The heterogeneity of the COVID-19 pandemic and national responses: an explanatory mixed-methods study
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, Southeas...
Saved in:
| Published in | BMC public health Vol. 21; no. 1; pp. 835 - 15 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
England
BioMed Central Ltd
01.05.2021
BioMed Central BMC |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| 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. |
|---|---|
| AbstractList | 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.BACKGROUNDThe 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.METHODSThis 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.RESULTSAs 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.CONCLUSIONThe 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. Background 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. Methods 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. Results 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. Conclusion 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. Background 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. Methods 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. Results 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. Conclusion 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. Keywords: COVID-19 pandemic response, Australia, Brazil, China, Germany, Italy, New Zealand, South Korea, Thailand, United States Abstract Background 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. Methods 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. Results 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. Conclusion 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. 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. 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. |
| ArticleNumber | 835 |
| Audience | Academic |
| Author | Chen, Yi-Ying Assefa, Yibeltal |
| Author_xml | – sequence: 1 givenname: Yi-Ying surname: Chen fullname: Chen, Yi-Ying – sequence: 2 givenname: Yibeltal surname: Assefa fullname: Assefa, Yibeltal |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33933062$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9kk1vEzEQhleoiH7AH-CAVuLCZYu_dtfmgFSFFiJV6qVwtfwxThztroPtoObf4yYtNBVCPow1885jzfg9rY6mMEFVvcXoHGPefUyYcC4aRHCDEedtw19UJ5j1uCGs5UdP7sfVaUorhHDPW_KqOqZUUIo6clLB7RLqJWSIYQET-Lytg6tzSc5ufsy_NFjUazVZGL2pS6wnlX2Y1FBHSOswJUifSr6Gu_WgSi3EbT36O7DNCHkZbKpT3tjt6-qlU0OCNw_xrPp-dXk7-9Zc33ydzy6uG9MRkRslkOWa9RYDg67XmgFzpHfaMusUBmOZE8K0mLWut0YorYxBDjtEkBIE6Fk133NtUCu5jn5UcSuD8nKXCHEhVczeDCCdIj1VGtNWAyPQc2oxRQQYx1rrXhTW5z1rvdEjWANTjmo4gB5WJr-Ui_BLcsR7zmkBfHgAxPBzAynL0ScDQ1kUhE2SpCWYCdF3qEjfP5OuwiaWNe9UXDDecfxXtVBlAD-5UN4191B50XWYUdqhrqjO_6EqZ_eJxUHOl_xBw7ung_6Z8NEkRcD3AhNDShGcND7vfFDIfpAYyXs_yr0fZfGj3PlR8tJKnrU-0v_T9BtOKuJp |
| CitedBy_id | crossref_primary_10_3390_ijerph182312595 crossref_primary_10_1080_00472336_2022_2106883 crossref_primary_10_1016_j_healthplace_2023_103164 crossref_primary_10_3947_ic_2022_0111 crossref_primary_10_1186_s12913_024_11197_4 crossref_primary_10_1200_GO_22_00001 crossref_primary_10_1590_1413_812320232812_13562022 crossref_primary_10_1016_j_lanwpc_2022_100518 crossref_primary_10_55905_cuadv15n8_010 crossref_primary_10_1007_s11739_022_03107_5 crossref_primary_10_3389_fsurg_2022_962844 