Dataset Information

Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

ABSTRACT: The role of geospatial disparities in the dynamics of the COVID-19 pandemic is poorly understood. We developed a spatially-explicit mathematical model to simulate transmission dynamics of COVID-19 disease infection in relation with the uneven distribution of the healthcare capacity in Ohio, U.S. The results showed substantial spatial variation in the spread of the disease, with localized areas showing marked differences in disease attack rates. Higher COVID-19 attack rates experienced in some highly connected and urbanized areas (274 cases per 100,000 people) could substantially impact the critical health care response of these areas regardless of their potentially high healthcare capacity compared to more rural and less connected counterparts (85 cases per 100,000). Accounting for the spatially uneven disease diffusion linked to the geographical distribution of the critical care resources is essential in designing effective prevention and control programmes aimed at reducing the impact of COVID-19 pandemic.

SUBMITTER: Cuadros DF

PROVIDER: S-EPMC7381891 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

Cuadros Diego F DF Xiao Yanyu Y Mukandavire Zindoga Z Correa-Agudelo Esteban E Hernández Andrés A Kim Hana H MacKinnon Neil J NJ

Health & place 20200725

The role of geospatial disparities in the dynamics of the COVID-19 pandemic is poorly understood. We developed a spatially-explicit mathematical model to simulate transmission dynamics of COVID-19 disease infection in relation with the uneven distribution of the healthcare capacity in Ohio, U.S. The results showed substantial spatial variation in the spread of the disease, with localized areas showing marked differences in disease attack rates. Higher COVID-19 attack rates experienced in some hi ...[more]

PMID: 32736312

Similar Datasets

Project description:BackgroundThe COVID-19 pandemic has severely affected health systems and medical research worldwide but its impact on the global publication dynamics and non-COVID-19 research has not been measured. We hypothesized that the COVID-19 pandemic may have impacted the scientific production of non-COVID-19 research.MethodsWe conducted a comprehensive meta-research on studies (original articles, research letters and case reports) published between 01/01/2019 and 01/01/2021 in 10 high-impact medical and infectious disease journals (New England Journal of Medicine, Lancet, Journal of the American Medical Association, Nature Medicine, British Medical Journal, Annals of Internal Medicine, Lancet Global Health, Lancet Public Health, Lancet Infectious Disease and Clinical Infectious Disease). For each publication, we recorded publication date, publication type, number of authors, whether the publication was related to COVID-19, whether the publication was based on a case series, and the number of patients included in the study if the publication was based on a case report or a case series. We estimated the publication dynamics with a locally estimated scatterplot smoothing method. A Natural Language Processing algorithm was designed to calculate the number of authors for each publication. We simulated the number of non-COVID-19 studies that could have been published during the pandemic by extrapolating the publication dynamics of 2019 to 2020, and comparing the expected number to the observed number of studies.ResultsAmong the 22,525 studies assessed, 6319 met the inclusion criteria, of which 1022 (16.2%) were related to COVID-19 research. A dramatic increase in the number of publications in general journals was observed from February to April 2020 from a weekly median number of publications of 4.0 (IQR: 2.8-5.5) to 19.5 (IQR: 15.8-24.8) (p < 0.001), followed afterwards by a pattern of stability with a weekly median number of publications of 10.0 (IQR: 6.0-14.0) until December 2020 (p = 0.045 in comparison with April). Two prototypical editorial strategies were found: 1) journals that maintained the volume of non-COVID-19 publications while integrating COVID-19 research and thus increased their overall scientific production, and 2) journals that decreased the volume of non-COVID-19 publications while integrating COVID-19 publications. We estimated using simulation models that the COVID pandemic was associated with a 18% decrease in the production of non-COVID-19 research. We also found a significant change of the publication type in COVID-19 research as compared with non-COVID-19 research illustrated by a decrease in the number of original articles, (47.9% in COVID-19 publications vs 71.3% in non-COVID-19 publications, p < 0.001). Last, COVID-19 publications showed a higher number of authors, especially for case reports with a median of 9.0 authors (IQR: 6.0-13.0) in COVID-19 publications, compared to a median of 4.0 authors (IQR: 3.0-6.0) in non-COVID-19 publications (p < 0.001).ConclusionIn this meta-research gathering publications from high-impact medical journals, we have shown that the dramatic rise in COVID-19 publications was accompanied by a substantial decrease of non-COVID-19 research. META-RESEARCH REGISTRATION: https://osf.io/9vtzp/ .

Dataset Information

Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

Publications

Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets