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10.1016/j.jbi.2021.103818 http://scihub22266oqcxt.onion/10.1016/j.jbi.2021.103818 34022420!8555375!34022420     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Biomed+Inform 2021 ; 119 (ä): 103818 Nephropedia Template TP {{tp|p=34022420|t=2021. Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates |pdf=|usr=}}{{34022420}} gab.com Text Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates JO: J Biomed Inform http://www.kidney.de/pget.php?&tw=1&pmid=34022420 #FOAvip OBJECTIVE: Study the impact of local policies on near-future hospitalization and mortality rates. MATERIALS AND METHODS: We introduce a novel risk-stratified SIR-HCD model that introduces new variables to model the dynamics of low-contact (e.g., work from home) and high-contact (e.g., work on-site) subpopulations while sharing parameters to control their respective R(0)(t) over time. We test our model on data of daily reported hospitalizations and cumulative mortality of COVID-19 in Harris County, Texas, from May 1, 2020, until October 4, 2020, collected from multiple sources (USA FACTS, U.S. Bureau of Labor Statistics, Southeast Texas Regional Advisory Council COVID-19 report, TMC daily news, and Johns Hopkins University county-level mortality reporting). RESULTS: We evaluated our model's forecasting accuracy in Harris County, TX (the most populated county in the Greater Houston area) during Phase-I and Phase-II reopening. Not only does our model outperform other competing models, but it also supports counterfactual analysis to simulate the impact of future policies in a local setting, which is unique among existing approaches. DISCUSSION: Mortality and hospitalization rates are significantly impacted by local quarantine and reopening policies. Existing models do not directly account for the effect of these policies on infection, hospitalization, and death rates in an explicit and explainable manner. Our work is an attempt to improve prediction of these trends by incorporating this information into the model, thus supporting decision-making. CONCLUSION: Our work is a timely effort to attempt to model the dynamics of pandemics under the influence of local policies. Twit Text FOAVip Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates ????J Biomed Inform http://www.kidney.de/pget.php?&tw=1&pmid=34022420 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34022420 #FOAvip English Wikipedia <ref>{{Cite pmid|34022420}}</ref> Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates #MMPMID34022420 Huang T; Chu Y; Shams S; Kim Y; Annapragada AV; Subramanian D; Kakadiaris I; Gottlieb A; Jiang X J Biomed Inform 2021[Jul]; 119 (ä): 103818 PMID34022420show ga OBJECTIVE: Study the impact of local policies on near-future hospitalization and mortality rates. MATERIALS AND METHODS: We introduce a novel risk-stratified SIR-HCD model that introduces new variables to model the dynamics of low-contact (e.g., work from home) and high-contact (e.g., work on-site) subpopulations while sharing parameters to control their respective R(0)(t) over time. We test our model on data of daily reported hospitalizations and cumulative mortality of COVID-19 in Harris County, Texas, from May 1, 2020, until October 4, 2020, collected from multiple sources (USA FACTS, U.S. Bureau of Labor Statistics, Southeast Texas Regional Advisory Council COVID-19 report, TMC daily news, and Johns Hopkins University county-level mortality reporting). RESULTS: We evaluated our model's forecasting accuracy in Harris County, TX (the most populated county in the Greater Houston area) during Phase-I and Phase-II reopening. Not only does our model outperform other competing models, but it also supports counterfactual analysis to simulate the impact of future policies in a local setting, which is unique among existing approaches. DISCUSSION: Mortality and hospitalization rates are significantly impacted by local quarantine and reopening policies. Existing models do not directly account for the effect of these policies on infection, hospitalization, and death rates in an explicit and explainable manner. Our work is an attempt to improve prediction of these trends by incorporating this information into the model, thus supporting decision-making. CONCLUSION: Our work is a timely effort to attempt to model the dynamics of pandemics under the influence of local policies. |*COVID-19[MESH] |Hospitalization[MESH] |Humans[MESH] |Pandemics[MESH] |Policy[MESH] |SARS-CoV-2[MESH]Population stratification enables modeling effects of reopening polici(epmc).pdf DeepDyve Pubget Overpricing