Country‐level determinants of COVID‐19 case rates and death rates: An ecological study
The Coronavirus Disease 2019 (COVID‐19) pandemic has had a variable worldwide impact, likely related to country‐level characteristics. In this ecological study, we explored the association of COVID‐19 case rates (per 100,000 people) and death rates (per 100,000 people) with country‐level population...
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| Veröffentlicht in: | Transboundary and emerging diseases 2022-07, Vol.69 (4), p.e906-e915 |
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| creator | El Mouhayyar, Christopher Jaber, Luke T. Bergmann, Matthias Tighiouart, Hocine Jaber, Bertrand L. |
| description | The Coronavirus Disease 2019 (COVID‐19) pandemic has had a variable worldwide impact, likely related to country‐level characteristics. In this ecological study, we explored the association of COVID‐19 case rates (per 100,000 people) and death rates (per 100,000 people) with country‐level population health characteristics, economic and human development indicators, and habitat‐related variables. To calculate country‐level COVID‐19 case and death rates, the number of cases and deaths were extracted from the Johns Hopkins Coronavirus Resource Center through September 30, 2021. Country‐level population health characteristics, economic, human development, and habitat‐related indicators were extracted from several publicly available online sources of international organizations. Results were tabulated according to world zones and country economies. Unadjusted and adjusted multiple imputation linear regression analyses were performed to examine the association between country‐level variables (per 1‐standard deviation [SD] increase) and COVID‐19 case and death rates. To satisfy the linear regression model assumptions of normality of residuals, we used the square root transformation of both outcomes. A total of 187 countries and territories were analyzed, with a median (25th, 75th percentiles) aggregate COVID‐19 case rate of 3,605 (463, 8,228) per 100,000, a COVID‐19 death rate of 45.9 (8.9, 137.1) per 100,000, and a case‐fatality rate of 1.6% (1.2%, 2.6%). On multivariable analyses, each country‐level 1‐SD higher percentage of adults with obesity (β coefficient 13.7; 95% confidence interval [CI] 13.7; 8.9, 18.4), percentage of smokers (5.8; 95% CI 1.2, 10.5), percentage of adults with high blood pressure (4.9; 95% CI 0.3, 9.6), and gross national income (GNI) per capita (9.5; 95% CI 4.6, 14.5) was independently associated with higher square root of COVID‐19 case rate, while average household size (−1.7; 95% CI −12.3, −3.2) was independently associated with lower square root of COVID‐19 case rate. Similarly, each 1‐SD higher percentage of adults with obesity (1.76; 95% CI 0.99, 2.52), percentage of adults with high blood pressure (1.11; 95% CI 0.48, 1.74), percentage of adults with physical inactivity (1.01; 95% CI 0.10, 1.191), and travel & tourism competitiveness index (1.05; 95% CI 0.06, 2.04) was independently associated with higher square root of COVID‐19 death rate, whereas GNI per capita (−0.92; 95% CI −1.81, −0.03), and average household size (−1.07; 95% CI |
| doi_str_mv | 10.1111/tbed.14360 |
| format | Article |
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In this ecological study, we explored the association of COVID‐19 case rates (per 100,000 people) and death rates (per 100,000 people) with country‐level population health characteristics, economic and human development indicators, and habitat‐related variables. To calculate country‐level COVID‐19 case and death rates, the number of cases and deaths were extracted from the Johns Hopkins Coronavirus Resource Center through September 30, 2021. Country‐level population health characteristics, economic, human development, and habitat‐related indicators were extracted from several publicly available online sources of international organizations. Results were tabulated according to world zones and country economies. Unadjusted and adjusted multiple imputation linear regression analyses were performed to examine the association between country‐level variables (per 1‐standard deviation [SD] increase) and COVID‐19 case and death rates. To satisfy the linear regression model assumptions of