Prevalence, patterns, and determinants of breastfeeding cessation among mothers of children under 24 months in Uganda.

BACKGROUND: Breastfeeding duration is a critical component of infant and child nutrition, providing immediate and long-term benefits to both children and their mothers. This study uses data from the lot quality assurance sampling (LQAS) survey to examine the prevalence, patterns, and determinants of breastfeeding cessation in Uganda. METHODS: This study was a secondary analysis of data collected by the cross-sectional LQAS surveys in 2021 and 2022 covering 77 districts in Uganda. The LQAS survey methodology employs a systematic sampling approach to assess whether predefined quality standards are met within specific subgroups of a population. The study employed spatial analysis, bivariate analysis and logistic regression, both with and without clustering, to explore associations between independent variables and breastfeeding cessation. Unadjusted and adjusted odds ratios with 95% confidence intervals were calculated. Statistical significance was set at 5%. RESULTS: Overall, the study analysed 26,377 records of mothers with children under 24 months old. The mothers' mean age was 27.9 years while that of their children was 11.0 months. While the general breastfeeding cessation rate was 17.7%, cessation was highest (49.7%) among mothers of children 18-23 months. Factors associated with increased odds of breastfeeding cessation included older child's age, older mother's age, using modern family planning, being pregnant and having an unknown pregnancy status. Lower odds of breastfeeding cessation were observed among mothers who; were married, lived in larger households, lived in rural residences, whose children received vitamin A supplementation and among all other regions compared to Kampala. CONCLUSION: One in five mothers cessed breastfeeding before their child reached 2 years, with a significant increase in cessation odds among mothers of older children. These findings underscore the importance of interventions to promote breastfeeding continuation and adequate nutrition for non-breastfed infants, particularly in regions with high cessation rates.

Assessment of knowledge about malaria and LLIN ownership and its use in Bankura, West Bengal, India.

BACKGROUND & OBJECTIVES: Community participation is one of the key factors for implementation and success of a public health programme which depends upon knowledge about that disease. Therefore, understanding the community knowledge about malaria is important for designing sustainable control programmes. This study was conducted to assess the knowledge about malaria, to evaluate long lasting insecticidal nets (LLINs) distribution and their use by LQAS method in endemic areas of Bankura district, West Bengal state, India Methods: It was a community based cross-sectional survey conducted in Bankura during December 2019-March 2020. Structured questionnaire under four categories: socio-demographic variables, knowledge of malaria, owner ship of LLINs and its use were used for the interview. Ownership of LLINs and its use were analysed by LQAS method. Data were analysed by binary logistic regression model and chi-squared test. RESULTS: Out of 456 respondents, 88.59% had good knowledge, 97.37% had good ownership of LLIN and 78.95% used LLINs properly. The knowledge about malaria was significantly associated with education level (p-value<0.0001). Out of 24 lots studied, 3, 2, 4 lots were underperforming with respect to knowledge, ownership of LLIN and its use, respectively. INTERPRETATION & CONCLUSION: The study population had a good knowledge about malaria. In spite of good coverage of LLIN distribution, the use of LLINs was not up to the mark. LQAS analysis showed underperformance in few lots about knowledge, ownership of LLIN and its use. The IEC and BCC activities about LLIN should be done to achieve the impact of this intervention at the community level.

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.

Evaluation of the impact of 2 years of a dosing intervention on canine echinococcosis in the Alay Valley, Kyrgyzstan.

Echinococcosis is a re-emerging zoonotic disease in Kyrgyzstan. In 2012, an echinococcosis control scheme was started that included dosing owned dogs in the Alay Valley, Kyrgyzstan with praziquantel. Control programmes require large investments of money and resources; as such it is important to evaluate how well these are meeting their targets. However, problems associated with echinococcosis control schemes include remoteness and semi-nomadic customs of affected communities, and lack of resources. These same problems apply to control scheme evaluations, and quick and easy assessment tools are highly desirable. Lot quality assurance sampling was used to assess the impact of approximately 2 years of echinococcosis control in the Alay valley. A pre-intervention coproELISA prevalence was established, and a 75% threshold for dosing compliance was set based on previous studies. Ten communities were visited in 2013 and 2014, with 18-21 dogs sampled per community, and questionnaires administered to dog owners. After 21 months of control efforts, 8/10 communities showed evidence of reaching the 75% praziquantel dosing target, although only 3/10 showed evidence of a reduction in coproELISA prevalence. This is understandable, since years of sustained control are required to effectively control echinococcosis, and efforts in the Alay valley should be and are being continued.

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.

Assessing delivery practices of mothers over time and over space in Uganda, 2003-2012.

BACKGROUND: It is well known that safe delivery in a health facility reduces the risks of maternal and infant mortality resulting from perinatal complications. What is less understood are the factors associated with safe delivery practices. We investigate factors influencing health facility delivery practices while adjusting for multiple other factors simultaneously, spatial heterogeneity, and trends over time. METHODS: We fitted a logistic regression model to Lot Quality Assurance Sampling (LQAS) data from Uganda in a framework that considered individual-level covariates, geographical features, and variations over five time points. We accounted for all two-covariate interactions and all three-covariate interactions for which two of the covariates already had a significant interaction, were able to quantify uncertainty in outputs using computationally intensive cluster bootstrap methods, and displayed outputs using a geographical information system. Finally, we investigated what information could be predicted about districts at future time-points, before the next LQAS survey is carried out. To do this, we applied the model to project a confidence interval for the district level coverage of health facility delivery at future time points, by using the lower and upper end values of known demographics to construct a confidence range for the prediction and define priority groups. RESULTS: We show that ease of access, maternal age and education are strongly associated with delivery in a health facility; after accounting for this, there remains a significant trend towards greater uptake over time. We use this model together with known demographics to formulate a nascent early warning system that identifies candidate districts expected to have low prevalence of facility-based delivery in the immediate future. CONCLUSIONS: Our results support the hypothesis that increased development, particularly related to education and access to health facilities, will act to increase facility-based deliveries, a factor associated with reducing perinatal associated mortality. We provide a statistical method for using inexpensive and routinely collected monitoring and evaluation data to answer complex epidemiology and public health questions in a resource-poor setting. We produced a model based on this data that explained the spatial distribution of facility-based delivery in Uganda. Finally, we used this model to make a prediction about the future priority of districts that was validated by monitoring and evaluation data collected in the next year.

Associations with HIV testing in Uganda: an analysis of the Lot Quality Assurance Sampling database 2003-2012.

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.

Can local staff reliably assess their own programs? A confirmatory test-retest study of Lot Quality Assurance Sampling data collectors in Uganda.

BACKGROUND: Data 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. METHODS: This 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. RESULTS: The 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. CONCLUSION: The 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.

Improving malaria treatment and prevention in India by aiding district managers to manage their programmes with local information: a trial assessing the impact of Lot Quality Assurance Sampling on programme outcomes.

OBJECTIVES: This paper reports the first trial of Lot Quality Assurance Sampling (LQAS) assessing associations between access to LQAS data and subsequent improvements in district programming. This trial concerns India's approach to addressing an increase in malaria-attributable deaths by training community health workers to diagnose, treat and prevent malaria, while using LQAS to monitor sub-district performance and make programme improvements. METHODS: The Ministry of Health introduced LQAS into four matched high malaria burden districts (Annual Parasite Incidence >5) (N > 5 million). In each sub-district, we sampled four populations in three 6-monthly surveys: households, children <5 years, people with fever in the last 2 weeks and community health workers. In three districts, trained local staff collected, analysed and used data for programme management; in one control district, non-local staff collected data and did not disseminate results. For eight indicators, we calculated the change in proportion from survey one to three and used a Difference-in-Differences test to compare the relative change between intervention and control districts. RESULTS: Coverage increased from survey one to three for 24 of 32 comparisons. Difference-in-Differences tests revealed that intervention districts exhibited significantly greater change in four of six vertical strategies (insecticide treated bed-nets and indoor residual spraying), one of six treatment-seeking behaviours and four of 12 health worker capacity indicators. The control district displayed greater improvement than two intervention districts for one health worker capacity indicator. One district with poor management did not improve. CONCLUSIONS: In this study, LQAS results appeared to support district managers to increase coverage in underperforming areas, especially for vertical strategies in the presence of diligent managers.

Assessing the quality of care in a new nation: South Sudan's first national health facility assessment.