crossref_primary_10_1186_s12889_023_15975_3 crossref_primary_10_4081_gh_2022_1145 crossref_primary_10_1016_j_jpsychires_2024_02_031 crossref_primary_10_1111_eci_13682 crossref_primary_10_3390_ijerph19148767 crossref_primary_10_1080_01612840_2024_2396984 crossref_primary_10_1186_s12985_022_01771_9 crossref_primary_10_36472_msd_v10i10_1086 crossref_primary_10_53044_jinr_2023_0039 crossref_primary_10_1016_j_lanwpc_2022_100563 crossref_primary_10_1186_s12875_022_01786_9 crossref_primary_10_3390_app12063032 crossref_primary_10_1007_s10901_023_10065_7 crossref_primary_10_1080_13632469_2023_2185863 crossref_primary_10_1016_j_socscimed_2023_116007 crossref_primary_10_1186_s44263_024_00054_5 crossref_primary_10_3389_fmed_2022_999225 crossref_primary_10_3389_fpubh_2021_763645 crossref_primary_10_3390_healthcare10030489 crossref_primary_10_3390_ijerph21060787 crossref_primary_10_1016_j_socscimed_2023_116230 crossref_primary_10_1136_bmjgh_2023_012271 crossref_primary_10_1186_s12992_022_00805_9 crossref_primary_10_1590_1413_812320232812_13562022en crossref_primary_10_1016_j_celrep_2024_114930 crossref_primary_10_1016_j_puhip_2022_100301 |
| Cites_doi | 10.1017/err.2020.49 10.3390/ijerph17103356 10.2471/BLT.12.102178 10.1016/S2214-109X(17)30472-2 10.1126/science.abb5152 10.21106/ijma.389 10.1016/S1473-3099(20)30800-8 10.2139/ssrn.3693861 10.1080/15387216.2020.1762690 10.1136/postgradmedj-2020-137742 10.1007/s10272-020-0886-0 10.1590/0034-761220200290 10.1177/0275074020943708 10.1037/amp0000715 10.1080/13669877.2020.1758755 10.1097/ALN.0000000000003299 10.1001/jamainternmed.2020.1447 10.1136/bmj.m2296 10.1215/03616878-8641506 10.1016/j.worlddev.2020.105198 10.1016/S0140-6736(20)30567-5 10.1136/bmj.m2659 10.1016/S0140-6736(20)32228-5 10.4081/jphr.2014.199 10.1016/j.healthpol.2015.06.001 10.1136/bmj.m1592 10.1016/S0140-6736(20)31097-7 10.1136/bmj.m1222 10.1016/S0140-6736(20)31493-8 10.1186/s12889-020-09924-7 10.1186/s41256-020-00150-7 10.1016/j.jstrokecerebrovasdis.2020.105089 10.1080/17441692.2020.1783340 10.1016/j.hlpt.2020.09.003 10.1007/s10640-020-00466-5 10.1007/s40520-020-01664-3 10.1093/cid/ciaa1785 10.2139/ssrn.3722299 10.1001/jama.2020.2648 10.1016/j.healthpol.2015.07.008 10.1007/s11684-020-0766-9 10.7189/jogh.10.010350 10.1080/13678868.2020.1779543 10.1371/journal.pntd.0008412 10.1111/1467-923X.12893 10.1056/NEJMoa2001017 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2021 BioMed Central Ltd. 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Author(s) 2021 |
| Copyright_xml | – notice: COPYRIGHT 2021 BioMed Central Ltd. – notice: 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: The Author(s) 2021 |
| DBID | AAYXX CITATION NPM 3V. 7T2 7X7 7XB 88E 8C1 8FE 8FG 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA AN0 ATCPS AZQEC BENPR BGLVJ BHPHI C1K CCPQU COVID DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. L6V M0S M1P M7S PATMY PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY 7X8 5PM DOA |
| DOI | 10.1186/s12889-021-10885-8 |
