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Article ; Online: More to Offer Than Direct Clinical Benefit: FDA's Vaccine Licensure Process Ignores Population Health and Social Determinants of Disease.

Jones, Malia / Jetelina, Katelyn K

2023 Volume 193, Issue 1, Page(s) 1–5

Abstract: The current US Food and Drug Administration (FDA) licensure process underestimates the potential benefits of vaccines at both the individual and population levels by considering only direct clinical outcomes of vaccination. While all approved vaccines do ...

Abstract	The current US Food and Drug Administration (FDA) licensure process underestimates the potential benefits of vaccines at both the individual and population levels by considering only direct clinical outcomes of vaccination. While all approved vaccines do protect the person who takes them from poor clinical outcomes for a specific infectious disease, many vaccines also have the potential to offer measurable, direct nonclinical benefits. For example, coronavirus disease 2019 (COVID-19) vaccinations for school-aged children may prevent school absenteeism. Also, by preventing infection or reducing its length and severity, some vaccines also protect-to some extent-the patient's immediate contacts from contracting the same disease. These nonclinical and population-level benefits are not considered as part of the FDA's current vaccine approval process, but they could be. We argue that the FDA's structured benefit-risk assessment framework, used for vaccine approvals, can and should consider both clinical and nonclinical benefits of vaccination when sufficient evidence exists to make an informed assessment. Including them could incentivize vaccine developers to measure additional vaccination effects, inform population health, and address health inequalities-including inequalities in the social determinants of health.
MeSH term(s)	Humans ; Population Health ; Risk Assessment ; Social Determinants of Health ; Vaccination ; Vaccines ; Licensure ; Drug Approval ; United States Food and Drug Administration
Chemical Substances	Vaccines
Language	English
Publishing date	2023-08-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2937-3
ISSN	1476-6256 ; 0002-9262
ISSN (online)	1476-6256
ISSN	0002-9262
DOI	10.1093/aje/kwad161
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Article ; Online: Estimated Impact of the US COVID-19 Vaccination Campaign-Getting to 94% of Deaths Prevented.

Jones, Malia / Khader, Karim / Branch-Elliman, Westyn

JAMA network open

2022 Volume 5, Issue 7, Page(s) e2220391

MeSH term(s)	COVID-19/prevention & control ; COVID-19 Vaccines ; Humans ; Mass Vaccination
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2022-07-01
Publishing country	United States
Document type	Journal Article ; Comment
ISSN	2574-3805
ISSN (online)	2574-3805
DOI	10.1001/jamanetworkopen.2022.20391
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Explaining the U.S. rural disadvantage in COVID-19 case and death rates during the Delta-Omicron surge: The role of politics, vaccinations, population health, and social determinants.

Jones, Malia / Bhattar, Mahima / Henning, Emma / Monnat, Shannon M

Social science & medicine (1982)

2023 Volume 335, Page(s) 116180

Abstract: The Delta-Omicron wave of the COVID-19 pandemic (Wave 4) in the United States occurred in Fall of 2021 through Spring of 2022. Although vaccinations were widely available, this was the deadliest period to date in the U.S., and the toll was especially ... ...

Abstract	The Delta-Omicron wave of the COVID-19 pandemic (Wave 4) in the United States occurred in Fall of 2021 through Spring of 2022. Although vaccinations were widely available, this was the deadliest period to date in the U.S., and the toll was especially high in rural areas, exacerbating an existing rural mortality penalty. This paper uses county-level multilevel regression models and publicly available data for 47 U.S. states and the District of Columbia. We describe differences in COVID-19 case and mortality rates across the rural-urban continuum during Wave 4 of the COVID-19 pandemic. Using a progressive modeling approach, we evaluate the relative contribution of a range of explanatory factors for the rural disadvantage we observe, including: pre-pandemic population health composition, vaccination rates, political partisanship, socioeconomic composition, access to broadband internet rate, and primary care physicians per capita. Results show that rural counties had higher observed burdens of cases and deaths in Wave 4 compared to more urban counties. The most remote rural counties had Wave 4 COVID-19 mortality rates 52% higher than the most urban counties. Older age composition, worse pre-pandemic population health, lower vaccination rates, higher share of votes cast for Donald Trump in the 2020 Presidential election, and lower socioeconomic composition completely explained the rural disadvantage in reported COVID-19 case rates in Wave 4, and accounting for these factors reversed the observed rural disadvantage in COVID-19 mortality. In models of mortality rate, Trump vote share had the largest effect size, followed by the percentage of the population age 50 or older, the poverty rate, the pre-pandemic mortality rate, the share of residents with a 4-year college degree, and the vaccination rate. These findings add to a growing literature describing the disproportionate toll of the COVID-19 pandemic on rural America, highlighting the combined effect of multiple sources of rural disadvantage.
MeSH term(s)	Humans ; United States/epidemiology ; Middle Aged ; COVID-19/epidemiology ; COVID-19/prevention & control ; Pandemics ; Social Determinants of Health ; Population Health ; Rural Population ; District of Columbia ; Politics
Language	English
Publishing date	2023-08-17
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	4766-1
ISSN	1873-5347 ; 0037-7856 ; 0277-9536
ISSN (online)	1873-5347
ISSN	0037-7856 ; 0277-9536
DOI	10.1016/j.socscimed.2023.116180
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Article: Designing and testing social media campaign messages to promote COVID-19 vaccine confidence among rural adults: A community-engaged approach featuring rural community leader and clinician testimonials.

Yang, Sijia / Tao, Ran / Bhattar, Mahima / Shen, Liwei / Jones, Malia / Garbacz, Andy / Passmore, Susan Racine

Preventive medicine reports

2023 Volume 36, Page(s) 102508

Abstract: Despite the growing availability of effective COVID-19 vaccines in rural communities in the United States, widespread vaccine hesitancy delays COVID-19 vaccine coverage in rural communities and threatens to worsen pre-pandemic rural-urban disparities in ... ...

Abstract	Despite the growing availability of effective COVID-19 vaccines in rural communities in the United States, widespread vaccine hesitancy delays COVID-19 vaccine coverage in rural communities and threatens to worsen pre-pandemic rural-urban disparities in other vaccination rates, including influenza and routine pediatric immunizations. Therefore, there is an urgent need to develop communication-based interventions to improve vaccine confidence in rural America. This study demonstrates the efficacy of a community-engaged approach to developing social media campaign messages in promoting COVID-19 vaccine uptake and pro-vaccine social diffusion among rural adults. Using a community-engaged approach, we developed social media campaign videos varying in (a) featured messengers (clinicians versus community leaders) and (b) the presence of personal testimonials. We conducted a national online experiment (
Language	English
Publishing date	2023-11-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	2785569-7
ISSN	2211-3355
ISSN	2211-3355
DOI	10.1016/j.pmedr.2023.102508
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Article ; Online: Immune Therapy for Central Nervous System Metastasis.

McAvoy, Malia B / Choi, Bryan D / Jones, Pamela S

Neurosurgery clinics of North America

2020 Volume 31, Issue 4, Page(s) 627–639

Abstract: Brain metastases lead to substantial morbidity and mortality among patients with advanced malignancies. Although treatment options have traditionally included largely palliative measures, studies of brain metastasis response to immunotherapy are ... ...

Abstract	Brain metastases lead to substantial morbidity and mortality among patients with advanced malignancies. Although treatment options have traditionally included largely palliative measures, studies of brain metastasis response to immunotherapy are promising. Immune checkpoint inhibitors have shown efficacy in studies of patients with melanoma, renal cell carcinoma, and lung cancer brain metastases. Patients with brain metastases are more frequently included in clinical trials, ushering in a new era in immunotherapy and management for patients with brain metastases. Gaining an understanding of the molecular determination for response to immunotherapies remains a major challenge and is an active area of future research.
MeSH term(s)	Animals ; Brain Neoplasms/immunology ; Brain Neoplasms/physiopathology ; Brain Neoplasms/therapy ; Central Nervous System Neoplasms/immunology ; Central Nervous System Neoplasms/physiopathology ; Central Nervous System Neoplasms/therapy ; Combined Modality Therapy/methods ; Humans ; Immunotherapy ; Treatment Outcome ; Tumor Microenvironment
Language	English
Publishing date	2020-08-15
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1196855-2
ISSN	1558-1349 ; 1042-3680
ISSN (online)	1558-1349
ISSN	1042-3680
DOI	10.1016/j.nec.2020.06.014
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Article ; Online: Fight Like a Nerdy Girl: The Dear Pandemic Playbook for Combating Health Misinformation.

Leininger, Lindsey J / Albrecht, Sandra S / Buttenheim, Alison / Dowd, Jennifer Beam / Ritter, Ashley Z / Simanek, Amanda M / Valentino, Mary-Jo / Jones, Malia

American journal of health promotion : AJHP

2022 Volume 36, Issue 3, Page(s) 563–567

MeSH term(s)	Communication ; Female ; Humans ; Pandemics ; Social Media
Language	English
Publishing date	2022-02-14
Publishing country	United States
Document type	Editorial
ZDB-ID	645160-3
ISSN	2168-6602 ; 0890-1171
ISSN (online)	2168-6602
ISSN	0890-1171
DOI	10.1177/08901171211070956
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Article ; Online: Computational fluid dynamics modeling of cough transport in an aircraft cabin.

Zee, Malia / Davis, Angela C / Clark, Andrew D / Wu, Tateh / Jones, Stephen P / Waite, Lindsay L / Cummins, Joshua J / Olson, Nels A

Scientific reports

2021 Volume 11, Issue 1, Page(s) 23329

Abstract: To characterize the transport of respiratory pathogens during commercial air travel, Computational Fluid Dynamics simulations were performed to track particles expelled by coughing by a passenger assigned to different seats on a Boeing 737 aircraft. ... ...

Abstract	To characterize the transport of respiratory pathogens during commercial air travel, Computational Fluid Dynamics simulations were performed to track particles expelled by coughing by a passenger assigned to different seats on a Boeing 737 aircraft. Simulation data were post-processed to calculate the amounts of particles inhaled by nearby passengers. Different airflow rates were used, as well as different initial conditions to account for random fluctuations of the flow field. Overall, 80% of the particles were removed from the cabin in 1.3-2.6 min, depending on conditions, and 95% of the particles were removed in 2.4-4.6 min. Reducing airflow increased particle dispersion throughout the cabin but did not increase the highest exposure of nearby passengers. The highest exposure was 0.3% of the nonvolatile mass expelled by the cough, and the median exposure for seats within 3 feet of the cough discharge was 0.1%, which was in line with recent experimental testing.
MeSH term(s)	Air Movements ; Air Pollution, Indoor/analysis ; Aircraft/instrumentation ; Computer Simulation ; Cough/pathology ; Humans ; Hydrodynamics ; Lung/physiopathology
Language	English
Publishing date	2021-12-02
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-02663-8
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Article ; Online: Dear Pandemic

Aleksandra M Golos / Sharath Chandra Guntuku / Rachael Piltch-Loeb / Lindsey J Leininger / Amanda M Simanek / Aparna Kumar / Sandra S Albrecht / Jennifer Beam Dowd / Malia Jones / Alison M Buttenheim

PLoS ONE, Vol 18, Iss 3, p e

A topic modeling analysis of COVID-19 information needs among readers of an online science communication campaign.

2023 Volume 0281773

Abstract: Background The COVID-19 pandemic was accompanied by an "infodemic"-an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 ... ...

Abstract	Background The COVID-19 pandemic was accompanied by an "infodemic"-an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 infodemic, in part by soliciting submissions from readers to an online question box. Our study characterized the information needs of Dear Pandemic's readers by identifying themes and longitudinal trends among question box submissions. Methods We conducted a retrospective analysis of questions submitted from August 24, 2020, to August 24, 2021. We used Latent Dirichlet Allocation topic modeling to identify 25 topics among the submissions, then used thematic analysis to interpret the topics based on their top words and submissions. We used t-Distributed Stochastic Neighbor Embedding to visualize the relationship between topics, and we used generalized additive models to describe trends in topic prevalence over time. Results We analyzed 3839 submissions, 90% from United States-based readers. We classified the 25 topics into 6 overarching themes: 'Scientific and Medical Basis of COVID-19,' 'COVID-19 Vaccine,' 'COVID-19 Mitigation Strategies,' 'Society and Institutions,' 'Family and Personal Relationships,' and 'Navigating the COVID-19 Infodemic.' Trends in topics about viral variants, vaccination, COVID-19 mitigation strategies, and children aligned with the news cycle and reflected the anticipation of future events. Over time, vaccine-related submissions became increasingly related to those surrounding social interaction. Conclusions Question box submissions represented distinct themes that varied in prominence over time. Dear Pandemic's readers sought information that would not only clarify novel scientific concepts, but would also be timely and practical to their personal lives. Our question box format and topic modeling approach offers science communicators a robust methodology for tracking, understanding, and responding to the information needs of online audiences.
Keywords	Medicine ; R ; Science ; Q
Subject code	306 ; 028
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dear Pandemic

Aleksandra M. Golos / Sharath Chandra Guntuku / Rachael Piltch-Loeb / Lindsey J. Leininger / Amanda M. Simanek / Aparna Kumar / Sandra S. Albrecht / Jennifer Beam Dowd / Malia Jones / Alison M. Buttenheim

PLoS ONE, Vol 18, Iss

A topic modeling analysis of COVID-19 information needs among readers of an online science communication campaign

2023 Volume 3

Abstract: Background The COVID-19 pandemic was accompanied by an “infodemic”–an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 ... ...

Abstract	Background The COVID-19 pandemic was accompanied by an “infodemic”–an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 infodemic, in part by soliciting submissions from readers to an online question box. Our study characterized the information needs of Dear Pandemic’s readers by identifying themes and longitudinal trends among question box submissions. Methods We conducted a retrospective analysis of questions submitted from August 24, 2020, to August 24, 2021. We used Latent Dirichlet Allocation topic modeling to identify 25 topics among the submissions, then used thematic analysis to interpret the topics based on their top words and submissions. We used t-Distributed Stochastic Neighbor Embedding to visualize the relationship between topics, and we used generalized additive models to describe trends in topic prevalence over time. Results We analyzed 3839 submissions, 90% from United States-based readers. We classified the 25 topics into 6 overarching themes: ‘Scientific and Medical Basis of COVID-19,’ ‘COVID-19 Vaccine,’ ‘COVID-19 Mitigation Strategies,’ ‘Society and Institutions,’ ‘Family and Personal Relationships,’ and ‘Navigating the COVID-19 Infodemic.’ Trends in topics about viral variants, vaccination, COVID-19 mitigation strategies, and children aligned with the news cycle and reflected the anticipation of future events. Over time, vaccine-related submissions became increasingly related to those surrounding social interaction. Conclusions Question box submissions represented distinct themes that varied in prominence over time. Dear Pandemic’s readers sought information that would not only clarify novel scientific concepts, but would also be timely and practical to their personal lives. Our question box format and topic modeling approach offers science communicators a robust methodology for tracking, understanding, and responding to the information needs of online audiences.
Keywords	Medicine ; R ; Science ; Q
Subject code	306 ; 028
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: What Were the Information Voids? A Qualitative Analysis of Questions Asked by Dear Pandemic Readers between August 2020-August 2021.

Piltch-Loeb, Rachael / James, Richard / Albrecht, Sandra S / Buttenheim, Alison M / Dowd, Jennifer Beam / Kumar, Aparna / Jones, Malia / Leininger, Lindsey J / Simanek, Amanda / Aronowitz, Shoshana

Journal of health communication

2023 Volume 28, Issue sup1, Page(s) 25–33

Abstract: In the current infodemic, how individuals receive information (channel), who it is coming from (source), and how it is framed can have an important effect on COVID-19 related mitigation behaviors. In light of these challenges presented by the infodemic, ... ...

Abstract	In the current infodemic, how individuals receive information (channel), who it is coming from (source), and how it is framed can have an important effect on COVID-19 related mitigation behaviors. In light of these challenges presented by the infodemic, Dear Pandemic (DP) was created to directly address persistent questions related to COVID-19 and other health topics in the online environment. This is a qualitative analysis of 3806 questions that were submitted by DP readers to a question box on the Dear Pandemic website between August 30, 2020 and August 29, 2021. Analyses resulted in four themes: the need for clarification of other sources; lack of trust in information; recognition of possible misinformation; and questions on personal decision-making. Each theme reflects an unmet informational need of Dear Pandemic readers, which may be reflective of the broader informational gaps in our science communication efforts.This study highlights the role of an ad hoc risk communication platform in the current environment and uses questions submitted to the Dear Pandemic question box to identify informational needs of DP readers over the course of the COVID-19 pandemic. These findings may help clarify how organizations addressing health misinformation in the digital space can contribute to timely, responsive science communication and improve future communication efforts.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Pandemics/prevention & control ; Communication ; Trust
Language	English
Publishing date	2023-06-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	1427988-5
ISSN	1087-0415 ; 1081-0730
ISSN (online)	1087-0415
ISSN	1081-0730
DOI	10.1080/10810730.2023.2214986
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