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10.7554/eLife.66601 http://scihub22266oqcxt.onion/10.7554/eLife.66601 34003112!8221808!34003112     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Elife 2021 ; 10 (ä): ä Nephropedia Template TP {{tp|p=34003112|t=2021. Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics |pdf=|usr=}}{{34003112}} gab.com Text Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics JO: Elife http://www.kidney.de/pget.php?&tw=1&pmid=34003112 #FOAvip BACKGROUND: The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. METHODS: Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk change across groups. RESULTS: A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations: in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites. CONCLUSIONS: Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection. FUNDING: K.C.M. was supported by National Science Foundation GRFP grant DGE1745303. Y.H.G. and M.L. were funded by the Morris-Singer Foundation. M.L. was supported by SeroNet cooperative agreement U01 CA261277. Twit Text FOAVip Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics ????Elife http://www.kidney.de/pget.php?&tw=1&pmid=34003112 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34003112 #FOAvip English Wikipedia <ref>{{Cite pmid|34003112}}</ref> Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics #MMPMID34003112 Ma KC; Menkir TF; Kissler S; Grad YH; Lipsitch M Elife 2021[May]; 10 (ä): ä PMID34003112show ga BACKGROUND: The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. METHODS: Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk change across groups. RESULTS: A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations: in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites. CONCLUSIONS: Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection. FUNDING: K.C.M. was supported by National Science Foundation GRFP grant DGE1745303. Y.H.G. and M.L. were funded by the Morris-Singer Foundation. M.L. was supported by SeroNet cooperative agreement U01 CA261277. |*Health Status Disparities[MESH] |*Models, Statistical[MESH] |Asian People/statistics & numerical data[MESH] |Black or African American/statistics & numerical data[MESH] |COVID-19/blood/diagnosis/*epidemiology/immunology[MESH] |Cost of Illness[MESH] |Hispanic or Latino/statistics & numerical data[MESH] |Humans[MESH] |Immunity, Herd[MESH] |Minority Groups/statistics & numerical data[MESH] |New York/epidemiology[MESH] |Pandemics/*statistics & numerical data[MESH] |SARS-CoV-2/immunology/isolation & purification[MESH] |Seroepidemiologic Studies[MESH]Modeling the impact of racial and ethnic disparities on COVID-19 epide(epmc).pdf DeepDyve Pubget Overpricing