normality of residuals, we used the square root transformation of both outcomes. A total of 187 countries and territories were analyzed, with a median (25th, 75th percentiles) aggregate COVID‐19 case rate of 3,605 (463, 8,228) per 100,000, a COVID‐19 death rate of 45.9 (8.9, 137.1) per 100,000, and a case‐fatality rate of 1.6% (1.2%, 2.6%). On multivariable analyses, each country‐level 1‐SD higher percentage of adults with obesity (β coefficient 13.7; 95% confidence interval [CI] 13.7; 8.9, 18.4), percentage of smokers (5.8; 95% CI 1.2, 10.5), percentage of adults with high blood pressure (4.9; 95% CI 0.3, 9.6), and gross national income (GNI) per capita (9.5; 95% CI 4.6, 14.5) was independently associated with higher square root of COVID‐19 case rate, while average household size (−1.7; 95% CI −12.3, −3.2) was independently associated with lower square root of COVID‐19 case rate. Similarly, each 1‐SD higher percentage of adults with obesity (1.76; 95% CI 0.99, 2.52), percentage of adults with high blood pressure (1.11; 95% CI 0.48, 1.74), percentage of adults with physical inactivity (1.01; 95% CI 0.10, 1.191), and travel & tourism competitiveness index (1.05; 95% CI 0.06, 2.04) was independently associated with higher square root of COVID‐19 death rate, whereas GNI per capita (−0.92; 95% CI −1.81, −0.03), and average household size (−1.07; 95% CI −1.87, −0.27) was independently associated with lower square root of COVID‐19 death rate. This ecological study informs the need to develop country‐specific public health interventions to better target populations at high risk for COVID‐19, and test interventions to prevent transmission of SARS‐CoV‐2, taking into consideration cross‐country differences in population health characteristics, and economic, human development and habitat‐related factors.</description><identifier>ISSN: 1865-1674</identifier><identifier>EISSN: 1865-1682</identifier><identifier>DOI: 10.1111/tbed.14360</identifier><identifier>PMID: 34706146</identifier><language>eng</language><publisher>Germany: Hindawi Limited</publisher><subject>Adults ; Blood pressure ; Competitiveness ; Confidence intervals ; Coronaviruses ; COVID-19 ; Death ; Disease transmission ; Ecological studies ; Economics ; environment and public health ; Fatalities ; geographic locations ; GNI ; Gross National Income ; Habitats ; Health promotion ; Hypertension ; Indicators ; International organizations ; Mortality ; Normality ; Obesity ; Original ; Pandemics ; population health ; Public health ; Regression analysis ; Regression models ; SARS‐CoV‐2 ; Severe acute respiratory syndrome coronavirus 2 ; Smoking ; Statistical analysis ; Tourism ; Viral diseases</subject><ispartof>Transboundary and emerging diseases, 2022-07, Vol.69 (4), p.e906-e915</ispartof><rights>2021 Wiley‐VCH GmbH</rights><rights>2021 Wiley-VCH GmbH.</rights><rights>2022 Wiley‐VCH GmbH</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5140-3c4676247b18a5791e241ed3d6a024bdaed895e09561e2520e3e0bac17d7d7d43</citedby><cites>FETCH-LOGICAL-c5140-3c4676247b18a5791e241ed3d6a024bdaed895e09561e2520e3e0bac17d7d7d43</cites><orcidid>0000-0003-3935-1054 ; 0000-0003-0577-0605</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Ftbed.14360$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Ftbed.14360$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34706146$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>El Mouhayyar, Christopher</creatorcontrib><creatorcontrib>Jaber, Luke T.</creatorcontrib><creatorcontrib>Bergmann, Matthias</creatorcontrib><creatorcontrib>Tighiouart, Hocine</creatorcontrib><creatorcontrib>Jaber, Bertrand L.</creatorcontrib><title>Country‐level determinants of COVID‐19 case rates and death rates: An ecological study</title><title>Transboundary and emerging diseases</title><addtitle>Transbound Emerg Dis</addtitle><description>The Coronavirus Disease 2019 (COVID‐19) pandemic has had a variable worldwide impact, likely related to country‐level characteristics. In this ecological study, we explored the association of COVID‐19 case rates (per 100,000 people) and death rates (per 100,000 people) with country‐level population health characteristics, economic and human development indicators, and habitat‐related variables. To calculate country‐level COVID‐19 case and death rates, the