COVID-19 pandemic and access to healthcare in Brazil's largest cities

The Institute for Applied Economic Research (Ipea) published yesterday our study looking at 'Urban mobility and access to the healthcare system by patients with suspected and severe cases of COVID-19 in the 20 largest cities of Brazil'. The work is published in Portuguese but there is a Twitter thread with the main findings. In any case, I included a summary of the publication in English below.

obs. This is a by-product of the Access to Opportunities Project. I'm grateful for an amazing team of co-authors who helped me put this piece together in such a short time.

Summary:

The Covid-19 epidemic crisis is causing a rapid growth in the number of hospitalizations for severe acute respiratory syndrome (SARS) in Brazil. According to recent studies, this could soon overload the country's public health system (SUS). As of this writing, most of the confirmed cases of Covid-19 are concentrated in the country's largest cities, where the spread of the disease is at a rapid pace and affecting a growing number of people in disadvantaged communities.

In this policy report, we analyze accessibility to healthcare services in Brazil's 20 largest cities. The research focuses on how easily patients with suspected and severe cases of COVID-19 could reach public health facilities. The study has two purposes:

1. In the first half of the report we estimate how many vulnerable people (low-income above 50 years old) live in areas with poor access to healthcare facilities that could either screen suspected cases of Covid-19 or provide hospitalization of severe cases with the support of ICU beds and mechanical ventilators.
2. In the second half, we estimate the ratio between the number of ICU beds and mechanical ventilators available at each hospital and the population living withing its catchment area.

These two analyses combined provide actionable information to local authorities. The study puts disadvantaged communities with poor access to health services on the map, indicating in which neighborhoods local authorities could build makeshift hospitals or develop strategies via pre-hospital care with mobile units or through the work of health community agents. This research also helps local authorities identify which hospitals could more likely struggle with the rising demand for hospitalizations, and hence would need investments to expand capacity.

Assorted Links

1. Evolution of European Motorways 1920-2020
   
   
2. Dataviz of spatial and temporal spread in networks
   
   
3. paper: Open office architecture seems to decrease the volume of face-to-face employees' interaction and increase electronic interaction.
   
   
4. Global Mapping of GDP at 1 km2 Using VIIRS Nighttime Satellite Imagery
   
   
5. Microsoft releases 18M building footprints in Uganda and Tanzania to enable AI Assisted Mapping
   
   
6. OpenRailwayMap, the open online map of the worldwide railroad infrastructure
   
   
7. In 2019, Helsinki had 0 pedestrian or cyclist fatalities for the first time since 1960. How Lowering speeds and traffic calming.

A spatial database of health facilities in sub Saharan Africa

Interesting new paper analyzing accessibility to emergency hospital care in sub-Saharan Africa in 2015. The authors have done a laborious work to map public health facilities and the data is openly available here. HT Moritz Kraemer.

Ouma, P. O., et al. (2018). Access to emergency hospital care provided by the public sector in sub-Saharan Africa in 2015: a geocoded inventory and spatial analysis. The Lancet Global Health, 6(3), e342-e350.

Abstract:

Background

Timely access to emergency care can substantially reduce mortality. International benchmarks for access to emergency hospital care have been established to guide ambitions for universal health care by 2030. However, no Pan-African database of where hospitals are located exists; therefore, we aimed to complete a geocoded inventory of hospital services in Africa in relation to how populations might access these services in 2015, with focus on women of child bearing age.

Methods

We assembled a geocoded inventory of public hospitals across 48 countries and islands of sub-Saharan Africa, including Zanzibar, using data from various sources. We only included public hospitals with emergency services that were managed by governments at national or local levels and faith-based or non-governmental organisations. For hospital listings without geographical coordinates, we geocoded each facility using Microsoft Encarta (version 2009), Google Earth (version 7.3), Geonames, Fallingrain, OpenStreetMap, and other national digital gazetteers. We obtained estimates for total population and women of child bearing age (15–49 years) at a 1 km2 spatial resolution from the WorldPop database for 2015. Additionally, we assembled road network data from Google Map Maker Project and OpenStreetMap using ArcMap (version 10.5). We then combined the road network and the population locations to form a travel impedance surface. Subsequently, we formulated a cost distance algorithm based on the location of public hospitals and the travel impedance surface in AccessMod (version 5) to compute the proportion of populations living within a combined walking and motorised travel time of 2 h to emergency hospital services.

Findings

We consulted 100 databases from 48 sub-Saharan countries and islands, including Zanzibar, and identified 4908 public hospitals. 2701 hospitals had either full or partial information about their geographical coordinates. We estimated that 287 282 013 (29·0%) people and 64 495 526 (28·2%) women of child bearing age are located more than 2-h travel time from the nearest hospital. Marked differences were observed within and between countries, ranging from less than 25% of the population within 2-h travel time of a public hospital in South Sudan to more than 90% in Nigeria, Kenya, Cape Verde, Swaziland, South Africa, Burundi, Comoros, São Tomé and Príncipe, and Zanzibar. Only 16 countries reached the international benchmark of more than 80% of their populations living within a 2-h travel time of the nearest hospital.

Interpretation

Physical access to emergency hospital care provided by the public sector in Africa remains poor and varies substantially within and between countries. Innovative targeting of emergency care services is necessary to reduce these inequities. This study provides the first spatial census of public hospital services in Africa.

Who pollutes and who gets exposed to road traffic-related air pollution in the UK

In 2003, Gordon Mitchell and Danny Dorling published "An environmental justice analysis of British air quality", a widely cited paper that became a key reference in the environmental justice literature. Now, 16 years latter, a new paper by Joanna Barnes (Twitter), Tim Chatterton (Twitter) and James Longhurst update the original study with new data and more in depth analysis on the social inequalities in traffic-related pollution exposure and emission.

Barnes, J. H., Chatterton, T. J., and; Longhurst, J. W. (2019). Emissions vs exposure: Increasing injustice from road traffic-related air pollution in the United Kingdom. Transportation Research Part D: Transport and Environment, 73, 56-66.

Abstract:

This paper presents unique spatial analyses identifying substantial discrepancies in traffic-related emissions generation and exposure by socioeconomic and demographic groups. It demonstrates a compelling environmental and social injustice narrative with strong policy implications for the UK and beyond.

In the first instance, this research presents a decadal update for England and Wales to Mitchell and Dorling’s 2003 analysis of environmental justice in the UK. Using 2011 UK Government pollution and emissions data with 2011 UK Census socioeconomic and demographic data based on small area census geographies, this paper demonstrates a stronger relationship between age, poverty, road NOxemissions and exposure to NO2 concentrations. Areas with the highest proportions of under-fives and young adults, and poorer households, have the highest concentrations of traffic-related pollution.

In addition, exclusive access to UK annual vehicle safety inspection records (‘MOT’ tests) allowed annual private vehicle NOx emissions to be spatially attributed to registered keepers. Areal analysis against Census-based socioeconomic characteristics identified that households in the poorest areas emit the least NOxand PM, whilst the least poor areas emitted the highest, per km, vehicle emissions per household through having higher vehicle ownership, owning more diesel vehicles and driving further.

In conclusion, the analysis indicates that, despite more than a decade of air quality policy, environmental injustice of air pollution exposure has worsened. New evidence regarding the responsibility for generation of road traffic emissions provides a clear focus for policy development and targeted implementation.

Related post:

• Racial inequity in who pollutes and who gets exposed to pollution in the US

credit: Barnes et al 2019

More evidence on the health benefits of active transport

“Women who averaged approx. 4400 steps/d had significantly lower mortality rates [..] compared with the least active women who took approx. 2700 steps/d; as more steps per day were accrued, mortality rates progressively decreased before leveling at approximately 7500 steps/d.”

This is from a new paper that just came out in JAMA (via Eric Topol). And yes, the authors are have addressed reverse causation bias. Read the methods section.

Fig. Dose-Response Association Between Mean Steps per Day and All-Cause Mortality

credit: I-Min Lee et al. 2019

Racial inequity in who pollutes and who gets exposed to pollution

A recent paper led by Chris Tessum (University of Washington) and published in PNAS brings novel estimates of racial-ethnic disparities in air pollution cause and exposure in the US. They find that air pollution is disproportionately caused by consumption by white Americans, but disproportionately affects Black and Hispanic Americans. The air pollution input-output model used in the paper is freely available and there's an experimental live version of the model running, here. (thanks Marko Tainio for pointing to this paper)

Abstract

Fine particulate matter (PM2.5) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM2.5 exposure to the human activities responsible for PM2.5 pollution. We use these results to explore “pollution inequity”: the difference between the environmental health damage caused by a racial–ethnic group and the damage that group experiences. We show that, in the United States, PM2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a “pollution advantage”: They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a “pollution burden” of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM2.5 exposures declined ∼50% during 2002–2015 for all three racial–ethnic groups, but pollution inequity has remained high.

credit: Tessum et a..

Travel time to closest healthcare facility in Rio de Janeiro

The map shows how long it takes (in minutes) to travel by public transport and walking to the closest healthcare facility across the city of Rio de Janeiro. The analysis is disaggregated for facilities providing low-, medium- and high-complexity services. 

The first thing to note here is that physical accessibility to public health is relatively high in Rio. Approximately 94% of Rio`s population could reach at least one facility providing low-complexity services under 30 minutes. Under the same time, medium- and high-complexity services could be reached by 81% and 72% of the population, respectively. This is explained to some extent by the spatial planning of healthcare in the region, which has been relatively successful in spreading low- and medium-complexity facilities across the city. The map also gives a good sense of how the distribution of healthcare facilities vis-à-vis the public transport network varies across space, and how access to public health tend to be much lower in the west and particularly in the urban fringes of the city.

ps. This is a map I created for my PhD research but I didn't include it in the thesis in the end . To create this map I used a 2015 dataset of healthcare facilities and the GTFS of Rio's public transport network from March 2017. The dataviz and data wrangling were done in R. In case you're interested in doing similar analyses, I've created a simple tutorial with reproducible example on how to use OpenTripPlanner (OTP) to estimate travel times.

[click on the image to enlarge it]

Should cyclists be forced to wear helmets?

Here is a short summary of the evidence on bike helmets and cycle safety provided by some experts interviewed by the Guardian - HT Rachel Aldred and Phil Maynard.

Assorted Links

1. Using geolocated tweets and the Google Books datasets to map the Americanization of English in space and time, by Bruno Gonçalves et al.
   
   
2. Sony World Photography Awards 2018
   
   
3. Interactive maps with deforestation and reforestation of national parks at the border between Brazil and Argentina, between the 1950s and the 2010s, including some aerial and satellite pictures from US spy satellites from the 1960s. via Frederico Freitas
   
   
4. Why the New Research on Mobility Matters - via Juan Pablo Chauvin
   
   
5. Do peoples' judgments on hypothetical trolley dilemmas predict what they would do in a real-life trolley dilemma situation? via Dina Pomeranz
   
   
6. Meaning of the colors in country flags. The explanation of the Brazilian flag hurts
   
   
7. Life expectancy vs. health expenditure over time... needless to say the USA has a problem here. via Max Roser et al at Our World in Data

The health and economic benefits of cycling network expansion in 167 European cities

A recent study has analyzed the associations between cycling network length and mode share, and estimated the health impacts of the expansion of cycling networks across 167 cities in 11 European countries. According to the study, if all 167 cities assessed achieved a 24.7% bicycle mode share, over 10,000 premature deaths could be avoided annually. The study was led by Natalie Mueller and conducted by a network of European researchers. Thanks Christian Brand for the pointer.

Mueller, N., et al. (2018). Health impact assessment of cycling network expansions in European cities. Preventive medicine. (in press).

Abstract:

We conducted a health impact assessment (HIA) of cycling network expansions in seven European cities. We modeled the association between cycling network length and cycling mode share and estimated health impacts of the expansion of cycling networks. First, we performed a non-linear least square regression to assess the relationship between cycling network length and cycling mode share for 167 European cities. Second, we conducted a quantitative HIA for the seven cities of different scenarios (S) assessing how an expansion of the cycling network [i.e. 10% (S1); 50% (S2); 100% (S3), and all-streets (S4)] would lead to an increase in cycling mode share and estimated mortality impacts thereof. We quantified mortality impacts for changes in physical activity, air pollution and traffic incidents. Third, we conducted a cost–benefit analysis. The cycling network length was associated with a cycling mode share of up to 24.7% in European cities. The all-streets scenario (S4) produced greatest benefits through increases in cycling for London with 1210 premature deaths (95% CI: 447–1972) avoidable annually, followed by Rome (433; 95% CI: 170–695), Barcelona (248; 95% CI: 86–410), Vienna (146; 95% CI: 40–252), Zurich (58; 95% CI: 16–100) and Antwerp (7; 95% CI: 3–11). The largest cost–benefit ratios were found for the 10% increase in cycling networks (S1). If all 167 European cities achieved a cycling mode share of 24.7% over 10,000 premature deaths could be avoided annually. In European cities, expansions of cycling networks were associated with increases in cycling and estimated to provide health and economic benefits.

credit: Mueller et al. (2018)

