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Spatio-temporal evolution of the COVID-19 across African countries
The aim of this study is to make a comparative study on the reproduction number computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It...
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| Published in: | Frontiers in public health 2022-11, Vol.10, p.1039925 |
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| Language: | English |
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| cites | cdi_FETCH-LOGICAL-c432t-74455f5e191f7c2030950886fe98c13ca74718fad9a8d7838839b4c988328c043 |
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| container_start_page | 1039925 |
| container_title | Frontiers in public health |
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| creator | Naffeti, Bechir Bourdin, Sebastien Ben Aribi, Walid Kebir, Amira Ben Miled, Slimane |
| description | The aim of this study is to make a comparative study on the reproduction number
computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It links pandemic variables, reproduction number
, demographic variable, median age of the population, economic variables,
and
per capita, and climatic variables, mean temperature at the beginning of each waves. The results show that the diffusion of COVID-19 in Africa was heterogeneous even between geographical proximal countries. The difference of the basic reproduction number
values is very large between countries and is significantly correlated with economic and climatic variables
and temperature and to a less extent with the mean age of the population. |
| doi_str_mv | 10.3389/fpubh.2022.1039925 |
| format | article |
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computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It links pandemic variables, reproduction number
, demographic variable, median age of the population, economic variables,
and
per capita, and climatic variables, mean temperature at the beginning of each waves. The results show that the diffusion of COVID-19 in Africa was heterogeneous even between geographical proximal countries. The difference of the basic reproduction number
values is very large between countries and is significantly correlated with economic and climatic variables
and temperature and to a less extent with the mean age of the population.</description><identifier>ISSN: 2296-2565</identifier><identifier>EISSN: 2296-2565</identifier><identifier>DOI: 10.3389/fpubh.2022.1039925</identifier><identifier>PMID: 36518575</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>Africa ; Africa - epidemiology ; African People ; Business administration ; COVID-19 ; COVID-19 - epidemiology ; epidemiology ; Humanities and Social Sciences ; Humans ; Pandemics ; Public Health ; regional analysis ; reproduction number R0 ; SARS-CoV-2 ; SIR model</subject><ispartof>Frontiers in public health, 2022-11, Vol.10, p.1039925</ispartof><rights>Copyright © 2022 Naffeti, Bourdin, Ben Aribi, Kebir and Ben Miled.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>Copyright © 2022 Naffeti, Bourdin, Ben Aribi, Kebir and Ben Miled. 2022 Naffeti, Bourdin, Ben Aribi, Kebir and Ben Miled</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c432t-74455f5e191f7c2030950886fe98c13ca74718fad9a8d7838839b4c988328c043</citedby><cites>FETCH-LOGICAL-c432t-74455f5e191f7c2030950886fe98c13ca74718fad9a8d7838839b4c988328c043</cites><orcidid>0000-0001-7669-705X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742427/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742427/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36518575$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://normandie-univ.hal.science/hal-04454688$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Naffeti, Bechir</creatorcontrib><creatorcontrib>Bourdin, Sebastien</creatorcontrib><creatorcontrib>Ben Aribi, Walid</creatorcontrib><creatorcontrib>Kebir, Amira</creatorcontrib><creatorcontrib>Ben Miled, Slimane</creatorcontrib><title>Spatio-temporal evolution of the COVID-19 across African countries</title><title>Frontiers in public health</title><addtitle>Front Public Health</addtitle><description>The aim of this study is to make a comparative study on the reproduction number
computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It links pandemic variables, reproduction number
, demographic variable, median age of the population, economic variables,
and
per capita, and climatic variables, mean temperature at the beginning of each waves. The results show that the diffusion of COVID-19 in Africa was heterogeneous even between geographical proximal countries. The difference of the basic reproduction number
values is very large between countries and is significantly correlated with economic and climatic variables
and temperature and to a less extent with the mean age of the population.</description><subject>Africa</subject><subject>Africa - epidemiology</subject><subject>African People</subject><subject>Business administration</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>epidemiology</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Pandemics</subject><subject>Public Health</subject><subject>regional analysis</subject><subject>reproduction number R0</subject><subject>SARS-CoV-2</subject><subject>SIR model</subject><issn>2296-2565</issn><issn>2296-2565</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpdkU1P4zAQhq0VCBDwBziscoRDuvbYju0LUul-UKkSh124Wo5j06A0LnZSiX-_7sci2NNY43ee0TsvQlcETyiV6ptfj_VyAhhgQjBVCvgXdAagqhJ4xY8-vE_RZUovGOOsYxjICTqlFSeSC36G7n6vzdCGcnCrdYimK9wmdGPu9EXwxbB0xezhaf69JKowNoaUiqmPrTV9YcPYD7F16QIde9Mld3mo5-jx548_s_ty8fBrPpsuSssoDKVgjHPPHVHECwuYYsWxlJV3SlpCrRFMEOlNo4xshKRSUlUzq3IFaTGj52i-5zbBvOh1bFcmvulgWr1rhPisTRxa2znNVG1qrxpS8ZpVHtcNSFBeVdxSwonLrNs9K19x5RrrshXTfYJ-_unbpX4OG60EAwYiA272gOV_Y_fThd72cLbLKik3JGuvD8tieB1dGvSqTdZ1neldGJMGwZnMQRGVpbCX7m4dnX9nE6y3uetd7nqbuz7knoe-fjTzPvIvZfoXKnenew</recordid><startdate>20221128</startdate><enddate>20221128</enddate><creator>Naffeti, Bechir</creator><creator>Bourdin, Sebastien</creator><creator>Ben Aribi, Walid</creator><creator>Kebir, Amira</creator><creator>Ben Miled, Slimane</creator><general>Frontiers Media S.A</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>1XC</scope><scope>BXJBU</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7669-705X</orcidid></search><sort><creationdate>20221128</creationdate><title>Spatio-temporal evolution of the COVID-19 across African countries</title><author>Naffeti, Bechir ; Bourdin, Sebastien ; Ben Aribi, Walid ; Kebir, Amira ; Ben Miled, Slimane</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c432t-74455f5e191f7c2030950886fe98c13ca74718fad9a8d7838839b4c988328c043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Africa</topic><topic>Africa - epidemiology</topic><topic>African People</topic><topic>Business administration</topic><topic>COVID-19</topic><topic>COVID-19 - epidemiology</topic><topic>epidemiology</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Pandemics</topic><topic>Public Health</topic><topic>regional analysis</topic><topic>reproduction number R0</topic><topic>SARS-CoV-2</topic><topic>SIR model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Naffeti, Bechir</creatorcontrib><creatorcontrib>Bourdin, Sebastien</creatorcontrib><creatorcontrib>Ben Aribi, Walid</creatorcontrib><creatorcontrib>Kebir, Amira</creatorcontrib><creatorcontrib>Ben Miled, Slimane</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>HAL-SHS: Archive ouverte en Sciences de l'Homme et de la Société</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Naffeti, Bechir</au><au>Bourdin, Sebastien</au><au>Ben Aribi, Walid</au><au>Kebir, Amira</au><au>Ben Miled, Slimane</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio-temporal evolution of the COVID-19 across African countries</atitle><jtitle>Frontiers in public health</jtitle><addtitle>Front Public Health</addtitle><date>2022-11-28</date><risdate>2022</risdate><volume>10</volume><spage>1039925</spage><pages>1039925-</pages><issn>2296-2565</issn><eissn>2296-2565</eissn><abstract>The aim of this study is to make a comparative study on the reproduction number
computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It links pandemic variables, reproduction number
, demographic variable, median age of the population, economic variables,
and
per capita, and climatic variables, mean temperature at the beginning of each waves. The results show that the diffusion of COVID-19 in Africa was heterogeneous even between geographical proximal countries. The difference of the basic reproduction number
values is very large between countries and is significantly correlated with economic and climatic variables
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| subjects | Africa Africa - epidemiology African People Business administration COVID-19 COVID-19 - epidemiology epidemiology Humanities and Social Sciences Humans Pandemics Public Health regional analysis reproduction number R0 SARS-CoV-2 SIR model |
| title | Spatio-temporal evolution of the COVID-19 across African countries |
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