/KEMRI-CGMR-C, Kilifi, Kenya
| | - Sarah Mwangi
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia
| | - Harris Onywera
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia
| | | | - Daniel Gyamfi Amoako
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- College of Health Sciences, University of KwaZulu Natal, Durban, South Africa
| | - Idowu Olawoye
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | | | - Placide Mbala-Kingebeni
- Institut National de Recherche Biomédicale, Université de Kinshasa, Kinshasa, Democratic Republic of the Congo
| | - Samuel O Oyola
- International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Bright Adu
- Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Accra, Ghana
| | | | - Pascale Ondoa
- African Society for Laboratory Medicine (ASLM), Addis Ababa, Ethiopia
| | | | | | - Nicksy Gumede
- WHO Regional Office for Africa, Brazzaville, Republic of Congo
| | - Sofonias K Tessema
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia.
| | - Ahmed Ogwell Ouma
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia
| | - Yenew Kebede Tebeje
- Africa Centres for Disease Control and Prevention (Africa CDC), African Union Commission, Addis Ababa, Ethiopia
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4
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Abramowitz S, Stevens LA, Kyomba G, Mayaka S, Grépin KA. Data flows during public health emergencies in LMICs: A people-centered mapping of data flows during the 2018 ebola epidemic in Equateur, DRC. Soc Sci Med 2023; 318:115116. [PMID: 36610244 DOI: 10.1016/j.socscimed.2022.115116] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 05/31/2022] [Accepted: 06/05/2022] [Indexed: 01/24/2023]
Abstract
In infectious outbreaks, rapid case detection and reporting, coordination, and context-specific strategies are needed for rapid containment. Data sharing between actors, and the speed and content of data flows, is essential for expediting epidemic response. In this study, researchers mapped data flows during the 2018 Ebola Virus Disease (EVD) outbreak in Equateur Province in the Democratic Republic of the Congo using semi-structured interviews, ethnographic research, and focus groups with EVD response actors. During this research, we mapped and tracked data collection, transmission, storage, sharing, and use patterns. Target participants included: key organizational actors in the EVD outbreaks responses, including local (primary health, community-based, hospital), provincial (MoPH, DRC Red Cross), and international (WHO, UN organizations, international first-responders) stakeholders. We found that a community-based surveillance system enabled the rapid detection of a hemorrhagic fever outbreak, resulting in the rapid laboratory confirmation of EVD. With the arrival of international organizations to provide support to the EVD response, routine surveillance systems continued to function robustly. However, the establishment of a vertical EVD response architecture created challenges for the response. Data flows during the Equateur outbreak were hampered by numerous challenges in the domains of early warning, line lists of cases, and contact tracing, which impeded surveillance and data flows. We therefore argue that structuring health information systems for preparedness requires taking a person-centered approach to data production, flow, and analysis.
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Affiliation(s)
- Sharon Abramowitz
- Center for Global Health Science and Security, Georgetown University, 3900 Reservoir Road, NW, Medical-Dental Building, Room NW 306, Washington DC, 20057, United States.
| | - Lys Alcayna Stevens
- Department of Anthropology, Peabody Museum, Harvard University, 11 Divinity Avenue, Cambridge, MA, 02138, United States.
| | - Gabriel Kyomba
- Kinshasa School of Public Health, Université de Kinshasa, Plateau, Commune de Lemba, Ville de Kinshasa, B.P. 11850 Kin I, Kinshasa, Democratic Republic of the Congo.
| | - Serge Mayaka
- Public Health School of Kinshasa/Faculty of Medecine, Kinshasa University, B.P 11850 Kin I. Democratic Republic of the Congo.
| | - Karen A Grépin
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong Special Administrative Region.
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Wang H. Public health emergency decision-making and management system sound research using rough set attribute reduction and blockchain. Sci Rep 2022; 12:3600. [PMID: 35246582 PMCID: PMC8897403 DOI: 10.1038/s41598-022-07493-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 02/14/2022] [Indexed: 11/24/2022] Open
Abstract
Public health emergency decisions are explored to ensure the emergency response measures in an environment where various emergencies occur frequently. An emergency decision is essentially a multi-criteria risk decision-making problem. The feasibility of applying prospect theory to emergency decisions is analyzed, and how psychological behaviors of decision-makers impact decision-making results are quantified. On this basis, the cognitive process of public health emergencies is investigated based on the rough set theory. A Decision Rule Extraction Algorithm (denoted as A-DRE) that considers attribute costs is proposed, which is then applied for attribute reduction and rule extraction on emergency datasets. In this way, decision-makers can obtain reduced decision table attributes quickly. Considering that emergency decisions require the participation of multiple departments, a framework is constructed to solve multi-department emergency decisions. The technical characteristics of the blockchain are in line with the requirements of decentralization and multi-party participation in emergency management. The core framework of the public health emergency management system-plan, legal system, mechanism, and system can play an important role. When [Formula: see text], the classification accuracy under the K-Nearest Neighbor (KNN) classifier reaches 73.5%. When [Formula: see text], the classification accuracy under the Support Vector Machines (SVM) classifier reaches 86.4%. It can effectively improve China's public health emergency management system and improve the efficiency of emergency management. By taking Coronavirus Disease 2019 (COVID-19) as an example, the weight and prospect value functions of different decision-maker attributes are constructed based on prospect theory. The optimal rescue plan is finally determined. A-DRE can consider the cost of each attribute in the decision table and the ability to classify it correctly; moreover, it can reduce the attributes and extract the rules on the COVID-19 dataset, suitable for decision-makers' situation face once an emergency occurs. The emergency decision approach based on rough set attribute reduction and prospect theory can acquire practical decision-making rules while considering the different risk preferences of decision-makers facing different decision-making results, which is significant for the rapid development of public health emergency assistance and disaster relief.
