Hybrid prevalence estimation: Method to improve intervention coverage estimations.
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ABSTRACT:
SUBMITTER: Jeffery C
PROVIDER: S-EPMC6304954 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMany studies have assessed the level of bed net coverage in populations at risk of malaria infection. These revealed large variations in bed net use across countries, regions and social strata. Such studies are often aimed at identifying populations with low access to bed nets that should be prioritized in future interventions. However, often spatial differences in malaria endemicity are not taken into account. By ignoring variability in malaria endemicity, these studies prioritize populations with little access to bed nets, even if these happen to live in low endemicity areas. Conversely, populations living in regions with high malaria endemicity will receive a lower priority once a seizable proportion is protected by bed nets. Adequately assigning priorities requires accounting for both the current level of bed net coverage and the local malaria endemicity. Indeed, as shown here for 23 African countries, there is no correlation between the level of bed net coverage and the level of malaria endemicity in a region. Therefore, the need for future interventions can not be assessed based on current bed net coverage alone. This paper proposes the Adjusted Bed net Coverage (ABC) statistic as a measure taking into account both local malaria endemicity and the level of bed net coverage. The measure allows setting priorities for future interventions taking into account both local malaria endemicity and bed net coverage.MethodsA mathematical formulation of the ABC as a weighted difference of bed net coverage and malaria endemicity is presented. The formulation is parameterized based on a model of malaria epidemiology (Smith et al. Trends Parasitol 25:511-516, 2009). By parameterizing the ABC based on this model, the ABC as used in this paper is proxy for the steady-state malaria burden given the current level of bed net coverage. Data on the bed net coverage in under five year olds and malaria endemicity in 23 Sub-Saharan countries is used to show that the ABC prioritizes different populations than the level of bed net coverage by itself. Data from the following countries was used: Angola, Burkina Faso, Burundi, Cameroon, Congo Democratic Republic, Ethiopia, Ghana, Guinea, Kenya, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Sierra Leone, Tanzania, Uganda, Zambia and Zimbabwe. The priority order given by the ABC and the bed net coverage are compared at the countries' level, the first level administrative divisions and for five different wealth quintiles.ResultsBoth at national level and at the level of the administrative divisions the ABC suggests a different priority order for selecting countries and divisions for future interventions. When taking into account malaria endemicity, measures assessing equality in access to bed nets across wealth quintiles, such as slopes of inequality, are prone to change. This suggests that when assessing inequality in access to bed nets one should take into account the local malaria endemicity for populations from different wealth quintiles.ConclusionAccounting for malaria endemicity highlights different countries, regions and socio-economic strata for future intervention than the bed net coverage by itself. Therefore, care should be taken to factor out any effects of local malaria endemicity in assessing bed net coverage and in prioritizing populations for further scale-up of bed net coverage. The ABC is proposed as a simple means to do this that is derived from an existing model of malaria epidemiology.
| S-EPMC4021220 | biostudies-literature
Project description:Antenatal care (ANC) coverage estimates commonly rely on self-reported data, which may carry biases. Leveraging prospectively collected longitudinal data from the Birhan field site and its pregnancy and birth cohort, the Birhan Cohort, this study aimed to estimate the coverage of ANC, minimizing assumptions and biases due to self-reported information and describing retention patterns in ANC in rural Amhara, Ethiopia. The study population were women enrolled and followed during pregnancy between December 2018 and April 2020. ANC visits were measured by prospective facility chart abstraction and self-report at enrollment. The primary study outcomes were the total number of ANC visits attended during pregnancy and the coverage of at least one, four, or eight ANC visits. Additionally, we estimated ANC retention patterns. We included 2069 women, of which 150 (7.2%) women enrolled <13 weeks of gestation with complete prospective facility reporting. Among these 150 women, ANC coverage of at least one visit was 97.3%, whereas coverage of four visits or more was 34.0%. Among all women, coverage of one ANC visit was 92.3%, while coverage of four or more visits was 28.8%. No women were found to have attended eight or more ANC visits. On retention in care, 70.3% of participants who had an ANC visit between weeks 28 and <36 of gestation did not return for a subsequent visit. Despite the high proportion of pregnant women who accessed ANC at least once in our study area, the coverage of four visits remains low. Further efforts are needed to enhance access to more ANC visits, retain women in care, and adhere to the most recent Ethiopian National ANC guideline of at least eight ANC visits. It is essential to identify the factors that lead a large proportion of women to discontinue ANC follow-up.
| S-EPMC10651002 | biostudies-literature
Project description:IntroductionRespondent-driven sampling (RDS) is a variant of a link-tracing design intended for generating unbiased estimates of the composition of hidden populations that typically involves giving participants several coupons to recruit their peers into the study. RDS may generate biased estimates if coupons are distributed non-randomly or if potential recruits present for interview non-randomly. We explore if biases detected in an RDS study were due to either of these mechanisms, and propose and apply weights to reduce bias due to non-random presentation for interview.MethodsUsing data from the total population, and the population to whom recruiters offered their coupons, we explored how age and socioeconomic status were associated with being offered a coupon, and, if offered a coupon, with presenting for interview. Population proportions were estimated by weighting by the assumed inverse probabilities of being offered a coupon (as in existing RDS methods), and also of presentation for interview if offered a coupon by age and socioeconomic status group.ResultsYounger men were under-recruited primarily because they were less likely to be offered coupons. The under-recruitment of higher socioeconomic status men was due in part to them being less likely to present for interview. Consistent with these findings, weighting for non-random presentation for interview by age and socioeconomic status group greatly improved the estimate of the proportion of men in the lowest socioeconomic group, reducing the root-mean-squared error of RDS estimates of socioeconomic status by 38%, but had little effect on estimates for age. The weighting also improved estimates for tribe and religion (reducing root-mean-squared-errors by 19-29%), but had little effect for sexual activity or HIV status.ConclusionsData collected from recruiters on the characteristics of men to whom they offered coupons may be used to reduce bias in RDS studies. Further evaluation of this new method is required.
| S-EPMC3814964 | biostudies-literature
Project description:The electrostatic features of highly charged biomolecules are crucial and challenging tasks in computational biophysics. The electrostatic calculations by traditional implicit solvent methods are efficient but have difficulties on highly charged biomolecules. We have developed a Hybridizing Ion Treatment (HIT) tool, which successfully hybridizes the explicit ions and implicit solvation model to accurately calculate the electrostatic potential for highly charged biomolecules. Here we implemented the HIT tool into a web server. In this study, a training set was prepared to optimize the number of frames for the HIT web server. The results on tubulins, DNAs, and RNAs, reveal the mechanisms for the motor proteins, DNA of HIV, and tRNA. This HIT web server can be widely used to study highly charged biomolecules, including DNAs, RNAs, molecular motors, and other highly charged biomolecules.
| S-EPMC8991293 | biostudies-literature
Project description:BackgroundEstimates of the total number of prevalent HIV infections attributable to the major routes of infection make an important contribution to public health policy, as they are used for planning services.MethodsIn the UK, estimates were derived through the "direct method" which estimated the total number of diagnosed and undiagnosed HIV infections in the population. The direct method has been improved over a number of years since first used in 1994, as further data became available such as the inclusion of newly available behavioural survey data both from the National Survey of Sexual Attitudes and Lifestyles (Natsal 2000) and community surveys of men who have sex with men (MSM). These data were used to re-estimate numbers of people unaware of their infection and provided ethnic breakdowns within behavioural categories. The total population was divided into 10 mutually exclusive behavioural categories relevant to HIV risk in the UK-for example, MSM and injecting drug users. Estimates of the population size within each group were derived from Natsal 2000 and National Statistics mid-year population estimates. The total number of undiagnosed HIV infections was calculated by multiplying the undiagnosed HIV prevalence for each group, derived from the Unlinked Anonymous HIV Prevalence Monitoring Programme surveys (UAPMP), by the population size. These estimates were then added to the prevalent diagnosed HIV infections within each group derived from the national census of diagnosed HIV infections, the Survey of Prevalent HIV Infections Diagnosed (SOPHID). The estimates were then adjusted to include all adults in the UK. Because undiagnosed HIV prevalence estimates were not available for each of the behavioural categories, the UAPMP prevalence estimates were adjusted using available data to provide the best estimates for each group.ResultsIt is estimated that 53,000 individuals are infected with HIV in the UK in 2003, of whom 27% were unaware of their infection. Of the total of 53,000, an estimated 26,000 were among heterosexually infected and 24,500 among MSM.ConclusionThe direct method uses an explicit framework and data from different components of the HIV surveillance system to estimate HIV prevalence in the UK, allowing for a comprehensive picture of the epidemic.
| S-EPMC2657482 | biostudies-literature
Project description:As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small.
| S-EPMC5800695 | biostudies-literature
Project description:In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact population size and susceptibility. We use satellite imagery to quantify population fluctuations and the coverage achieved by a measles outbreak response vaccination campaign in urban Niger and compare campaign estimates to measurements from a post-campaign survey. Vaccine coverage was overestimated because the campaign underestimated resident numbers and seasonal migration further increased the target population. We combine satellite-derived measurements of fluctuations in population distribution with high-resolution measles case reports to develop a dynamic model that illustrates the potential improvement in vaccination campaign coverage if planners account for predictable population fluctuations. Satellite imagery can improve retrospective estimates of vaccination campaign impact and future campaign planning by synchronizing interventions with predictable population fluxes.
| S-EPMC5050518 | biostudies-literature
Project description:We analysed DNA from two brain regions (cerebellum, CER and frontal cortex, FC) from 4 Parkinson's disease (PD) and 4 control brains on a custom design 8x60k Agilent aCGH targeted to PD genes. All brain DNA samples were hybridised with Agilent sex-matched reference DNA, and three CER samples were hybridised against the FC of the same brain, with a dye swap in one. Male and female reference DNA were hybridised to eachother. The samples were then re-extracted with additional protocols, and hybridisations were performed for two CER samples betwen DNA extracted from the same CER with different protocols, and for one brain between the CER and FC new extraction.
2016-02-01 | GSE71360 | GEO
Project description:Monitoring universal health coverage (UHC) focuses on information on health intervention coverage and financial protection. This paper addresses monitoring intervention coverage, related to the full spectrum of UHC, including health promotion and disease prevention, treatment, rehabilitation, and palliation. A comprehensive core set of indicators most relevant to the country situation should be monitored on a regular basis as part of health progress and systems performance assessment for all countries. UHC monitoring should be embedded in a broad results framework for the country health system, but focus on indicators related to the coverage of interventions that most directly reflect the results of UHC investments and strategies in each country. A set of tracer coverage indicators can be selected, divided into two groups-promotion/prevention, and treatment/care-as illustrated in this paper. Disaggregation of the indicators by the main equity stratifiers is critical to monitor progress in all population groups. Targets need to be set in accordance with baselines, historical rate of progress, and measurement considerations. Critical measurement gaps also exist, especially for treatment indicators, covering issues such as mental health, injuries, chronic conditions, surgical interventions, rehabilitation, and palliation. Consequently, further research and proxy indicators need to be used in the interim. Ideally, indicators should include a quality of intervention dimension. For some interventions, use of a single indicator is feasible, such as management of hypertension; but in many areas additional indicators are needed to capture quality of service provision. The monitoring of UHC has significant implications for health information systems. Major data gaps will need to be filled. At a minimum, countries will need to administer regular household health surveys with biological and clinical data collection. Countries will also need to improve the production of reliable, comprehensive, and timely health facility data. Please see later in the article for the Editors' Summary.
| S-EPMC4171108 | biostudies-literature
Project description:Animal behavior is the final and integrated output of brain activity. Thus, recording and analyzing behavior is critical to understand the underlying brain function. While recording animal behavior has become easier than ever with the development of compact and inexpensive devices, detailed behavioral data analysis requires sufficient prior knowledge and/or high content data such as video images of animal postures, which makes it difficult for most of the animal behavioral data to be efficiently analyzed. Here, we report a versatile method using a hybrid supervised/unsupervised machine learning approach for behavioral state estimation and feature extraction (STEFTR) only from low-content animal trajectory data. To demonstrate the effectiveness of the proposed method, we analyzed trajectory data of worms, fruit flies, rats, and bats in the laboratories, and penguins and flying seabirds in the wild, which were recorded with various methods and span a wide range of spatiotemporal scales-from mm to 1,000 km in space and from sub-seconds to days in time. We successfully estimated several states during behavior and comprehensively extracted characteristic features from a behavioral state and/or a specific experimental condition. Physiological and genetic experiments in worms revealed that the extracted behavioral features reflected specific neural or gene activities. Thus, our method provides a versatile and unbiased way to extract behavioral features from simple trajectory data to understand brain function.
| S-EPMC6611002 | biostudies-literature