Pregnancy during COVID-19: social contact patterns and vaccine coverage of pregnant women from CoMix in 19 European countries.

BACKGROUND Evidence and advice for pregnant women evolved during the COVID-19 pandemic. We studied social contact behaviour and vaccine uptake in pregnant women between March 2020 and September 2021 in 19 European countries. METHODS In each country, repeated online survey data were collected from a panel of nationally-representative participants. We calculated the adjusted mean number of contacts reported with an individual-level generalized additive mixed model, modelled using the negative binomial distribution and a log link function. Mean proportion of people in isolation or quarantine, and vaccination coverage by pregnancy status and gender were calculated using a clustered bootstrap. FINDINGS We recorded 4,129 observations from 1,041 pregnant women, and 115,359 observations from 29,860 non-pregnant individuals aged 18-49. Pregnant women made slightly fewer contacts (3.6, 95%CI = 3.5-3.7) than non-pregnant women (4.0, 95%CI = 3.9-4.0), driven by fewer work contacts but marginally more contacts in non-essential social settings. Approximately 15-20% pregnant and 5% of non-pregnant individuals reported to be in isolation and quarantine for large parts of the study period. COVID-19 vaccine coverage was higher in pregnant women than in non-pregnant women between January and April 2021. Since May 2021, vaccination in non-pregnant women began to increase and surpassed that in pregnant women. INTERPRETATION Limited social contact to avoid pathogen exposure during the COVID-19 pandemic has been a challenge to many, especially women going through pregnancy. More recognition of maternal social support desire is needed in the ongoing pandemic. As COVID-19 vaccination continues to remain an important pillar of outbreak response, strategies to promote correct information can provide reassurance and facilitate informed pregnancy vaccine decisions in this vulnerable group

Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations

Google Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API’s in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors

Developing policy-ready digital dashboards of geospatial access to emergency obstetric care: a survey of policymakers and researchers in sub-Saharan Africa

Background Dashboards are increasingly being used in sub-Saharan Africa (SSA) to support health policymaking and governance. However, their use has been mostly limited to routine care, not emergency services like emergency obstetric care (EmOC). To ensure a fit-for-purpose dashboard, we conducted an online survey with policymakers and researchers to understand key considerations needed for developing a policy-ready dashboard of geospatial access to EmOC in SSA. Methods Questionnaires targeting both stakeholder groups were pre-tested and disseminated in English, French, and Portuguese across SSA. We collected data on participants’ awareness of concern areas for geographic accessibility of EmOC and existing technological resources used for planning of EmOC services, the dynamic dashboard features preferences, and the dashboard's potential to tackle lack of geographic access to EmOC. Questions were asked as multiple-choice, Likert-scale, or open-ended. Descriptive statistics were used to summarise findings using frequencies or proportions. Free-text responses were recoded into themes where applicable. Results Among the 206 participants (88 policymakers and 118 researchers), 90% reported that rural areas and 23% that urban areas in their countries were affected by issues of geographic accessibility to EmOC. Five percent of policymakers and 38% of researchers were aware of the use of maps of EmOC facilities to guide planning of EmOC facility location. Regarding dashboard design, most visual components such as location of EmOC facilities had almost universal desirability; however, there were some exceptions. Nearly 70% of policymakers considered the socio-economic status of the population and households relevant to the dashboard. The desirability for a heatmap showing travel time to care was lower among policymakers (53%) than researchers (72%). Nearly 90% of participants considered three to four data updates per year or less frequent updates adequate for the dashboard. The potential usability of a dynamic dashboard was high amongst both policymakers (60%) and researchers (82%). Conclusion This study provides key considerations for developing a policy-ready dashboard for EmOC geographical accessibility in SSA. Efforts should now be targeted at establishing robust estimation of geographical accessibility metrics, integrated with existing health system data, and developing and maintaining the dashboard with up-to-date data to maximise impact in these settings

Systematic review on intentional non-medical fentanyl use among people who use drugs

ObjectivesFentanyl is a highly potent opioid and has, until recently, been considered an unwanted contaminant in the street drug supply among people who use drugs (PWUD). However, it has become a drug of choice for an increasing number of individuals. This systematic review evaluated intentional non-medical fentanyl use among PWUD, specifically by summarizing demographic variance, reasons for use, and resulting patterns of use.MethodsThe search strategy was developed with a combination of free text keywords and MeSH and non-MeSH keywords, and adapted with database-specific filters to Ovid MEDLINE, Embase, Web of Science, and PsychINFO. Studies included were human studies with intentional use of non-medical fentanyl or analogues in individuals older than 13. Only peer-reviewed original articles available in English were included.ResultsThe search resulted in 4437 studies after de-duplication, of which 132 were selected for full-text review. Out of 41 papers included, it was found that individuals who use fentanyl intentionally were more likely to be young, male, and White. They were also more likely to have experienced overdoses, and report injection drug use. There is evidence that fentanyl seeking behaviours are motivated by greater potency, delay of withdrawal, lower cost, and greater availability.ConclusionsAmong PWUD, individuals who intentionally use fentanyl have severe substance use patterns, precarious living situations, and extensive overdose history. In response to the increasing number of individuals who use fentanyl, alternative treatment approaches need to be developed for more effective management of withdrawal and opioid use disorder.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42021272111