OBJECTIVES: We adapted a rapid quality of care monitoring method to a fragile state with two aims: to assess the delivery of child health services in South Sudan at the time of independence and to strengthen local capacity to perform regular rapid health facility assessments. METHODS: Using a two-stage lot quality assurance sampling (LQAS) design, we conducted a national cross-sectional survey among 156 randomly selected health facilities in 10 states. In each of these facilities, we obtained information on a range of access, input, process and performance indicators during structured interviews and observations. RESULTS: Quality of care was poor with all states failing to achieve the 80% target for 14 of 19 indicators. For example, only 12% of facilities were classified as acceptable for their adequate utilisation by the population for sick-child consultations, 16% for staffing, 3% for having infection control supplies available and 0% for having all child care guidelines. Health worker performance was categorised as acceptable in only 6% of cases related to sick-child assessments, 38% related to medical treatment for the given diagnosis and 33% related to patient counselling on how to administer the prescribed drugs. Best performance was recorded for availability of in-service training and supervision, for seven and ten states, respectively. CONCLUSIONS: Despite ongoing instability, the Ministry of Health developed capacity to use LQAS for measuring quality of care nationally and state-by-state, which will support efficient and equitable resource allocation. Overall, our data revealed a desperate need for improving the quality of care in all states.

Extending cluster lot quality assurance sampling designs for surveillance programs.

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate.

Evaluating Antiretroviral Therapy Service Delivery Models Through Lot Quality Assurance Sampling in Central Uganda.

Background: This study evaluated the effectiveness and responsiveness of differentiated Human Immunodeficiency Virus (HIV)/Acquired Immuno-Deficiency Syndrome (AIDS) service delivery models (DSDMs) implemented to enhance antiretroviral therapy (ART) access and outcomes for patients while addressing Tuberculosis (TB)-HIV integration, focusing on four of the five DSDMs currently implemented in Uganda. Methodology: A descriptive cross-sectional survey was conducted in eight districts of central Uganda using Lot Quality Assurance Sampling approach from 7th to 23rd March 2023. We randomly sampled 2668 patients who have been on ART for at least 1 year in a Facility-Based Individual Management (FBIM) model or in a non-FBIM DSDM for at least one year. Data were collected through patient interviews and review of records in ART and DSDM registers as well as ART cards. We analyzed the data in proportions, comparing the selected ART outcome and responsiveness indicators between Community Client Led ART Distribution (CCLAD), Community Drugs Distribution Point (CDDP) and Fast-Track Drug Refill (FTDR) DSDMs with the standard care (FBIM) model. The ART outcome variables include patients retained in the 1st line of the ART regimen, patients in World Health Organization clinical stage 1 during the last facility visit, patients who had no CD4 request during the past 12 months, viral load suppression, ART adherence, and patients who reported that they did not experience HIV/AIDS-related symptoms in the past 6 months. The variables on TB care include screening for TB using the intensified case finding form and patients tested positive for TB. Responsiveness variables include the perceived; travel time for ART refill, travel distance for ART refill, convenience and flexibility during ART refill, cost of travel for ART refill, fear of being seen at ART refill point, waiting time before service, adequacy of service time, crowding and risk of infections, social support, ability to address ART treatment challenges, HIV status disclosure and barriers to access. Non-overlap in 95% confidence interval in indicator proportion between non-FBIM DSDM and FBIM means a statistically significant difference in proportion, or otherwise non-significant. Results: Higher proportions of ART patients in the CCLAD and CDDP DSDMs adhered to ART, had suppressed viral load, and a lower TB prevalence than those in FBIM model. Additionally, more CCLAD and CDDP clients reported shorter travel time and distance to access ART than their counterparts in the FBIM model. Compared to FBIM model, higher proportions of those in CCLAD and CDDP also reported flexibility in ART refill scheduling, reduced transport costs, fewer privacy concerns, less HIV/AIDS-related stigma, shorter waiting times, more efficient services, decreased congestion at ART pickup sites, enhanced peer support, improved problem-solving assistance, and increased HIV status disclosure. The FTDR model outperformed FBIM in proportions with fewer requests for CD4 testing, viral load suppression, as well as proportions of clients who reported; shorter travel time, lower transportation cost, decreased privacy concerns, shorter waiting time, and efficient service provision. Compared to both CDDP and FTDR, the FBIM had a higher proportion of clients remain on the first-line ART regimen. Conclusion: Community-based DSDMs show responsiveness to clients' needs without compromising the effectiveness of ART care for patients. Although FTDR also demonstrates high effectiveness and responsiveness for clients on ART, there is potential for further improvement. Planners and implementers of ART programs should consider both demand- and supply-side innovations to sustain the continuation of DSDMs.

Prevalence of and factors associated with zero-dose and under-immunized children in selected areas of Bangladesh: Findings from Lot Quality Assurance Sampling Survey.

BACKGROUND: In the era of Gavi's 5.0 vision of "leaving no one behind with immunization", childhood routine vaccination in missed communities is considered as a priority concern. Despite having a success story at the national level, low uptake of immunization is still persistent in selected pocket areas of Bangladesh. However, prevalence and the associated factors of zero-dose (ZD) and under-immunization (UI) are still unknown at those geo-pockets of Bangladesh. Thus, the study aims to report and identify the factors associated with ZD and UI in selected geographical locations. METHODS: This study used data from a Lot Quality Assurance Sampling (LQAS) survey where 504 households from 18 clusters of four hard to reach (HTR) and one urban slum were included. Caregivers of children aged 4.5 to 23 months were interviewed. Three outcome variables- ZD, UI and ZD/UI were considered and several related attributes were considered as independent variables. Data were analyzed through bivariate analysis, binary logistic regression and dominance analysis. RESULTS: Overall, 32% of the children were either ZD (8%) or UI (26%) in the selected areas. The adjusted odds of ZD/UI for urban slum and haor (wetlands) areas were 5.62 and 3.61 respectively considering coastal areas as reference. However, distance of nearest EPI center, availability of EPI card, age of caregivers, education and occupation of mother and number of earning members in household were influential factors for ZD/UI. According to dominance analysis, availability of EPI card can explain the most of the variation of ZD/UI in this study. CONCLUSION: The study findings highlight the high prevalence ZD/UI in certain geo-pockets of the country. It provided a powerful insight of current situation and associated factors in regards to ZD/UI in the country which will help policy-makers and programme managers in designing programmes to reduce missed communities in Bangladesh.

Unbiased antimicrobial resistance prevalence estimates through population-based surveillance.

BACKGROUND: Current antimicrobial resistance surveillance (AMR) is mainly laboratory based. This approach can have inherent biases given the potential for selective specimen submission for microbiological analysis and for its inability to map antibiotic susceptibility test results to a clinical syndrome. OBJECTIVES: To discuss the need for population-based surveillance of AMR, and highlight the pros and cons of threshold surveys. SOURCES: Studies on methodology for AMR surveillance published in the last 10 years, obtained through a PubMed search on antimicrobial resistance (all fields) and surveillance/method (MeSH term). CONTENT: We discuss the use of threshold surveys to overcome the challenge of sample size in population-bases AMR surveys, which are a suitable approach in both low- and high-resource settings. IMPLICATIONS: Scale up in the use of population-based threshold survey on the prevalence of AMR will provide necessary information to triangulate the data from routinely-reported laboratory-based AMR surveillance at the local, national, and global level.

Coverage of a Population-Based Non-Communicable Disease Screening Program Using Lot Quality Assurance Sampling in Rural North India: A Mixed Methods Study.

AIM: We aimed to estimate the coverage of a population-based Non-communicable Disease (NCD) screening program using lot quality assurance sampling (LQAS) and identify factors affecting its implementation in district Nuh of Haryana, India. METHOD: A mixed-methods study was conducted with an initial LQAS coverage survey, followed by in-depth interviews. Thirty lots (villages or towns) were sampled in the district, and 20 people aged ≥ 30 years were randomly sampled from each lot. Participants were asked about receiving services under the program. Weighted coverage estimates, which is the proportion of people who had received screening services, were estimated. Using a decision value of more than nine negative responses out of 20 persons, all 30 lots were classified as good or poor performing. In-depth interviews of healthcare providers of good performing lots and district-level health officials were conducted, and factors affecting program implementation were identified. FINDINGS: Six hundred participants were interviewed (mean age of 44.8 years, 57.2% women). The proportion of people who reported having undergone screening for diabetes or hypertension was 2.1%, and all lots performed poorly based on decision value. Key factors affecting the program were leadership, prioritization of NCD activities, ensuring human resource and material requirements, regular incentives, qualities of workers, and community engagement. CONCLUSION: The screening coverage under the population-based NCD screening program was low in district Nuh, Haryana. This needs to be improved by addressing the identified health system and community-related factors.

Assessment of Squalor in Migrant Colonies of Thiruvalla Province of Kerala, India using Rapid Survey Technique.

