301 research outputs found
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
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The Impacts of Automated Vehicles on Center City Parking Demand
The potential for automated vehicles (AVs) to reduce parking in city centers has generated much excitement among urban planners. AVs could drop-off (DO) and pick-up (PU) passengers in areas where parking costs are high: personal AVs could return home or park in less expensive locations, and shared AVs could serve other passengers. Reduced on-street and off-street parking present numerous opportunities for redevelopment that could improve the livability of cities, for example, more street and sidewalk space for pedestrian and bicycle travel. However, reduced demand for parking would be accompanied by increased demand for curbside DO/PU space with related movements to enter and exit the flow of traffic. This change could be particularly challenging for traffic flows in downtown urban areas during peak hours, where high volumes of DOs and PUs are likely to occur. Only limited research examines the travel effects of a shift from parking to DO/PU travel and the impact of changes in parking supply. This study uses a microscopic road traffic model with local travel activity data to simulate personal AV parking scenarios in San Francisco's downtown central business district. These scenarios vary (1) the demand for DO and PU travel versus parking, (2) the supply of on-street and off-street parking, and (3) the total demand for parking and DO/PU travel due to an increase in the cost of travel to the central business district.View the NCST Project Webpag
Measuring health system resilience in a highly fragile nation during protracted conflict: South Sudan 2011-2015
Health systems resilience (HSR) is defined as the ability of a health system to continue providing normal services in response to a crisis, making it a critical concept for analysis of health systems in fragile and conflict-affected settings (FCAS). However, no consensus for this definition exists and even less about how to measure HSR. We examine three current HSR definitions (maintaining function, improving function and achieving health system targets) using real-time data from South Sudan to develop a data-driven understanding of resilience. We used 14 maternal, newborn and child health (MNCH) coverage indicators from household surveys in South Sudan collected at independence (2011) and following 2 years of protracted conflict (2015), to construct a resilience index (RI) for 9 of the former 10 states and nationally. We also assessed health system stress using conflict-related indicators and developed a stress index. We cross tabulated the two indices to assess the relationship of resilience and stress. For maintaining function for 80% of MNCH indicators, seven state health systems were resilient, compared with improving function for 50% of the indicators (two states were resilient). Achieving the health system national target of 50% coverage in half of the MNCH indicators displayed no resilience. MNCH coverage levels were low, with state averages ranging between 15% and 44%. Central Equatoria State displayed high resilience and high system stress. Lakes and Northern Bahr el Ghazal displayed high resilience and low stress. Jonglei and Upper Nile States had low resilience and high stress. This study is the first to investigate HSR definitions using a resilience metric and to simultaneously measure health system stress in FCAS. Improving function is the HSR definition detecting the greatest variation in the RI. HSR and health system stress are not consistently negatively associated. HSR is highly complex warranting more in-depth analyses in FCAS
Sexual and Reproductive Health Among Ugandan Youth: 2003-04 to 2012
Purpose
Suboptimal sexual and reproductive health (SRH) increases morbidity, mortality, and gender inequity and slows development. In Uganda, youths represent 20% of the population, and the burden of sexually transmitted infections (STIs), including human immunodeficiency virus (HIV), is substantial.
Methods
We analyzed survey data collected using the lot quality assurance sampling (LQAS) technique from two time periods, 2003–2004 and 2012. We assessed knowledge, behaviors, and access to SRH services of youths aged 15–24 years. Using logistic regression, we examined factors associated with these indicators.
Results
All indicators have improved between the early and later time period. Youths knowing where to get HIV tests increased from <40% to 80% (both sexes); the number of youths reporting ever having an HIV test increased from 8% to 48% (males) and 10% to 64% (females). Knowledge of other STIs improved but remains low; only half of respondents know signs and symptoms of STIs, and less than half know what action to take when infected. In the late period, 85% of female youths, compared with 93% of males reported knowing where to obtain condoms. The proportion of youths reporting sexual debut before age 15 years decreased, less so for males than that for females. Increased age and level of education are associated with positive change for most indicators.
Conclusions
Over the last decade, progress has been made toward improving the SRH of young people in Uganda. Further efforts are required to ensure universal access and sufficient health education to facilitate the continued improvement of safe sexual behaviors among youth aged 15–24 years
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 and 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
Cost-Benefit Analysis of Novel Access Modes: A Case Study in the San Francisco Bay Area
The first-mile, last-mile problem is a significant deterrent for potential transit riders, especially in suburban neighborhoods with low density. Transit agencies have typically sought to solve this problem by adding parking spaces near transit stations and adding stops to connect riders to fixed-route transit. However, these measures are often only short-term solutions. In the last few years, transit agencies have tested whether new mobility services, such as ridehailing, ridesharing, and microtransit, can offer fast, reliable connections to and from transit stations. However, there is limited research that evaluates the potential impacts of these projects. Concurrently, there is growing interest in the future of automated vehicles (AVs) and the potential of AVs to solve this first-mile problem by reducing the cost of providing these new mobility services to promote access to transit. This paper expands upon existing research to model the simulate the travel and revenue impacts of a fleet of automated vehicles that provide transit access services in the San Francisco Bay Area offered over a range of fares. The model simulates a fleet of AVs for first-mile transit access at different price points for three different service models (door-to-door ridehailing and ridesharing and meeting point ridesharing services). These service models include home-based drop-off and pick-up for single passenger service (e.g., Uber and Lyft), home-based drop-off and pick-up for multi-passenger service (e.g.,microtransit), and meeting point multi-passenger service (e.g., Via)
Putting the C Back into the ABCs: A Multi-Year, Multi-Region Investigation of Condom Use by Ugandan Youths 2003-2010
A major strategy for preventing transmission of HIV and other STIs is the consistent use of condoms during sexual intercourse. Condom use among youths is particularly important to reduce the number of new cases and the national prevalence. Condom use has been often promoted by the Uganda National AIDS Commission. Although a number of studies have established an association between condom use at one's sexual debut and future condom use, few studies have explored this association over time, and whether the results are generalizable across multiple locations. This multi time point, multi district study assesses the relationship between sexual debut and condom use and consistent use of condoms thereafter. Uganda has used Lot Quality Assurance Sampling surveys since 2003 to monitor district level HIV programs and improve access to HIV health services. This study includes 4518 sexually active youths interviewed at five time points (2003-2010) in up to 23 districts located across Uganda. Using logistic regression, we measured the association of condom use at first sexual intercourse on recent condom usage, controlling for several factors including: age, sex, education, marital status, age at first intercourse, geographical location, and survey year. The odds of condom use at last intercourse, using a condom at last intercourse with a non-regular partner, and consistently using a condom are, respectively, 9.63 (95%WaldCI = 8.03-11.56), 3.48 (95%WaldCI = 2.27-5.33), and 11.12 (95%WaldCI = 8.95-13.81) times more likely for those individuals using condoms during their sexual debut. These values did not decrease by more than 20% when controlling for potential confounders. The results suggest that HIV prevention programs should encourage condom use among youth during sexual debut. Success with this outcome may have a lasting influence on preventing HIV and other STIs later in life
Combining national survey with facility-based HIV testing data to obtain more accurate estimate of HIV prevalence in districts in Uganda.
BACKGROUND: National or regional population-based HIV prevalence surveys have small sample sizes at district or sub-district levels; this leads to wide confidence intervals when estimating HIV prevalence at district level for programme monitoring and decision making. Health facility programme data, collected during service delivery is widely available, but since people self-select for HIV testing, HIV prevalence estimates based on it, is subject to selection bias. We present a statistical annealing technique, Hybrid Prevalence Estimation (HPE), that combines a small population-based survey sample with a facility-based sample to generate district level HIV prevalence estimates with associated confidence intervals. METHODS: We apply the HPE methodology to combine the 2011 Uganda AIDS indicator survey with the 2011 health facility HIV testing data to obtain HIV prevalence estimates for districts in Uganda. Multilevel logistic regression was used to obtain the propensity of testing for HIV in a health facility, and the propensity to test was used to combine the population survey and health facility HIV testing data to obtain the HPEs. We assessed comparability of the HPEs and survey-based estimates using Bland Altman analysis. RESULTS: The estimates ranged from 0.012 to 0.178 and had narrower confidence intervals compared to survey-based estimates. The average difference between HPEs and population survey estimates was 0.00 (95% CI: - 0.04, 0.04). The HPE standard errors were 28.9% (95% CI: 23.4-34.4) reduced, compared to survey-based standard errors. Overall reduction in HPE standard errors compared survey-based standard errors ranged from 5.4 to 95%. CONCLUSIONS: Facility data can be combined with population survey data to obtain more accurate HIV prevalence estimates for geographical areas with small population survey sample sizes. We recommend use of the methodology by district level managers to obtain more accurate HIV prevalence estimates to guide decision making without incurring additional data collection costs
Is development aid to strengthen health systems during protracted conflict a useful investment? The case of South Sudan, 2011-2015.
Introduction: Is achievement of Sustainable Development Goal (SDG) 16 (building peaceful societies) a precondition for achieving SDG 3 (health and well-being in all societies, including conflict-affected countries)? Do health system investments in conflict-affected countries waste resources or benefit the public's health? To answer these questions, we examine the maternal, newborn, child and reproductive health (MNCRH) service provision during protracted conflicts and economic shocks in the Republic of South Sudan between 2011 (at independence) and 2015. Methods: We conducted two national cross-sectional probability surveys in 10 states (2011) and nine states (2015). Trained state-level health workers collected data from households randomly selected using probability proportional to size sampling of villages in each county. County data were weighted by their population sizes to measure state and national MNCRH services coverage. A two-sample, two-sided Z-test of proportions tested for changes in national health service coverage between 2011 (n=11 800) and 2015 (n=10 792). Results: Twenty-two of 27 national indicator estimates (81.5%) of MNCRH service coverage improved significantly. Examples: malaria prophylaxis in pregnancy increased by 8.6% (p<0.001) to 33.1% (397/1199 mothers, 95% CI ±2.9%), institutional deliveries by 10.5% (p<0.001) to 20% (230/1199 mothers, ±2.6%) and measles vaccination coverage in children aged 12-23 months by 11.2% (p<0.001) to 49.7% (529/1064 children, ±2.3%). The largest increase (17.7%, p<0.001) occurred for mothers treating diarrhoea in children aged 0-59 months with oral rehydration salts to 51.4% (635/1235 children, ±2.9%). Antenatal and postnatal care, and contraceptive prevalence did not change significantly. Child vitamin A supplementation decreased. Despite significant increases, coverage remained low (median of all indicators = 31.3%, SD = 19.7). Coverage varied considerably by state (mean SD for all indicators and states=11.1%). Conclusion: Health system strengthening is not a uniform process and not necessarily deterred by conflict. Despite the conflict, health system investments were not wasted; health service coverage increased
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