Dataset Information

A Predictive Model for Severe COVID-19 in the Medicare Population: A Tool for Prioritizing Primary and Booster COVID-19 Vaccination.

ABSTRACT: Recommendations for prioritizing COVID-19 vaccination have focused on the elderly at higher risk for severe disease. Existing models for identifying higher-risk individuals lack the needed integration of socio-demographic and clinical risk factors. Using multivariate logistic regression and random forest modeling, we developed a predictive model of severe COVID-19 using clinical data from Medicare claims for 16 million Medicare beneficiaries and socio-economic data from the CDC Social Vulnerability Index. Predicted individual probabilities of COVID-19 hospitalization were then calculated for population risk stratification and vaccine prioritization and mapping. The leading COVID-19 hospitalization risk factors were non-white ethnicity, end-stage renal disease, advanced age, prior hospitalization, leukemia, morbid obesity, chronic kidney disease, lung cancer, chronic liver disease, pulmonary fibrosis or pulmonary hypertension, and chemotherapy. However, previously reported risk factors such as chronic obstructive pulmonary disease and diabetes conferred modest hospitalization risk. Among all social vulnerability factors, residence in a low-income zip code was the only risk factor independently predicting hospitalization. This multifactor risk model and its population risk dashboard can be used to optimize COVID-19 vaccine allocation in the higher-risk Medicare population.

SUBMITTER: Experton B

PROVIDER: S-EPMC8614832 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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A Predictive Model for Severe COVID-19 in the Medicare Population: A Tool for Prioritizing Primary and Booster COVID-19 Vaccination.

Experton Bettina B Tetteh Hassan A HA Lurie Nicole N Walker Peter P Elena Adrien A Hein Christopher S CS Schwendiman Blake B Vincent Justin L JL Burrow Christopher R CR

Biology 20211115 11

Recommendations for prioritizing COVID-19 vaccination have focused on the elderly at higher risk for severe disease. Existing models for identifying higher-risk individuals lack the needed integration of socio-demographic and clinical risk factors. Using multivariate logistic regression and random forest modeling, we developed a predictive model of severe COVID-19 using clinical data from Medicare claims for 16 million Medicare beneficiaries and socio-economic data from the CDC Social Vulnerabil ...[more]

PMID: 34827181

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Project description:ImportanceData about the association of COVID-19 vaccination and prior SARS-CoV-2 infection with risk of SARS-CoV-2 infection and severe COVID-19 outcomes may guide prevention strategies.ObjectiveTo estimate the time-varying association of primary and booster COVID-19 vaccination and prior SARS-CoV-2 infection with subsequent SARS-CoV-2 infection, hospitalization, and death.Design, setting, and participantsCohort study of 10.6 million residents in North Carolina from March 2, 2020, through June 3, 2022.ExposuresCOVID-19 primary vaccine series and boosters and prior SARS-CoV-2 infection.Main outcomes and measuresRate ratio (RR) of SARS-CoV-2 infection and hazard ratio (HR) of COVID-19-related hospitalization and death.ResultsThe median age among the 10.6 million participants was 39 years; 51.3% were female, 71.5% were White, and 9.9% were Hispanic. As of June 3, 2022, 67% of participants had been vaccinated. There were 2 771 364 SARS-CoV-2 infections, with a hospitalization rate of 6.3% and mortality rate of 1.4%. The adjusted RR of the primary vaccine series compared with being unvaccinated against infection became 0.53 (95% CI, 0.52-0.53) for BNT162b2, 0.52 (95% CI, 0.51-0.53) for mRNA-1273, and 0.51 (95% CI, 0.50-0.53) for Ad26.COV2.S 10 months after the first dose, but the adjusted HR for hospitalization remained at 0.29 (95% CI, 0.24-0.35) for BNT162b2, 0.27 (95% CI, 0.23-0.32) for mRNA-1273, and 0.35 (95% CI, 0.29-0.42) for Ad26.COV2.S and the adjusted HR of death remained at 0.23 (95% CI, 0.17-0.29) for BNT162b2, 0.15 (95% CI, 0.11-0.20) for mRNA-1273, and 0.24 (95% CI, 0.19-0.31) for Ad26.COV2.S. For the BNT162b2 primary series, boosting in December 2021 with BNT162b2 had the adjusted RR relative to primary series of 0.39 (95% CI, 0.38-0.40) and boosting with mRNA-1273 had the adjusted RR of 0.32 (95% CI, 0.30-0.34) against infection after 1 month and boosting with BNT162b2 had the adjusted RR of 0.84 (95% CI, 0.82-0.86) and boosting with mRNA-1273 had the adjusted RR of 0.60 (95% CI, 0.57-0.62) after 3 months. Among all participants, the adjusted RR of Omicron infection compared with no prior infection was estimated at 0.23 (95% CI, 0.22-0.24) against infection, and the adjusted HRs were 0.10 (95% CI, 0.07-0.14) against hospitalization and 0.11 (95% CI, 0.08-0.15) against death after 4 months.Conclusions and relevanceReceipt of primary COVID-19 vaccine series compared with being unvaccinated, receipt of boosters compared with primary vaccination, and prior infection compared with no prior infection were all significantly associated with lower risk of SARS-CoV-2 infection (including Omicron) and resulting hospitalization and death. The associated protection waned over time, especially against infection.

Project description:BackgroundWhile mass COVID-19 vaccination programs are underway in high-income countries, limited availability of doses has resulted in few vaccines administered in low and middle income countries (LMICs). The COVID-19 Vaccines Global Access (COVAX) is a WHO-led initiative to promote vaccine access equity to LMICs and is providing many of the doses available in these settings. However, initial doses are limited and countries, such as Madagascar, need to develop prioritization schemes to maximize the benefits of vaccination with very limited supplies. There is some consensus that dose deployment should initially target health care workers, and those who are more vulnerable including older individuals. However, questions of geographic deployment remain, in particular associated with limits around vaccine access and delivery capacity in underserved communities, for example in rural areas that may also include substantial proportions of the population.MethodsTo address these questions, we developed a mathematical model of SARS-CoV-2 transmission dynamics and simulated various vaccination allocation strategies for Madagascar. Simulated strategies were based on a number of possible geographical prioritization schemes, testing sensitivity to initial susceptibility in the population, and evaluating the potential of tests for previous infection.ResultsUsing cumulative deaths due to COVID-19 as the main outcome of interest, our results indicate that distributing the number of vaccine doses according to the number of elderly living in the region or according to the population size results in a greater reduction of mortality compared to distributing doses based on the reported number of cases and deaths. The benefits of vaccination strategies are diminished if the burden (and thus accumulated immunity) has been greatest in the most populous regions, but the overall strategy ranking remains comparable. If rapid tests for prior immunity may be swiftly and effectively delivered, there is potential for considerable gain in mortality averted, but considering delivery limitations modulates this.ConclusionAt a subnational scale, our results support the strategy adopted by the COVAX initiative at a global scale.

Project description:BackgroundCOVID-19 vaccine effectiveness declines months after vaccination. Therefore, it is likely that during the next few years, people may be repeatedly offered a booster vaccine to enhance humoral immunity levels. A growing number of people are questioning whether the benefits of a booster vaccine outweigh the side-effects.ObjectiveThis study aims (1) to identify the most frequently reported side-effects after different doses of COVID-19 mRNA vaccines, (2) and the longest lasting symptoms; and (3) to predict the likelihood of having moderate-to-severe side-effects after a booster COVID-19 mRNA vaccine given individual- and vaccine-specific characteristics.Design, setting, and participantsSecondary analysis of a prospective cohort study in primary health care providers (PHCPs) in Belgium conducted between December 2020 and December 2021, and in February-March 2023.MethodsIn nine subsequent surveys over a period of 2 years vaccine dose-number and side-effects after COVID-19 vaccines were collected. A Generalized Estimation Equations approach on the data of the first and second booster dose was used to investigate the probability of having moderate-to-severe side-effects after mRNA booster vaccination. Predictive performance of a binary classifier was assessed by looking at discrimination (i.e., quantified in terms of the area under the receiver operating characteristic curve). The final prediction model was validated using data with regard to the third booster by assessing misclassification rate, sensitivity and specificity.ResultsIn total, 11% of the PHCPs had moderate-to-severe side-effects after their booster COVID-19 mRNA vaccine. The most common side-effects of COVID-19 mRNA doses included fatigue, local pain at the injection site, general pains, and headache. These side-effects typically lasted for a median of 1 to 2 days. The final model included five predictors: sex, alcohol consumption, history of moderate-to-severe side-effects after any previous dose, recent COVID-19 infection, and the booster dose-number (first, second). Having experienced moderate-to-severe side-effects after any previous dose was the strongest predictor of moderate-to-severe side-effects following an mRNA vaccine booster, with an odds ratio (OR) of 3.64 (95% CI: 2.80-4.75). The OR for female sex was 1.49 (95% CI: 1.21-1.84) implying that females have a higher odds of moderate-to-severe side-effects following booster vaccination. The differences in effect for booster dose-number, alcohol consumption and recent COVID-19 infection was not significant.Conclusion and relevanceCOVID-19 mRNA booster vaccination implies a low prevalence of moderate-to-severe side-effects among PHCPs, with a short median duration of symptoms if any. The strongest predictors are a history of moderate-to-severe side-effects after any previous dose and being female. These reassuring findings can help addressing concerns about booster vaccination and encourage their uptake.Trial registrationNCT04779424 (registration date: 2021-02-22).

Dataset Information

A Predictive Model for Severe COVID-19 in the Medicare Population: A Tool for Prioritizing Primary and Booster COVID-19 Vaccination.

Publications

A Predictive Model for Severe COVID-19 in the Medicare Population: A Tool for Prioritizing Primary and Booster COVID-19 Vaccination.

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