Towards Real-Time Monitoring of the Hajj

An automated approach to explore the fundamental properties of high-density pedestrian traffic is outlined. The framework operates on video or time lapse images captured from surveillance cameras. For pedestrian velocity extraction, the framework incorporates cross-correlation based Particle Image Velocimetry (PIV) techniques. For pedestrian density estimation, the framework relies on the Machine Learning technique of the Boosted Regression Trees. The information collected from images in pixel coordinates are transformed to world coordinates with a pin-hole camera based projective transformation technique. The framework has been tested with high density crowd images acquired during the Muslim religious event, the Hajj. Accuracy and performance of the framework are reported

Extracting Crowd Velocities at High Density

Velocity is a fundamental property of foot traffic flow. Monitoring the change of velocity patterns at high pedestrian densities may provide valuable insights on foot traffic dynamics. In this paper, a closer look is taken to explore the capability of the Particle Image Velocimetry (PIV) technique on extracting crowd velocities from surveillance camera images. Experiments are performed to report the accuracy of pedestrian velocity extraction with PIV. Quantitative accuracy is reported with manual tracking of pedestrians, surveying correlation misses at different window sizes and compute times. The results indicate that the PIV algorithm can be a good candidate for velocity extraction in real-time

Understanding biological mechanisms underlying adverse birth outcomes in developing countries: Protocol for a prospective cohort (AMANHI bio-banking) study

Objectives: The AMANHI study aims to seek for biomarkers as predictors of important pregnancy-related outcomes, and establish a biobank in developing countries for future research as new methods and technologies become available.Methods: AMANHI is using harmonised protocols to enrol 3000 women in early pregnancies (8-19 weeks of gestation) for population-based follow-up in pregnancy up to 42 days postpartum in Bangladesh, Pakistan and Tanzania, with collection taking place between August 2014 and June 2016. Urine pregnancy tests will be used to confirm reported or suspected pregnancies for screening ultrasound by trained sonographers to accurately date the pregnancy. Trained study field workers will collect very detailed phenotypic and epidemiological data from the pregnant woman and her family at scheduled home visits during pregnancy (enrolment, 24-28 weeks, 32-36 weeks & 38+ weeks) and postpartum (days 0-6 or 42-60). Trained phlebotomists will collect maternal and umbilical blood samples, centrifuge and obtain aliquots of serum, plasma and the buffy coat for storage. They will also measure HbA1C and collect a dried spot sample of whole blood. Maternal urine samples will also be collected and stored, alongside placenta, umbilical cord tissue and membrane samples, which will both be frozen and prepared for histology examination. Maternal and newborn stool (for microbiota) as well as paternal and newborn saliva samples (for DNA extraction) will also be collected. All samples will be stored at -80°C in the biobank in each of the three sites. These samples will be linked to numerous epidemiological and phenotypic data with unique study identification numbers.Importance of the study: AMANHI biobank proves that biobanking is feasible to implement in LMICs, but recognises that biobank creation is only the first step in addressing current global challenges

Neonatal mortality within 24 hours of birth in six low- and lower-middle-income countries

OBJECTIVE: To assess the rates, timing and causes of neonatal deaths and the burden of stillbirths in rural Uttar Pradesh, India. We discuss the implications of our findings for neonatal interventions. METHODS: We used verbal autopsy interviews to investigate 1048 neonatal deaths and stillbirths. FINDINGS: There were 430 stillbirths reported, comprising 41% of all deaths in the sample. Of the 618 live births, 32% deaths were on the day of birth, 50% occurred during the first 3 days of life and 71% were during the first week. The primary causes of death on the first day of life (i.e. day 0) were birth asphyxia or injury (31%) and preterm birth (26%). During days 1–6, the most frequent causes of death were preterm birth (30%) and sepsis or pneumonia (25%). Half of all deaths caused by sepsis or pneumonia occurred during the first week of life. The proportion of deaths attributed to sepsis or pneumonia increased to 45% and 36% during days 7–13 and 14–27, respectively. CONCLUSION: Stillbirths and deaths on the day of birth represent a large proportion of perinatal and neonatal deaths, highlighting an urgent need to improve coverage with skilled birth attendants and to ensure access to emergency obstetric care. Health interventions to improve essential neonatal care and care-seeking behavior are also needed, particularly for preterm neonates in the early postnatal period

Neonatal mortality within 24 hours of birth in six low- and lower-middle-income countries.