BACKGROUND: Domestic squalor refers to households that are extremely cluttered, in a filthy condition, and where the accumulation of items such as personal possessions, rubbish, excrement and decomposing food creates an environment that jeopardizes the health and wellbeing of the occupant(s). In India, an estimated 258 million are migrants. They are more likely to live in squalor due to inferior socio-economic status and no permanent residence. This poses a threat to the health of the migrants and the neighbors. OBJECTIVE: To assess the squalor and morbidity pattern among the migrants of Migrant colonies in Thiruvalla using Rapid survey technique. METHODOLOGY: The state of squalor in migrant colonies was assessed by Lot Quality Assurance Sampling Methodology using the Environment Cleanliness and Clutter Scale (ECCS). The sample size for each lot/colony was '14' dwellings according to LQAS table. The details were collected from 14 inhabitants of different dwellings of the same colony. The inhabitants were selected randomly and were excluded if he belonged to the same dwelling. Fifteen colonies were randomly selected to achieve the sample size of 210 (15*14). The study was done in Tiruvalla municipality. RESULTS AND CONCLUSION: Only two colonies (n = 15) were squalor free. Majority of the dwellings (n = 210) were having an ECCS score between 13 and 15. Common ailments affecting migrants include Common cold, Skin disorders, and dental caries and gastritis. Squalor was found in most of the migrant colonies as they are living in inhuman conditions.

Lot quality assurance sampling: Information provided to female users of contraceptive methods regarding side effects.

Women need to receive accurate information on the proper use of contraceptive methods (CM). The objective of our analysis was to evaluate the quality of CM counseling in health institutions of the public sector using the Lot Quality Assurance Sampling (LQAS) technique. We specifically analyzed whether health-service providers informed CM users of all the side effects they might experience, as specified under the Mexican health-care regulations. Our results demonstrated that, among the four CM analyzed -the intrauterine device, hormonal injection, condom and subdermal implant- only the users of the subdermal implant received complete information on side effects. Our findings thus indicate that the quality of family planning services in the institutions analyzed is deficient. We recommend that service providers be regularly trained in order to improve their performance and that LQAS methodology be adopted as an effective means of regularly monitoring the quality of health services in Mexico.

How well do mothers recall their own and their infants' perinatal events? A two-district study using cross-sectional stratified random sampling in Bihar, India.

OBJECTIVE: Global monitoring of maternal, newborn and child health (MNCH) programmes use self-reported data subject to recall error which may lead to incorrect decisions for improving health services and wasted resources. To minimise this risk, samples of mothers of infants aged 0-2 and 3-5 months are sometimes used. We test whether a single sample of mothers of infants aged 0-5 months provides the same information. DESIGN: An annual MNCH household survey in two districts of Bihar, India (n=6 million). PARTICIPANTS: Independent samples (n=475 each) of mothers of infants aged 0-5, 0-2 and 3-5 months. OUTCOME MEASURES: Main analyses compare responses from the samples of infants aged 0-5 and 0-2 months with Mantel-Haenszel-Cochran statistics using 51 indicators in two districts. RESULTS: No measurable differences are detected in 79.4% (81/102) comparisons; 20.6% (21/102) display differences for the main comparison. Subanalyses produce similar results. A difference detected for exclusive breast feeding is due to premature complementary feeding by older infants. Measurable differences are detected in 33% (8/24) of the indicators on Front Line Worker (FLW) support, 26.9% (7/26) of indicators of birth preparedness and place of birth and attendant, and 9.5% (4/42) of the indicators on neonatal and antenatal care. CONCLUSIONS: Differences in FLW visits and compliance with their advice may be due to seasonal effects: mothers of older infants aged 3-5 months were pregnant during the dry season; mothers of infants aged 0-2 months were pregnant during the monsoons, making transportation difficult. Useful coverage estimates can be obtained by sampling mothers with infants aged 0-5 months as with two samples suggesting that mothers of young infants recall their own perinatal events and those of their children. For some indicators (eg, exclusive breast feeding), it may be necessary to adjust targets. Excessive stratification wastes resources, does not improve the quality of information and increases the burden placed on data collectors and communities which can increase non-sampling error.

Review of Lot Quality Assurance Sampling, Methodology and its Application in Public Health.

Rapid collection of data is of utmost importance in monitoring and evaluation of activities of public health importance. Among others techniques, 30 by 7 cluster sampling and Lot quality assurance sampling(LQAS) methods have been described in literature for this purpose. However, LQAS is often sparingly used in most settings, undermining its importance as a effective epidemiological tool in public health practice. To some extent LQAS is inadequately understood and even less emphasized method, especially in the postgraduate teaching and training. In this paper we aim to explain the use, method and application of LQAS in public health settings as well as discuss common pitfalls to avoid while planning and drawing inferences based on data collected through LQAS.

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.