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Affiliation(s)
- Hanyi Wang
- School of Economics and Management, Kunming University, Kunming, 650214, China.
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Salholz-Hillel M, Grabitz P, Pugh-Jones M, Strech D, DeVito NJ. Results availability and timeliness of registered COVID-19 clinical trials: interim cross-sectional results from the DIRECCT study. BMJ Open 2021; 11:e053096. [PMID: 34810189 PMCID: PMC8609493 DOI: 10.1136/bmjopen-2021-053096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 10/18/2021] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE To examine how and when the results of COVID-19 clinical trials are disseminated. DESIGN Cross-sectional study. SETTING The COVID-19 clinical trial landscape. PARTICIPANTS 285 registered interventional clinical trials for the treatment and prevention of COVID-19 completed by 30 June 2020. MAIN OUTCOME MEASURES Overall reporting and reporting by dissemination route (ie, by journal article, preprint or results on a registry); time to reporting by dissemination route. RESULTS Following automated and manual searches of the COVID-19 literature, we located 41 trials (14%) with results spread across 47 individual results publications published by 15 August 2020. The most common dissemination route was preprints (n=25) followed by journal articles (n=18), and results on a registry (n=2). Of these, four trials were available as both a preprint and journal publication. The cumulative incidence of any reporting surpassed 20% at 119 days from completion. Sensitivity analyses using alternate dates and definitions of results did not appreciably change the reporting percentage. Expanding minimum follow-up time to 3 months increased the overall reporting percentage to 19%. CONCLUSION COVID-19 trials completed during the first 6 months of the pandemic did not consistently yield rapid results in the literature or on clinical trial registries. Our findings suggest that the COVID-19 response may be seeing quicker results disclosure compared with non-emergency conditions. Issues with the reliability and timeliness of trial registration data may impact our estimates. Ensuring registry data are accurate should be a priority for the research community during a pandemic. Data collection is underway for the next phase of the DIssemination of REgistered COVID-19 Clinical Trials study expanding both our trial population and follow-up time.
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Affiliation(s)
- Maia Salholz-Hillel
- QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charite Universitatsmedizin Berlin, Berlin, Germany
| | - Peter Grabitz
- QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charite Universitatsmedizin Berlin, Berlin, Germany
| | - Molly Pugh-Jones
- QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charite Universitatsmedizin Berlin, Berlin, Germany
| | - Daniel Strech
- QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charite Universitatsmedizin Berlin, Berlin, Germany
| | - Nicholas J DeVito
- DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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Brown J, Bhatnagar M, Gordon H, Goodner J, Cobb JP, Lutrick K. Data Collection during Public Health Emergencies: Design Tenets and Usability of an Electronic Data Capture Tool (Preprint). JMIR Hum Factors 2021; 9:e35032. [PMID: 35679114 PMCID: PMC9227656 DOI: 10.2196/35032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/23/2022] [Accepted: 04/23/2022] [Indexed: 11/17/2022] Open
Abstract
Background The Discovery Critical Care Research Network Program for Resilience and Emergency Preparedness (Discovery PREP) partnered with a third-party technology vendor to design and implement an electronic data capture tool that addressed multisite data collection challenges during public health emergencies (PHE) in the United States. The basis of the work was to design an electronic data capture tool and to prospectively gather data on usability from bedside clinicians during national health system stress queries and influenza observational studies. Objective The aim of this paper is to describe the lessons learned in the design and implementation of a novel electronic data capture tool with the goal of significantly increasing the nation’s capability to manage real-time data collection and analysis during PHE. Methods A multiyear and multiphase design approach was taken to create an electronic data capture tool, which was used to pilot rapid data capture during a simulated PHE. Following the pilot, the study team retrospectively assessed the feasibility of automating the data captured by the electronic data capture tool directly from the electronic health record. In addition to user feedback during semistructured interviews, the System Usability Scale (SUS) questionnaire was used as a basis to evaluate the usability and performance of the electronic data capture tool. Results Participants included Discovery PREP physicians, their local administrators, and data collectors from tertiary-level academic medical centers at 5 different institutions. User feedback indicated that the designed system had an intuitive user interface and could be used to automate study communication tasks making for more efficient management of multisite studies. SUS questionnaire results classified the system as highly usable (SUS score 82.5/100). Automation of 17 (61%) of the 28 variables in the influenza observational study was deemed feasible during the exploration of automated versus manual data abstraction.
The creation and use of the Project Meridian electronic data capture tool identified 6 key design requirements for multisite data collection, including the need for the following: (1) scalability irrespective of the type of participant; (2) a common data set across sites; (3) automated back end administrative capability (eg, reminders and a self-service status board); (4) multimedia communication pathways (eg, email and SMS text messaging); (5) interoperability and integration with local site information technology infrastructure; and (6) natural language processing to extract nondiscrete data elements. Conclusions The use of the electronic data capture tool in multiple multisite Discovery PREP clinical studies proved the feasibility of using the novel, cloud-based platform in practice. The lessons learned from this effort can be used to inform the improvement of ongoing global multisite data collection efforts during the COVID-19 pandemic and transform current manual data abstraction approaches into reliable, real time, and automated information exchange. Future research is needed to expand the ability to perform automated multisite data extraction during a PHE and beyond.
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Affiliation(s)
- Joan Brown
- Clinical Operations Business Intelligence, The Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
| | - Manas Bhatnagar
- Department of Surgery, The Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
| | - Hugh Gordon
- Akido Labs Inc, Los Angeles, CA, United States
| | | | - J Perren Cobb
- Department of Surgery, The Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
| | - Karen Lutrick
- Department of Family and Community Medicine, University of Arizona, Tucson, AZ, United States
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Djekidel MN, Rosikiewicz W, Peng JC, Kanneganti TD, Hui Y, Jin H, Hedges D, Schreiner P, Fan Y, Wu G, Xu B. CovidExpress: an interactive portal for intuitive investigation on SARS-CoV-2 related transcriptomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.05.14.444026. [PMID: 34075382 PMCID: PMC8168395 DOI: 10.1101/2021.05.14.444026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans could cause coronavirus disease 2019 (COVID-19). Since its first discovery in Dec 2019, SARS-CoV-2 has become a global pandemic and caused 3.3 million direct/indirect deaths (2021 May). Amongst the scientific community's response to COVID-19, data sharing has emerged as an essential aspect of the combat against SARS-CoV-2. Despite the ever-growing studies about SARS-CoV-2 and COVID-19, to date, only a few databases were curated to enable access to gene expression data. Furthermore, these databases curated only a small set of data and do not provide easy access for investigators without computational skills to perform analyses. To fill this gap and advance open-access to the growing gene expression data on this deadly virus, we collected about 1,500 human bulk RNA-seq datasets from publicly available resources, developed a database and visualization tool, named CovidExpress (https://stjudecab.github.io/covidexpress). This open access database will allow research investigators to examine the gene expression in various tissues, cell lines, and their response to SARS-CoV-2 under different experimental conditions, accelerating the understanding of the etiology of this disease to inform the drug and vaccine development. Our integrative analysis of this big dataset highlights a set of commonly regulated genes in SARS-CoV-2 infected lung and Rhinovirus infected nasal tissues, including OASL that were under-studied in COVID-19 related reports. Our results also suggested a potential FURIN positive feedback loop that might explain the evolutional advantage of SARS-CoV-2.
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Affiliation(s)
- Mohamed Nadhir Djekidel
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
- These authors contributed equally to this study
| | - Wojciech Rosikiewicz
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
- These authors contributed equally to this study
| | - Jamy C. Peng
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | | | - Yawei Hui
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Hongjian Jin
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Dale Hedges
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Patrick Schreiner
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Yiping Fan
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Gang Wu
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Beisi Xu
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
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Brown J, Bhatnagar M, Gordon H, Lutrick K, Goodner J, Blum J, Bartz R, Uslan D, David-DiMarino E, Sorbello A, Jackson G, Walsh J, Neal L, Cyran M, Francis H, Cobb JP. Clinical Data Extraction During Public Health Emergencies: A Blockchain Technology Assessment. Biomed Instrum Technol 2021; 55:103-111. [PMID: 34460906 PMCID: PMC8657842 DOI: 10.2345/0899-8205-55.3.103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
OBJECTIVE We sought to explore the technical and legal readiness of healthcare institutions for novel data-sharing methods that allow clinical information to be extracted from electronic health records (EHRs) and submitted securely to the Food and Drug Administration's (FDA's) blockchain through a secure data broker (SDB). MATERIALS AND METHODS This assessment was divided into four sections: an institutional EHR readiness assessment, legal consultation, institutional review board application submission, and a test of healthcare data transmission over a blockchain infrastructure. RESULTS All participating institutions reported the ability to electronically extract data from EHRs for research. Formal legal agreements were deemed unnecessary to the project but would be needed in future tests of real patient data exchange. Data transmission to the FDA blockchain met the success criteria of data connection from within the four institutions' firewalls, externally to the FDA blockchain via a SDB. DISCUSSION The readiness survey indicated advanced analytic capability in hospital institutions and highlighted inconsistency in Fast Healthcare Interoperability Resources format utilitzation across institutions, despite requirements of the 21st Century Cures Act. Further testing across more institutions and annual exercises leveraging the application of data exchange over a blockchain infrastructure are recommended actions for determining the feasibility of this approach during a public health emergency and broaden the understanding of technical requirements for multisite data extraction. CONCLUSION The FDA's RAPID (Real-Time Application for Portable Interactive Devices) program, in collaboration with Discovery, the Critical Care Research Network's PREP (Program for Resilience and Emergency Preparedness), identified the technical and legal challenges and requirements for rapid data exchange to a government entity using the FDA blockchain infrastructure.
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Affiliation(s)
- Joan Brown
- Joan Brown, EdD, MBA, CCE, is an associate administrator of clinical operations business intelligence in the Keck Hospital at the University of Southern California in Los Angeles, CA.
| | - Manas Bhatnagar
- Manas Bhatnagar, MS, Director of Analytics, Department of Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, California.
| | - Hugh Gordon
- Hugh Gordon, MD, is the chief technology officer at Akido Labs in Los Angeles, CA.
| | - Karen Lutrick
- Karen Lutrick, PhD, is an assistant professor of family & community medicine in the College of Medicine at the University of Arizona in Tucson.
| | - Jared Goodner
- Jared Goodner is the chief product officer at Akido Labs in Los Angeles, CA.
| | - James Blum
- James Blum, MD, FCCM, is the chief medical information officer in the Department of Anesthesiology at the University of Iowa in Iowa City.
| | - Raquel Bartz
- Raquel Bartz, MD, is the division chief of critical care medicine in the Department of Anesthesia and Medicine at the Duke University School of Medicine in Durham, NC.
| | - Daniel Uslan
- Daniel Uslan, MD, MBA, is the clinical chief and a clinical professor in the David Geffen School of Medicine at the University of California Los Angeles in Los Angeles, CA.
| | - Ernesto David-DiMarino
- Ernesto David-DiMarino, MS, is the head of enterprise applications and data at Cortica Advanced Therapies for Autism and Neurodevelopment in Los Angeles, CA.
| | - Alfred Sorbello
- Alfred Sorbello, DO, MPH, is a medical officer in the Office of Translational Sciences at the Center for Drug Evaluation and Research of the Food and Drug Administration in Silver Spring, MD.
| | - Gregory Jackson
- Gregory Jackson is a program management officer in the Office of Translational Sciences at the Center for Drug Evaluation and Research of the Food and Drug Administration in Silver Spring, MD.
| | - Jeremy Walsh
- Jeremy Walsh, is a chief technologist in the Strategic Innovation Group at Booz Allen Hamilton in McLean, VA.
| | - Lauren Neal
- Lauren Neal, PhD, is the vice president of Strategic Innovation Group at Booz Allen Hamilton in McLean, VA.
| | - Marek Cyran
- Marek Cyran, is a chief technologist in the Strategic Innovation Group at Booz Allen Hamilton in McLean, VA.
| | - Henry Francis
- Henry Francis, MD, is an associate director for data mining and informatics evaluation and research in the Office of Translational Sciences at the Center for Drug Evaluation and Research of the Food and Drug Administration in Silver Spring, MD.
| | - J. Perren Cobb
- J. Perren Cobb, MD, FACS, FCCM, is the director of surgical critical care, a professor, and a clinical scholar in the Departments of Surgery and of Anesthesiology at Keck School of Medicine of the University of Southern California in Los Angeles, CA.
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Brown J, Bhatnagar M, Gordon H, Lutrick K, Goodner J, Blum J, Bartz R, Uslan D, David-DiMarino E, Sorbello A, Jackson G, Walsh J, Neal L, Cyran M, Francis H, Cobb JP. Clinical Data Extraction During Public Health Emergencies: A Blockchain Technology Assessment. Biomed Instrum Technol 2021. [PMID: 34460906 DOI: 10.2345/0890-8205-55.3.103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE We sought to explore the technical and legal readiness of healthcare institutions for novel data-sharing methods that allow clinical information to be extracted from electronic health records (EHRs) and submitted securely to the Food and Drug Administration's (FDA's) blockchain through a secure data broker (SDB). MATERIALS AND METHODS This assessment was divided into four sections: an institutional EHR readiness assessment, legal consultation, institutional review board application submission, and a test of healthcare data transmission over a blockchain infrastructure. RESULTS All participating institutions reported the ability to electronically extract data from EHRs for research. Formal legal agreements were deemed unnecessary to the project but would be needed in future tests of real patient data exchange. Data transmission to the FDA blockchain met the success criteria of data connection from within the four institutions' firewalls, externally to the FDA blockchain via a SDB. DISCUSSION The readiness survey indicated advanced analytic capability in hospital institutions and highlighted inconsistency in Fast Healthcare Interoperability Resources format utilitzation across institutions, despite requirements of the 21st Century Cures Act. Further testing across more institutions and annual exercises leveraging the application of data exchange over a blockchain infrastructure are recommended actions for determining the feasibility of this approach during a public health emergency and broaden the understanding of technical requirements for multisite data extraction. CONCLUSION The FDA's RAPID (Real-Time Application for Portable Interactive Devices) program, in collaboration with Discovery, the Critical Care Research Network's PREP (Program for Resilience and Emergency Preparedness), identified the technical and legal challenges and requirements for rapid data exchange to a government entity using the FDA blockchain infrastructure.