Application of GIS in public health practice: a consortium’s approach to tackling travel delays in obstetric emergencies in urban areas

Geographic Information System (GIS) has become an effective and reliable tool for researchers, policymakers, and decision-makers to map health outcomes and inform targeted planning, evaluation, and monitoring. With the advent of big data-enabled GIS, researchers can now identify disparities and spatial inequalities in health at more granular levels, enabling them to provide more accurate and robust services and products for healthcare. This paper aims to showcase the progress of the On Tackling In-transit Delays for Mothers in Emergency (OnTIME) project, which is a unique collaborative effort between academia, policymakers, and industrial partners. The paper demonstrates how the limitations of traditional spatial accessibility models and data gaps have been overcome by combining GIS and big data to map the geographic accessibility and coverage of health facilities capable of providing emergency obstetric care (EmOC) in conurbations in Africa. The OnTIME project employs various GIS technologies and concepts, such as big spatial data, spatial databases, and public participation geographic information systems (PPGIS). We provide an overview of these concepts in relation to the OnTIME project to demonstrate the application of GIS in public health practice

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

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

Socio-spatial equity analysis of relative wealth index and emergency obstetric care accessibility in urban Nigeria

Background. Better geographical accessibility to comprehensive emergency obstetric care (CEmOC) facilities can significantly improve pregnancy outcomes. However, with other factors, such as affordability critical for care access, it is important to explore accessibility across groups. We assessed CEmOC geographical accessibility by wealth status in the 15 most-populated Nigerian cities. Methods. We mapped city boundaries, verified and geocoded functional CEmOC facilities, and assembled population distribution for women of childbearing age and Meta’s Relative Wealth Index (RWI). We used the Google Maps Platform’s internal Directions Application Programming Interface to obtain driving times to public and private facilities. City-level median travel time (MTT) and number of CEmOC facilities reachable within 60min were summarised for peak and non-peak hours per wealth quintile. The correlation between RWI and MTT to the nearest public CEmOC was calculated. Results We show that MTT to the nearest public CEmOC facility is lowest in the wealthiest 20%in all cities, with the largest difference in MTT between the wealthiest 20% and least wealthy 20% seen in Onitsha (26 vs 81min) and the smallest in Warri(20vs30min). Similarly, the average number of public CEmOC facilities reachable within 60min varies (11 among the wealthiest 20% and six among the least wealthy in Kano). In five cities, zero facilities are reachable under 60min for the least wealthy 20%. Those who live in the suburbs particularly have poor accessibility to CEmOC facilities. Conclusions. Our findings show that the least wealthy mostly have poor accessibility to care. Interventions addressing CEmOC geographical accessibility targeting poor people are needed to address inequities in urban settings

SFRP1 reduction results in an increased sensitivity to TGF-β signaling

Background Transforming growth factor (TGF)-β plays a dual role during mammary gland development and tumorigenesis and has been shown to stimulate epithelial-mesenchymal transition (EMT) as well as cellular migration. The Wnt/β-catenin pathway is also implicated in EMT and inappropriate activation of the Wnt/β-catenin signaling pathway leads to the development of several human cancers, including breast cancer. Secreted frizzled-related protein 1 (SFRP1) antagonizes this pathway and loss of SFRP1 expression is frequently observed in breast tumors and breast cancer cell lines. We previously showed that when SFRP1 is knocked down in immortalized non-malignant mammary epithelial cells, the cells (TERT-siSFRP1) acquire characteristics associated with breast tumor initiating cells. The phenotypic and genotypic changes that occur in response to SFRP1 loss are consistent with EMT, including a substantial increase in the expression of ZEB2. Considering that ZEB2 has been shown to interact with mediators of TGF-β signaling, we sought to determine whether TGF-β signaling is altered in TERT-siSFRP1 cells. Methods Luciferase reporter assays and real-time PCR analysis were employed to measure TGF-β transcriptional targets. Western blot analysis was used to evaluate TGF-β-mediated ERK1/2 phosphorylation. Migration chamber assays were utilized to quantify cellular migration. TERT-siSFRP1 cells were transfected with Stealth RNAi™ siRNA in order to knock-down the expression of ZEB2. Results TERT-siSFRP1 cells exhibit a significant increase in both TGF-β-mediated luciferase activity as well as TGF-β transcriptional targets, including Integrin β3 and PAI-1. Phosphorylation of ERK1/2 is increased in TERT-siSFRP1 cells in response to enhanced TGF-β signaling. Furthermore, when the TGF-β pathway is blocked with a TGF-βR antagonist (LY364947), cellular migration is significantly hindered. Finally, we found that when ZEB2 is knocked-down, there is a significant reduction in the expression of exogeneous and endogenous TGF-β transcriptional targets and cellular migration is impeded. Conclusions We demonstrate that down-regulation of SFRP1 renders mammary epithelial cells more sensitive to TGF-β signaling which can be partially ameliorated by blocking the expression of ZEB2

A framework for future national pediatric pandemic respiratory disease severity triage: The HHS pediatric COVID-19 data challenge

Abstract Introduction: With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist. Methods: HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions? Results: This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected. Conclusion: This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic