Interpreting results of cluster surveys in emergency settings: is the LQAS test the best option?

Cluster surveys are commonly used in humanitarian emergencies to measure health and nutrition indicators. Deitchler et al. have proposed to use Lot Quality Assurance Sampling (LQAS) hypothesis testing in cluster surveys to classify the prevalence of global acute malnutrition as exceeding or not exceeding the pre-established thresholds. Field practitioners and decision-makers must clearly understand the meaning and implications of using this test in interpreting survey results to make programmatic decisions. We demonstrate that the LQAS test–as proposed by Deitchler et al. – is prone to producing false-positive results and thus is likely to suggest interventions in situations where interventions may not be needed. As an alternative, to provide more useful information for decision-making, we suggest reporting the probability of an indicator's exceeding the threshold as a direct measure of "risk". Such probability can be easily determined in field settings by using a simple spreadsheet calculator. The "risk" of exceeding the threshold can then be considered in the context of other aggravating and protective factors to make informed programmatic decisions

Comparison of anthropometric data quality in children aged 6-23 and 24-59 months: lessons from population-representative surveys from humanitarian settings

BACKGROUND: Ensuring the quality of anthropometry data is paramount for getting accurate estimates of malnutrition prevalence among children aged 6-59 months in humanitarian and refugee settings. Previous reports based on data from Demographic and Health Surveys suggested systematic differences in anthropometric data quality between the younger and older groups of preschool children. METHODS: We analyzed 712 anthropometric population-representative field surveys from humanitarian and refugee settings conducted during 2011-2018. We examined and compared the quality of five anthropometric indicators in children aged 6-23 months and children aged 24-59 months: weight for height, weight for age, height for age, body mass index for age and mid-upper arm circumference (MUAC) for age. Using the z-score distribution of each indicator, we calculated the following parameters: standard deviation (SD), percentage of outliers, and measures of distribution normality. We also examined and compared the quality of height, weight, MUAC and age measurements using missing data and rounding criteria. RESULTS: Both SD and percentage of flags were significantly smaller on average in older than in younger age group for all five anthropometric indicators. Differences in SD between age groups did not change meaningfully depending on overall survey quality or on the quality of age ascertainment. Over 50% of surveys overall did not deviate significantly from normality. The percentage of non-normal surveys was higher in older than in the younger age groups. Digit preference score for weight, height and MUAC was slightly higher in younger age group, and for age slightly higher in the older age group. Children with reported exact date of birth (DOB) had much lower digit preference for age than those without exact DOB. SD, percentage flags and digit preference scores were positively correlated between the two age groups at the survey level, such as those surveys showing higher anthropometry data quality in younger age group also tended to show higher quality in older age group. CONCLUSIONS: There should be an emphasis on increased rigor of training survey measurers in taking anthropometric measurements in the youngest children. Standardization test, a mandatory component of the pre-survey measurer training and evaluation, of 10 children should include at least 4-5 children below 2 years of age

A Decade Later, How Much of Rwanda's Musculoskeletal Impairment Is Caused by the War in 1994 and by Related Violence?

BACKGROUND: In 1994 there was a horrific genocide in Rwanda following years of tension, resulting in the murder of at least 800,000 people. Although many people were injured in addition to those killed, no attempt has been made to assess the lasting burden of physical injuries related to these events. The aim of this study was to estimate the current burden of musculoskeletal impairment (MSI) attributable to the 1994 war and related violence. METHODOLOGY/PRINCIPAL FINDINGS: A national cross-sectional survey of MSI was conducted in Rwanda. 105 clusters of 80 people were selected through probability proportionate to size sampling. Households within clusters were selected through compact segment sampling. Enumerated people answered a seven-question screening test to assess whether they might have an MSI. Those who were classed as potential cases in the screening test were examined and interviewed by a physiotherapist, using a standard protocol that recorded the site, nature, cause, and severity of the MSI. People with MSI due to trauma were asked whether this trauma occurred during the 1990-1994 war or during the episodes that preceded or followed this war. Out of 8,368 people enumerated, 6,757 were available for screening and examination (80.8%). 352 people were diagnosed with an MSI (prevalence=5.2%, 95% CI=4.5-5.9%). 106 cases of MSI (30.6%) were classified as resulting from trauma, based on self-report and the physiotherapist's assessment. Of these, 14 people (13.2%) reported that their trauma-related MSI occurred during the 1990-1994 war, and a further 7 (6.6%) that their trauma-related MSI occurred during the violent episodes that preceded and followed the war, giving an overall prevalence of trauma-related MSI related to the 1990-1994 war of 0.3% (95% CI=0.2-0.4%). CONCLUSIONS/SIGNIFICANCE: A decade on, the overall prevalence of MSI was relatively high in Rwanda but few cases appeared to be the result of the 1994 war or related violence

Old and new cluster designs in emergency field surveys: in search of a one-fits-all solution

<p>Abstract</p> <p>Introduction</p> <p>Cluster surveys are frequently used to measure key nutrition and health indicators in humanitarian emergencies. The survey design of 30 clusters of 7 children (30 × 7) was initially proposed by the World Health Organization for measuring vaccination coverage, and later a design of 30 clusters of 30 children (30 × 30) was introduced to measure acute malnutrition in emergency settings. Recently, designs of 33 clusters of 6 children (33 × 6) and 67 clusters of 3 children (67 × 3) have been proposed as alternatives that enable measurement of several key indicators with sufficient precision, while offering substantial savings in time. This paper explores expected effects of using 67 × 3, 33 × 6, or 30 × 7 designs instead of a "standard" 30 × 30 design on precision and accuracy of estimates, and on time required to complete the survey.</p> <p>Analysis</p> <p>The 67 × 3, 33 × 6, and 30 × 7 designs are expected to be more statistically efficient for measuring outcomes having high design effects (e.g., vaccination coverage, vitamin A distribution coverage, or access to safe water sources), and less efficient for measuring outcomes with more within-cluster variability, such as global acute malnutrition or anemia. Because of small sample sizes, these designs may not provide sufficient levels of precision to measure crude mortality rates. Given the small number (3 to 7) of survey subjects per cluster, it may be hard to select representative samples of subjects within clusters.</p> <p>The smaller sample size in these designs will likely result in substantial time savings. The magnitude of the savings will depend on several factors, including the average travel time between clusters. The 67 × 3 design will provide the least time savings. The 33 × 6 and 30 × 7 designs perform similarly to each other, both in terms of statistical efficiency and in terms of time required to complete the survey.</p> <p>Conclusion</p> <p>Cluster designs discussed in this paper may offer substantial time and cost savings compared to the traditional 30 × 30 design, and may provide acceptable levels of precision when measuring outcomes that have high intracluster homogeneity. Further investigation is required to determine whether these designs can consistently provide accurate point estimates for key outcomes of interest. Organizations conducting cluster surveys in emergency settings need to build their technical capacity in survey design to be able to calculate context-specific sample sizes individually for each planned survey.</p

Interventions to prevent youth violence in Latin America: a systematic review

Objectives: This review aims to summarise evidence on the effectiveness of interventions to prevent youth violence in Latin America. Methods: A systematic search on 13 academic databases was conducted to locate studies evaluating a primary or secondary prevention intervention in Latin America. Studies could use any type of quantitative design to assess outcomes related to youth violence. A search of websites, references and citation searching was also carried out. The quality of each study was assessed. Results: Nine studies were identified. Most documented positive effects of the interventions on the perception of youth violence present in the community/school. Evidence was found of a reduction in homicides and juvenile crimes in three studies, two of which evaluated a community-based intervention. There were mixed results for the self-report of participation on violent acts. The majority of the studies lacked of a rigorous design. Conclusions: Most of the interventions had some promising results, including the reduction of homicides within communities. Community-based programmes were the most consistent regarding an effectiveness to prevent violence. However, the evidence for Latin America is still scarce and relies on non-rigorously designed studies

Methods of nutrition surveillance in low-income countries

Background In 1974 a joint FAO/UNICEF/WHO Expert Committee met to develop methods for nutrition surveillance. There has been much interest and activity in this topic since then, however there is a lack of guidance for practitioners and confusion exists around the terminology of nutrition surveillance. In this paper we propose a classification of data collection activities, consider the technical issues for each category, and examine the potential applications and challenges related to information and communication technology. Analysis There are three major approaches used to collect primary data for nutrition surveillance: repeated cross-sectional surveys; community-based sentinel monitoring; and the collection of data in schools. There are three major sources of secondary data for surveillance: from feeding centres, health facilities, and community-based data collection, including mass screening for malnutrition in children. Surveillance systems involving repeated surveys are suitable for monitoring and comparing national trends and for planning and policy development. To plan at a local level, surveys at district level or in programme implementation areas are ideal, but given the usually high cost of primary data collection, data obtained from health systems are more appropriate provided they are interpreted with caution and with contextual information. For early warning, data from health systems and sentinel site assessments may be valuable, if consistent in their methods of collection and any systematic bias is deemed to be steady. For evaluation purposes, surveillance systems can only give plausible evidence of whether a programme is effective. However the implementation of programmes can be monitored as long as data are collected on process indicators such as access to, and use of, services. Surveillance systems also have an important role to provide information that can be used for advocacy and for promoting accountability for actions or lack of actions, including service delivery. Conclusion This paper identifies issues that affect the collection of nutrition surveillance data, and proposes definitions of terms to differentiate between diverse sources of data of variable accuracy and validity. Increased interest in nutrition globally has resulted in high level commitments to reduce and prevent undernutrition. This review helps to address the need for accurate and regular data to convert these commitments into practice