Sociodemographic and health-related factors associated with exclusive breastfeeding in 77 districts of Uganda.

BACKGROUND: Uganda surpasses many African nations and the global average in exclusive breastfeeding (EBF) rates. Yet, malnutrition is a critical issue, with stunting impacting roughly 29% of children under 5 years. Enhancing EBF could mitigate such nutritional challenges. This study focused on determining the current EBF prevalence and identifying associated factors across 77 surveyed districts. METHODS: Pooled data from the Lot Quality Assurance Sampling (LQAS) surveys conducted in 77 districts in Uganda during 2021 and 2022 were analyzed. The analysis involved 7,210 mothers of children under 6 months, EBF was considered as the proportion of infants who received breast milk only in the 24 hours before the survey. A mother practicing EBF was (1) currently breastfeeding (2) had not started giving foods other than breastmilk (3) had not given any other probed liquids or (4) semi-solid foods the previous day or night. Multivariable logistic regression was used to identify factors associated with EBF, presenting adjusted odds ratios (aOR) with corresponding 95% confidence intervals at a 5% significance level. RESULTS: The prevalence of EBF was 62.3%. In the adjusted analysis, EBF was more common among older mothers 20-24 years, 25-29 years and 30 + years (aOR 1.4; 95% CI 1.2,1.6), (aOR 1.4; 95% CI 1.1, 1.6) and (aOR 1.3; 95% CI 1.1, 1.5) respectively compared to teenage mothers. Also, EBF was more likely among mothers who lived in rural areas compared to urban areas (aOR 1.1; 95% CI 1.0, 1.3) and those who attended antenatal care (ANC) (aOR 2.2; 95% CI 1.5, 3.1). On the contrary, EBF was less common for children aged 3-5 months compared to younger (aOR 0.5; 95% CI 0.5, 0.6) and children who had received Vitamin A supplementation (aOR 0.7; 95% 0.6, 0.8). CONCLUSION: The study suggests that most districts in Uganda might not have made significant strides in improving EBF rates over the last twenty years, pointing to possible ongoing hurdles that need urgent attention. Particularly, there's a pressing need to focus on teenage mothers. Maintaining and strengthening programs that advocate EBF, such as ANC, is crucial to bridge the gaps and bring about more equitable rates among different groups.

Caregiver acceptance of malaria vaccination for children under 5 years of age and associated factors: cross-sectional household survey, Guinea and Sierra Leone, 2022.

BACKGROUND: Malaria is a leading cause of death and reduced life span in Guinea and Sierra Leone, where plans for rolling out the malaria vaccine for children are being made. There is little evidence about caregiver acceptance rates to guide roll-out policies. To inform future vaccine implementation planning, this analysis aimed to assess potential malaria vaccine acceptance by caregivers and identify factors associated with acceptance in Guinea and Sierra Leone. METHODS: A cross-sectional household survey using lot quality assurance sampling was conducted in three regions per country between May 2022 and August 2022. The first survey respondent in each household provided sociodemographic information. A household member responsible for childcare shared their likelihood of accepting a malaria vaccine for their children under 5 years and details about children's health. The prevalence of caregiver vaccine acceptance was calculated and associated factors were explored using multivariable logistic regression modelling calculating adjusted odds ratios (aOR) with 95% confidence intervals (CI). RESULTS: Caregivers in 76% of 702 sampled households in Guinea and 81% of 575 households in Sierra Leone were accepting of a potential vaccine for their children. In both countries, acceptance was lower in remote areas than in urban areas (Guinea: aOR 0.22 [95%CI 0.09-0.50], Sierra Leone: 0.17 [0.06-0.47]). In Guinea, acceptance was lower among caregivers living in the richest households compared to the poorest households (0.10 [0.04-0.24]), among those whose children were tested for malaria when febrile (0.54 [0.34-0.85]) and in households adopting more preventative measures against malaria (0.39 [0.25-0.62]). Better knowledge of the cause of malaria infection was associated with increased acceptance (3.46 [1.01-11.87]). In Sierra Leone, vaccine acceptance was higher among caregivers living in households where the first respondent had higher levels of education as compared to lower levels (2.32 [1.05-5.11]). CONCLUSION: In both countries, malaria vaccine acceptance seems promising for future vaccine roll-out programmes. Policy makers might consider regional differences, sociodemographic factors, and levels of knowledge about malaria for optimization of implementation strategies. Raising awareness about the benefits of comprehensive malaria control efforts, including vaccination and other preventive measures, requires attention in upcoming campaigns.

