Mixed Methods Lot Quality Assurance Sampling: A novel, rapid methodology to inform equity focused maternal health programming in rural Rajasthan, India.

India has experienced a significant increase in facility-based delivery (FBD) coverage and reduction in maternal mortality. Nevertheless, India continues to have high levels of maternal health inequity. Improving equity requires data collection methods that can produce a better contextual understanding of how vulnerable populations access and interact with the health care system at a local level. While large population-level surveys are valuable, they are resource intensive and often lack the contextual specificity and timeliness to be useful for local health programming. Qualitative methods can be resource intensive and may lack generalizability. We describe an innovative mixed-methods application of Large Country-Lot Quality Assurance Sampling (LC-LQAS) that provides local coverage data and qualitative insights for both FBD and antenatal care (ANC) in a low-cost and timely manner that is useful for health care providers working in specific contexts. LC-LQAS is a version of LQAS that combines LQAS for local level classification with multistage cluster sampling to obtain precise regional or national coverage estimates. We integrated qualitative questions to uncover mothers' experiences accessing maternal health care in the rural district of Sri Ganganagar, Rajasthan, India. We interviewed 313 recently delivered, low-income women in 18 subdistricts. All respondents participated in both qualitative and quantitative components. All subdistricts were classified as having high FBD coverage with the upper threshold set at 85%, suggesting that improved coverage has extended to vulnerable women. However, only two subdistricts were classified as high ANC coverage with the upper threshold set at 40%. Qualitative data revealed a severe lack of agency among respondents and that household norms of care seeking influenced uptake of ANC and FBD. We additionally report on implementation outcomes (acceptability, feasibility, appropriateness, effectiveness, fidelity, and cost) and how study results informed the programs of a local health non-profit.

Comparison of different lots of endotoxin and evaluation of in vivo potency over time in the experimental human endotoxemia model.

The experimental human endotoxemia model is used to study the systemic inflammatory response in vivo. The previously used lot of endotoxin, which was used for over a decade, is no longer approved for human use and a new Good Manufacturing Practices-grade batch has become available. We compared the inflammatory response induced by either bolus or continuous administration of either the previously used lot #1188844 or new lots of endotoxin (#94332B1 and #94332B4). Compared with lot #1188844, bolus administration of lot #94332B1 induced a more pronounced systemic inflammatory response including higher plasma levels of pro-inflammatory cytokines and more pronounced clinical signs of inflammation. In contrast, continuous infusion of lot #94332B4 resulted in a slightly less pronounced inflammatory response compared with lot #1188844. Furthermore, we evaluated whether lot #1188844 displayed in vivo potency loss by reviewing inflammatory parameters obtained from 17 endotoxemia studies performed in our centre between 2007 and 2016. Despite inter-study variability in endotoxemia-induced effects on temperature, heart rate, symptoms, and leukocyte counts, the magnitude of these effects did not decrease over time. In conclusion, although all lots of endotoxin induce a pronounced inflammatory response, the magnitude differs between lots. We observed no potency loss of endotoxin over time.

Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling.

Global surveillance of antimicrobial resistance (AMR) is a key component of the 68th World Health Assembly Global Action Plan on AMR. Laboratory-based surveillance is inherently biased and lacks local relevance due to aggregation of data. We assessed the feasibility, sensitivity, and affordability of a population-based AMR survey using lot quality assurance sampling (LQAS), which classifies a population as having a high or low prevalence of AMR based on a priori defined criteria. Three studies were carried out in Medan and Bandung, Indonesia, between April 2014 and June 2017. LQAS classifications for 15 antibiotics were compared with AMR estimates from a conventional population-based survey, with an assessment of the cost of a single LQAS classification using microcosting methodology, among patients suspected of urinary tract infection at 11 sites in Indonesia. The sensitivity of LQAS was above 98%. The approach detected local variation in the prevalence of AMR across sites. Time to reach LQAS results ranged from 47 to 138 days. The average cost of an LQAS classification in a single facility was US$466. The findings indicate that LQAS-based AMR survey is a feasible, sensitive, and affordable strategy for population-based AMR surveys, providing essential data to inform local empirical treatment guidelines and antimicrobial stewardship efforts.

Optimal design of multiple-objective Lot Quality Assurance Sampling (LQAS) plans.

Lot Quality Assurance Sampling (LQAS) plans are widely used for health monitoring purposes. We propose a systematic approach to design multiple-objective LQAS plans that meet user-specified type 1 and 2 error rates and targets for selected diagnostic accuracy metrics. These metrics may include sensitivity, specificity, positive predictive value, and negative predictive value in high or low anticipated prevalence rate populations. We use Mixed Integer Nonlinear Programming (MINLP) tools to implement our design methodology. Our approach is flexible in that it can directly generate classic LQAS plans that control error rates only and find optimal LQAS plans that meet multiple objectives in terms of diagnostic metrics. We give examples, compare results with the classic LQAS and provide an application using a malaria outcome indicator survey in Mozambique.

Using lot quality assurance sampling to assess access to water, sanitation and hygiene services in a refugee camp setting in South Sudan: a feasibility study.

BACKGROUND: Humanitarian 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. METHODS: Using 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. RESULTS: The 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. CONCLUSIONS: This 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.

The use of a lot quality assurance sampling methodology to assess and manage primary health interventions in conflict-affected West Darfur, Sudan.

BACKGROUND: Organizations working in conflict-affected areas have a need to monitor and evaluate their programs, however this is often difficult due to the logistical challenges of conflict areas. Lot quality assurance sampling may be a suitable method of assessing programs in these situations. METHODS: We conducted a secondary data analysis of information collected during Medair's routine program management functions. Medair's service area in West Darfur, Sudan was divided into seven supervisory areas. Using the available population information, a sampling frame was developed and interviews were conducted from randomly selected caretakers of children in each supervisory area every six months over 19 months. A survey instrument with questions related to key indicators for immunizations and maternal, newborn, and child health was used for the interviews. Based on Medair's goals for each indicator, decision rules were calculated for the indicators; these decision rules determined which supervisory areas and indicators performed adequately in each assessment period. Pearson's chi-squared tests, adjusted for the survey design using STATA "svy: tab" commands, were used to detect overall differences in coverage in this analysis. RESULTS: The coverage of tetanus toxoid vaccination among pregnant women increased from 47.2 to 69.7 % (p value = 0.046), and births attended by a skilled health professional increased from 35.7 to 52.7 % (p value = 0.025) from the first to last assessment periods. Measles vaccinations declined from 72.0 to 54.1 % (p value = 0.046). The estimated coverage for the proportion of women receiving a postpartum dose of vitamin A (54.7 to 61.3 %, p value = 0.44); pregnant women receiving a clean delivery kit (54.6 to 47.1 %, p value = 0.49); and pentavalent vaccinations (49.7 to 42.1 %, p value = 0.28) did not significantly change. CONCLUSIONS: Lot quality assurance sampling was a feasible method for Medair staff to evaluate and optimize primary health programs in a conflict-affected area. Medair managers were able to collect, analyze, and disseminate data to staff alongside the routine work of the organization. These results suggest LQAS may be used in other complex humanitarian emergencies in which there are logistical challenges and limited resources.

Empowering districts to target priorities for improving child health service in Uganda using change management and rapid assessment methods.

BACKGROUND: Local health system managers in low- and middle-income countries have the responsibility to set health priorities and allocate resources accordingly. Although tools exist to aid this process, they are not widely applied for various reasons including non-availability, poor knowledge of the tools, and poor adaptability into the local context. In Uganda, delivery of basic services is devolved to the District Local Governments through the District Health Teams (DHTs). The Community and District Empowerment for Scale-up (CODES) project aims to provide a set of management tools that aid contextualised priority setting, fund allocation, and problem-solving in a systematic way to improve effective coverage and quality of child survival interventions. DESIGN: Although the various tools have previously been used at the national level, the project aims to combine them in an integral way for implementation at the district level. These tools include Lot Quality Assurance Sampling (LQAS) surveys to generate local evidence, Bottleneck analysis and Causal analysis as analytical tools, Continuous Quality Improvement, and Community Dialogues based on Citizen Report Cards and U reports. The tools enable identification of gaps, prioritisation of possible solutions, and allocation of resources accordingly. This paper presents some of the tools used by the project in five districts in Uganda during the proof-of-concept phase of the project. RESULTS: All five districts were trained and participated in LQAS surveys and readily adopted the tools for priority setting and resource allocation. All districts developed health operational work plans, which were based on the evidence and each of the districts implemented more than three of the priority activities which were included in their work plans. CONCLUSIONS: In the five districts, the CODES project demonstrated that DHTs can adopt and integrate these tools in the planning process by systematically identifying gaps and setting priority interventions for child survival.

Assessment on the ownership and use of mosquito nets in Mozambique.

OBJECTIVE: To assess the ownership and use of mosquito nets in 2014, in Mozambique. METHODS: This observational and cross-sectional study assessed, in February and March 2015, 69 districts (nine of 11 provinces of Mozambique) that have benefited from the mass distribution of mosquito nets. The Lot Quality Assurance Sampling methodology was used. Each locality was denominated supervision area. The Lot Quality Assurance Sampling opts for a minimum of 19 households (in this case, we decided for a minimum of 100 households per district) from each supervision area to assess an indicator (in this case, two indicators were assessed: ownership and use of mosquito nets). Two questions guided the research: a) received a mosquito net; b) used a mosquito net the night before. RESULTS: A total of 6,725 households were assessed. Eighty three percent of them had received mosquito nets in the campaign. Of the 6,232 respondents, 82.0% said they used mosquito nets the night before. The districts of the provinces with low coverage of ownership and use were Tete (69.5% and 60.0%, respectively), Zambezia (79.0% and 60.0%, respectively), and Gaza (81.6% and 70.7%, respectively). The largest coverage of ownership and use were observed in the districts of Nampula (96.7% and 93.8%, respectively) and Niassa (86.0% and 85.4% respectively). CONCLUSIONS: In the districts assessed, the progression of ownership and use of mosquito nets is satisfactory. Nampula and Niassa are the only provinces where ownership and use are at desired levels. OBJECTIVO: Avaliar a posse e o uso das redes mosquiteiras no ano de 2014 em Moçambique. MÉTODOS: Este estudo observacional transversal avaliou, em fevereiro e março de 2015, 68 distritos (nove das 11 províncias de Moçambique) que se beneficiaram da distribuição de redes em massa. Usou-se a metodologia Lot Quality Assurance Sampling. Cada localidade foi designada de área de supervisão. O Lot Quality Assurance Sampling opta por um mínimo de 19 agregados familiares (neste caso decidiu-se um mínimo de 100 agregados familiares por distrito) de cada área de supervisão, a fim de avaliar um indicador (neste caso dois indicadores foram avaliados: posse e uso de redes mosquiteiras). Duas perguntas nortearam a pesquisa: a) recebeu rede; b) usou rede na noite anterior. RESULTADOS: Foram avaliados 6.725 agregados familiares . Desses, 83,0% tinham recebido redes na campanha. Dos 6.232 inqueridos, 82,0% disseram que usaram na noite anterior. As províncias com distritos com menores coberturas de posse e uso foram Tete (69,5% e 60,0%, respectivamente), Zambézia (79,0% e 60,0%, respectivamente) e Gaza (81,6% e 70,7%, respectivamente). As maiores coberturas de posse e uso foram observadas nos distritos de Nampula (96,7% e 93,8%, respectivamente) e Niassa (86,0% e 85,4%, respectivamente). CONCLUSÕES: Nos distritos avaliados, a progressão para a posse e uso de redes mosquiteiras é satisfatória. Nampula e Niassa são as únicas províncias onde a posse e o uso estão em níveis desejados.

Assessment on the ownership and use of mosquito nets in Mozambique / Avaliação sobre a posse e uso de redes mosquiteiras em Moçambique

ABSTRACT OBJECTIVE To assess the ownership and use of mosquito nets in 2014, in Mozambique. METHODS This observational and cross-sectional study assessed, in February and March 2015, 69 districts (nine of 11 provinces of Mozambique) that have benefited from the mass distribution of mosquito nets. The Lot Quality Assurance Sampling methodology was used. Each locality was denominated supervision area. The Lot Quality Assurance Sampling opts for a minimum of 19 households (in this case, we decided for a minimum of 100 households per district) from each supervision area to assess an indicator (in this case, two indicators were assessed: ownership and use of mosquito nets). Two questions guided the research: a) received a mosquito net; b) used a mosquito net the night before. RESULTS A total of 6,725 households were assessed. Eighty three percent of them had received mosquito nets in the campaign. Of the 6,232 respondents, 82.0% said they used mosquito nets the night before. The districts of the provinces with low coverage of ownership and use were Tete (69.5% and 60.0%, respectively), Zambezia (79.0% and 60.0%, respectively), and Gaza (81.6% and 70.7%, respectively). The largest coverage of ownership and use were observed in the districts of Nampula (96.7% and 93.8%, respectively) and Niassa (86.0% and 85.4% respectively). CONCLUSIONS In the districts assessed, the progression of ownership and use of mosquito nets is satisfactory. Nampula and Niassa are the only provinces where ownership and use are at desired levels.

RESUMO OBJECTIVO Avaliar a posse e o uso das redes mosquiteiras no ano de 2014 em Moçambique. MÉTODOS Este estudo observacional transversal avaliou, em fevereiro e março de 2015, 68 distritos (nove das 11 províncias de Moçambique) que se beneficiaram da distribuição de redes em massa. Usou-se a metodologia Lot Quality Assurance Sampling. Cada localidade foi designada de área de supervisão. O Lot Quality Assurance Sampling opta por um mínimo de 19 agregados familiares (neste caso decidiu-se um mínimo de 100 agregados familiares por distrito) de cada área de supervisão, a fim de avaliar um indicador (neste caso dois indicadores foram avaliados: posse e uso de redes mosquiteiras). Duas perguntas nortearam a pesquisa: a) recebeu rede; b) usou rede na noite anterior. RESULTADOS Foram avaliados 6.725 agregados familiares . Desses, 83,0% tinham recebido redes na campanha. Dos 6.232 inqueridos, 82,0% disseram que usaram na noite anterior. As províncias com distritos com menores coberturas de posse e uso foram Tete (69,5% e 60,0%, respectivamente), Zambézia (79,0% e 60,0%, respectivamente) e Gaza (81,6% e 70,7%, respectivamente). As maiores coberturas de posse e uso foram observadas nos distritos de Nampula (96,7% e 93,8%, respectivamente) e Niassa (86,0% e 85,4%, respectivamente). CONCLUSÕES Nos distritos avaliados, a progressão para a posse e uso de redes mosquiteiras é satisfatória. Nampula e Niassa são as únicas províncias onde a posse e o uso estão em níveis desejados.

Monitoring maternal, newborn, and child health interventions using lot quality assurance sampling in Sokoto State of northern Nigeria.

BACKGROUND: Maternal mortality ratio and infant mortality rate are as high as 1,576 per 100,000 live births and 78 per 1,000 live births, respectively, in Nigeria's northwestern region, where Sokoto State is located. Using applicable monitoring indicators for tracking progress in the UN/WHO framework on continuum of maternal, newborn, and child health care, this study evaluated the progress of Sokoto toward achieving the Millennium Development Goals (MDGs) 4 and 5 by December 2015. The changes in outcomes in 2012-2013 associated with maternal and child health interventions were assessed. DESIGN: We used baseline and follow-up lot quality assurance sampling (LQAS) data obtained in 2012 and 2013, respectively. In each of the surveys, data were obtained from 437 households sampled from 19 LQAS locations in each of the 23 local government areas (LGAs). The composite state-level coverage estimates of the respective indicators were aggregated from estimated LGA coverage estimates. RESULTS: None of the nine indicators associated with the continuum of maternal, neonatal, and child care satisfied the recommended 90% coverage target for achieving MDGs 4 and 5. Similarly, the average state coverage estimates were lower than national coverage estimates. Marginal improvements in coverage were obtained in the demand for family planning satisfied, antenatal care visits, postnatal care for mothers, and exclusive breast-feeding. Antibiotic treatment for acute pneumonia increased significantly by 12.8 percentage points. The majority of the LGAs were classifiable as low-performing, high-priority areas for intensified program intervention. CONCLUSIONS: Despite the limited time left in the countdown to December 2015, Sokoto State, Nigeria, is not on track to achieving the MDG 90% coverage of indicators tied to the continuum of maternal and child care, to reduce maternal and childhood mortality by a third by 2015. Targeted health system investments at the primary care level remain a priority, for intensive program scale-up to accelerate impact.

Finding the gap: revealing local disparities in coverage of maternal, newborn and child health services in South Sudan using lot quality assurance sampling.

OBJECTIVES: We adapted a rapid monitoring method to South Sudan, a new nation with one of the world's highest maternal and child mortality rates, aiming to assess coverage of maternal, neonatal and child health (MNCH) services at the time of independence, and introducing a monitoring and evaluation system (M&E) for equity-sensitive tracking of progress related to Millennium Development Goals (MDG) 4 and 5 at national, state and county levels to detect local variability. METHODS: We conducted a national cross-sectional household survey among women from six client populations in all, but six of South Sudan's 79 counties. We used lot quality assurance sampling (LQAS) to measure coverage with diverse MNCH indicators to obtain information for national-, state- and county-level health system management decision-making. RESULTS: National coverage of MNCH services was low for all maternal and neonatal care, child immunisation, and child care indicators. However, results varied across states and counties. Central Equatoria State (CES), where the capital is located, showed the highest coverage for most indicators (e.g. ≥4 antenatal care visits range: 4.5% in Jonglei to 40.1% in CES). Urban counties often outperformed rural ones. CONCLUSIONS: This adaptation of LQAS to South Sudan demonstrates how it can be used in the future as an M&E system to track progress of MDGs at national, state and county levels to detect local disparities. Overall, our data reveal a desperate need for improving MNCH service coverage in all states.

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

OBJECTIVES: Two 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. METHODS: We 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. RESULTS: The 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, which are clinically (or managerially) not significant; 5 had differences >0.10 and <0.20 (mean = 0.137, SD = 0.031) and four differences were >0.20 (mean = 0.261, SD = 0.083). CONCLUSION: There 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.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Cluster lot quality assurance sampling: effect of increasing the number of clusters on classification precision and operational feasibility.

BACKGROUND: To assess the quality of supplementary immunization activities (SIAs), the Global Polio Eradication Initiative (GPEI) has used cluster lot quality assurance sampling (C-LQAS) methods since 2009. However, since the inception of C-LQAS, questions have been raised about the optimal balance between operational feasibility and precision of classification of lots to identify areas with low SIA quality that require corrective programmatic action. METHODS: To determine if an increased precision in classification would result in differential programmatic decision making, we conducted a pilot evaluation in 4 local government areas (LGAs) in Nigeria with an expanded LQAS sample size of 16 clusters (instead of the standard 6 clusters) of 10 subjects each. RESULTS: The results showed greater heterogeneity between clusters than the assumed standard deviation of 10%, ranging from 12% to 23%. Comparing the distribution of 4-outcome classifications obtained from all possible combinations of 6-cluster subsamples to the observed classification of the 16-cluster sample, we obtained an exact match in classification in 56% to 85% of instances. CONCLUSIONS: We concluded that the 6-cluster C-LQAS provides acceptable classification precision for programmatic action. Considering the greater resources required to implement an expanded C-LQAS, the improvement in precision was deemed insufficient to warrant the effort.

Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.

OBJECTIVES: To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (LQAS) is ignored, to present unbiased estimators, to consider the impact of cluster sampling by simulation and to apply our method to published polio immunization data from Nigeria. METHODS: We present estimators of coverage when using two kinds of curtailed LQAS strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field-tested LQAS designs for assessing polio vaccination coverage, with samples of size 60 and decision rules of 9, 21 and 33, and compare them to biased maximum likelihood estimators. Lastly, we present estimates of polio vaccination coverage from previously published data in 20 local government authorities (LGAs) from five Nigerian states. RESULTS: Simulations illustrate substantial bias if one ignores the curtailed sampling design. Proposed estimators show no bias. Clustering does not affect the bias of these estimators. Across simulations, standard errors show signs of inflation as clustering increases. Neither sampling strategy nor LQAS design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed LQAS strategies considerably reduces the sample size required to make a decision. Curtailed LQAS designs further reduce the sample size when coverage is high. CONCLUSIONS: Results presented dispel the misconception that curtailed LQAS data are unsuitable for estimation. These findings augment the utility of LQAS as a tool for monitoring vaccination efforts by demonstrating that unbiased estimation using curtailed designs is not only possible but these designs also reduce the sample size.

Monitoring health interventions--who's afraid of LQAS?

Lot quality assurance sampling (LQAS) is used to evaluate health services. Subunits of a population (lots) are accepted or rejected according to the number of failures in a random sample (N) of a given lot. If failures are greater than decision value (d), we reject the lot and recommend corrective actions in the lot (i.e. intervention area); if they are equal to or less than d, we accept it. We used LQAS to monitor coverage during the last 3 days of a meningitis vaccination campaign in Niger. We selected one health area (lot) per day reporting the lowest administrative coverage in the previous 2 days. In the sampling plan we considered: N to be small enough to allow us to evaluate one lot per day, deciding to sample 16 individuals from the selected villages of each health area, using probability proportionate to population size; thresholds and d to vary according to administrative coverage reported; α ≤5% (meaning that, if we would have conducted the survey 100 times, we would have accepted the lot up to five times when real coverage was at an unacceptable level) and ß ≤20% (meaning that we would have rejected the lot up to 20 times, when real coverage was equal or above the satisfactory level). We classified all three lots as with the acceptable coverage. LQAS appeared to be a rapid, simple, and statistically sound method for in-process coverage assessment. We encourage colleagues in the field to consider using LQAS in complement with other monitoring techniques such as house-to-house monitoring.

Public awareness of and support for smoke-free legislation in Turkey: a national survey using the lot quality sampling technique.

Six months after new legislation in Turkey banning smoking in all public places, a national survey was carried out to assess its implementation. This paper summarizes the main findings on the public's awareness of and support for the new law. In a household interview survey of 32 972 adults representative of the Turkish adult population, a high proportion of both non-smokers and current smokers (91.4% and 67.2% respectively) strongly supported the new law. Knowledge about the health hazards of passive smoking and support for the law, however, were relatively lower among smokers than non-smokers. After controlling for smoking status, people with better knowledge about passive smoking were over 5 times more likely to support the new law. Tobacco control activities should be tailored to local needs, with afocus on increasing awareness about the health hazards of passive smoking. The study also demonstrated application of the lot quality sampling technique (LQT) for monitoring tobacco control activities in a national survey.

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.

Multidrug resistance among new tuberculosis cases: detecting local variation through lot quality-assurance sampling.

BACKGROUND: Current methodology for multidrug-resistant tuberculosis (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. METHODS: We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored 3 classification systems- two-way static, three-way static, and three-way truncated sequential sampling-at 2 sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. RESULTS: The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. CONCLUSIONS: Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired.