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Beginning in 2003, Uganda used Lot Quality Assurance Sampling (LQAS) to assist district managers collect and use data to improve their human immunodeficiency virus (HIV)/AIDS program. Uganda's LQAS-database (2003-2012) covers up to 73 of 112 districts. Our multidistrict analysis of the LQAS data-set at 2003-2004 and 2012 examined gender variation among adults who ever tested for HIV over time, and attributes associated with testing. Conditional logistic regression matched men and women by community with seven model effect variables. HIV testing prevalence rose from 14% (men) and 12% (women) in 2003-2004 to 62% (men) and 80% (women) in 2012. In 2003-2004, knowing the benefits of testing (Odds Ratio [OR] = 6.09, 95% CI = 3.01-12.35), knowing where to get tested (OR = 2.83, 95% CI = 1.44-5.56), and secondary education (OR = 3.04, 95% CI = 1.19-7.77) were significantly associated with HIV testing. By 2012, knowing the benefits of testing (OR = 3.63, 95% CI = 2.25-5.83), where to get tested (OR = 5.15, 95% CI = 3.26-8.14), primary education (OR = 2.01, 95% CI = 1.39-2.91), being female (OR = 3.03, 95% CI = 2.53-3.62), and being married (OR = 1.81, 95% CI = 1.17-2.8) were significantly associated with HIV testing. HIV testing prevalence in Uganda has increased dramatically, more for women than men. Our results concurred with other authors that education, knowledge of HIV, and marriage (women only) are associated with testing for HIV and suggest that couples testing is more prevalent than other authors.

BackgroundHumanitarian agencies working in refugee camp settings require rapid assessment methods to measure the needs of the populations they serve. Due to the high level of dependency of refugees, agencies need to carry out these assessments. Lot Quality Assurance Sampling (LQAS) is a method commonly used in development settings to assess populations living in a project catchment area to identify their greatest needs. LQAS could be well suited to serve the needs of refugee populations, but it has rarely been used in humanitarian settings. We adapted and implemented an LQAS survey design in Batil refugee camp, South Sudan in May 2013 to measure the added value of using it for sub-camp level assessment.MethodsUsing pre-existing divisions within the camp, we divided the Batil catchment area into six contiguous segments, called ‘supervision areas’ (SA). Six teams of two data collectors randomly selected 19 respondents in each SA, who they interviewed to collect information on water, sanitation, hygiene, and diarrhoea prevalence. These findings were aggregated into a stratified random sample of 114 respondents, and the results were analysed to produce a coverage estimate with 95% confidence interval for the camp and to prioritize SAs within the camp.ResultsThe survey provided coverage estimates on WASH indicators as well as evidence that areas of the camp closer to the main road, to clinics and to the market were better served than areas at the periphery of the camp. This assumption did not hold for all services, however, as sanitation services were uniformly high regardless of location. While it was necessary to adapt the standard LQAS protocol used in low-resource communities, the LQAS model proved to be feasible in a refugee camp setting, and program managers found the results useful at both the catchment area and SA level.ConclusionsThis study, one of the few adaptations of LQAS for a camp setting, shows that it is a feasible method for regular monitoring, with the added value of enabling camp managers to identify and advocate for the least served areas within the camp. Feedback on the results from stakeholders was overwhelmingly positive.

BackgroundData collection techniques that routinely provide health system information at the local level are in demand and needed. LQAS is intended for use by local health teams to collect data at the district and sub-district levels. Our question is whether local health staff produce biased results as they are responsible for implementing the programs they also assess.MethodsThis test-retest study replicates on a larger scale an earlier LQAS reliability assessment in Uganda. We conducted in two districts an LQAS survey using 15 local health staff as data collectors. A week later, the data collectors swapped districts, where they acted as disinterested non-local data collectors, repeating the LQAS survey with the same respondents. We analysed the resulting two data sets for agreement using Cohens’ Kappa.ResultsThe average Kappa score for the knowledge indicators was k = 0.43 (SD = 0.16) and for practice indicators k = 0.63 (SD = 0.17). These scores show moderate agreement for knowledge indicators and substantial agreement for practice indicators. Analyses confirm that respondents were more knowledgeable on retest; no evidence of bias was found for practice indicators.ConclusionThe findings of this study are remarkably similar to those produced in the first reliability study. There is no evidence that using local healthcare staff to collect LQAS data biases data collection in an LQAS study. The bias observed in the knowledge indicators was most likely due to a ‘practice effect’, whereby respondents increased their knowledge as a result of completing the first survey; no corresponding effect was seen in the practice indicators.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-016-1655-4) contains supplementary material, which is available to authorized users.

Objectives Nutrition International (NI) sought to standardize and add novel indicators to the multiple coverage surveys conducted each year on maternal, newborn, infant and child nutrition programs to assure quality and timely, gender-related data that meets next-generation monitoring needs. Methods In collaboration with Campbell Collaboration (CC) and University of Toronto (UT), NI developed a comprehensive step-wise survey toolkit with multiple intervention modules using a systematic process for selecting and contextualizing indicators (NI), validating data quality (NI-UT) and piloting gender indicators derived based on statistical modelling results using Demographic and Health Survey gender and nutrition related data (CC-NI). The resulting Nutrition Information Monitoring Systems (NIMS) toolkit now includes ODK formatted questionnaire templates, quality control and assurance checklists and ready-to-use SPSS syntax for data analysis and interpretation purposes. NIMS derives its results from household-level information through the following modules: zinc and Oral Rehydration Salts coverage for diarrhea treatment, maternal-newborn nutrition, weekly iron-folic acid supplementation among adolescent girls, and infant and young child nutrition – each with selected knowledge components and newly-devised gender-related questions to inform NI's nutrition-sensitive programs. Selected modules were implemented in NI's ten intervention countries 2019–20. Results Application of these procedures and quality metrics allowed NI program officers to: 1) systematically assess quality during data collection – identifying and correcting surveyor errors and potential sampling bias in a timely fashion, 2) validate and visually demonstrate data quality to relevant stakeholders, and 3) produce quality assured data within 1–3 weeks, compared to 1–3 months for previous surveys that did not use the NIMS procedures and tools. Conclusions This systematic approach facilitated reporting timely, quality assured nutrition program data to inform how NI interventions and gender-related analyses will identify how NI's programming can be more gender-responsive. Funding Sources CanWaCH, Global Affairs Canada and Nutrition International.