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The heterogeneity of the COVID-19 pandemic and national responses: an explanatory mixed-methods study

Overview of attention for article published in BMC Public Health, May 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)

Mentioned by

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3 tweeters

Citations

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13 Dimensions

Readers on

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82 Mendeley
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Title
The heterogeneity of the COVID-19 pandemic and national responses: an explanatory mixed-methods study
Published in
BMC Public Health, May 2021
DOI 10.1186/s12889-021-10885-8
Pubmed ID
Authors

Yi-Ying Chen, Yibeltal Assefa

Abstract

The coronavirus disease of 2019 (COVID-19) has quickly spread to all corners of the world since its emergence in Wuhan, China in December of 2019. The disease burden has been heterogeneous across regions of the world, with Americas leading in cumulative cases and deaths, followed by Europe, Southeast Asia, Eastern Mediterranean, Africa and Western Pacific. Initial responses to COVID-19 also varied between governments, ranging from proactive containment to delayed intervention. Understanding these variabilities allow high burden countries to learn from low burden countries on ways to create more sustainable response plans in the future. This study used a mixed-methods approach to perform cross-country comparisons of pandemic responses in the United States (US), Brazil, Germany, Australia, South Korea, Thailand, New Zealand, Italy and China. These countries were selected based on their income level, relative COVID-19 burden and geographic location. To rationalize the epidemiological variability, a list of 14 indicators was established to assess the countries' preparedness, actual response, and socioeconomic and demographic profile in the context of COVID-19. As of 1 April 2021, the US had the highest cases per million out of the nine countries, followed by Brazil, Italy, Germany, South Korea, Australia, New Zealand, Thailand and China. Meanwhile, Italy ranked first out of the nine countries' total deaths per million, followed by the US, Brazil, Germany, Australia, South Korea, New Zealand, China and Thailand. The epidemiological differences between these countries could be explained by nine indicators, and they were 1) leadership, governance and coordination of response, 2) communication, 3) community engagement, 4) multisectoral actions, 5) public health capacity, 6) universal health coverage, 7) medical services and hospital capacity, 8) demography and 9) burden of non-communicable diseases. The COVID-19 pandemic manifests varied outcomes due to differences in countries' vulnerability, preparedness and response. Our study rationalizes why South Korea, New Zealand, Thailand, Australia and China performed better than the US, Italy and Brazil. By identifying the strengths of low burden countries and weaknesses of hotspot countries, we elucidate factors constituting an effective pandemic response that can be adopted by leaders in preparation for re-emerging public health threats.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 15%
Researcher 11 13%
Student > Bachelor 7 9%
Student > Ph. D. Student 5 6%
Librarian 4 5%
Other 19 23%
Unknown 24 29%
Readers by discipline Count As %
Nursing and Health Professions 11 13%
Medicine and Dentistry 11 13%
Social Sciences 8 10%
Economics, Econometrics and Finance 5 6%
Immunology and Microbiology 3 4%
Other 14 17%
Unknown 30 37%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 December 2021.
All research outputs
#12,618,516
of 21,774,582 outputs
Outputs from BMC Public Health
#8,833
of 14,119 outputs
Outputs of similar age
#158,159
of 341,351 outputs
Outputs of similar age from BMC Public Health
#1
of 1 outputs
Altmetric has tracked 21,774,582 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,119 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one is in the 36th percentile – i.e., 36% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,351 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them