Using Lot Quality Assurance Sampling to Monitor the Prevalence of Abortions and the Quality of Reproductive Health Care in Armenia

Monitoring abortion prevalence is essential to plan control efforts. Lot Quality Assurance Sampling (LQAS) is an inexpensive, reliable method for monitoring abortion prevalence and access to quality reproductive health (RH) services. This chapter presents survey results from 2000 in three sites of Armenia (Gyumri, Gavar and Goris) using LQAS principles (i.e., 44%, 95% CI: ±6% of women had an induced abortion in their lifetime, a total abortion rate (TAR) of 2.0 abortions per woman). Modern contraceptive use was lowest in Goris (16%. 95% CI: ±7%) and highest in Gyumri (43%, 95% CI: ±11%). Only 37% (95% CI: ±9%) of women with an induced abortion received family planning information and 21% (95% CI: ±4%) of mothers were counselled about family planning after delivery. While limited access to family planning information and contraceptives is still an issue in Armenia, recently new reproductive health priorities—such as infertility, sex-selective abortions and abortions due to socio-economic difficulties—have become more common and can be investigated using LQAS in both community surveys and health facility assessments. This study demonstrates that measuring national abortion prevalence and access to services mask underlying variations; the awareness of which is essential for health program planning

Rapid Assessment of Centers for Displaced Unaccompanied Children in Rwanda during the 1994 Crisis

This paper assesses aIl of the Centers for Unaccompanied Children (CUCs) in four prefectures of Rwanda during November 1994 using quantitative and qualitative methods. The purpose of the survey was to assess the quality of services delivered as weIl as the need for standards to be developed for planning and managing CUCs. This paper reveals that CUCs exhibit a large variability amongst themselves as weIl as numerous deficiencies in the quality ofservices delivered, and suggests the need for clear performance standards, and regular monitoring and supervision.Cet article procède à une évaluation de tous les Centres pour Enfants Non Accompagnés dans quatre préfectures du Rwanda au cours du mois de novembre 1994, grâce à des observations directes et à un questionnaire. Le but de l'enquête est d'évaluer la qualité des services fournis, autant que de se donner une idée des besoins en matière de formulations des normes à développer pour la mise sur pied et la gestion de ces CUC. Cet article révèle que les CUC sont très peu semblables, et manifestent de larges disparités autant que de multiples déficiences dans la qualité des services qu'ils diffusent. On conclut en affirmant qu'il y se manifeste un net besoin de normes de performance autant que d'un suivi et d'une supervision constante de ces services

Multiple Category-Lot Quality Assurance Sampling: A New Classification System with Application to Schistosomiasis Control

Background: Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa. Methodology We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n = 15 and n = 25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa. Principle Findings Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n = 15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error. Conclusion/Significance: This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools

Combining national survey with facility-based HIV testing data to obtain more accurate estimate of HIV prevalence in districts in Uganda.

BACKGROUND: National or regional population-based HIV prevalence surveys have small sample sizes at district or sub-district levels; this leads to wide confidence intervals when estimating HIV prevalence at district level for programme monitoring and decision making. Health facility programme data, collected during service delivery is widely available, but since people self-select for HIV testing, HIV prevalence estimates based on it, is subject to selection bias. We present a statistical annealing technique, Hybrid Prevalence Estimation (HPE), that combines a small population-based survey sample with a facility-based sample to generate district level HIV prevalence estimates with associated confidence intervals. METHODS: We apply the HPE methodology to combine the 2011 Uganda AIDS indicator survey with the 2011 health facility HIV testing data to obtain HIV prevalence estimates for districts in Uganda. Multilevel logistic regression was used to obtain the propensity of testing for HIV in a health facility, and the propensity to test was used to combine the population survey and health facility HIV testing data to obtain the HPEs. We assessed comparability of the HPEs and survey-based estimates using Bland Altman analysis. RESULTS: The estimates ranged from 0.012 to 0.178 and had narrower confidence intervals compared to survey-based estimates. The average difference between HPEs and population survey estimates was 0.00 (95% CI: - 0.04, 0.04). The HPE standard errors were 28.9% (95% CI: 23.4-34.4) reduced, compared to survey-based standard errors. Overall reduction in HPE standard errors compared survey-based standard errors ranged from 5.4 to 95%. CONCLUSIONS: Facility data can be combined with population survey data to obtain more accurate HIV prevalence estimates for geographical areas with small population survey sample sizes. We recommend use of the methodology by district level managers to obtain more accurate HIV prevalence estimates to guide decision making without incurring additional data collection costs

Hybrid prevalence estimation: Method to improve intervention coverage estimations

Delivering excellent health services requires accurate health information systems (HIS) data. Poor-quality data can lead to poor judgments and outcomes. Unlike probability surveys, which are representative of the population and carry accuracy estimates, HIS do not, but in many countries the HIS is the primary source of data used for administrative estimates. However, HIS are not structured to detect gaps in service coverage and leave communities exposed to unnecessary health risks. Here we propose a method to improve informatics by combining HIS and probability survey data to construct a hybrid estimator. This technique provides a more accurate estimator than either data source alone and facilitates informed decision-making. We use data from vitamin A and polio vaccination campaigns in children from Madagascar and Benin to demonstrate the effect. The hybrid estimator is a weighted average of two measurements and produces SEs and 95% confidence intervals (CIs) for the hybrid and HIS estimators. The estimates of coverage proportions using the combined data and the survey estimates differ by no more than 3%, while decreasing the SE by 1-6%; the administrative estimates from the HIS and combined data estimates are very different, with 3-25 times larger CI, questioning the value of administrative estimates. Estimators of unknown accuracy may lead to poorly formulated policies and wasted resources. The hybrid estimator technique can be applied to disease prevention services for which population coverages are measured. This methodology creates more accurate estimators, alongside measured HIS errors, to improve tracking the public's health

Difference in HIV prevalence by testing venue: results from population level survey in Uganda

Growing demand for use of Health Facility (HF) HIV testing data, in addition to other testing data to obtain district level HIV prevalence requires understanding the comparability of these various sources. We analysed the 2011 Uganda AIDS indicator survey data to assess: the proportion of people tested for HIV across Uganda by venue of testing; HIV prevalence ratio for those tested in a HF compared to those tested in community setting; [Katz, D., Baptista, J., Azen, S. P., & Pike, M. C. (1978). Obtaining confidence intervals for the risk ratio in cohort studies. International Biometric Society, 34(3), 469-474. https://doi.org/10.2307/2530610] and factors associated with HIV positivity in each subgroup. Of the 11,685 individuals, 8978 (77.1%) had ever tested for HIV in a HF. Fifty nine per cent tested in a HF in the 12 months preceding the survey (female: 5507, 72.7% versus male: 1413, 34.9%). HIV prevalence ratio was 1.8 times among those tested in a HF compared to those tested at community setting (10.9% [95% CI: 10.0-11.7] versus 6.2% [95% CI: 5.4-7.0]). Among HF testers, older age group, previously married and having no sexual partner was associated with significantly higher HIV prevalence. Using facility testing data for planning and decisions should take into consideration the elevated and varying HIV prevalence among individuals accessing HIV testing services at HFs as well as differences in their social-demographic characteristics

A Novel Approach to Evaluating the Iron and Folate Status of Women of Reproductive Age in Uzbekistan after 3 Years of Flour Fortification with Micronutrients

Background: The Uzbekistan 1996 Demographic Health Survey reported 60.4% of women of reproductive age (WRA) had low hemoglobin concentrations (5 mg/L). Severe anemia was more prevalent among folate deficient than iron depleted WRA. Presence of UDM first grade flour or the grey loaf was reported in 71.3% of households. Among WRA, 32.1% were aware of UDM fortification; only 3.7% mentioned the benefits of fortification and 12.5% understood causes of anemia. Consumption of heme iron-containing food (91%) and iron absorption enhancers (97%) was high, as was the consumption of iron absorption inhibitors (95%). Conclusions/Significance: The NFFP coincided with a substantial decline in the prevalence of anemia. Folate deficiency was a stronger predictor of severe anemia than iron depletion. However, the prevalence of iron depletion was high, suggesting that women are not eating enough iron or iron absorption is inhibited. Fortified products were prevalent throughout Uzbekistan, though UDM flour must be adequately fortified and monitored in the future. Knowledge of fortification and anemia was low, suggesting consumer education should be prioritized

Comparing two survey methods of measuring health-related indicators: Lot Quality Assurance Sampling and Demographic Health Surveys

ObjectivesTwo common methods used to measure indicators for health programme monitoring and evaluation are the demographic and health surveys (DHS) and lot quality assurance sampling (LQAS); each one has different strengths. We report on both methods when utilised in comparable situations.MethodsWe compared 24 indicators in south-west Uganda, where data for prevalence estimations were collected independently for the two methods in 2011 (LQAS: n = 8876; DHS: n = 1200). Data were stratified (e.g. gender and age) resulting in 37 comparisons. We used a two-sample two-sided Z-test of proportions to compare both methods.ResultsThe average difference between LQAS and DHS for 37 estimates was 0.062 (SD = 0.093; median = 0.039). The average difference among the 21 failures to reject equality of proportions was 0.010 (SD = 0.041; median = 0.009); among the 16 rejections, it was 0.130 (SD = 0.010, median = 0.118). Seven of the 16 rejections exhibited absolute differences of 0.10 and 0.20 (mean = 0.261, SD = 0.083).ConclusionThere is 75.7% agreement across the two surveys. Both methods yield regional results, but only LQAS provides information at less granular levels (e.g. the district level) where managerial action is taken. The cost advantage and localisation make LQAS feasible to conduct more frequently, and provides the possibility for real-time health outcomes monitoring

Sexual and Reproductive Health Among Ugandan Youth: 2003-04 to 2012

PurposeSuboptimal sexual and reproductive health (SRH) increases morbidity, mortality, and gender inequity and slows development. In Uganda, youths represent 20% of the population, and the burden of sexually transmitted infections (STIs), including human immunodeficiency virus (HIV), is substantial.MethodsWe analyzed survey data collected using the lot quality assurance sampling (LQAS) technique from two time periods, 2003-2004 and 2012. We assessed knowledge, behaviors, and access to SRH services of youths aged 15-24 years. Using logistic regression, we examined factors associated with these indicators.ResultsAll indicators have improved between the early and later time period. Youths knowing where to get HIV tests increased from ConclusionsOver the last decade, progress has been made toward improving the SRH of young people in Uganda. Further efforts are required to ensure universal access and sufficient health education to facilitate the continued improvement of safe sexual behaviors among youth aged 15-24 years