33 research outputs found

    A new trajectory for spatial data infrastructure evolution in the developing world

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    Includes abstract.Includes bibliographical references (leaves 107-113).Spatial Data is a key resource in the development of cities. There is a lot of socio-economic potential that is locked away in spatial data holdings and this potential is unlocked by making the datasets widely available for use. Spatial Data Infrastructures (SDIs) have served this primary purpose; to make data accessible through the use of web based technologies. However, SDIs have not had their anticipated impact at local levels of governance. They have traditionally served as platforms that facilitate access to raw spatial datasets. They have not fully facilitated for the use of these datasets and therefore have attracted minimal attention from decision makers and users. This research suggests a new trajectory for SDI evolution; a trajectory that will allow them to evolve into more relevant platforms for confronting the urban crisis in developing nations and thereby ensuring that they have the societal impact that they are intended to. The research explores the characteristics of the mainstream efforts to counter urban crises in the developing world to determine how the new SDI should be re-conceptualised to more adequately assist in responding to the urban crisis. This leads to the incorporation of Evidence Based Practice (EBP) into SDI through the use of urban indicators and knowledge creation processes to reflect on the pressing societal issues. From the new SDI concept, an architectural design is implemented as a “proof of concept”. At the heart of this new concept is the SDIs ability to provide access to more than just raw spatial datasets but useful information products that are based on these data. This proves that EBP can be incorporated into SDI to make them more efficient in responding to the urban problems in developing nation and consequently more relevant Information Infrastructures for urban decision makers

    Harnessing the PRECISE network as a platform to strengthen global capacity for maternal and child health research in sub-Saharan Africa

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    It is widely acknowledged across the global health sector that research programmes need to be designed and implemented in a way that maximise opportunities for strengthening local capacity. This paper examines how the United Kingdom Research and Innovation (UKRI) Grand Challenges Research Fund (GCRF) funded PRECISE (PREgnancy Care Integrating translational Science, Everywhere) Network has been established as a platform to strengthen global capacity for research focused on the improvement of maternal, fetal and newborn health in subSaharan Africa. Best practice principles outlined in an ESSENCE on Health Research report have been considered in relation to the PRECISE Network capacity-building activities described in this paper. These activities are described at the individual, programmatic and institutional levels, and successes, challenges and recommendations for future work are outlined. The paper concludes that the PRECISE leadership have an opportunity to review and refresh activity plans for capacity building at this stage in the project to build on achievements to date

    Interactions between the Physical and Social Environments with Adverse Pregnancy Events Related to Placental Disorders—A Scoping Review

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    Background: Due to different social and physical environments across Africa, understanding how these environments differ in interacting with placental disorders will play an important role in developing effective interventions. Methods: A scoping review was conducted, to identify current knowledge on interactions between the physical and social environment and the incidence of placental disease in Africa. Results: Heavy metals were said to be harmful when environmental concentrations are beyond critical limits. Education level, maternal age, attendance of antenatal care and parity were the most investigated social determinants. Conclusions: More evidence is needed to determine the relationships between the environment and placental function in Africa. The results show that understanding the nature of the relationship between social determinants of health (SDH) and placental health outcomes plays a pivotal role in understanding the risk in the heterogenous communities in Africa

    The contribution of qualitative research within the PRECISE study in sub-Saharan Africa

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    The PRECISE Network is a cohort study established to investigate hypertension, fetal growth restriction and stillbirth (described as “placental disorders”) in Kenya, Mozambique and The Gambia. Several pregnancy or birth cohorts have been set up in low- and middle-income countries, focussed on maternal and child health. Qualitative research methods are sometimes used alongside quantitative data collection from these cohorts. Researchers affiliated with PRECISE are also planning to use qualitative methods, from the perspective of multiple subject areas. This paper provides an overview of the different ways in which qualitative research methods can contribute to achieving PRECISE’s objectives, and discusses the combination of qualitative methods with quantitative cohort studies more generally. We present planned qualitative work in six subject areas (health systems, health geography, mental health, community engagement, the implementation of the TraCer tool, and respectful maternity care). Based on these plans, with reference to other cohort studies on maternal and child health, and in the context of the methodological literature on mixed methods approaches, we find that qualitative work may have several different functions in relation to cohort studies, including informing the quantitative data collection or interpretation. Researchers may also conduct qualitative work in pursuit of a complementary research agenda. The degree to which integration between qualitative and quantitative methods will be sought and achieved within PRECISE remains to be seen. Overall, we conclude that the synergies resulting from the combination of cohort studies with qualitative research are an asset to the field of maternal and child health

    Leveraging big data for improving the estimation of close to reality travel time to obstetric emergency services in urban low- and middle-income settings.

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    Maternal and perinatal mortality remain huge challenges globally, particularly in low- and middle-income countries (LMICs) where >98% of these deaths occur. Emergency obstetric care (EmOC) provided by skilled health personnel is an evidence-based package of interventions effective in reducing these deaths associated with pregnancy and childbirth. Until recently, pregnant women residing in urban areas have been considered to have good access to care, including EmOC. However, emerging evidence shows that due to rapid urbanization, this so called "urban advantage" is shrinking and in some LMIC settings, it is almost non-existent. This poses a complex challenge for structuring an effective health service delivery system, which tend to have poor spatial planning especially in LMIC settings. To optimize access to EmOC and ultimately reduce preventable maternal deaths within the context of urbanization, it is imperative to accurately locate areas and population groups that are geographically marginalized. Underpinning such assessments is accurately estimating travel time to health facilities that provide EmOC. In this perspective, we discuss strengths and weaknesses of approaches commonly used to estimate travel times to EmOC in LMICs, broadly grouped as reported and modeled approaches, while contextualizing our discussion in urban areas. We then introduce the novel OnTIME project, which seeks to address some of the key limitations in these commonly used approaches by leveraging big data. The perspective concludes with a discussion on anticipated outcomes and potential policy applications of the OnTIME project

    A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations

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    Travel time estimation accounting for on-the-ground realities between the location where a need for emergency obstetric care (EmOC) arises and the health facility capable of providing EmOC is essential for improving pregnancy outcomes. Current understanding of travel time to care is inadequate in many urban areas of Africa, where short distances obscure long travel times and travel times can vary by time of day and road conditions. Here, we describe a database of travel times to comprehensive EmOC facilities in the 15 most populated extended urban areas of Nigeria. The travel times from cells of approximately 0.6 × 0.6 km to facilities were derived from Google Maps Platform’s internal Directions Application Programming Interface, which incorporates traffic considerations to provide closer-to-reality travel time estimates. Computations were done to the first, second and third nearest public or private facilities. Travel time for eight traffic scenarios (including peak and non-peak periods) and number of facilities within specific time thresholds were estimated. The database offers a plethora of opportunities for research and planning towards improving EmOC accessibility

    Protocol of an individual participant data meta-analysis to quantify the impact of high ambient temperatures on maternal and child health in Africa (HE 2 AT IPD)

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    Introduction: Globally, recognition is growing of the harmful impacts of high ambient temperatures (heat) on health in pregnant women and children. There remain, however, major evidence gaps on the extent to which heat increases the risks for adverse health outcomes, and how this varies between settings. Evidence gaps are especially large in Africa. We will conduct an individual participant data (IPD) meta-analysis to quantify the impacts of heat on maternal and child health in sub-Saharan Africa. A detailed understanding and quantification of linkages between heat, and maternal and child health is essential for developing solutions to this critical research and policy area. Methods and analysis: We will use IPD from existing, large, longitudinal trial and cohort studies, on pregnant women and children from sub-Saharan Africa. We will systematically identify eligible studies through a mapping review, searching data repositories, and suggestions from experts. IPD will be acquired from data repositories, or through collaboration with data providers. Existing satellite imagery, climate reanalysis data, and station-based weather observations will be used to quantify weather and environmental exposures. IPD will be recoded and harmonised before being linked with climate, environmental, and socioeconomic data by location and time. Adopting a one-stage and two-stage meta-analysis method, analytical models such as time-to-event analysis, generalised additive models, and machine learning approaches will be employed to quantify associations between exposure to heat and adverse maternal and child health outcomes. Ethics and dissemination: The study has been approved by ethics committees. There is minimal risk to study participants. Participant privacy is protected through the anonymisation of data for analysis, secure data transfer and restricted access. Findings will be disseminated through conferences, journal publications, related policy and research fora, and data may be shared in accordance with data sharing policies of the National Institutes of Health. PROSPERO registration number: CRD42022346068
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