Population-Based HIV Impact Assessments Survey Methods, Response, and Quality in Zimbabwe, Malawi, and Zambia.

BACKGROUND: The population-based HIV impact assessment (population-based HIV impact assessments) surveys are among the first to estimate national adult HIV incidence, subnational prevalence of viral load suppression, and pediatric HIV prevalence. We summarize the survey methods implemented in Zimbabwe, Malawi, and Zambia, as well as response rates and quality metrics. METHODS: Each cross-sectional, household-based survey used a 2-stage cluster design. Survey preparations included sample design, questionnaire development, tablet programming for informed consent and data collection, community mobilization, establishing a network of satellite laboratories, and fieldworker training. Interviewers collected demographic, behavioral, and clinical information using tablets. Blood was collected for home-based HIV testing and counseling (HBTC) and point-of-care CD4+ T-cell enumeration with results immediately returned. HIV-positive blood samples underwent laboratory-based confirmatory testing, HIV incidence testing, RNA polymerase chain reaction (viral load), DNA polymerase chain reaction (early infant diagnosis), and serum antiretroviral drug detection. Data were weighted for survey design, and chi square automatic interaction detection-based methods were used to adjust for nonresponse. RESULTS: Each survey recruited a nationally representative, household-based sample of children and adults over a 6-10-month period in 2015 and 2016. Most (84%-90%) of the 12,000-14,000 eligible households in each country participated in the survey, with 77%-81% of eligible adults completing an interview and providing blood for HIV testing. Among eligible children, 59%-73% completed HIV testing. Across the 3 surveys, 97.8% of interview data were complete and had no errors. CONCLUSION: Conducting a national population-based HIV impact assessment with immediate return of HIV and other point-of-care test results was feasible, and data quality was high.

Improving Sampling Efficiency for Determining Pediatric HIV Prevalence in National Surveys: Evidence From 8 Sub-Saharan African Countries.

BACKGROUND: Measurement of mother-to-child HIV transmission through population-based surveys requires large sample sizes because of low HIV prevalence among children. We estimate potential improvements in sampling efficiency resulting from a targeted sample design. SETTING: Eight countries in sub-Saharan Africa with completed Population-based HIV Impact Assessment (PHIA) surveys as of 2017. METHODS: The PHIA surveys used a geographically stratified 2-stage sample design with households sampled from randomly selected census enumeration areas. Children (0-14 years of age) were eligible for HIV testing within a random subsample of households (usually 50%). Estimates of child HIV prevalence in each country were calculated using jackknife replicate weights. We compared sample sizes and precision achieved using this design with a 2-phase disproportionate sample design applied to strata defined by maternal HIV status and mortality. RESULTS: HIV prevalence among children ranged from 0.4% (95% confidence interval: 0.2 to 0.6) in Tanzania to 2.8% (95% confidence interval: 2.2 to 3.4) in Eswatini with achieved relative standard errors between 11% and 21%. The expected precision improved in the targeted design in all countries included in the analysis, with proportionate reductions in mean squared error ranging from 27% in Eswatini to 61% in Tanzania, assuming an equal sample size. CONCLUSIONS: Population-based surveys of adult HIV prevalence that also measure child HIV prevalence should consider targeted sampling of children to reduce required sample size, increase precision, and increase the number of positive children tested. The findings from the PHIA surveys can be used as baseline data for informing future sample designs.

Design and methods of the Population Assessment of Tobacco and Health (PATH) Study.

BACKGROUND: This paper describes the methods and conceptual framework for Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study data collection. The National Institutes of Health, through the National Institute on Drug Abuse, is partnering with the Food and Drug Administration's (FDA) Center for Tobacco Products to conduct the PATH Study under a contract with Westat. METHODS: The PATH Study is a nationally representative, longitudinal cohort study of 45 971 adults and youth in the USA, aged 12 years and older. Wave 1 was conducted from 12 September 2013 to 15 December 2014 using Audio Computer-Assisted Self-Interviewing to collect information on tobacco-use patterns, risk perceptions and attitudes towards current and newly emerging tobacco products, tobacco initiation, cessation, relapse behaviours and health outcomes. The PATH Study's design allows for the longitudinal assessment of patterns of use of a spectrum of tobacco products, including initiation, cessation, relapse and transitions between products, as well as factors associated with use patterns. Additionally, the PATH Study collects biospecimens from consenting adults aged 18 years and older and measures biomarkers of exposure and potential harm related to tobacco use. CONCLUSIONS: The cumulative, population-based data generated over time by the PATH Study will contribute to the evidence base to inform FDA's regulatory mission under the Family Smoking Prevention and Tobacco Control Act and efforts to reduce the Nation's burden of tobacco-related death and disease.

Effects of the National Youth Anti-Drug Media Campaign on youths.

OBJECTIVES: We examined the cognitive and behavioral effects of the National Youth Anti-Drug Media Campaign on youths aged 12.5 to 18 years and report core evaluation results. METHODS: From September 1999 to June 2004, 3 nationally representative cohorts of US youths aged 9 to 18 years were surveyed at home 4 times. Sample size ranged from 8117 in the first to 5126 in the fourth round (65% first-round response rate, with 86%-93% of still eligible youths interviewed subsequently). Main outcomes were self-reported lifetime, past-year, and past-30-day marijuana use and related cognitions. RESULTS: Most analyses showed no effects from the campaign. At one round, however, more ad exposure predicted less intention to avoid marijuana use (gamma = -0.07; 95% confidence interval [CI] = -0.13, -0.01) and weaker antidrug social norms (gamma = -0.05; 95% CI = -0.08, -0.02) at the subsequent round. Exposure at round 3 predicted marijuana initiation at round 4 (gamma = 0.11; 95% CI = 0.00, 0.22). CONCLUSIONS: Through June 2004, the campaign is unlikely to have had favorable effects on youths and may have had delayed unfavorable effects. The evaluation challenges the usefulness of the campaign.

Survey research methods in evaluation and case-control studies.

Survey research methods are widely used in two types of analytic studies: evaluation studies that measure the effects of interventions; and population-based case-control studies that investigate the effects of various risk factors on the presence of disease. This paper provides a broad overview of some design and analysis issues related to such studies, illustrated with examples. The lack of random assignment to treatment and control groups in many evaluation studies makes controlling for confounders critically important. Confounder control can be achieved by matching in the design and by various alternative methods in the analysis. One popular analytic method of controlling for confounders is propensity scoring, which bears a close resemblance to survey weighting. The use of population-based controls has become common in case-control studies. For reasons of cost, population-based controls are often identified by telephone surveys using random digit dialling (RDD) sampling methods. However, RDD surveys are now experiencing serious problems with response rates. A recent alternative approach is to select controls from frames such as driver license lists that contain valuable demographic information for use in matching. Methods of analysis developed in the survey sampling literature are applicable, at least to some degree, in the analyses of evaluation and population-based case-control studies. In particular, the effects of complex sample designs can be taken into account using survey sampling variance estimation methods. Several survey analysis software packages are available for carrying out the computations.

Immunization coverage levels among 19- to 35-month-old children in 4 diverse, medically underserved areas of the United States.

BACKGROUND: The National Immunization Survey demonstrates that national immunization coverage in 2002 remained near the all-time highs achieved in 2000. However, that survey cannot detect whether coverage is uniformly high within relatively small areas or populations. The measles resurgence in the early 1990s revealed that coverage was low in some areas, particularly among inner-city children from racial and ethnic minority groups. Today, identifying areas with low childhood-vaccination coverage remains important, particularly if these areas are at risk for the introduction of disease. In 1995, the Centers for Disease Control and Prevention launched a congressionally mandated demonstrated project now called the Childhood Immunization Demonstration project of Community Health Networks. This mandate specified an assessment to determine whether a network of primary care providers affiliated with university teaching hospitals could assume a public health responsibility for raising immunization levels among preschoolers in medically underserved communities. Communities with federally designated health professional shortage areas were invited to submit proposals, and 4 were selected: Detroit, MI, New York, NY, San Diego, CA, and rural Colorado. OBJECTIVES: To measure immunization coverage among preschool children in the 4 selected medically underserved areas and determine predictors of coverage levels. DESIGN AND SETTING: Surveys in the 4 areas were based on stratified cluster probability sample designs in which clusters of dwelling units were selected and all households in selected clusters were screened for the presence of children aged 12 to 35 months. Immunization histories were obtained from parents and providers for these children. For each age-eligible child, the information collected on utilization of immunization health services included a listing of all clinics or offices ever used for the child's well-child care and/or for obtaining immunizations. Information was also collected on whether the child currently had health insurance (public and/or private) and whether the child had a medical home. A child was classified as having a medical home if the survey respondent reported a source of well care that was the same as the source of sick care and that this place was not an emergency department. PARTICIPANTS: Children 12 to 35 months of age in Detroit, New York, San Diego, and rural Colorado. OUTCOME MEASURE: Community-wide up-to-date (UTD) immunization coverage levels at 19 to 35 months of age, defined as receipt of 4 doses of diphtheria and tetanus toxoids and pertussis vaccine, 3 doses of poliovirus vaccine, 1 dose of measles, mumps, and rubella vaccine, 3 doses of Haemophilus influenzae type B vaccine, and 3 doses of hepatitis B vaccine (the 4:3:1:3:3 series). ANALYSIS: We examined the association between coverage level and independent variables and performed chi2 and t tests to determine whether differences observed within and between groups and sites were significant. RESULTS: The overall response rate for eligible children ranged from 79.4% to 88.1%. Coverage levels for most individual vaccines were >90% in all sites except Detroit. Coverage for the 4:3:1:3:3 series was significantly higher for children in New York (84%) and San Diego (86%) than for children in Detroit (66%) and rural Colorado (75%). Demographic risk factors related to UTD immunization status varied by site. Although differences in coverage levels by ethnicity varied by site, differences were not significant. In Colorado and New York, coverage was slightly lower among Hispanic than white children (71% vs 76% and 83% vs 91%, respectively). In San Diego, coverage was lower among whites, compared with Hispanics (76% vs 85%). Coverage was also lower for African American than white children only in New York (75% vs 91%). However, in San Diego and Colorado, children receiving their vaccinations from private providers had lower coverage levels than children receiving their vaccinations from other providers (78% vs 91% and 71% vs 57%, respectively). Ictively). In all 4 sites, children for whom respondents reported having an immunization card at the time of the interview were more likely to have higher series coverage levels than children for whom a parent-held card was not available. Also, children who were UTD at 3 months of age had significantly higher vaccination-series coverage levels than children who were not UTD at 3 months of age. In addition, the vaccination coverage was lower for children in Detroit whose parents reported problems accessing the health care system because lack of transportation (46%), compared with those who did not report such problems (65%); however, this difference did not reach significance (chi2 = 6.0). In Colorado, the small proportion of children in families without a phone had a lower vaccination coverage level (58%) than those in households with a phone (75%) (chi2 = 6.3). In all sites, children who were UTD at 3 months of age and had a parent-held vaccination card were more likely to be UTD at 19 to 35 months of age. CONCLUSIONS: Preschoolers in these medically underserved areas were not at uniform risk for underimmunization. Because they were designated as health professional shortage areas, the 4 sites in this study were expected to have low immunization-coverage rates. However, this was not the case. In fact, coverage in 3 of the 4 areas was quite high compared with US national figures (73%); only Detroit had a much lower UTD rate (66%). Efforts are needed to improve methods to identify areas with low immunization coverage so that resources can be directed to places where interventions are needed. Our results reveal that an area's need for childhood immunization interventions is not well predicted by a low number of providers per capita. Other criteria must be developed to predict areas or populations with low immunization coverage. Understanding more about the characteristics of children/provider pairs for children who are UTD at 3 months and more about the role of parental hand-held cards, along with finding strategies to improve immunization delivery by providers in Vaccines for Children Program facilities, suggest potentially productive avenues for increasing and sustaining high coverage levels.