Level of minimum acceptable diet and its associated factors among children aged 12-23 months in Ugandan districts.

Uganda has made notable progress in improving child nutrition indicators, albeit not fast enough to meet global targets. Navigating the landscape of child nutrition in Uganda demands attention, particularly in light of the necessity for a minimum acceptable diet (MAD) for children aged 12-23 months. While the focus on local nutritional planning is crucial, the absence of routine-specific nutritional status data creates a significant information gap. To bridge this void, this study used datasets from the 2021 Lot Quality Assurance Sampling (LQAS) survey. Data were analysed using multilevel mixed-effects logistic regression (clustering districts based on regional boundaries) at a 5% statistical significance level using STATA version 17. Of the 7,111 children surveyed, 3,256 (49.20%) received the minimum meal frequency, 695 (9.80%) received the minimum dietary diversity, and only 380 (5.34%) received the MAD. There was a notable variation in the proportion of children that received the MAD across regions and districts. Children living in urban areas, children whose mothers had a higher education, and children whose mothers had a diverse diet were more likely to receive the MAD. Children were less likely to receive the MAD if they lived in a household that did not receive a health worker visit within the year. These findings suggest a need to prioritize initiatives aimed at increasing dietary diversity among children in Uganda. This could be done through a variety of approaches, such as leveraging the use of home gardens to boost nutrition through diverse crop cultivation, demonstration gardens, and offering nutrition counselling through village health teams.

A general framework to support cost-efficient survey design choices for the control of soil-transmitted helminths when deploying Kato-Katz thick smear.

BACKGROUND: To monitor and evaluate soil-transmitted helminth (STH) control programs, the World Health Organization (WHO) recommends screening stools from 250 children, deploying Kato-Katz thick smear (KK). However, it remains unclear whether these recommendations are sufficient to make adequate decisions about stopping preventive chemotherapy (PC) (prevalence of infection <2%) or declaring elimination of STHs as a public health problem (prevalence of moderate-to-heavy intensity (MHI) infections <2%). METHODOLOGY: We developed a simulation framework to determine the effectiveness and cost of survey designs for decision-making in STH control programs, capturing the operational resources to perform surveys, the variation in egg counts across STH species, across schools, between and within individuals, and between repeated smears. Using this framework and a lot quality assurance sampling approach, we determined the most cost-efficient survey designs (number of schools, subjects, stool samples per subject, and smears per stool sample) for decision-making. PRINCIPAL FINDINGS: For all species, employing duplicate KK (sampling 4 to 6 schools and 64 to 70 subjects per school) was the most cost-efficient survey design to assess whether prevalence of any infection intensity was above or under 2%. For prevalence of MHI infections, single KK was the most cost-efficient (sampling 11 to 25 schools and 52 to 84 children per school). CONCLUSIONS/SIGNIFICANCE: KK is valuable for monitoring and evaluation of STH control programs, though we recommend deploying a duplicate KK on a single stool sample to stop PC, and a single KK to declare the elimination of STHs as a public health problem.

Optimal quantification of residence time distribution profiles from a quality assurance perspective.

Residence time distribution (RTD) has been widely applied across various fields of chemical engineering, including pharmaceutical manufacturing, for applications such as material traceability, quality assurance, system health monitoring, and fault detection. Determination of a representative RTD, in principle, requires an accurate process analytical technology (PAT) procedure capturing the entire range of tracer concentrations from zero to maximum. Such a wide concentration range creates at least two problems: i) decreased accuracy of the model across the entire range of concentrations, relating to limit of quantification, and ii) ambiguity associated with the detection of the tracer for low concentration levels, relating to limit of detection (LOD). These problems affect not only the RTD profile itself, but also RTD-based applications, which can potentially lead to erroneous conclusions. This article seeks to minimize the impact of these problems by understanding the relative importance of different features of RTD on the detection of out-of-specification (OOS) products. In this work, the RTD obtained experimentally was truncated at different levels, to investigate the impact of the truncation of RTD on funnel plots for OOS detection. The main finding is that the tail of the RTD can be truncated with no loss of accuracy in the determination of exclusion intervals. This enables the manufacturing scientist to focus entirely on the peak region, maximizing the accuracy of chemometric models.

The Effect of Community Health Information System on Health Care Services Utilization in Rural Ethiopia.

Background: In Ethiopia, the community health information system (CHIS) is implemented at the health post (hp) level with the aim of improving service delivery and use. We conducted a national level assessment of CHIS utilization and explored the associations of CHIS utilization with use of antenatal care (ANC), postnatal care (PNC), institutional delivery and child immunization in rural Ethiopia. Methods: We conducted a cross-sectional study measuring community-based health service use and HP based CHIS assessment from March to May 2019. Data were collected from 343 HPs and 2,864 women who delivered in the last five years, and multistage sampling was used to select the study subjects. We used descriptive statistics for CHIS implementation and service utilization and multilevel logistic regression to investigate the association of CHIS implementation with maternal and child health care services use. Results: Fifty five percent of the HPs were implementing CHIS. These HPs were using a paper-based household data collection tool called family folder (FF). Of the HPs, one third implemented lot quality assurance sampling (LQAS) based data quality check and 60.4% documented and followed execution of decisions. Overall, among the eligible women, 40% used ANC, close to 50% of currently married women used ANC services; 28% of women that fall in the high wealth index category used PNC within 48 hours after delivery; and 86.1% of women who had at least a high school education delivered at a health facility. Implementation of CHIS and family folder utilization and conducting LQAS based data quality check in the HPs were significantly associated with increased odds of ANC, delivery, and vaccination services use. Conclusion: We found that better implementation of CHIS was associated with better maternal and child health service use which implies that increasing utilization of CHIS at HPs will improve mother and child health service use.

Providing information for decision-making in the Nigerian Polio Eradication Program, 2016-2020.

Nigeria made a coordinated effort to be certified by the World Health Organization's African Region for interrupting endemic transmission of wild poliovirus type-1 (WPV1) in August 2020 as a response to the resurgence of WPV1 cases in August 2016 after going two years without a case. The NEOC Data Working Group (DWG) was instrumental in providing quality and timely surveillance and campaign information for decision-making in order to interrupt WPV1 transmission and provide data toward documentation of its elimination for regional certification. The polio pre-campaign dashboard was used to assess the level of preparedness for Oral Poliovirus Vaccine (OPV) polio supplementary immunization activities (SIA) at three weeks, two weeks, one week, and three days to the start of each campaign implemented during 2016-2020. The administrative tally sheet, independent monitoring survey, and Lot Quality Assurance Sampling (LQAS) survey data collected and shared from the implementation level were analyzed by the EOC DWG to provide information by person, place, and time. Using a 90% threshold in LQAS surveys defining quality SIAs, the proportion of Local Government Areas (LGAs) in Nigeria's states in which post-SIA LQAS surveys were conducted that met this threshold were assessed over time. The highest level of preparedness attained by 3 days to a polio campaign during August 2016-February 2020 was 95% and the lowest attained was 77%. The admin, independent monitoring, and LQAS data analysis results were given to EOC working groups for assessing the performance and quality of each campaign. Twenty-twenty five percent of LGAs that failed LQAS were identified for repeat vaccination. Further, acute flaccid paralysis and environmental surveillance data and laboratory results were analyzed and shared with NEOC and partners. The government and partners used the information generated by the Data Working Group to take evidence-based action including determining the scope of the polio campaign, intensification of surveillance and routine immunization activities, and special intervention activities. On average, 12% of the 774 LGAs were identified as polio high risk LGAs for intervention using selected surveillance, routine immunization (RI), SIAs, and other relevant data sets. National Emergency Operation Centre Data Working Group provided quality and timely information that supported decision-making processes for the polio program in Nigeria. The quality and timely information enabled the NEOC to make evidence-based and timely decisions that contributed to gap identification and decision-making.

Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti.

BACKGROUND: Lot Quality Assurance Sampling (LQAS), a tool used for monitoring health indicators in low resource settings resulting in "high" or "low" classifications, assumes that determination of the trait of interest is perfect. This is often not true for diagnostic tests, with imperfect sensitivity and specificity. Here, we develop Lot Quality Assurance Sampling for Imperfect Tests (LQAS-IMP) to address this issue and apply it to a COVID-19 serosurveillance study design in Haiti. METHODS: We first derive a modified procedure, LQAS-IMP, that accounts for the sensitivity and specificity of a diagnostic test to yield correct classification errors. We then apply the novel LQAS-IMP to design an LQAS system to classify prevalence of SARS-CoV-2 antibodies among healthcare workers at eleven Zanmia Lasante health facilities in Haiti. Finally, we show the performance of the LQAS-IMP procedure in a simulation study. RESULTS: We found that when an imperfect diagnostic test is used, the classification errors in the standard LQAS procedure are larger than specified. In the modified LQAS-IMP procedure, classification errors are consistent with the specified maximum classification error. We then utilized the LQAS-IMP procedure to define valid systems for sampling at eleven hospitals in Haiti. CONCLUSION: The LQAS-IMP procedure accounts for imperfect sensitivity and specificity in system design; if the accuracy of a test is known, the use of LQAS-IMP extends LQAS to applications for indicators that are based on laboratory tests, such as SARS-CoV-2 antibodies.

Two-stage lot quality assurance sampling framework for monitoring and evaluation of neglected tropical diseases, allowing for imperfect diagnostics and spatial heterogeneity.

BACKGROUND: Monitoring and evaluation (M&E) is a key component of large-scale neglected tropical diseases (NTD) control programs. Diagnostic tests deployed in these M&E surveys are often imperfect, and it remains unclear how this affects the population-based program decision-making. METHODOLOGY: We developed a 2-stage lot quality assurance sampling (LQAS) framework for decision-making that allows for both imperfect diagnostics and spatial heterogeneity of infections. We applied the framework to M&E of soil-transmitted helminth control programs as a case study. For this, we explored the impact of the diagnostic performance (sensitivity and specificity), spatial heterogeneity (intra-cluster correlation), and survey design on program decision-making around the prevalence decisions thresholds recommended by WHO (2%, 10%, 20% and 50%) and the associated total survey costs. PRINCIPAL FINDINGS: The survey design currently recommended by WHO (5 clusters and 50 subjects per cluster) may lead to incorrect program decisions around the 2% and 10% prevalence thresholds, even when perfect diagnostic tests are deployed. To reduce the risk of incorrect decisions around the 2% prevalence threshold, including more clusters (≥10) and deploying highly specific diagnostic methods (≥98%) are the most-cost saving strategies when spatial heterogeneity is moderate-to-high (intra-cluster correlation >0.017). The higher cost and lower throughput of improved diagnostic tests are compensated by lower required sample sizes, though only when the cost per test is <6.50 US$ and sample throughput is ≥3 per hour. CONCLUSION/SIGNIFICANCE: Our framework provides a means to assess and update M&E guidelines and guide product development choices for NTD. Using soil-transmitted helminths as a case study, we show that current M&E guidelines may severely fall short, particularly in low-endemic and post-control settings. Furthermore, specificity rather than sensitivity is a critical parameter to consider. When the geographical distribution of an NTD within a district is highly heterogeneous, sampling more clusters (≥10) may be required.

A National Cross-Sectional Study from the Republic of Kosovo on Lot Quality Assurance Sampling (LQAS) to Evaluate the Vaccination Status of Children Between 12 and 24 Months of Age During 2018 to 2020.

BACKGROUND In the Republic of Kosovo, full vaccination status in children under age 2 years includes: 1 dose of Bacillus Calmette-Guerin (BCG) hepatitis B virus (HBV) vaccine; 3 doses of diphtheria, tetanus, pertussis, hepatitis B, polio, and Haemophilus influenzae type b (DTaP-HB-IPV-Hib) vaccine; 3 doses of inactivated polio vaccine (IPV); and 1 dose of measles, mumps, and rubella (MMR) vaccine. Lot quality assurance sampling (LQAS) is a method used to assess the performance of health quality indicators. MATERIAL AND METHODS A national cross-sectional study with children aged between 12 and 24 months from Kosovo was performed between 2018 and 2020. The vaccination status of children was assessed with lot quality assurance sampling (LQAS) using randomized samples. RESULTS Among 430 children, more than 90% had completed the full immunization schedule. Delays in children's immunizations were observed. Most vaccinations showed short delays of less than 1 month, followed by delays of up to 3 months. The main reason for vaccination delay was the COVID-19 pandemic, following by child's illness at the scheduled time of vaccination or the parents were too busy to take the child to the vaccination site. Meanwhile, child age was the only parameter that showed difference among non-vaccinated and fully vaccinated (P<0.001). CONCLUSIONS LQAS analysis showed that between 2018 and 2020 lack of full immunization was due to delay caused by the parent not taking the child to the vaccination site, which may be prevented by improving information given to parents and the use of vaccination reminders.

