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Impact of COVID-19 vaccination on hospitalization, hospital utilization and expenditure for COVID-19: A retrospective cohort analysis of a South African private health insured population.
PLoS One
January 2025
Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa.
This study quantifies the impact of COVID-19 vaccination on hospitalization for COVID-19 infection in a South African private health insurance population. This retrospective cohort study is based on the analysis of demographic and claims records for 550,332 individuals belonging to two health insurance funds between 1 March 2020 and 31 December 2022. A Cox Proportional Hazards model was used to estimate the impact of vaccination (non-vaccinated, partly vaccinated, fully vaccinated) on COVID-19 hospitalization risk; and zero-inflated negative binomial models were used to estimate the impact of vaccination on hospital utilization and hospital expenditure for COVID-19 infection, with adjustments for age, sex, comorbidities and province of residence.
View Article and Find Full Text PDFHow is maternal employment associated with infant and young child feeding in Bangladesh? A systematic literature review and meta-analysis.
PLoS One
January 2025
Department of Clinical Sciences, Health Economics Unit, Lund University, Lund, Sweden.
Background: In the last three decades, the increasing trend in female employment in Bangladesh has been critically analyzed from a socioeconomic point of view; however, its impact on infant and young child feeding (IYCF) practices has yet to be systematically reviewed. The aim of this systematic review and meta-analysis is to investigate the association between these variables.
Methods: A systematic literature search was conducted in PubMed, Medline, Web of Science, Embase, CINAHL, and Google Scholar to retrieve relevant records with no restriction of publication period.
Spatial-temporal evolution of the allometric relationship between urban economic and health resources in the Yangtze River Delta urban agglomeration.
PLoS One
January 2025
School of Pharmaceutical Economics and Management, Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China.
The evolution of the spatiotemporal relationship between urban economic growth and health resources within the Yangtze River Delta urban agglomeration provides an important context for understanding the regional development dynamics in China. Previous studies focused on equity in health-resource allocation and service efficiency, often overlooking the allometric growth relationships between health resources and economic variables. This study employs an allometric growth model to elucidate the changing interactions between the number of medical beds, doctors, and urban economic indicators in the Yangtze River Delta region from 2009 to 2022.
View Article and Find Full Text PDFHealthcare resource utilization and costs in immunodeficient patients receiving subcutaneous Ig: Real-world evidence from France.
PLoS One
January 2025
French National Reference Center for Primary Immunodeficiencies (CEREDIH) and Pediatric Immunology, Hematology and Rheumatology Unit, Necker Enfants Malades University Hospital, Assistance Publique - Hôpitaux de Paris (APHP), Paris, France.
Background: Subcutaneous immunoglobulin (SCIg) replacement therapy is indicated for patients with hypogammaglobulinemia caused by primary (PID) and secondary immunodeficiencies (SID).
Objective: To compare healthcare resource utilization (HCRU) and related direct medical costs of patients in France treated with weekly conventional SCIg (cSCIg) vs monthly hyaluronidase-facilitated SCIg (fSCIg).
Methods: This retrospective study of Ig-naïve patients with PID or SID newly receiving a SCIg between 2016 and 2018, extracted from the French National Healthcare reimbursement database (SNDS), analyzed the SCIg-related HCRU and reimbursed costs generated from in-hospital (hospitalizations and SCIg doses) or at-home (nurse visits [NV] and pump provider visits [PPV], drug doses) SCIg administration.
Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal.
PLoS One
January 2025
Nova School of Business and Economics, Universidade Nova de Lisboa, Carcavelos, Portugal.
This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. To train and test the model, we used data from 2,133 students attending schools in a Portuguese municipality.
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