A recent study published in the New England Journal of Medicine is making the news- Mortality in Puerto Rico after Hurricane Maria
The study puts the number at around 4,600 deaths which may be attributable to the hurricanes (Irma and Maria) which damaged Puerto Rico’s infrastructure. The storms left a significant portion of the island without electricity, potable water, and communications for an extended period of time. Access to supplies and movement was hampered by landslides, damaged roads and bridges.
While there is no dispute in the sharp uptick in overall deaths in Puerto Rico in the months immediately following the storms, linking the deaths to the storm has been a contentious issue. In the days and weeks following the storm hospitals were either functioning with reduced capacity or none at all. Government resources understandably were directed to recovery efforts, so counting the dead was not a top priority. The way that the government tallies the dead does not help either as storm related deaths are counted only if they are certified as directly caused the storm – dying after getting hit by flying debris during the storm counts. Yet, an elderly diabetic person who’s insulin spoiled because of a lack of refrigeration and died because his glucose got out of whack is considered to have died of complications from diabetes. A person with a respiratory infection may have gone without early treatment because of damaged roads and died as a result of complications – died of respiratory disease not because of the storm. No communications meant no 911. Such conditions, also takes a toll on mental health, so suicide rates also increased during this period.
OpenStreetMap data aided this study in ways not possible only a few years ago. On a recent radio interview, Domingo Marqués, one of the study’s authors, said that without the map density data this study would not have been possible¹. Thanks to a worldwide push lead by the Humanitarian OpenStreet Maps Team and other contributors holding map-a-thons and working individually – sufficient map data for Puerto Rico was largely available by the time the study needed it. For this study in particular, OSM information was used for selecting the sample.
Sampling buildings using OpenStreetMap
Households within barrios were identified using OpenStreetMap (OSM) layers for structures identified as “buildings”. For each randomly selected barrio, we iteratively downloaded structure information using the OSM overpass API, calculated centroids for structures identified as buildings, and randomly sampled 35 locations. We generated geospatial PDFs for each barrio level with an OSM base layer, a barrio boundary and the sampled building points. The geospatial PDFs were loaded on Samsung Tab A 7” Android devices and displayed using PDFMaps. Enumerators were trained to load maps, identify their position and navigate using these geospatial PDFs.
The study thanked OSM contributors and serves as another example to OpenStreetMap’s usefulness.
As somber as this mortality study is, it can give us hope for better responding for catastrophes in the future by understanding how these deaths occurred. Traditional hurricane preparedness centered towards seeking shelter away from areas prone to flooding. Analysis of the causes of these fatalities along with OpenStreetMap may change this thinking. A location may not be prone to flooding, but may be still vulnerable because of landslide cutting off the only access road. Medicine, Potable Water and other supplies could be pre-positioned prior to the storm’s arrival and tailored on demographic figures to better serve communities which may have a hard time evacuating. After a storm, rapid post disaster data analysis can optimize relief resources to people in need. Temporary clinics could be set quickly up after a storm in critical locations to tend people suffering from chronic diseases or respiratory disease in order to avoid any complications which could lead to death.
OpenStreetMap and the continuing contribution its volunteers in drawing and identifying buildings and other physical features will hopefully play a role in many other studies and applications in understanding this disaster and preparing for future ones worldwide.