Promotion of Early Childhood Development Using mHealth: Learnings From an Implementation Experience in Haryana.

Pregnancy and the early years of life (0-3 years) are of crucial importance for a child's survival, health, growth and development. Improving care for young children is now considered fundamental to achieving the Sustainable Development Goals by 2030. With support from WHO and Intervida (an international non-governmental organization), implementation on care for early childhood development was carried out by Survival for Women and Children Foundation in 100 villages in Haryana, India. In addition to the implementation of evidence-based interventions, mHealth (phone message (SMS) and phone call) was used as a complementary strategy. The intention was to promote self-care, increase coverage, and improve inter-sectoral collaboration. One message per day was developed (915 messages) and 1564630 SMS were sent to all beneficiaries and providers to facilitate interaction. Based on learnings, the consolidation of this approach into 46 core themes helped to refine interactions. Lot Quality Assurance Sampling was used for evaluation. SMS was received, read and practiced by the caregivers and the care providers in the intervention block, being substantially higher than in the control blocks. There was a remarkable improvement in under-nutrition and wasting; however, the reduction in stunting was modest in the intervention area as compared with two control blocks. This is attributed to implementation of all strategies in the project including the complementary approach of use of mHealth. The application of SMS and phone communication continues to have relevance, since people most in need are poor and require integrated package of services maximally during this crucial period for improving equity and coverage.

Assessment of the required performance and the development of corresponding program decision rules for neglected tropical diseases diagnostic tests: Monitoring and evaluation of soil-transmitted helminthiasis control programs as a case study.

Recently, the World Health Organization established the Diagnostic Technical Advisory Group to identify and prioritize diagnostic needs for neglected tropical diseases, and to ultimately describe the minimal and ideal characteristics for new diagnostic tests (the so-called target product profiles (TPPs)). We developed two generic frameworks: one to explore and determine the required sensitivity (probability to correctly detect diseased persons) and specificity (probability to correctly detect persons free of disease), and another one to determine the corresponding samples sizes and the decision rules based on a multi-category lot quality assurance sampling (MC-LQAS) approach that accounts for imperfect tests. We applied both frameworks for monitoring and evaluation of soil-transmitted helminthiasis control programs. Our study indicates that specificity rather than sensitivity will become more important when the program approaches the endgame of elimination and that the requirements for both parameters are inversely correlated, resulting in multiple combinations of sensitivity and specificity that allow for reliable decision making. The MC-LQAS framework highlighted that improving diagnostic performance results in a smaller sample size for the same level of program decision making. In other words, the additional costs per diagnostic tests with improved diagnostic performance may be compensated by lower operational costs in the field. Based on our results we proposed the required minimal and ideal diagnostic sensitivity and specificity for diagnostic tests applied in monitoring and evaluating of soil-transmitted helminthiasis control programs.

Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.

BACKGROUND: Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda. METHODS: Our analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area-level models, respectively. RESULTS: Estimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area-level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (ß1 = 0.66, r2 = 0.862), and correlation between area-level model and direct survey estimates was (ß1 = 0.44, r2 = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and area-level models, respectively, compared to the direct survey estimates. CONCLUSIONS: Although the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available.

Predictors of Health Seeking Behaviours for Common Childhood Illnesses in Poor Resource Settings in Zambia, A Community Cross Sectional Study.

Background: Developing countries, including Zambia, account for larger share of child morbidities and mortalities due to common childhood illnesses. Studies on wider determinants of behaviour pertaining to treatment seeking for childhood febrile illnesses in poor resource settings are limited. This study investigated health seeking behaviours of mothers in poor resource settings of Zambia and identified associated factors. Methods: Secondary data from a community cross sectional study design from the Health for the Poorest Population (HPP) Project was analysed between March and May 2019. Data was collected between May and August, 2013. It was collected by means of administering a structured questionnaire from the mothers of under-five children. The survey took place in Samfya and Chiengi of Luapula province while in Northern Province, Luwingu and Mungwi were settled for. A total of 1 653 mothers of under 5 years who had an episode of diarrhoea, malaria, pneumonia or a combination of any of them not more than 14 days before the interview were included in the study. A sample size was arrived at using A Lot Quality Assurance Sampling (LQAS) method. In order to determine the associations between respondent's demographic characteristics and health seeking behaviour, chi square test of independence was carried out. Multivariable logistic regression was also done to identify predictors of health seeking behaviours for common childhood illnesses in children aged <5 years old in poor resource settings. Results: Among the mothers interviewed, 64.6% were married while 35.4% were unmarried. Their mean age was 32 years. Mothers who took their sick children to the health facilities for the purpose of seeking health care for their child for either of the illnesses accounted for 75.2%, [95% CI: 0.62-0.96], while 24.8% did not seek health care for their sick child. Factors typically associated with health seeking behaviours were mothers' marital status [aOR = 0.74; 95% CI: 0.58-0.94], and mothers 'education level [aOR = 1.47; 95% CI: 1.13-1.92]. Conclusion: It was established in this study that health care seeking behaviours for these common childhood illnesses in poor resource settings was relatively high and could be predicted by mother's education level and mothers' marital status. Integrating interventions targeted at increasing utilisation of maternal and child health services with basic education to women and moral support counselling to families may potentially maximise health seeking behaviours in marginalised communities.

Surveillance strategies using routine microbiology for antimicrobial resistance in low- and middle-income countries.

BACKGROUND: Routine microbiology results are a valuable source of antimicrobial resistance (AMR) surveillance data in low- and middle-income countries (LMICs) as well as in high-income countries. Different approaches and strategies are used to generate AMR surveillance data. OBJECTIVES: We aimed to review strategies for AMR surveillance using routine microbiology results in LMICs and to highlight areas that need support to generate high-quality AMR data. SOURCES: We searched PubMed for papers that used routine microbiology to describe the epidemiology of AMR and drug-resistant infections in LMICs. We also included papers that, from our perspective, were critical in highlighting the biases and challenges or employed specific strategies to overcome these in reporting AMR surveillance in LMICs. CONTENT: Topics covered included strategies of identifying AMR cases (including case-finding based on isolates from routine diagnostic specimens and case-based surveillance of clinical syndromes), of collecting data (including cohort, point-prevalence survey, and case-control), of sampling AMR cases (including lot quality assurance surveys), and of processing and analysing data for AMR surveillance in LMICs. IMPLICATIONS: The various AMR surveillance strategies warrant a thorough understanding of their limitations and potential biases to ensure maximum utilization and interpretation of local routine microbiology data across time and space. For instance, surveillance using case-finding based on results from clinical diagnostic specimens is relatively easy to implement and sustain in LMIC settings, but the estimates of incidence and proportion of AMR is at risk of biases due to underuse of microbiology. Case-based surveillance of clinical syndromes generates informative statistics that can be translated to clinical practices but needs financial and technical support as well as locally tailored trainings to sustain. Innovative AMR surveillance strategies that can easily be implemented and sustained with minimal costs will be useful for improving AMR data availability and quality in LMICs.

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.

Evaluation of neonatal mortality data completeness and accuracy in Ghana.

BACKGROUND: Cause-specific mortality data are required to set interventions to reduce neonatal mortality. However, in many developing countries, these data are either lacking or of low quality. We assessed the completeness and accuracy of cause of death (COD) data for neonates in Ghana to assess their usability for monitoring the effectiveness of health system interventions aimed at improving neonatal survival. METHODS: A lot quality assurance sampling survey was conducted in 20 hospitals in the public sector across four regions of Ghana. Institutional neonatal deaths (IND) occurring from 2014 through 2017 were divided into lots, defined as neonatal deaths occurring in a selected facility in a calendar year. A total of 52 eligible lots were selected: 10 from Ashanti region, and 14 each from Brong Ahafo, Eastern and Volta region. Nine lots were from 2014, 11 from 2015 and 16 each were from 2016 and 2017. The cause of death (COD) of 20 IND per lot were abstracted from admission and discharge (A&D) registers and validated against the COD recorded in death certificates, clinician's notes or neonatal death audit reports for consistency. With the error threshold set at 5%, ≥ 17 correctly matched diagnoses in a sample of 20 deaths would make the lot accurate for COD diagnosis. Completeness of COD data was measured by calculating the proportion of IND that had death certificates completed. RESULTS: Nineteen out of 52 eligible (36.5%) lots had accurate COD diagnoses recorded in their A&D registers. The regional distribution of lots with accurate COD data is as follows: Ashanti (4, 21.2%), Brong Ahafo (7, 36.8%), Eastern (4, 21.1%) and Volta (4, 21.1%). Majority (9, 47.4%) of lots with accurate data were from 2016, followed by 2015 and 2017 with four (21.1%) lots. Two (10.5%) lots had accurate COD data in 2014. Only 22% (239/1040) of sampled IND had completed death certificates. CONCLUSION: Death certificates were not reliably completed for IND in a sample of health facilities in Ghana from 2014 through 2017. The accuracy of cause-specific mortality data recorded in A&D registers was also below the desired target. Thus, recorded IND data in public sector health facilities in Ghana are not valid enough for decision-making or planning. Periodic data quality assessments can determine the magnitude of the data quality concerns and guide site-specific improvements in mortality data management.

National Stop Transmission of Polio Program support for polio supplemental immunization activities in Nigeria 2012-2016: deployment of management support team.

Introduction: to support polio eradication activities in Nigeria, in 2012 the National Polio Emergency Operation Center (NEOC) created the Management Support Teams (MST) to address gaps in the quality of supervision of polio vaccination teams. The National Stop Transmission of Polio (NSTOP) Program supported the polio eradication activities by deploying trained supervisors as part of the MST for polio and non-polio immunization campaigns. Methods: trained MST members were deployed approximately 4 days before the start of the campaign to participate in pre-implementation activities and supervise vaccination teams during campaigns. Terms of reference (TOR) developed by NEOC was provided to MST members to guide their activities. Qualified MSTs that met pre-determined criteria were selected and deployed to the field to support pre, intra and post campaigns activities. Results: a pool of over 400 MST personnel have been identified, trained, and repeatedly deployed from 2012 till 2016. The number of deployed MST personnel rose from 40 per campaign in October 2012 to 342 in May 2016. Of these, 270 (79%) MST personnel were deployed to 11 polio high-risk states of northern Nigeria, where campaigns are conducted between eight and ten times yearly as planned by NEOC. For measles campaigns, about 300 (75%) MST personnel were deployed for the one-off northern and southern campaigns in 2016. The results of clustered Lot Quality Assurance Sampling (LQAS) post-campaign vaccination coverage surveys, a measure of campaign quality, of which introduction into the polio program coincided with deployment of MSTs, showed improvement over time, from 10% (very poor quality) in February 2012 to about 90% (good quality) in December 2016. Conclusion: the deployment of MST personnel increased the number of trained supervisors in the field, frequency of supervisory visits and had a positive impact on the quality of polio campaigns.

Simulating a Transmission Assessment Survey: An evaluation of current methods used in determining the elimination of the neglected tropical disease, Lymphatic Filariasis.

INTRODUCTION: The World Health Organization (WHO) recommends Transmission Assessment Surveys (TAS) to determine when an evaluation unit (EU) (a designated population survey area) has achieved elimination of transmission of the vector-borne macroparasitic disease Lymphatic Filariasis (LF). These determinations are based on combining data from multiple survey units within an EU; it is unclear how underlying cluster-level variation influences the outcome of the TAS at EU level. We simulate LF infection distribution in an EU and compare three methods for assessing whether LF elimination has occurred based on currently recommended decision thresholds and sampling methods. METHODS: We simulate an EU divided into clusters of varying size and disease prevalence. We produce 1000 samples according to LF TAS examples and WHO guidelines and compare three decision-making approaches: lot quality assurance sampling (LQAS) (recommended by WHO), one-sided interval estimate (CI), and nth order statistic (MAX). Summary statistics demonstrating the "pass" rate for the EU under different disease transmission conditions are generated using a versatile SAS® macro. RESULTS: As the prevalence of LF decreases, the LQAS and CI approaches produce increased likelihood of a pass outcome for an EU while some cluster units may still have a high likelihood of transmission. The MAX provides an alternative that increases the likelihood of determining a pass only once the whole area has a low likelihood of transmission. LQAS and CI approaches designed to estimate the LF prevalence in the EU miss hotspots that will continue to transmit infection while the MAX approach focuses on identifying clusters with high risk of transmission. CONCLUSIONS: The current TAS methodology has a flaw that may result in false predictions of LF transmission interruption throughout an EU. Modifying the TAS methodology to address results from extreme clusters rather than being based on mean prevalence over an EU will result in greater success for global elimination of LF.