number of cases and deaths were extracted from the Johns Hopkins Coronavirus Resource Center through September 30, 2021. Country‐level population health characteristics, economic, human development, and habitat‐related indicators were extracted from several publicly available online sources of international organizations. Results were tabulated according to world zones and country economies. Unadjusted and adjusted multiple imputation linear regression analyses were performed to examine the association between country‐level variables (per 1‐standard deviation [SD] increase) and COVID‐19 case and death rates. To satisfy the linear regression model assumptions of normality of residuals, we used the square root transformation of both outcomes. A total of 187 countries and territories were analyzed, with a median (25th, 75th percentiles) aggregate COVID‐19 case rate of 3,605 (463, 8,228) per 100,000, a COVID‐19 death rate of 45.9 (8.9, 137.1) per 100,000, and a case‐fatality rate of 1.6% (1.2%, 2.6%). On multivariable analyses, each country‐level 1‐SD higher percentage of adults with obesity (β coefficient 13.7; 95% confidence interval [CI] 13.7; 8.9, 18.4), percentage of smokers (5.8; 95% CI 1.2, 10.5), percentage of adults with high blood pressure (4.9; 95% CI 0.3, 9.6), and gross national income (GNI) per capita (9.5; 95% CI 4.6, 14.5) was independently associated with higher square root of COVID‐19 case rate, while average household size (−1.7; 95% CI −12.3, −3.2) was independently associated with lower square root of COVID‐19 case rate. Similarly, each 1‐SD higher percentage of adults with obesity (1.76; 95% CI 0.99, 2.52), percentage of adults with high blood pressure (1.11; 95% CI 0.48, 1.74), percentage of adults with physical inactivity (1.01; 95% CI 0.10, 1.191), and travel & tourism competitiveness index (1.05; 95% CI 0.06, 2.04) was independently associated with higher square root of COVID‐19 death rate, whereas GNI per capita (−0.92; 95% CI −1.81, −0.03), and average household size (−1.07; 95% CI −1.87, −0.27) was independently associated with lower square root of COVID‐19 death rate. This ecological study informs the need to develop country‐specific public health interventions to better target populations at high risk for COVID‐19, and test interventions to prevent transmission of SARS‐CoV‐2, taking into consideration cross‐country differences in population health characteristics, and economic, human development and habitat‐related factors.</description><subject>Adults</subject><subject>Blood pressure</subject><subject>Competitiveness</subject><subject>Confidence intervals</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Death</subject><subject>Disease transmission</subject><subject>Ecological studies</subject><subject>Economics</subject><subject>environment and public health</subject><subject>Fatalities</subject><subject>geographic locations</subject><subject>GNI</subject><subject>Gross National Income</subject><subject>Habitats</subject><subject>Health promotion</subject><subject>Hypertension</subject><subject>Indicators</subject><subject>International organizations</subject><subject>Mortality</subject><subject>Normality</subject><subject>Obesity</subject><subject>Original</subject><subject>Pandemics</subject><subject>population health</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>SARS‐CoV‐2</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Smoking</subject><subject>Statistical analysis</subject><subject>Tourism</subject><subject>Viral diseases</subject><issn>1865-1674</issn><issn>1865-1682</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kc9O3DAQxi0E4s-2Fx6gssQFIS14EttJekCCZSlISFxoD71Yjj0LQd4Y7AS0Nx6hz9gnwdvQFfTQ8WHG-n76NKOPkF1gh5DqqKvRHgLPJVsj21BKMQZZZuurueBbZCfGe8Ykq6TYJFs5L5gELrfJz4nv2y4sfr_8cviEjlrsMMybVrddpH5GJ9c_Ls-SChU1OiINusNIdWsTqbu74f-VnrQUjXf-tjHa0dj1dvGJbMy0i_j5rY_I9_PpzeRifHX97XJycjU2Ajgb54bLQma8qKHUoqgAMw5ocys1y3htNdqyEsgqIZMkMoY5slobKOzy8XxEjgffh76eozWY7tFOPYRmrsNCed2oj0rb3Klb_6RKKTOAKhnsvxkE_9hj7NS8iQad0y36PqpMlEUhZC4goXv_oPe-D206T2WyShkkNk_UwUCZ4GMMOFstA0wtI1PLyNSfyBL85f36K_RvRgmAAXhuHC7-Y6VuTqdng-krOVKicA</recordid><startdate>202207</startdate><enddate>202207</enddate><creator>El Mouhayyar, Christopher</creator><creator>Jaber, Luke T.</creator><creator>Bergmann, Matthias</creator><creator>Tighiouart, Hocine</creator><creator>Jaber, Bertrand L.</creator><general>Hindawi Limited</general><general>John Wiley and Sons Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7T7</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-3935-1054</orcidid><orcidid>https://orcid.org/0000-0003-0577-0605</orcidid></search><sort><creationdate>202207</creationdate><title>Country‐level determinants of COVID‐19 case rates and death rates: An ecological study</title><author>El Mouhayyar, Christopher ; 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In this ecological study, we explored the association of COVID‐19 case rates (per 100,000 people) and death rates (per 100,000 people) with country‐level population health characteristics, economic and human development indicators, and habitat‐related variables. To calculate country‐level COVID‐19 case and death rates, the number of cases and deaths were extracted from the Johns Hopkins Coronavirus Resource Center through September 30, 2021. Country‐level population health characteristics, economic, human development, and habitat‐related indicators were extracted from several publicly available online sources of international organizations. Results were tabulated according to world zones and country economies. Unadjusted and adjusted multiple imputation linear regression analyses were performed to examine the association between country‐level variables (per 1‐standard deviation [SD] increase) and COVID‐19 case and death rates. To satisfy the linear regression model assumptions of normality of residuals, we used the square root transformation of both outcomes. A total of 187 countries and territories were analyzed, with a median (25th, 75th percentiles) aggregate COVID‐19 case rate of 3,605 (463, 8,228) per 100,000, a COVID‐19 death rate of 45.9 (8.9, 137.1) per 100,000, and a case‐fatality rate of 1.6% (1.2%, 2.6%). On multivariable analyses, each country‐level 1‐SD higher percentage of adults with obesity (β coefficient 13.7; 95% confidence interval [CI] 13.7; 8.9, 18.4), percentage of smokers (5.8; 95% CI 1.2, 10.5), percentage of adults with high blood pressure (4.9; 95% CI 0.3, 9.6), and gross national income (GNI) per capita (9.5; 95% CI 4.6, 14.5) was independently associated with higher square root of COVID‐19 case rate, while average household size (−1.7; 95% CI −12.3, −3.2) was independently associated with lower square root of COVID‐19 case rate. Similarly, each 1‐SD higher percentage of adults with obesity (1.76; 95% CI 0.99, 2.52), percentage of adults with high blood pressure (1.11; 95% CI 0.48, 1.74), percentage of adults with physical inactivity (1.01; 95% CI 0.10, 1.191), and travel & tourism competitiveness index (1.05; 95% CI 0.06, 2.04) was independently associated with higher square root of COVID‐19 death rate, whereas GNI per capita (−0.92; 95% CI −1.81, −0.03), and average household size (−1.07; 95% CI −1.87, −0.27) was independently associated with lower square root of COVID‐19 death rate. This ecological study informs the need to develop country‐specific public health interventions to better target populations at high risk for COVID‐19, and test interventions to prevent transmission of SARS‐CoV‐2, taking into consideration cross‐country differences in population health characteristics, and economic, human development and habitat‐related factors.</abstract><cop>Germany</cop><pub>Hindawi Limited</pub><pmid>34706146</pmid><doi>10.1111/tbed.14360</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3935-1054</orcidid><orcidid>https://orcid.org/0000-0003-0577-0605</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adults Blood pressure Competitiveness Confidence intervals Coronaviruses COVID-19 Death Disease transmission Ecological studies Economics environment and public health Fatalities geographic locations GNI Gross National Income Habitats Health promotion Hypertension Indicators International organizations Mortality Normality Obesity Original Pandemics population health Public health Regression analysis Regression models SARS‐CoV‐2 Severe acute respiratory syndrome coronavirus 2 Smoking Statistical analysis Tourism Viral diseases |
| title | Country‐level determinants of COVID‐19 case rates and death rates: An ecological study |
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