| DatabaseName | CrossRef PubMed ProQuest Central (Corporate) Health and Safety Science Abstracts (Full archive) ProQuest Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Public Health Database ProQuest SciTech Collection ProQuest Technology Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability (subscription) ProQuest Central UK/Ireland British Nursing Database (Proquest) Agricultural & Environmental Science Collection ProQuest Central Essentials ProQuest Central Technology Collection Natural Science Collection Environmental Sciences and Pollution Management ProQuest One Coronavirus Research Database ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) ProQuest Engineering Collection Health & Medical Collection (Alumni) Medical Database ProQuest Engineering Database Environmental Science Database ProQuest Central Premium ProQuest One Academic Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering collection Environmental Science Collection MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China Environmental Sciences and Pollution Management ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability ProQuest Health & Medical Research Collection ProQuest Engineering Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Agricultural & Environmental Science Collection Health & Safety Science Abstracts ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Engineering Database ProQuest Public Health ProQuest One Academic Eastern Edition British Nursing Index with Full Text Coronavirus Research Database ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) Environmental Science Collection ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition Materials Science & Engineering Collection Environmental Science Database ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic Publicly Available Content Database PubMed |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Public Health |
| EISSN | 1471-2458 |
| EndPage | 15 |
| ExternalDocumentID | oai_doaj_org_article_fa273ab135be42e783d1302e481bbb79 PMC8087883 A661433606 33933062 10_1186_s12889_021_10885_8 |
| Genre | Journal Article |
| GeographicLocations | Australia New Zealand South Korea United States--US Europe China Africa Brazil Italy Thailand Germany |
| GeographicLocations_xml | – name: Australia – name: Germany – name: South Korea – name: Italy – name: China – name: New Zealand – name: Thailand – name: Africa – name: Europe – name: United States--US – name: Brazil |
| GroupedDBID | --- 0R~ 23N 2WC 2XV 44B 53G 5VS 6J9 6PF 7X7 7XC 88E 8C1 8FE 8FG 8FH 8FI 8FJ A8Z AAFWJ AAJSJ AASML AAWTL AAYXX ABDBF ABJCF ABUWG ACGFO ACGFS ACIHN ACIWK ACPRK ACUHS ADBBV ADUKV AEAQA AENEX AEUYN AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALIPV ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AN0 AOIJS ATCPS BAPOH BAWUL BCNDV BENPR BFQNJ BGLVJ BHPHI BMC BNQBC BPHCQ BVXVI C6C CCPQU CITATION CS3 DIK DU5 E3Z EAD EAP EAS EBD EBLON EBS EMB EMK EMOBN ESX F5P FYUFA GROUPED_DOAJ GX1 HCIFZ HMCUK HYE IAO IHR INH INR ITC KQ8 L6V M1P M48 M7S M~E O5R O5S OK1 OVT P2P PATMY PHGZM PHGZT PIMPY PQQKQ PROAC PSQYO PTHSS PYCSY RBZ RNS ROL RPM RSV SMD SOJ SV3 TR2 TUS U2A UKHRP W2D WOQ WOW XSB NPM PMFND 3V. 7T2 7XB 8FK AZQEC C1K COVID DWQXO GNUQQ K9. PJZUB PKEHL PPXIY PQEST PQGLB PQUKI PRINS 7X8 5PM PUEGO |
| ID | FETCH-LOGICAL-c629t-a90d8b47d1e4e67bb4e4f27fbd4dfa1ecd4f99c5145f7dc9abacc0f1f020a92e3 |
| IEDL.DBID | M48 |
| ISSN | 1471-2458 |
| IngestDate | Wed Aug 27 01:24:24 EDT 2025 Thu Aug 21 14:40:13 EDT 2025 Fri Jul 11 11:24:46 EDT 2025 Fri Jul 25 19:14:52 EDT 2025 Tue Jun 17 20:54:59 EDT 2025 Tue Jun 10 20:54:16 EDT 2025 Thu Apr 03 07:02:18 EDT 2025 Tue Jul 01 00:56:14 EDT 2025 Thu Apr 24 22:59:45 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | New Zealand South Korea United States China Brazil COVID-19 pandemic response Italy Australia Thailand Germany |
| Language | English |
| License | Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c629t-a90d8b47d1e4e67bb4e4f27fbd4dfa1ecd4f99c5145f7dc9abacc0f1f020a92e3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | http://journals.scholarsportal.info/openUrl.xqy?doi=10.1186/s12889-021-10885-8 |
| PMID | 33933062 |
| PQID | 2528948681 |
| PQPubID | 44782 |
| PageCount | 15 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_fa273ab135be42e783d1302e481bbb79 pubmedcentral_primary_oai_pubmedcentral_nih_gov_8087883 proquest_miscellaneous_2521499760 proquest_journals_2528948681 gale_infotracmisc_A661433606 gale_infotracacademiconefile_A661433606 pubmed_primary_33933062 crossref_citationtrail_10_1186_s12889_021_10885_8 crossref_primary_10_1186_s12889_021_10885_8 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2021-05-01 |
| PublicationDateYYYYMMDD | 2021-05-01 |
| PublicationDate_xml | – month: 05 year: 2021 text: 2021-05-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: London |
| PublicationTitle | BMC public health |
| PublicationTitleAlternate | BMC Public Health |
| PublicationYear | 2021 |
| Publisher | BioMed Central Ltd BioMed Central BMC |
| Publisher_xml | – name: BioMed Central Ltd – name: BioMed Central – name: BMC |
| References | 10885_CR109 10885_CR107 BBC News (10885_CR68) 2020 10885_CR67 M Ke (10885_CR78) 2020 10885_CR62 10885_CR113 10885_CR65 10885_CR110 10885_CR61 10885_CR114 10885_CR60 R Tikkanen (10885_CR89) 2020 D Dongarwar (10885_CR116) 2020; 9 S Mazey (10885_CR13) 2020; 91 10885_CR79 10885_CR74 J Thornton (10885_CR75) 2020; 370 10885_CR101 10885_CR73 10885_CR102 B Balmford (10885_CR122) 2020; 76 10885_CR100 10885_CR70 10885_CR105 10885_CR106 10885_CR72 10885_CR103 10885_CR71 10885_CR104 M Baker (10885_CR64) 2020 10885_CR49 10885_CR48 10885_CR45 10885_CR47 10885_CR46 V Abazi (10885_CR40) 2020; 11 MR Azarpazhooh (10885_CR108) 2020; 29 JC Rhee (10885_CR84) 2015; 119 JY Yoo (10885_CR2) 2020; 20 J Park (10885_CR18) 2021; 137 R Pal (10885_CR120) 2020; 96 Z Wu (10885_CR98) 2020; 323 RM Anderson (10885_CR112) 2020; 395 DE McMahon (10885_CR6) 2020; 14 H Yu (10885_CR77) 2015; 119 DR Hogan (10885_CR117) 2018; 6 10885_CR56 10885_CR55 10885_CR58 10885_CR57 10885_CR52 H Kang (10885_CR16) 2020 10885_CR51 10885_CR54 D McGuire (10885_CR14) 2020; 23 10885_CR50 AMO Al Saidi (10885_CR111) 2020; 396 F GAdAL (10885_CR76) 2020; 54 T Burki (10885_CR44) 2020; 20 W Patcharanaruamol (10885_CR17) 2020 ML Ruiu (10885_CR37) 2020; 23 10885_CR19 M Narkvichien (10885_CR63) 2020 10885_CR27 10885_CR26 10885_CR28 10885_CR23 SE Gollust (10885_CR53) 2020; 45 10885_CR22 10885_CR25 10885_CR24 10885_CR21 10885_CR20 K Keisler-Starkey (10885_CR90) 2020 10885_CR38 S Cousins (10885_CR82) 2020; 395 10885_CR39 10885_CR34 10885_CR36 Budget 2020–21 (10885_CR66) 2020 10885_CR35 FJ Prante (10885_CR88) 2020; 55 10885_CR30 10885_CR32 10885_CR31 X Chen (10885_CR43) 2020; 61 Z Desson (10885_CR33) 2020; 9 C Dyer (10885_CR41) 2020; 369 C Aluttis (10885_CR59) 2014; 3 10885_CR5 10885_CR4 10885_CR7 10885_CR1 10885_CR3 Ministry of Health NZ (10885_CR83) 2020 Y Li (10885_CR115) 2012; 90 10885_CR86 10885_CR81 10885_CR80 10885_CR118 10885_CR119 B Armocida (10885_CR87) 2020; 10 10885_CR15 WHO (10885_CR85) 2010 P Fronstin (10885_CR94) 2020 10885_CR9 10885_CR12 10885_CR8 10885_CR11 10885_CR99 10885_CR96 10885_CR95 10885_CR10 10885_CR121 10885_CR97 SL Greer (10885_CR29) 2020; 15 10885_CR92 10885_CR91 J You (10885_CR42) 2020; 50 S Boccia (10885_CR69) 2020; 180 10885_CR93 |
| References_xml | – ident: 10885_CR39 – ident: 10885_CR7 – ident: 10885_CR97 – volume: 11 start-page: 375 issue: 2 year: 2020 ident: 10885_CR40 publication-title: Eur J Risk Regulat doi: 10.1017/err.2020.49 – ident: 10885_CR5 doi: 10.3390/ijerph17103356 – ident: 10885_CR60 – volume: 90 start-page: 664 issue: 9 year: 2012 ident: 10885_CR115 publication-title: Bull World Health Organ doi: 10.2471/BLT.12.102178 – ident: 10885_CR22 – ident: 10885_CR31 – volume: 6 start-page: e152 issue: 2 year: 2018 ident: 10885_CR117 publication-title: Lancet Glob Health doi: 10.1016/S2214-109X(17)30472-2 – ident: 10885_CR54 – ident: 10885_CR102 – volume-title: Brazil's march towards universal coverage year: 2010 ident: 10885_CR85 – ident: 10885_CR25 – ident: 10885_CR71 doi: 10.1126/science.abb5152 – ident: 10885_CR80 – ident: 10885_CR107 – volume: 9 start-page: 213 issue: 2 year: 2020 ident: 10885_CR116 publication-title: Int J MCH AIDS doi: 10.21106/ijma.389 – ident: 10885_CR57 – ident: 10885_CR36 – ident: 10885_CR74 – volume-title: International Health Care System Profiles: Italy year: 2020 ident: 10885_CR89 – volume: 20 start-page: 1240 issue: 11 year: 2020 ident: 10885_CR44 publication-title: Lancet Infect Dis doi: 10.1016/S1473-3099(20)30800-8 – volume-title: COVID-19 Health System Response Monitor: Republic of Korea year: 2020 ident: 10885_CR16 – ident: 10885_CR23 doi: 10.2139/ssrn.3693861 – volume: 61 start-page: 435 issue: 4–5 year: 2020 ident: 10885_CR43 publication-title: Eurasian Geogr Econ doi: 10.1080/15387216.2020.1762690 – volume: 96 start-page: 429 issue: 1137 year: 2020 ident: 10885_CR120 publication-title: Postgrad Med J doi: 10.1136/postgradmedj-2020-137742 – ident: 10885_CR9 – ident: 10885_CR95 – ident: 10885_CR24 – volume: 55 start-page: 147 issue: 3 year: 2020 ident: 10885_CR88 publication-title: Intereconomics. doi: 10.1007/s10272-020-0886-0 – ident: 10885_CR47 – volume: 54 start-page: 595 issue: 4 year: 2020 ident: 10885_CR76 publication-title: Revista de Administração Pública doi: 10.1590/0034-761220200290 – volume: 50 start-page: 801 issue: 6–7 year: 2020 ident: 10885_CR42 publication-title: Am Rev Public Adm doi: 10.1177/0275074020943708 – volume-title: Covid-19: China's Qingdao to test nine million in five days year: 2020 ident: 10885_CR68 – ident: 10885_CR19 doi: 10.1037/amp0000715 – volume: 23 start-page: 1007 issue: 7–8 year: 2020 ident: 10885_CR37 publication-title: J Risk Res doi: 10.1080/13669877.2020.1758755 – ident: 10885_CR81 – ident: 10885_CR99 doi: 10.1097/ALN.0000000000003299 – ident: 10885_CR52 – ident: 10885_CR10 – volume: 180 start-page: 927 issue: 7 year: 2020 ident: 10885_CR69 publication-title: JAMA Intern Med doi: 10.1001/jamainternmed.2020.1447 – ident: 10885_CR100 – ident: 10885_CR92 – ident: 10885_CR38 doi: 10.1136/bmj.m2296 – ident: 10885_CR86 – volume: 45 start-page: 967 issue: 6 year: 2020 ident: 10885_CR53 publication-title: J Health Polit Policy Law doi: 10.1215/03616878-8641506 – ident: 10885_CR61 – volume: 137 start-page: 105198 year: 2021 ident: 10885_CR18 publication-title: World Dev doi: 10.1016/j.worlddev.2020.105198 – ident: 10885_CR27 – volume: 395 start-page: 931 issue: 10228 year: 2020 ident: 10885_CR112 publication-title: Lancet doi: 10.1016/S0140-6736(20)30567-5 – volume: 370 start-page: m2659 year: 2020 ident: 10885_CR75 publication-title: BMJ. doi: 10.1136/bmj.m2659 – ident: 10885_CR4 doi: 10.1016/S0140-6736(20)32228-5 – ident: 10885_CR55 – volume: 3 start-page: 199 issue: 1 year: 2014 ident: 10885_CR59 publication-title: J Public Health Res doi: 10.4081/jphr.2014.199 – ident: 10885_CR105 – volume: 119 start-page: 1319 issue: 10 year: 2015 ident: 10885_CR84 publication-title: Health Policy. doi: 10.1016/j.healthpol.2015.06.001 – volume: 369 start-page: m1592 year: 2020 ident: 10885_CR41 publication-title: BMJ. doi: 10.1136/bmj.m1592 – ident: 10885_CR72 – ident: 10885_CR30 – volume-title: How China pays for its COVID-19 medical bills year: 2020 ident: 10885_CR78 – ident: 10885_CR70 – ident: 10885_CR93 – volume-title: COVID-19: Questions and answers year: 2020 ident: 10885_CR83 – ident: 10885_CR49 – volume: 395 start-page: 1474 issue: 10235 year: 2020 ident: 10885_CR82 publication-title: Lancet doi: 10.1016/S0140-6736(20)31097-7 – ident: 10885_CR26 – ident: 10885_CR113 doi: 10.1136/bmj.m1222 – ident: 10885_CR106 – volume: 396 start-page: 295 issue: 10247 year: 2020 ident: 10885_CR111 publication-title: Lancet doi: 10.1016/S0140-6736(20)31493-8 – ident: 10885_CR3 – ident: 10885_CR58 – ident: 10885_CR12 – ident: 10885_CR73 – ident: 10885_CR50 – ident: 10885_CR35 – volume: 20 start-page: 1853 issue: 1 year: 2020 ident: 10885_CR2 publication-title: BMC Public Health doi: 10.1186/s12889-020-09924-7 – ident: 10885_CR45 doi: 10.1186/s41256-020-00150-7 – ident: 10885_CR67 – ident: 10885_CR8 – ident: 10885_CR46 – ident: 10885_CR21 – volume: 29 start-page: 105089 issue: 9 year: 2020 ident: 10885_CR108 publication-title: J Stroke Cerebrovasc Dis doi: 10.1016/j.jstrokecerebrovasdis.2020.105089 – volume-title: How Many Americans Have Lost Jobs with Employer Health Coverage During the Pandemic? year: 2020 ident: 10885_CR94 – volume: 15 start-page: 1413 issue: 9 year: 2020 ident: 10885_CR29 publication-title: Global Public Health doi: 10.1080/17441692.2020.1783340 – volume: 9 start-page: 405 issue: 4 year: 2020 ident: 10885_CR33 publication-title: Health Policy Technol doi: 10.1016/j.hlpt.2020.09.003 – volume: 76 start-page: 525 issue: 4 year: 2020 ident: 10885_CR122 publication-title: Environ Resour Econ doi: 10.1007/s10640-020-00466-5 – volume-title: COVID-19 Response: Supporting Australians through the crisis. Economic Recovery Plan for Australia year: 2020 ident: 10885_CR66 – ident: 10885_CR103 – ident: 10885_CR15 – ident: 10885_CR32 – ident: 10885_CR91 – ident: 10885_CR118 – ident: 10885_CR119 doi: 10.1007/s40520-020-01664-3 – ident: 10885_CR114 doi: 10.1093/cid/ciaa1785 – ident: 10885_CR28 doi: 10.2139/ssrn.3722299 – ident: 10885_CR62 – ident: 10885_CR110 – ident: 10885_CR20 – volume: 323 start-page: 1239 issue: 13 year: 2020 ident: 10885_CR98 publication-title: JAMA. doi: 10.1001/jama.2020.2648 – volume: 119 start-page: 1145 issue: 9 year: 2015 ident: 10885_CR77 publication-title: Health Policy doi: 10.1016/j.healthpol.2015.07.008 – ident: 10885_CR79 – ident: 10885_CR56 – volume-title: Thailand’s 1 million village health volunteers - “unsung heroes” - are helping guard communities nationwide from COVID-19 year: 2020 ident: 10885_CR63 – ident: 10885_CR11 doi: 10.1007/s11684-020-0766-9 – ident: 10885_CR104 – ident: 10885_CR121 – ident: 10885_CR65 – volume-title: Health Insurance Coverage in the United States: 2019 year: 2020 ident: 10885_CR90 – ident: 10885_CR96 – ident: 10885_CR48 – volume-title: COVID-19 Health System Response Monitor: Thailand year: 2020 ident: 10885_CR17 – volume: 10 start-page: 010350 issue: 1 year: 2020 ident: 10885_CR87 publication-title: J Glob Health doi: 10.7189/jogh.10.010350 – volume: 23 start-page: 361 issue: 4 year: 2020 ident: 10885_CR14 publication-title: Hum Resour Dev Int doi: 10.1080/13678868.2020.1779543 – volume-title: 100 days without COVID-19: how New Zealand got rid of a virus that keeps spreading across the world year: 2020 ident: 10885_CR64 – ident: 10885_CR109 – volume: 14 start-page: e0008412 issue: 7 year: 2020 ident: 10885_CR6 publication-title: Plos Negl Trop Dis doi: 10.1371/journal.pntd.0008412 – ident: 10885_CR101 – volume: 91 start-page: 561 issue: 3 year: 2020 ident: 10885_CR13 publication-title: Polit Q doi: 10.1111/1467-923X.12893 – ident: 10885_CR34 – ident: 10885_CR51 – ident: 10885_CR1 doi: 10.1056/NEJMoa2001017 |
| SSID | ssj0017852 |
| Score | 2.4892783 |
| Snippet | 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... Background 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.... Abstract Background The coronavirus disease of 2019 (COVID-19) has quickly spread to all corners of the world since its emergence in Wuhan, China in December... |
| SourceID | doaj pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | 835 |
| SubjectTerms | Australia Brazil China Community involvement Community participation Containment Control Coronaviruses COVID-19 COVID-19 pandemic response Demography Disease transmission Epidemics Epidemiology Evaluation Fatalities Geographical locations Germany GNI Gross National Income Health risks Health services Heterogeneity High income Indicators Italy Leadership Low income groups Mixed methods research Pandemics Public health Public health administration Viral diseases |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LaxUxFA7SlSCi1sfUKhEKLiR08pgk467WltqFbqx0F_KkhXbupfcW-vM9SWYudxB042ogj2GSc86cL8nJdxA64Fx2NChFknacCC0osYAiiGWtFjz1MrjC9vldnl2I88vucivVV44Jq_TAdeIOkwUHax3lnYuCRaV5yGdtUQDeck6Vq3vg86bF1Hh-oHTHpisyWh6u4C-cQ4NYDt_SuiN65oYKW_-f_-QtpzQPmNzyQKfP0NMROuKj-snP0aM4vEBP6r4brteJdlEEueOrHOOyANWIgLHxImFAefj4x69vXwnt8TLvG99CH3jiaTMQ39Vg2bj6DOU4Pixv7FBO4PHt9UMMpKaaXuHCR_sSXZye_Dw-I2MqBeIl69fE9m3QTqhAo4hSOSeiSEwlF0RIlkYfROp7D-ipSyr43jrrfZtoAjRpexb5K7QzLIb4BmEZGPUJ3pVCZnrxTqnIc6IY2-rQd75BdJpZ40ee8Zzu4saU9YaWpkrDgDRMkYbRDfq06bOsLBt_bf0lC2zTMjNklwLQGzPqjfmX3jToYxa3yXYMn-fteB0BBpkZscxRBi6gya1s0P6sJdifn1dPCmNG-18Z1sFCVmipaYM-bKpzzxzTNsTFfWkDy1OAg22DXlf92gyJ87zRJFmD1EzzZmOe1wzXV4UdXLdaac33_sckvUWPWTaaEuC5j3bWd_fxHYCwtXtf7O03IhEt3A priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Technology Collection dbid: 8FG