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Delivering Humanitarian Health Services in Violent Conflict

Paul Wise

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Unsplash/Robina Weermeijer/Unsplash/Kidney

Deceased Donor Kidney Transplantation for Older Transplant Candidates: A New Microsimulation Model for Determining Risks and Benefits

Matthew Kaufmann

Deceased Donor Kidney Transplantation for Older Transplant Candidates: A New Microsimulation Model for Determining Risks and Benefits

Joshua Salomon

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Journal Articles

Generating simple classification rules to predict local surges in COVID-19 hospitalizations

Health Care Management Science, 2023

Abstract

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes and relaxation of mitigation measures leave many US communities at risk for surges of COVID-19 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop a framework to generate simple classification rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. This framework uses a simulation model of SARS-CoV-2 transmission and COVID-19 hospitalizations in the US to train classification decision trees that are robust to changes in the data-generating process and future uncertainties. These generated classification rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We show that these classification rules present reasonable accuracy, sensitivity, and specificity (all ≥ 80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19. Our proposed classification rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.

Journal Articles

Protection against Omicron from Vaccination and Previous Infection in a Prison System

New England Journal of Medicine, 2022

Journal Articles

COVID-19 in the California State Prison System: an Observational Study of Decarceration, Ongoing Risks, and Risk Factors

Journal of General Internal Medicine , 2021

Journal Articles

Impact of Treatment Duration on Mortality Among Veterans with Opioid Use Disorder in The United States Veterans Health Administration

Wiley Online Library, 2021

Journal Articles

Featured Publications

Delivering Humanitarian Health Services in Violent Conflict

Deceased Donor Kidney Transplantation for Older Transplant Candidates: A New Microsimulation Model for Determining Risks and Benefits

Generating simple classification rules to predict local surges in COVID-19 hospitalizations

Abstract

Protection against Omicron from Vaccination and Previous Infection in a Prison System

COVID-19 in the California State Prison System: an Observational Study of Decarceration, Ongoing Risks, and Risk Factors

Impact of Treatment Duration on Mortality Among Veterans with Opioid Use Disorder in The United States Veterans Health Administration

Alternative Dose Allocation Strategies to Increase Benefits From Constrained COVID-19 Vaccine Supply

Modeling Contact Tracing Strategies for COVID-19 in the Context of Relaxed Physical Distancing Measures

Federal Funding For State And Local Contact Tracing Efforts Is An Urgent Priority, And A Bargain

Quantifying Child Mortality Reductions Related to Measles Vaccination

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