Challenges to estimating vaccine impact using hospitalization data

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• 作者：Cynthia Schuck-Paim^a ; ^{cschuck@sageanalytica.com} ; Robert J. Taylor^a ; Lone Simonsen^b ; Roger Lustig^a ; Esra K&uuml ; r&uuml ; m^c ; ^d ; Christian A.W. Bruhn^c ; Daniel M. Weinberger^c
• 关键词：Vaccines ; Hospitalization ; Health impact assessment ; Pneumococcal vaccines ; Pneumonia ; Confounding factors ; Bias ; Delivery of health care ; Brazil ; Latin America ; Pneumococcus ; Pneumococcal conjugate vaccines ; Observational studies ; Public health
• 刊名：Vaccine
• 出版年：2017
• 出版时间：3 January 2017
• 年：2017
• 卷：35
• 期：1
• 页码：118-124
• 全文大小：358 K
• 卷排序：35

文摘

Changes in healthcare delivery can bias vaccine impact estimates based on hospitalization data. Improvements in primary care that reduce hospitalizations often coincide with vaccine introduction. Vaccine benefits may be underestimated if hospitals are operating at full capacity. Commonly used adjustments are not always sufficient to control for bias and confounding. We suggest ways to strengthen vaccine impact assessments based on hospitalization data.