Objective: To estimate neonatal mortality, particularly within 24 hours of birth, in six low- and lower-middle-income countries. Methods: We analysed epidemiological data on a total of 149 570 live births collected between 2007 and 2013 in six prospective randomized trials and a cohort study from predominantly rural areas of Bangladesh, Ghana, India, Pakistan, the United Republic of Tanzania and Zambia. The neonatal mortality rate and mortality within 24 hours of birth were estimated for all countries and mortality within 6 hours was estimated for four countries with available data. The findings were compared with published model-based estimates of neonatal mortality. Findings: Overall, the neonatal mortality rate observed at study sites in the six countries was 30.5 per 1000 live births (range: 13.6 in Zambia to 47.4 in Pakistan). Mortality within 24 hours was 14.1 per 1000 live births overall (range: 5.1 in Zambia to 20.1 in India) and 46.3% of all neonatal deaths occurred within 24 hours (range: 36.2% in Pakistan to 65.5% in the United Republic of Tanzania). Mortality in the first 6 hours was 8.3 per 1000 live births, i.e. 31.9% of neonatal mortality. Conclusion: Neonatal mortality within 24 hours of birth in predominantly rural areas of six low- and lower-middle-income countries was higher than model-based estimates for these countries. A little under half of all neonatal deaths occurred within 24 hours of birth and around one third occurred within 6 hours. Implementation of high-quality, effective obstetric and early newborn care should be a priority in these settings

Neonatal mortality within 24 hours of birth in six low- and lower-middle-income countries.

OBJECTIVE: To estimate neonatal mortality, particularly within 24 hours of birth, in six low- and lower-middle-income countries. METHODS: We analysed epidemiological data on a total of 149 570 live births collected between 2007 and 2013 in six prospective randomized trials and a cohort study from predominantly rural areas of Bangladesh, Ghana, India, Pakistan, the United Republic of Tanzania and Zambia. The neonatal mortality rate and mortality within 24 hours of birth were estimated for all countries and mortality within 6 hours was estimated for four countries with available data. The findings were compared with published model-based estimates of neonatal mortality. FINDINGS: Overall, the neonatal mortality rate observed at study sites in the six countries was 30.5 per 1000 live births (range: 13.6 in Zambia to 47.4 in Pakistan). Mortality within 24 hours was 14.1 per 1000 live births overall (range: 5.1 in Zambia to 20.1 in India) and 46.3% of all neonatal deaths occurred within 24 hours (range: 36.2% in Pakistan to 65.5% in the United Republic of Tanzania). Mortality in the first 6 hours was 8.3 per 1000 live births, i.e. 31.9% of neonatal mortality. CONCLUSION: Neonatal mortality within 24 hours of birth in predominantly rural areas of six low- and lower-middle-income countries was higher than model-based estimates for these countries. A little under half of all neonatal deaths occurred within 24 hours of birth and around one third occurred within 6 hours. Implementation of high-quality, effective obstetric and early newborn care should be a priority in these settings

Community-based asthma assessment in young children:Adaptations for a multicentre longitudinal study in South Asia

BACKGROUND: Systematic assessment of childhood asthma is challenging in low- and middle-income country (LMIC) settings due to the lack of standardised and validated methodologies. We describe the contextual challenges and adaptation strategies in the implementation of a community-based asthma assessment in four resource-constrained settings in Bangladesh, India, and Pakistan. METHOD: We followed a group of children of age 6–8 years for 12 months to record their respiratory health outcomes. The study participants were enrolled at four study sites of the ‘Aetiology of Neonatal Infection in South Asia (ANISA)’ study. We standardised the research methods for the sites, trained field staff for uniform data collection and provided a ‘Child Card’ to the caregiver to record the illness history of the participants. We visited the children on three different occasions to collect data on respiratory-related illnesses. The lung function of the children was assessed in the outreach clinics using portable spirometers before and after 6-minute exercise, and capillary blood was examined under light microscopes to determine eosinophil levels. RESULTS: We enrolled 1512 children, 95.5% (1476/1512) of them completed the follow-up, and 81.5% (1232/1512) participants attended the lung function assessment tests. Pre- and post-exercise spirometry was performed successfully in 88.6% (1091/1232) and 85.7% (1056/1232) of children who attempted these tests. Limited access to health care services, shortage of skilled human resources, and cultural diversity were the main challenges in adopting uniform procedures across all sites. Designing the study implementation plan based on the local contexts and providing extensive training of the healthcare workers helped us to overcome these challenges. CONCLUSION: This study can be seen as a large-scale feasibility assessment of applying spirometry and exercise challenge tests in community settings of LMICs and provides confidence to build capacity to evaluate children’s respiratory outcomes in future translational research studies

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB