Working towards deadlines

Climate change and the glass half full

Quote of the day:

"Some people complain that this is the hottest summer in the last 125 years, but I like to think of it as the coolest summer of the next 125 years! Glass half full!" (Carter Bays)

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.

Off to the UK

I'm off to the UK to participate in my graduation ceremony at Oxford and to celebrate my partner's graduation at  Cambridge  the other place. Really excited because both our parents will be there to celebrate with us. Yep, this will require some serious diplomatic skills, though :)

My graduation will happen this Saturday, on July 13th between 11am and 12pm. So, you will be able to see a bunch of academics weirdly dressed wondering around Oxford at 12pm on that day. You can actually see this through the live webcam of the Oxford Martin School in case you really need something to procrastinate with.

ps. Blog activity will be low over the next couple of weeks but you'll probably see me Tweeting regularly while I'm queuing for something somewhere in England.

We're hiring research assistants to work with Spatial Data Science at Ipea

A few readers might be interested in this post. We are hiring 4 research assistants to work with (spatial) data science on urban, regional and environmental research and policies at the Institute for Applied Economic Research (Ipea), in Brasília. Great team with lots of computational resources, rich data sets and plenty of challenging data analyses to improve public policies.

*** All the positions are based in Brasília, Brazil.

 

Details here.

Music for the weekend

Soundtrack for a weekend of good bye to João Gilberto, one of the fathers of Bossa Nova. A Brazilian giant.

The winners and losers of the transport legacy of megaevents

Summarizing the core elements of one's research to communicate with a wide audience is among the most challenging and yet important aspects of what researchers do. Here's my best attempt so far to summarize my PhD research to a broad audience, published in my favorite online newspaper Nexo. The text is in Portuguese.

image credit: Nexo

geobr: shapefiles and official spatial data sets of Brazil in R

In 2012, I published here a blog post about where to find shapefiles of Brazil. Since then, this has become one of the most popular posts in 9 years of the blog. However, the links to the original data sets change every now and then, and it gets a bit tricky to find the most up to date data. My team and I at the Institute for Applied Economic Research (Ipea) have created geobr, an R package that allows users to easily access shapefiles of the Brazilian Institute of Geography and Statistics (IBGE) and other official spatial data sets of Brazil.

The geobr package currently includes a variety of data sets, such as the shapefiles of municipalities and states (from 1872 to 2018), census weighting areas, a spatial grid with population count at a resolution of 200 x 200 meters, a geolocated database of health facilities in the country etc. All the data sets are read into R as sf data. We will gradually add other databases to the package, but feel free to make specific requests and suggestions by opening new issues on the GitHub page of geobr or tweeting the hashtag #geobr.

The advantage of geobr: Intuitive syntax that provides easy and quick access to a wide variety shapefiles and official spatial data sets with updated geometries for various years using harmonazied attributes and geographic projections across geographies and years.

Here is a quick intro to geobr: