Dataset Information

Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates.

ABSTRACT:

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 R₀(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.

SUBMITTER: Huang T

PROVIDER: S-EPMC8555375 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Publications

Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates.

Huang Tongtong T Chu Yan Y Shams Shayan S Kim Yejin Y Annapragada Ananth V AV Subramanian Devika D Kakadiaris Ioannis I Gottlieb Assaf A Jiang Xiaoqian X

Journal of biomedical informatics 20210520

<h4>Objective</h4>Study the impact of local policies on near-future hospitalization and mortality rates.<h4>Materials and methods</h4>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<sub>0</sub>(t) over time. We test our model on data of daily reported hospitalizations and cumulative mortality of CO ...[more]

PMID: 34022420

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Dataset Information

Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates.

Objective

Materials and methods

Results

Discussion

Conclusion

Publications

Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates.

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