Adjusting HIV Prevalence Estimates for Non-participation: an Application to Demographic Surveillance

Introduction: HIV testing is a cornerstone of efforts to combat the HIV epidemic, and testing conducted as part of surveillance provides invaluable data on the spread of infection and the effectiveness of campaigns to reduce the transmission of HIV. However, participation in HIV testing can be low, and if respondents systematically select not to be tested because they know or suspect they are HIV positive (and fear disclosure), standard approaches to deal with missing data will fail to remove selection bias. We implemented Heckman-type selection models, which can be used to adjust for missing data that are not missing at random, and established the extent of selection bias in a population-based HIV survey in an HIV hyperendemic community in rural South Africa.

Methods: We used data from a population-based HIV survey carried out in 2009 in rural KwaZulu-Natal, South Africa. In this survey, 5565 women (35%) and 2567 men (27%) provided blood for an HIV test. We accounted for missing data using interviewer identity as a selection variable which predicted consent to HIV testing but was unlikely to be independently associated with HIV status. Our approach involved using this selection variable to examine the HIV status of residents who would ordinarily refuse to test, except that they were allocated a persuasive interviewer. Our copula model allows for flexibility when modelling the dependence structure between HIV survey participation and HIV status.

Results: For women, our selection model generated an HIV prevalence estimate of 33% (95% CI 27–40) for all people eligible to consent to HIV testing in the survey. This estimate is higher than the estimate of 24% generated when only information from respondents who participated in testing is used in the analysis, and the estimate of 27% when imputation analysis is used to predict missing data on HIV status. For men, we found an HIV prevalence of 25% (95% CI 15–35) using the selection model, compared to 16% among those who participated in testing, and 18% estimated with imputation. We provide new confidence intervals that correct for the fact that the relationship between testing and HIV status is unknown and requires estimation.

Conclusions: We confirm the feasibility and value of adopting selection models to account for missing data in population-based HIV surveys and surveillance systems. Elements of survey design, such as interviewer identity, present the opportunity to adopt this approach in routine applications. Where non-participation is high, true confidence intervals are much wider than those generated by standard approaches to dealing with missing data suggest.

Demographic and temporal trends in out of hospital sudden cardiac death in belfast

Objective: To determine the epidemiology of out of hospital sudden cardiac death (OHSCD) in Belfast from 1 August 2003 to 31 July 2004.

Design: Prospective examination of out of hospital cardiac arrests by using the Utstein style and necropsy reports. World Health Organization criteria were applied to determine the number of sudden cardiac deaths.

Results: Of 300 OHSCDs, 197 (66%) in men, mean age (SD) 68 (14) years, 234 (78%) occurred at home. The emergency medical services (EMS) attended 279 (93%). Rhythm on EMS arrival was ventricular fibrillation (VF) in 75 (27%). The call to response interval (CRI) was mean (SD) 8 (3) minutes. Among patients attended by the EMS, 9.7% were resuscitated and 7.2% survived to leave hospital alive. The CRI for survivors was mean (SD) 5 (2) minutes and for non-survivors, 8 (3) minutes (p < 0.001). Ninety one (30%) OHSCDs were witnessed; of these 91 patients 48 (53%) had VF on EMS arrival. The survival rate for witnessed VF arrests was 20 of 48 (41.7%): all 20 survivors had VF as the presenting rhythm and CRI ? 7 minutes. The European age standardised incidence for OHSCD was 122/100 000 (95% confidence interval 111 to 133) for men and 41/100 000 (95% confidence interval 36 to 46) for women.

Conclusion: Despite a 37% reduction in heart attack mortality in Ireland over the past 20 years, the incidence of OHSCD in Belfast has not fallen. In this study, 78% of OHSCDs occurred at home.

Demographic Change, Social Security Systems, and Savings

Abstract In theory, improvements in healthy life expectancy should generate increases in the average age of retirement, with little effect on savings rates. In many countries, however, retirement incentives in social security programs prevent retirement ages from keeping pace with changes in life expectancy, leading to an increased need for life-cycle savings. Analyzing a cross-country panel of macroeconomic data, we find that increased longevity raises aggregate savings rates in countries with universal pension coverage and retirement incentives, though the effect disappears in countries with pay-as-you-go systems and high replacement rates.