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10.1371/journal.pone.0235306 http://scihub22266oqcxt.onion/10.1371/journal.pone.0235306 32589645!7319322!32589645     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+One 2020 ; 15 (6): e0235306 Nephropedia Template TP {{tp|p=32589645|t=2020. Exploring the young demographic profile of COVID-19 cases in Hong Kong: Evidence from migration and travel history data |pdf=|usr=}}{{32589645}} gab.com Text Exploring the young demographic profile of COVID-19 cases in Hong Kong: Evidence from migration and travel history data JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=32589645 #FOAvip This paper investigates the profile of COVID-19 cases in Hong Kong, highlighting the unique age structure of confirmed cases compared to other territories. While the majority of cases in most territories around the world have fitted an older age profile, our analysis shows that positive cases in Hong Kong have been concentrated among younger age groups, with the largest incidence of cases reported in the 15-24 age group. This is despite the population's rapidly aging structure and extremely high levels of population density. Using detailed case data from Hong Kong's Centre for Health Department and Immigration Department, we analyze the sex and age distribution of the confirmed cases along with their recent travel histories and immigration flows for the period January to April 2020. Our analysis highlights Hong Kong's high proportion of imported cases and large overseas student population in developing COVID-19 hotspot areas such as the United Kingdom. Combined with community action and targeted and aggressive early policy measures taken to contain the virus, these factors may have contributed to the uniquely younger age structure of COVID-19 cases in the city. Consequently, this young profile of confirmed cases may have prevented fatalities in the territory. Recent research has highlighted the importance of a demographic approach to understanding COVID-19 transmission and fatality rates. The experience in Hong Kong shows that while an older population age structure may be important for understanding COVID-19 fatality, it is not a given. From a social science perspective at least, there is 'no easy answer' to why one area should experience COVID-19 differently from another. Twit Text FOAVip Exploring the young demographic profile of COVID-19 cases in Hong Kong: Evidence from migration and travel history data ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=32589645 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32589645 #FOAvip English Wikipedia <ref>{{Cite pmid|32589645}}</ref> Exploring the young demographic profile of COVID-19 cases in Hong Kong: Evidence from migration and travel history data #MMPMID32589645 Cruz CJP; Ganly R; Li Z; Gietel-Basten S PLoS One 2020[]; 15 (6): e0235306 PMID32589645show ga This paper investigates the profile of COVID-19 cases in Hong Kong, highlighting the unique age structure of confirmed cases compared to other territories. While the majority of cases in most territories around the world have fitted an older age profile, our analysis shows that positive cases in Hong Kong have been concentrated among younger age groups, with the largest incidence of cases reported in the 15-24 age group. This is despite the population's rapidly aging structure and extremely high levels of population density. Using detailed case data from Hong Kong's Centre for Health Department and Immigration Department, we analyze the sex and age distribution of the confirmed cases along with their recent travel histories and immigration flows for the period January to April 2020. Our analysis highlights Hong Kong's high proportion of imported cases and large overseas student population in developing COVID-19 hotspot areas such as the United Kingdom. Combined with community action and targeted and aggressive early policy measures taken to contain the virus, these factors may have contributed to the uniquely younger age structure of COVID-19 cases in the city. Consequently, this young profile of confirmed cases may have prevented fatalities in the territory. Recent research has highlighted the importance of a demographic approach to understanding COVID-19 transmission and fatality rates. The experience in Hong Kong shows that while an older population age structure may be important for understanding COVID-19 fatality, it is not a given. From a social science perspective at least, there is 'no easy answer' to why one area should experience COVID-19 differently from another. |*Emigration and Immigration[MESH] |*Travel[MESH] |Adolescent[MESH] |Adult[MESH] |Age Distribution[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Child[MESH] |Child, Preschool[MESH] |Communicable Disease Control[MESH] |Coronavirus Infections/*epidemiology[MESH] |Female[MESH] |Hong Kong/epidemiology[MESH] |Humans[MESH] |Infant[MESH] |Infant, Newborn[MESH] |Male[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH] |Population Dynamics[MESH] |SARS-CoV-2[MESH] |Sex Distribution[MESH]Exploring the young demographic profile of COVID-19 cases in Hong Kong(epmc).pdf DeepDyve Pubget Overpricing