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Socio-spatial equity analysis of relative wealth index and emergency obstetric care accessibility in urban Nigeria
Kerry L. M. Wong
Aduragbemi Banke-Thomas
Tope Olubodun
Peter M. Macharia
Charlotte Stanton
Narayanan Sundararajan
Yash Shah
Mansi Kansal
Swapnil Vispute
Olakunmi Ogunyemi
Uchenna Gwacham-Anisiobi
Jia Wang
Ibukun-Oluwa Omolade Abejirinde
Prestige Tatenda Makanga
Bosede B. Afolabi
Lenka Beňová
Communications Medicine, 4(2024), pp. 34
Preview abstract
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 60 min 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 81 min) and the smallest in Warri (20 vs 30 min). Similarly, the average number of public CEmOC facilities reachable within 60 min varies (11 among the wealthiest 20% and six among the least wealthy in Kano). In five cities, zero facilities are reachable under 60 min 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.
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Geographical accessibility to emergency obstetric care in urban Nigeria using closer-to-reality travel time estimates
Aduragbemi Banke-Thomas
Kerry L. M. Wong
Tope Olubodun
Peter M. Macharia
Narayanan Sundararajan
Yash Shah
Mansi Kansal
Swapnil Vispute
Olakunmi Ogunyemi
Uchenna Gwacham-Anisiobi
Jia Wang
Ibukun-Oluwa Omolade Abejirinde
Prestige Tatenda Makanga
Ngozi Azodoh
Charles Nzelu, PhD
Charlotte Stanton
Bosede B. Afolabi
Lenka Beňová
Lancet Global Health(2024)
Preview abstract
Background
Better accessibility of emergency obstetric care (CEmOC) facilities can significantly reduce maternal and perinatal deaths. However, pregnant women living in urban settings face additional complex challenges travelling to facilities. We estimated geographical accessibility and coverage to the nearest, second nearest, and third nearest public and private CEmOC facilities in the 15 largest Nigerian cities.
Methods
We mapped city boundaries, verified and geocoded functional CEmOC facilities, and assembled population distribution for women of childbearing age (WoCBA). We used Google Maps Platform’s internal Directions Application Programming Interface (API) to derive driving times to public, private, or either facility-type. Median travel time (MTT) and percentage of WoCBA able to reach care were summarised for eight traffic scenarios (peak and non-peak hours on weekdays and weekends) by city and within-city (wards) under different travel time thresholds (<15, <30, <60 min).
Findings
City-level MTT to the nearest CEmOC facility ranged from 18min (Maiduguri) to 46min (Kaduna). Within cities, MTT varied by location, with informal settlements and peripheral areas being the worst off. The percentages of WoCBA within 60min to their nearest public CEmOC were nearly universal; whilst the percentages of WoCBA within 30min reach to their nearest public CEmOC were between 33% in Aba to over 95% in Ilorin and Maiduguri. During peak traffic times, the median number of public CEmOC facilities reachable by WoCBA under 30min was zero in eight of 15 cities.
Interpretation
This approach provides more context-specific, finer, and policy-relevant evidence to support improving CEmOC service accessibility in urban Africa.
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Revealed versus potential spatial accessibility of healthcare and changing patterns during the COVID-19 pandemic
Kristina Gligoric
Chaitanya Kamath
Daniel Weiss
Shailesh Bavadekar
Kevin Schulman
Evgeniy Gabrilovich
Nature Communications Medicine(2023)
Preview abstract
Background
Timely access to healthcare is essential but measuring access is challenging. Prior research focused on analyzing potential travel times to healthcare under optimal mobility scenarios that do not incorporate direct observations of human mobility, potentially underestimating the barriers to receiving care for many populations.
Methods
We introduce an approach for measuring accessibility by utilizing travel times to healthcare facilities from aggregated and anonymized smartphone Location History data. We measure these revealed travel times to healthcare facilities in over 100 countries and juxtapose our findings with potential (optimal) travel times estimated using Google Maps directions. We then quantify changes in revealed accessibility associated with the COVID-19 pandemic.