link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1Lb9QwELagXJAQ4k2gICMhcUBW40dshwsqhaVwgAtFvVl-tpXaZNlspf58xk52aYTUU6R4HNmZhz-PxzMIveVcNjQoRZJ2nAgtKLGAIohltRY8tTK4ku3zhzw8Et-Pm-PJ4TZMYZUbm1gMdeh99pHvsQa2BkJLTT8u_5BcNSqfrk4lNG6jOxRWmhzSpRdft6cISjdsc1FGy70BbHEOEGI5iEvrhujZYlRy9v9vma8tTfOwyWvr0OIBuj8BSLw_cvwhuhW7R-je6H3D46WixygC9_FpjnTpQUAiIG3cJwxYDx_8_P3tM6EtXmbv8QX0gSfeuATxagyZjcMHeI_j1fLcduUcHl-cXcVAxoLTAy5ZaZ-go8WXXweHZCqoQLxk7ZrYtg7aCRVoFFEq50QUiankggjJ0uiDSG3rAUM1SQXfWme9rxNNgCltyyJ_ina6vovPEZaBUZ_gWynkfC_eKRV5Lhdjax3axleIbv6s8VO28Vz04tyUXYeWZuSGAW6Ywg2jK_R-22c55tq4kfpTZtiWMufJLi_61YmZ1M4kC_DMOsobFwWLSvOQT2ojDNk5p9oKvcvsNlmbYXjeTpcSYJI5L5bZz_AF5LmWFdqdUYIW-nnzRmDMZAUG809mK_Rm25x75si2LvaXhQY2qQAK6wo9G-VrOyXOs7tJsgqpmeTN5jxv6c5OS45wXWulNX9x87Beorssq0MJ4NxFO-vVZXwFIGvtXhdN-gu1YyV0 priority: 102 providerName: ProQuest |
| Title | The heterogeneity of the COVID-19 pandemic and national responses: an explanatory mixed-methods study |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/33933062 https://www.proquest.com/docview/2528948681 https://www.proquest.com/docview/2521499760 https://pubmed.ncbi.nlm.nih.gov/PMC8087883 https://doaj.org/article/fa273ab135be42e783d1302e481bbb79 |
| Volume | 21 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3ri9QwEB_uAXIg4tvquUQQ_CDVPtImFURu11tPwVMOV5b7EvL0Dva66-4erP-9k3S7XvHwg19SaJLSdH7T_CaZzAA8z_OySA1jseMqjymnaSyRRcQySzjNXVUaFaJ9HpdHI_ppXIy3oE13tP6Ai2tNO59PajSfvFr9_PUOFf5tUHhevl7gP9Y7_mTeOYvzIubbsIszE_MZDT7TP7sKjBdZe3Dm2n57cCPPvYlfZp15KoTz__unfWXW6npUXpmihrfh1ppbkoMGDHdgy9Z34WazMEea80b3wCIwyJl3gpkidiyScDJ1BGkgGXz5_vF9nFZk5heWL7APXkm7WkjmjTetXbzB-8SuZhNZhy16cnG-siZuclEvSAhYex9Gw8Nvg6N4nWsh1mVWLWNZJYYrykxqqS2ZUtRSlzGnDDVOplYb6qpKI70qHDO6kkpqnbjUId2UVWbzB7BTT2v7CEhpslQ7fJYzPhSMVozZ3GeSkQk3VaEjSNsvK_Q6ELnPhzERwSDhpWgEI1AwIghG8AhebvrMmjAc_2zd9wLbtPQhtMON6fyHWGukcBKZm1RpXihLM8t4bvwmrsVXVkqxKoIXXtzCQw9fT8v1eQUcpA-ZJQ48s0GoJ2UE-52WqKC6W90CRrT4FlmBli7lJU8jeLap9j2901ttp5ehDdqvyBeTCB42-NoMqYVpBKyDvM6YuzX1-VkIH84TzjjPH_93zyewl3mlCW6f-7CznF_ap0jNlqoH22zMsOSD1JfDDz3Y7R8efz3phcWOXtBHLE_6p78B14Y8Kg |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Jb9QwFLZKOYCEEDuBAkYCcUBRE9uJHSSESsswQ0u5tKg31yut1CbDzFSUP8Vv5NlJhkZIvfUUKbYjO2_x9-y3IPSK0rLILeepF5qmTLA8VYAiUkUywaivSqtjts_dcrzPvhwUByvoTx8LE9wqe50YFbVtTDgjXycFmAZMlCL_MP2ZhqpR4Xa1L6HRssW2-_0LTLb5-8kW0Pc1IaNPe5vjtKsqkJqSVItUVZkVmnGbO-ZKrjVzzBPutWXWq9wZy3xVGQAShefWVEorYzKfewBWqiKOwnevoeuMwk4eItNHn5e3FlwUpA_MEeX6HHR_cEgiwWlMiCIVg80v1gj4fye4sBUO3TQv7HujO-h2B1jxRsthd9GKq--hW-1pH26DmO4jB9yGj4JnTQMM6QDZ48ZjwJZ489v3yVaaV3gaTqtPYQw8cX8EiWeti66bv4P32J1PT1Qd7_3x6fG5s2lb4HqOYxbcB2j_Sn71Q7RaN7V7jHBpSW48fMvbkF_GaM4dDeVpVCZsVZgE5f2flabLbh6KbJzIaOWIUrbUkEANGakhRYLeLsdM29wel_b-GAi27BnycscXzeyH7MRcegVwUOmcFtox4rigNtwMO5iy1ppXCXoTyC2D9oDpGdUFQcAiQx4uuRHgEshPViZobdATpN4Mm3uGkZ3Wmct_MpKgl8vmMDJ40tWuOYt9wCgGEJol6FHLX8slAUtTMCFJgviA8wZrHrbUx0cxJ7nIBBeCPrl8Wi_QjfHe1x25M9ndfopukiAa0Xl0Da0uZmfuGQC8hX4epQqjw6sW479MnWWA |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+heterogeneity+of+the+COVID-19+pandemic+and+national+responses%3A+an+explanatory+mixed-methods+study&rft.jtitle=BMC+public+health&rft.au=Chen%2C+Yi-Ying&rft.au=Assefa%2C+Yibeltal&rft.date=2021-05-01&rft.pub=BioMed+Central&rft.eissn=1471-2458&rft.volume=21&rft_id=info:doi/10.1186%2Fs12889-021-10885-8&rft_id=info%3Apmid%2F33933062&rft.externalDocID=PMC8087883 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1471-2458&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1471-2458&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1471-2458&client=summon |