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11
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Pillai P. How Do Data Bolster Pandemic Preparedness and Response? How Do We Improve Data and Systems to Be Better Prepared? PATTERNS (NEW YORK, N.Y.) 2021; 2:100190. [PMID: 33511371 PMCID: PMC7815962 DOI: 10.1016/j.patter.2020.100190] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
How are data driving the response for the ongoing COVID-19 pandemic? How do data support preparedness toward epidemics and pandemics? How do data inform the potential severity and spread of an outbreak? Past infectious disease outbreaks have demonstrated several challenges associated with rapid aggregation, integration, and sharing of data to inform a response during an outbreak. The ongoing pandemic response has demonstrated the value of timely data collection and sharing and the usage of data for decision-making.
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12
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Amit AML, Pepito VCF, Gutierrez B, Rawson T. Data Sharing in Southeast Asia During the First Wave of the COVID-19 Pandemic. Front Public Health 2021; 9:662842. [PMID: 34222173 PMCID: PMC8242246 DOI: 10.3389/fpubh.2021.662842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 05/11/2021] [Indexed: 11/13/2022] Open
Abstract
Background: When a new pathogen emerges, consistent case reporting is critical for public health surveillance. Tracking cases geographically and over time is key for understanding the spread of an infectious disease and effectively designing interventions to contain and mitigate an epidemic. In this paper we describe the reporting systems on COVID-19 in Southeast Asia during the first wave in 2020, and highlight the impact of specific reporting methods. Methods: We reviewed key epidemiological variables from various sources including a regionally comprehensive dataset, national trackers, dashboards, and case bulletins for 11 countries during the first wave of the epidemic in Southeast Asia. We recorded timelines of shifts in epidemiological reporting systems and described the differences in how epidemiological data are reported across countries and timepoints. Results: Our findings suggest that countries in Southeast Asia generally reported precise and detailed epidemiological data during the first wave of the pandemic. Changes in reporting rarely occurred for demographic data, while reporting shifts for geographic and temporal data were frequent. Most countries provided COVID-19 individual-level data daily using HTML and PDF, necessitating scraping and extraction before data could be used in analyses. Conclusion: Our study highlights the importance of more nuanced analyses of COVID-19 epidemiological data within and across countries because of the frequent shifts in reporting. As governments continue to respond to impacts on health and the economy, data sharing also needs to be prioritised given its foundational role in policymaking, and in the implementation and evaluation of interventions.
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Affiliation(s)
- Arianna Maever L Amit
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.,School of Medicine and Public Health, Ateneo de Manila University, Pasig, Philippines.,College of Medicine, University of the Philippines Manila, Manila, Philippines
| | | | - Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, United Kingdom.,School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Thomas Rawson
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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Park JH, Lee SG, Ahn S, Kim JY, Song J, Moon S, Cho H. Strategies to prevent COVID-19 transmission in the emergency department of a regional base hospital in Korea: From index patient until pandemic declaration. Am J Emerg Med 2020; 46:247-253. [PMID: 33059986 PMCID: PMC7378011 DOI: 10.1016/j.ajem.2020.07.056] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 07/17/2020] [Accepted: 07/17/2020] [Indexed: 01/19/2023] Open
Abstract
Objective This study aimed to describe the timely strategies used to prevent the spread of the emerging coronavirus disease 2019 (COVID-19) and present the activities performed in a regional base hospital in South Korea, from the identification of the index patient until the pandemic declaration. Methods This is a descriptive study detailing the step-by-step guidelines implemented to manage COVID-19 in a regional tertiary base hospital from January to March 2020. We described our three-phase response to the COVID-19 outbreak as per the national and global quarantine procedures applied during each critical event and highlighted the activities implemented from the perspective of public health crisis preparedness involving emerging infectious diseases. Results During the COVID-19 outbreak in Korea, we improved and implemented a rapid and flexible screening system for visiting patients using patient history and radiological testing and created a separate isolation zone for patients under investigation. This active identification-isolation strategy has been effectively applied in the COVID-19 outbreak. Conclusions The step-by-step enforced strategies to prevent the spread of COVID-19, though not perfect, adequately reduced the risk of transmission of the highly contagious infectious disease in the hospital while maintaining the emergency medical system.
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Affiliation(s)
- Jong-Hak Park
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Seong-Geun Lee
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Sejoong Ahn
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Joo Yeong Kim
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Juhyun Song
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Sungwoo Moon
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea; National Emergency Medical Center, Seoul, Republic of Korea
| | - Hanjin Cho
- Department of Emergency Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea.
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Abstract
PurposeThe control of particularly virulent communicable diseases such as COVID-19 can be considered a global public good. Unabated contagion, both within and across borders, can result in a global public bad. More effective control – such as by flattening the epidemiological curve – could prevent severe social and economic disruption by allowing domestic health and social protection systems to more adequately respond to the health crisis. This article elaborates on some of the main elements of counter COVID-19 responses, drawing on emerging international good practices. While a full evaluation of policy effectiveness is still forthcoming, it is critical to review and synthesize the emerging lessons and evidence even this early.Design/methodology/approachThis article reviews the international good practices in counter COVID-19 responses across countries.FindingsConcerted efforts across borders, such as by sharing data and collaborating in research and by coordinating international support for countercyclical economic and health responses at the national level, are some of the options for countering COVID-19 at the international level. Within countries, more inclusive social protection and health systems, combined with countercyclical economic policies, and concerted behavioral changes tend to produce more effective collective action against the spread of the disease.Research limitations/implicationsThis study is based on a review of emerging responses to the health crisis.Practical implicationsThe policies and practices reviewed in this paper could feed into better-informed crisis responses to COVID-19 and other types of health shocks.Originality/valueThis study is among the first general reviews of policy responses to the COVID-19 health crisis.
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15
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Egli A, Schrenzel J, Greub G. Digital microbiology. Clin Microbiol Infect 2020; 26:1324-1331. [PMID: 32603804 PMCID: PMC7320868 DOI: 10.1016/j.cmi.2020.06.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 06/15/2020] [Accepted: 06/20/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects. OBJECTIVE This review article summarizes the most important concepts of digital microbiology. The article gives microbiologists, clinicians and data scientists a viewpoint and practical examples along the diagnostic process. SOURCES We used peer-reviewed literature identified by a PubMed search for digitalization, machine learning, artificial intelligence and microbiology. CONTENT We describe the opportunities and challenges of digitalization in microbiological diagnostic processes with various examples. We also provide in this context key aspects of data structure and interoperability, as well as legal aspects. Finally, we outline the way for applications in a modern microbiology laboratory. IMPLICATIONS We predict that digitalization and the usage of machine learning will have a profound impact on the daily routine of laboratory staff. Along the analytical process, the most important steps should be identified, where digital technologies can be applied and provide a benefit. The education of all staff involved should be adapted to prepare for the advances in digital microbiology.
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Affiliation(s)
- A Egli
- Clinical Bacteriology and Mycology, University Hospital Basel, Basel, Switzerland; Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
| | - J Schrenzel
- Laboratory of Bacteriology, University Hospitals of Geneva, Geneva, Switzerland
| | - G Greub
- Institute of Medical Microbiology, University Hospital Lausanne, Lausanne, Switzerland
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16
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Pollett S, Fauver JR, Berry IM, Melendrez M, Morrison A, Gillis LD, Johansson MA, Jarman RG, Grubaugh ND. Genomic Epidemiology as a Public Health Tool to Combat Mosquito-Borne Virus Outbreaks. J Infect Dis 2020; 221:S308-S318. [PMID: 31711190 PMCID: PMC11095994 DOI: 10.1093/infdis/jiz302] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Next-generation sequencing technologies, exponential increases in the availability of virus genomic data, and ongoing advances in phylogenomic methods have made genomic epidemiology an increasingly powerful tool for public health response to a range of mosquito-borne virus outbreaks. In this review, we offer a brief primer on the scope and methods of phylogenomic analyses that can answer key epidemiological questions during mosquito-borne virus public health emergencies. We then focus on case examples of outbreaks, including those caused by dengue, Zika, yellow fever, West Nile, and chikungunya viruses, to demonstrate the utility of genomic epidemiology to support the prevention and control of mosquito-borne virus threats. We extend these case studies with operational perspectives on how to best incorporate genomic epidemiology into structured surveillance and response programs for mosquito-borne virus control. Many tools for genomic epidemiology already exist, but so do technical and nontechnical challenges to advancing their use. Frameworks to support the rapid sharing of multidimensional data and increased cross-sector partnerships, networks, and collaborations can support advancement on all scales, from research and development to implementation by public health agencies.
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Affiliation(s)
- S. Pollett
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland
- Department of Preventive Medicine and Biostatistics, Uniformed Services University, Bethesda, Maryland
- Marie Bashir Institute, University of Sydney, Camperdown, New South Wales, Australia
| | - J. R. Fauver
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut
- Infectious Diseases Division, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Irina Maljkovic Berry
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland
| | | | | | - L. D. Gillis
- Bureau of Public Health Laboratories–Miami, Florida Department of Health
| | - M. A. Johansson
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - R. G. Jarman
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland
| | - N. D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut
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17
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Kobres PY, Chretien JP, Johansson MA, Morgan JJ, Whung PY, Mukundan H, Del Valle SY, Forshey BM, Quandelacy TM, Biggerstaff M, Viboud C, Pollett S. A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern. PLoS Negl Trop Dis 2019; 13:e0007451. [PMID: 31584946 PMCID: PMC6805005 DOI: 10.1371/journal.pntd.0007451] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 10/22/2019] [Accepted: 08/27/2019] [Indexed: 01/04/2023] Open
Abstract
INTRODUCTION Epidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible, and actionable the information produced by these studies was. METHODS To improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE, and grey literature review, we identified studies that forecasted, predicted, or simulated ecological or epidemiological phenomena related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility, and clarity by independent reviewers. RESULTS 2034 studies were identified, of which n = 73 met the eligibility criteria. Spatial spread, R0 (basic reproductive number), and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barré Syndrome burden (4%), sexual transmission risk (4%), and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%), and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions, and 54% provided sufficient methodological detail to allow complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median of 119 days sooner than journal publication dates, they were used in only 30% of studies. CONCLUSIONS Many ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics, and pandemics.
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Affiliation(s)
- Pei-Ying Kobres
- School of Public Health, George Washington University, Washington, DC, United States of America
| | | | - Michael A. Johansson
- Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America
| | - Jeffrey J. Morgan
- Joint Research and Development Inc, Stafford, Virginia, United States of America
| | - Pai-Yei Whung
- Office of Research & Development, US Environmental Protection Agency, Washington, DC, United States of America
| | - Harshini Mukundan
- Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Sara Y. Del Valle
- Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Brett M. Forshey
- Armed Forces Health Surveillance Branch, Silver Spring, Maryland, United States of America
| | - Talia M. Quandelacy
- Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America
- Johns Hopkins School of Public Health, Baltimore, Maryland, United States of America
| | - Matthew Biggerstaff
- Influenza Division, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America
| | - Cecile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Simon Pollett
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America
- Department of Preventive Medicine & Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America
- Marie Bashir Institute, University of Sydney, Sydney, New South Wales, Australia
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18
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Oza S, Wing K, Sesay AA, Boufkhed S, Houlihan C, Vandi L, Sebba SC, McGowan CR, Cummings R, Checchi F. Improving health information systems during an emergency: lessons and recommendations from an Ebola treatment centre in Sierra Leone. BMC Med Inform Decis Mak 2019; 19:100. [PMID: 31133075 PMCID: PMC6537453 DOI: 10.1186/s12911-019-0817-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 04/16/2019] [Indexed: 11/11/2022] Open
Abstract
Background The 2014–2016 West Africa Ebola epidemic highlighted the difficulty of collecting patient information during emergencies, especially in highly infectious environments. Health information systems (HISs) appropriate for such settings were lacking prior to this outbreak. Here we describe our development and implementation of paper and electronic HISs at the Sierra Leone Kerry Town Ebola treatment centre (ETC) from 2014 to 2015. We share our approach, experiences, and recommendations for future health emergencies. Methods We developed eight fact-finding questions about data-related needs, priorities, and restrictions at the ETC (“inputs”) to inform eight structural decisions (“outputs”) across six core HIS components. Semi-structured interviews about the “inputs” were then conducted with HIS stakeholders, chosen based on their teams’ involvement in ETC HIS-related activities. Their responses were used to formulate the “output” results to guide the HIS design. We implemented the HIS using an Agile approach, monitored system usage, and developed a structured questionnaire on user experiences and opinions. Results Some key “input” responses were: 1) data needs for priorities (patient care, mandatory reporting); 2) challenges around infection control, limited equipment, and staff clinical/language proficiencies; 3) patient/clinical flows; and 4) weak points from staff turnover, infection control, and changing protocols. Key outputs included: 1) determining essential data, 2) data tool design decisions (e.g. large font sizes, checkboxes/buttons), 3) data communication methods (e.g. radio, “collective memory”), 4) error reduction methods (e.g. check digits, pre-written wristbands), and 5) data storage options (e.g. encrypted files, accessible folders). Implementation involved building data collection tools (e.g. 13 forms), preparing the systems (e.g. supplies), training staff, and maintenance (e.g. removing old forms). Most patients had basic (100%, n = 456/456), drug (96.9%, n = 442/456), and additional clinical/epidemiological (98.9%, n = 451/456) data stored. The questionnaire responses highlighted the importance of usability and simplicity in the HIS. Conclusions HISs during emergencies are often ad-hoc and disjointed, but systematic design and implementation can lead to high-quality systems focused on efficiency and ease of use. Many of the processes used and lessons learned from our work are generalizable to other health emergencies. Improvements should be started now to have rapidly adaptable and deployable HISs ready for the next health emergency. Electronic supplementary material The online version of this article (10.1186/s12911-019-0817-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shefali Oza
- London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. .,Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone.
| | - Kevin Wing
- London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone
| | - Alieu Amara Sesay
- Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone
| | - Sabah Boufkhed
- London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone
| | - Catherine Houlihan
- London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone.,University College London, Gower Street, London, WC1E 6BT, UK
| | - Lahai Vandi
- Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone
| | - Sahr Charles Sebba
- Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone
| | - Catherine R McGowan
- London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone.,Save the Children UK, London, 1 St John's Lane, London, EC1M 4AR, UK
| | - Rachael Cummings
- Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone.,Save the Children UK, London, 1 St John's Lane, London, EC1M 4AR, UK
| | - Francesco Checchi
- London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Save the Children International, Kerry Town, Rural District, Western Area, Sierra Leone.,Save the Children UK, London, 1 St John's Lane, London, EC1M 4AR, UK
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Kelly-Cirino C, Mazzola LT, Chua A, Oxenford CJ, Van Kerkhove MD. An updated roadmap for MERS-CoV research and product development: focus on diagnostics. BMJ Glob Health 2019; 4:e001105. [PMID: 30815285 PMCID: PMC6361340 DOI: 10.1136/bmjgh-2018-001105] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 10/13/2018] [Accepted: 10/23/2018] [Indexed: 01/12/2023] Open
Abstract
Diagnostics play a central role in the early detection and control of outbreaks and can enable a more nuanced understanding of the disease kinetics and risk factors for the Middle East respiratory syndrome-coronavirus (MERS-CoV), one of the high-priority pathogens identified by the WHO. In this review we identified sources for molecular and serological diagnostic tests used in MERS-CoV detection, case management and outbreak investigations, as well as surveillance for humans and animals (camels), and summarised the performance of currently available tests, diagnostic needs, and associated challenges for diagnostic test development and implementation. A more detailed understanding of the kinetics of infection of MERS-CoV is needed in order to optimise the use of existing assays. Notably, MERS-CoV point-of-care tests are needed in order to optimise supportive care and to minimise transmission risk. However, for new test development, sourcing clinical material continues to be a major challenge to achieving assay validation. Harmonisation and standardisation of laboratory methods are essential for surveillance and for a rapid and effective international response to emerging diseases. Routine external quality assessment, along with well-characterised and up-to-date proficiency panels, would provide insight into MERS-CoV diagnostic performance worldwide. A defined set of Target Product Profiles for diagnostic technologies will be developed by WHO to address these gaps in MERS-CoV outbreak management.
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Affiliation(s)
| | | | - Arlene Chua
- Department of Information, Evidence and Research, WHO, Geneva, Switzerland.,Medecins Sans Frontières, Geneva, Switzerland
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Aleixandre-Benavent R, Lucas-Domínguez R, Sixto-Costoya A, Vidal-Infer A. The Sharing of Research Data in the Cell & Tissue Engineering Area: Is It a Common Practice? Stem Cells Dev 2018; 27:717-722. [PMID: 29635977 DOI: 10.1089/scd.2018.0036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The availability of research data sets is an important milestone because it can enhance the dynamics of research. This study aims to analyze the PubMed Central repository to determine the availability and type of raw data sets in Cell & Tissue Engineering journals indexed in Journal Citation Reports. The number and types of files were registered. The main finding of this study is that, beyond the mandatory deposit of data in specific repositories that some journals require, the exchange of data as supplementary material in the Cell & Tissue Engineering journals is not a common practice since researchers are still reticent to do so.
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Affiliation(s)
- Rafael Aleixandre-Benavent
- 1 UISYS, Joint Research Unit (CSIC-University of Valencia) , Valencia, Spain .,2 Ingenio (CSIC-Politechnic University of Valencia) , Ciudad Politécnica de la Innovación, Valencia, Spain
| | - Rut Lucas-Domínguez
- 1 UISYS, Joint Research Unit (CSIC-University of Valencia) , Valencia, Spain .,3 Department of the History of Science and Information Science, School of Medicine and Dentistry, University of Valencia , Valencia, Spain
| | - Andrea Sixto-Costoya
- 1 UISYS, Joint Research Unit (CSIC-University of Valencia) , Valencia, Spain .,3 Department of the History of Science and Information Science, School of Medicine and Dentistry, University of Valencia , Valencia, Spain
| | - Antonio Vidal-Infer
- 1 UISYS, Joint Research Unit (CSIC-University of Valencia) , Valencia, Spain .,3 Department of the History of Science and Information Science, School of Medicine and Dentistry, University of Valencia , Valencia, Spain
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