Results
We find that revealed travel time differs substantially from potential travel time; in all but 4 countries this difference exceeds 30 minutes, and in 49 countries it exceeds 60 minutes. Substantial variation in revealed healthcare accessibility is observed and correlates with life expectancy (⍴=−0.70) and infant mortality (⍴=0.59), with this association remaining significant after adjusting for potential accessibility and wealth. The COVID-19 pandemic altered the patterns of healthcare access, especially for populations dependent on public transportation.
Conclusions
Our metrics based on empirical data indicate that revealed travel times exceed potential travel times in many regions. During COVID-19, inequitable accessibility was exacerbated. In conjunction with other relevant data, these findings provide a resource to help public health policymakers identify underserved populations and promote health equity by formulating policies and directing resources towards areas and populations most in need.
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A geospatial database of close to reality travel times to obstetric emergency care in 15 Nigerian conurbations
Peter M. Macharia
Kerry L. M. Wong
Tope Olubodun
Lenka Beňová
Charlotte Stanton
Narayanan Sundararajan
Yash Shah
Mansi Kansal
Swapnil Vispute
Uchenna Gwacham-Anisiobi
Olakunmi Ogunyemi
Jia Wang
Ibukun-Oluwa Omolade Abejirinde
Prestige Tatenda Makanga
Bosede B. Afolabi
Aduragbemi Banke-Thomas
Scientific Data, TBD(2023), TBD
Preview abstract
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 such services is essential for improving maternal and neonatal health outcomes. Current understanding of travel time to care is particularly inadequate in urban areas where short distances obscure long travel times, and also in low-resource settings. Here, we describe a database of travel times to facilities that can provide comprehensive EmOC in the 15 most populated extended urban areas (conurbations) in Nigeria. The travel times from cells of approximately 0.6 x 0.6km to facilities were derived based on Google Maps Platform’s internal Directions Application Programming Interface (API). The API incorporates estimates of traffic to provide closer-to-reality estimates of travel time. Computations were done to the first, second and third nearest public or private facilities. Travel time estimates 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.
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Comparing access to urban parks across six OECD countries
Talia Kaufmann
Swapnil Vispute
Mansi Kansal
Daniel T. O'Brien
Evgeniy Gabrilovich
Gregory A. Wellenius
Lewis Dijkstra
Paolo Veneri
OECD Regional Development Papers(2023)
Preview abstract
This work leverages globally consistent data on parks from Google Maps, in combination with the computational power of Google Maps Directions API to quantify accessibility to parks across nearly 500 metropolitan areas in six countries: Estonia, France, Greece, Mexico, Sweden, and the United States. We combined high resolution population data from Worldpop with parks data and navigation estimates to measure: (1) Fraction of the population with access to parks within a 10-minute walk; and (2) the median walking time to the closest park. We find large differences in access to parks between countries, as well as large variability across cities and their respective commuting zones. To demonstrate how this framework can support cross country comparisons and efforts to track progress towards SDG11, we assessed access to parks by income group in selected countries, finding that the median walking time to a park is shorter for residents of low income neighbourhoods both in French and American metropolitan areas.
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Identifying COVID-19 Vaccine Deserts and Ways to Reduce Them: A Digital Tool to Support Public Health Decision-Making
Rebecca L. Weintraub
Kate Miller
Benjamin Rader
Julie Rosenberg
Shreyas Srinath
Samuel R. Woodbury
Marinanicole Schultheiss
Mansi Kansal
Swapnil Vispute
Stelios Serghiou
Gerardo Flores
Akim Kumok
Evgeniy Gabrilovich
Iman Ahmad
Molly E. Chiang
John S. Brownstein
American Journal of Public Health(2023)
Preview abstract
A private–academic partnership built the Vaccine Equity Planner (VEP) to help decision-makers improve geographic access to COVID-19 vaccinations across the United States by identifying vaccine deserts and facilities that could fill those deserts. The VEP presented complex, updated data in an intuitive form during a rapidly changing pandemic situation. The persistence of vaccine deserts in every state as COVID-19 booster recommendations develop suggests that vaccine delivery can be improved. Underresourced public health systems benefit from tools providing real-time, accurate, actionable data. (Am J Public Health. 2023;113(4):363–367. https://doi.org/10.2105/AJPH.2022.307198)
Public health leaders can make better, more equitable decisions when they can clearly see and understand the problems. Being presented with potential solutions based on evidence further supports their decision-making and can aid in supporting health equity.
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High Resolution Building and Road Segmentation from Sentinel-2 Imagery
Abdoulaye Diack
Abel Tesfaye Korme
Emmanuel Asiedu Brempong
Jason Hickey
Juliana Marcos
Krishna Sapkota
Mohammed Alewi Hassen
Wojciech Sirko
arXiv, https://arxiv.org/abs/2310.11622(2023)
Preview abstract
Mapping buildings and roads automatically with remote sensing typically requires imagery of at least 50 cm resolution, which is expensive to obtain and often sparsely available. In this work we demonstrate how public, worldwide imagery from the Sentinel-2 Earth observation mission can be used to carry out this task at a much higher level of detail than the 10 m raw pixel resolution would suggest. To do this, we employ a teacher-student method in which a model with access to a temporal stack of Sentinel-2 images is trained to make the same predictions as a high-resolution model with access to corresponding 50 cm imagery. Evaluating at 50cm resolution, we achieve mIOU of 0.78, equivalent in accuracy to applying a single-frame high resolution model with imagery of 4m resolution.
This work opens up new possibilities for using freely available Sentinel-2 imagery for a range of downstream tasks that previously could only be done with high resolution satellite imagery.
The model will be made available soon to non-commercial, non-governmental entities at https://sites.research.google/open-buildings/ upon request.
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An evaluation of Internet searches as a marker of trends in population mental health in the US
Uma Vaidyanathan
Yuantong Sun
Katherine Chou
Sandro Galea
Evgeniy Gabrilovich
Gregory A. Wellenius
Scientific Reports(2022)
Preview abstract
The absence of continuous, real-time mental health assessment has made it challenging to quantify the impacts of the COVID-19 pandemic on population mental health. We examined publicly available, anonymized, aggregated data on weekly trends in Google searches related to anxiety, depression, and suicidal ideation from 2018 to 2020 in the US. We correlated these trends with (1) emergency department (ED) visits for mental health problems and suicide attempts, and (2) surveys of self-reported symptoms of anxiety, depression, and mental health care use. Search queries related to anxiety, depression, and suicidal ideation decreased sharply around March 2020, returning to pre-pandemic levels by summer 2020. Searches related to depression were correlated with the proportion of individuals reporting receiving therapy (r = 0.73), taking medication (r = 0.62) and having unmet mental healthcare needs (r = 0.57) on US Census Household Pulse Survey and modestly correlated with rates of ED visits for mental health conditions. Results were similar when considering instead searches for anxiety. Searches for suicidal ideation did not correlate with external variables. These results suggest aggregated data on Internet searches can provide timely and continuous insights into population mental health and complement other existing tools in this domain.
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Google COVID-19 Vaccination Search Insights: Anonymization Process Description
Adam Boulanger
Akim Kumok
Arti Patankar
Benjamin Miller
Chaitanya Kamath
Charlotte Stanton
Chris Scott
Damien Desfontaines
Evgeniy Gabrilovich
Gregory A. Wellenius
John S. Davis
Karen Lee Smith
Krishna Kumar Gadepalli
Mark Young
Shailesh Bavadekar
Tague Griffith
Yael Mayer
Arxiv.org(2021)
Preview abstract
This report describes the aggregation and anonymization process applied to the COVID-19 Vaccination Search Insights~\cite{vaccination}, a publicly available dataset showing aggregated and anonymized trends in Google searches related to COVID-19 vaccination. The applied anonymization techniques protect every user’s daily search activity related to COVID-19 vaccinations with $(\varepsilon, \delta)$-differential privacy for $\varepsilon = 2.19$ and $\delta = 10^{-5}$.
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Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: Insights from Spring 2020
Liana R. Woskie
Jonathan Hennessy
Valeria Espinosa
Thomas Tsai
Swapnil Vispute
Ciro Cattuto
Laetitia Gauvin
Michele Tizzoni
Krishna Gadepalli
Adam Boulanger
Adam Pearce
Chaitanya Kamath
Arran Schlosberg
Charlotte Stanton
Shailesh Bavadekar
Matthew Abueg
Michael Hogue
Andrew Oplinger
Katherine Chou
Ashish K. Jha
Greg Wellenius
Evgeniy Gabrilovich
PLOS ONE(2021)
