The three years of Ebola virus epidemic (2013-2016) wreaked havoc in Western African and other parts of the world. It was the most widespread outbreak of Ebola virus disease (EVD) in history, leading to massive loss of life and socioeconomic disruption. While the worst-hit countries were Guinea, Liberia and Sierra Leone, cases were reported from several parts of the world.
“At that time, ArcGIS was used to understand and predict disease transmission behavior, as well as support responding agencies to accurately specify where, how and when to deploy resources. The technology also helped communities to support communications with organizations and to collaborate in a more transparent way, so they could get the help they needed to the right location more rapidly,” recalls Esri Founder and President Jack Dangermond. During those years, mapping of cases by first responders ensured that Ebola treatment units were set up at the right places and remote areas with no connectivity received maximum assistance.
“In the beginning of the Ebola virus crisis, 23 of our member organizations were working in Liberia and Sierra Leone. It was very difficult to get information about rural areas as there was no connectivity,” Lauren Woodman, CEO of NetHope, a consortium of over 50 leading humanitarian, development and conservation organizations, told Geospatial World in an earlier interview. Frontline health workers couldn’t be paid because it would take four days to send a text message. NetHope went in with its technology partners and donor organizations and provided connectivity to more than 400 organizations. “When we started mapping, it emerged that infection rates were falling in areas with connectivity. Even then Ebola treatment units were being set up in such areas. However, in areas where the rates were high, there was no connectivity or treatment units. Had we not mapped these areas, we wouldn’t have found that correlation,” she added.
“There are so many applications of geospatial data for our members. When combined with other data, geospatial data becomes very rich,” she emphasized. The integration of geospatial with emerging technologies like Artificial Intelligence presents great opportunities and applications in healthcare, since the location factor plays a key role in both population and individual health. Multiple disciplines within public health such as precision medicine benefit from it. “With regard to Artificial Intelligence, we already see its deployment across the entire ArcGIS community. This is not a new trend — it started as far back as 2014, when AI was used along with ArcGIS in response efforts for the Ebola outbreak,” says Dangermond.
Apart from mapping, spatial-temporal analysis to assess household risk factors for Ebola in remote and severely-affected parts was performed and gravity spatial models of transmission for the epidemic were developed. Not only did geospatial tools and data help authorities in countering the virus, they also facilitated quick response and sound decision-making.