Assorted Links

1. Thanks to Geoff Boeing's great work, you can easily create isochrone maps for anywhere in the world automatically with Python and its OSMnx package
   
   
2. Christian Brand (TSU/Oxford) is one of the co-authors of a new WHO report on "Health economic assessment tools (HEAT) for walking and for cycling"
   
   
3. An AI experiment to find unsafe housing using street-level images, by Jonathan Jay
   
   
4. The Right to the City: Free Ebook Download
   
   
5. Rio's mega-event transportation investments did not address inequalities (or even improve mobility)
   
   
6. call for papers on supply chain and logistics:  2018 MIT SCALE Latin America Conference
   
   
7. The Harvard University Data Science Initiative is seeking applications for its Harvard Data Science Postdoctoral Fellows Program for the 2018-2019 academic year
   
   
8. Google has been mapping air pollution using Google Street View cars. So far, they've measured over one billion air quality data points and now air quality scientists can request access to their data

How Pollution Compares With Other Causes Of Global Deaths

The Lancet Commission on pollution and health has recently published a report that calls attention to the fact that pollution kills 3 times more than AIDS, tuberculosis and malaria combined. There is a good summary of the report in this piece, by NPR.

This chart below was created by Brittany Mayes and Matthew Zhang for the NPR piece, and it is based on data from the Global Health Data Exchange. Thanks Linsey Marr for the pointer on Twitter.

[click on the image to enlarge it]

Transport access to health services

As some of you might remember from an earlier post, my PhD research concentrates on questions of transportation equity, particularly focusing on issues of transport accessibility and inequality of opportunities. Because there is a substantial overlap between my PhD and the research on spatial access to health services, I've read quite a few papers in this literature.

This is a well-studied topic with plenty of publications for those interested.  if you would ask my opinion  I would strongly recommend these two papers below. Together they give a good summary of the cutting-edge research and a very thorough review of various approaches to measuring transport access to health services.

• Neutens, T. (2015). Accessibility, equity and health care: review and research directions for transport geographers. Journal of Transport Geography, 43, 14-27.
  
  
• Apparicio, P., Gelb, J., Dubé, A. S., Kingham, S., Gauvin, L., & Robitaille, É. (2017). The approaches to measuring the potential spatial access to urban health services revisited: distance types and aggregation-error issues. International Journal of Health Geographics, 16(1), 32.

Types of distance. (a) Cartesian distances. (b) Network distances

credit: Apparicio et al 2017

Assorted links

1. Personal details of ~200 million US citizens exposed. A 1.1 terabyte data set with names, home addresses, phone numbers, political views etc. This is approx. 2/3 of the american population. Probably the largest data leak in history  thus far 
   
   
   
   
2. New panel study with more than 260 K participants in the UK shows Biking to work is linked to lower risk of heart disease, cancer, and early death via Leo Monasterio
   
   
   
   
3. An alternative to lat long coordinates: A global addressing system, based on 57 trillion 3mx3m squares, each addressed with 3 simple words 
   
   
   
   
4. I've recently found out that the principal scientist at Amazon‘s Modeling and Optimization team is Renato Werneck, a Brazilian researcher who is also one of the authors of Raptor, the Round-Based Public Transit Routing algorithm
   
   
   
   
5. Incredible Photos Capture Street Scenes of São Paulo, Brazil in 1862 and 1887
   
   
   
   
6. Pyongyang photo series by Raphael Olivier
   
   
   
   
7. In the USA, both Democrats and Republicans agree there is a lot of discrimination against certain social groups. They just disagree which groups are discriminated against
   
   
   
   
8. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. Since 1980, obesity rates doubled in more than 70 countries and continuously increased in other countries

Prevalence of Obesity at the Global Level, According to Sociodemographic Index (SDI)

[click on the image to enlarge it]

Assorted Links

1. The Lone Man Building a Cathedral By Hand
   
   
2. Language Evolution Simulation w/ Agent-Based Modeling via Mara Averick
   
   
3. A research consortium is collecting DNA samples from subway systems around the world to improve our understanding of infectious disease in cities. Here is the interactive map of subway bacteria in New York
   
   
4. People Are Using Britain's New Plastic Money to Play Vinyl Records
   
   
5. Layered Drawings Exploring The Passing Of Time
   
   
6.  A bird that "sings" like chain saw, photographic cameras and car alarms 
   
   
7. Great maps by John Nelson on Five Years of Drought in the US

credit: John Nelson