{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:30:29Z","timestamp":1772166629514,"version":"3.50.1"},"reference-count":14,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T00:00:00Z","timestamp":1635552000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T00:00:00Z","timestamp":1635552000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Med Res"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>A pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (COVID 19) incidence data are largely available online. Until August 17, COVID 19 has hit more than 22 million individuals all over the globe. So, it is urged to get clear information about the prevalence of the virus. Therefore, one can manipulate easily a suitable mathematical model to fit these published data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We propose a mathematical model that considers the total population, in 25 countries, either infected by COVID 19 or confined (safe) during the period from November 17, 2019, to August 17, 2020. The model considers the total population as a complex number; the imaginary part is the number of infected individuals and the real part is the number of confined individuals. This classification combined with mathematical treatments leads to a transmission dynamics of the virus to be as wave-like motion. The virus can hit any country either by one wave or by successive waves (up to 11 waves).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      We find net discrimination between the 25 countries investigated in this report. The immediate response to the first attack is a substantial parameter to determine whether the epidemic attack will be in one wave or it can be in successive waves. For example, the best case was such as individuals in China hit by one wave while the individuals in the USA were attacked by nine waves; it is the worst case all over the globe. In addition, the model differentiates between the daily reproduction numbers (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>d0<\/jats:sub>\n                      ) and the median reproduction number (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>0<\/jats:sub>\n                      ). We have found that\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>d0<\/jats:sub>\n                      decreases exponentially with time from high values down to zero at the wave maximum point; and\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>0<\/jats:sub>\n                      varies from a country to another. For example, the virus hit individuals in Germany in\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>0<\/jats:sub>\n                      \u2009=\u20091.39 (96% CI 1.01\u20133.87) and in the USA\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>0<\/jats:sub>\n                      \u2009=\u20093.81 (91% CI 1.71\u20135.15). We have found that twice the virus has hit both the USA and Iran. The great protestation of black matter lives in the USA and the great assemblage of the new Iranian year, on March 21, 2020, have been the cause of the second epidemic attack in both countries.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation<\/jats:title>\n                    <jats:p>Our results show that COVID 19 transmission depends on the prompt reaction against the first viral-wave. The reaction depends on both the social behaviour of individuals and on the swift system-decision by the governmental decision-maker(s). The Chinese strictly follow the decision-maker and therefore the virus hit by only one wave; while in the USA, the system-decision was different and the American-responses were different, therefore ten waves followed the first wave.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s40001-021-00596-6","type":"journal-article","created":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T06:02:39Z","timestamp":1635573759000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Successive waves of COVID 19: confinement effects on virus-prevalence with a mathematical model"],"prefix":"10.1186","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3189-7642","authenticated-orcid":false,"given":"S.","family":"Abdalla","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Duaa","family":"Bakhshwin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"W.","family":"Shirbeeny","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed","family":"Bakhshwin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"F.","family":"Bahabri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdulaziz","family":"Bakhshwin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samar M.","family":"Alsaggaf","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"596_CR1","doi-asserted-by":"publisher","first-page":"102434","DOI":"10.1016\/j.jaut.2020.102434","volume":"109","author":"Y Yang","year":"2020","unstructured":"Yang Y, Peng F, Wang R, Guan K, Jiang T, Guogang X, Sun J, Chang C. 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