Kirk M. Wolter

Effect of Vaccine Shortages on Timeliness of Pneumococcal Conjugate Vaccination: Results From the 2001–2005 National Immunization Survey

BACKGROUND. In September 2001 and again in February 2004, the Centers for Disease Control and Prevention announced shortages in the supply of the pneumococcal conjugate vaccine. We describe the effects of the pneumococcal conjugate vaccine shortages in 2001–2003 and 2004 on the timeliness of vaccination uptake for quarterly birth cohorts affected by the shortages. METHODS. A total of 102478 19- to 35-month-old children were sampled by the National Immunization Survey between 2001 and 2005. Provider-reported vaccination histories were used to evaluate whether children had been administered ≥4 doses of pneumococcal conjugate vaccine by 16 months of age. RESULTS. Among successive birth cohorts affected by the first shortage, estimated coverage of ≥4 doses of pneumococcal conjugate vaccine by 16 months declined significantly from 28.8% to 18.2%. As the first shortage ended, estimated coverage of ≥4 doses of pneumococcal conjugate vaccine by 16 months increased steadily with each successive birth cohort to 40.2%. From the onset of the second shortage, estimated coverage of ≥4 doses of pneumococcal conjugate vaccine by 16 months declined steadily and significantly to 13.7%. As many as 27% of parents whose child was affected by the first shortage reported that their childs vaccination provider had delayed the administration of pneumococcal conjugate vaccine doses. Of those parents who said that a pneumococcal conjugate vaccine dose was delayed and whose child was not administered ≥4 doses, 2.9% received a reminder notice from the provider to schedule administration of those delayed doses, and 0.2% had an appointment to receive those delayed or missed doses. CONCLUSIONS. Vaccine shortages can result in delayed or missed doses and can have a dramatic impact on the vaccine coverage of children. Vaccination providers need to communicate effectively with parents so that doses that are delayed or missed during a vaccine shortage are administered when the shortage is resolved.

Hard-to-survey populations

This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.

Quantifying bias in a health survey: modeling total survey error in the national immunization survey.

Random-digit-dial telephone surveys are experiencing both declining response rates and increasing under-coverage due to the prevalence of households that substitute a wireless telephone for their residential landline telephone. These changes increase the potential for bias in survey estimates and heighten the need for survey researchers to evaluate the sources and magnitudes of potential bias. We apply a Monte Carlo simulation-based approach to assess bias in the NIS, a land-line telephone survey of 19-35 month-old children used to obtain national vaccination coverage estimates. We develop a model describing the survey stages at which component nonsampling error may be introduced due to nonresponse and under-coverage. We use that model and components of error estimated in special studies to quantify the extent to which noncoverage and nonresponse may bias the vaccination coverage estimates obtained from the NIS and present a distribution of the total survey error. Results indicated that the total error followed a normal distribution with mean of 1.72 per cent(95 per cent CI: 1.71, 1.74 per cent) and final adjusted survey weights corrected for this error. Although small, the largest contributor to error in terms of magnitude was nonresponse of immunization providers. The total error was most sensitive to declines in coverage due to cell phone only households. These results indicate that, while response rates and coverage may be declining, total survey error is quite small. Since response rates have historically been used to proxy for total survey error, the finding that these rates do not accurately reflect bias is important for evaluation of survey data. Published in 2011 by John Wiley & Sons, Ltd.

Design, Conduct, and Analysis of Random-Digit Dialing Surveys

Publisher Summary Random-digit dialing (RDD) is a method of probability sampling that provides a sample of households, families, or persons through a random selection of their telephone numbers. For simplicity of explication, the person is used as the final unit of analysis in this chapter; yet, virtually all the comments and methods extend to the household or family. The chapter discusses the design, conduct, and analysis of RDD surveys, primarily in the context of large-scale work performed in the United States. The material generalizes to other countries with an established landline infrastructure. In the United States, there is no sampling frame that enables a direct sampling of persons. RDD changes the sampling unit from the person to the telephone number, for which sampling frames do exist. Then people can be sampled indirectly through their telephone numbers, enabling valid inferences to populations of people. In the modern era, the RDD survey has come to embody the following three elements: (1) random sampling of telephone numbers from a listing of all (or most) assigned telephone numbers, (2) dialing the selected numbers from central call centers, and (3) administering the survey questionnaire to residential respondents through a system of computer-assisted telephone interviewing.

Using Auxiliary Sample Frame Information for Optimum Sampling of Rare Populations

Abstract We investigate disproportionate stratified sampling as a possibly efficient method of surveying members of a rare domain in circumstances in which there is no acceptable list of members. In this work, we assume that information is available at the sampling stage to stratify the general-population sampling frame into high- and low-density strata. Under a fixed constraint on the variance of the estimator of the domain mean, we make the optimum allocation of sample size to the several strata and show that, in comparison to proportional allocation, the optimum allocation requires (a) a smaller total sample size but (b) a larger number of interviews of members of the rare domain. We illustrate the methods using information about American consumers maintained by market-research companies. Such companies are able to develop lists of households that are thought to have a defined attribute of interest, such as at least one resident in a user-specified age range. The lists are imperfect, with false positives and negatives. We apply an age-targeted list to the National Immunization Survey (NIS), conducted by the Centers for Disease Control and Prevention, which targets the relatively rare population of children age 19–35 months. The age-targeted list comprises the high-density stratum and the rest of the survey’s sampling frame comprises the low-density stratum. Given the optimum allocation, we demonstrate potential cost savings for the NIS in excess of ten percent.

Hard-to-Survey Populations: List of contributors

This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.

Hard-to-Survey Populations: Conducting surveys with special populations

This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.

Hard-to-Survey Populations: Dedication

This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.

Hard-to-Survey Populations: Data collection strategies for the hard to survey

This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.

Hard-to-Survey Populations: List of figures

This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.