There are several types of data used by responders in a crisis. Most crisismapping has focused to date on the data generated during and immediately after a crisis: the tweets, messages, reports, alerts and other social media traffic that happens in response to crisis situations and needs.
But a country doesn’t suddenly change socially because a crisis happens. It doesn’t leap, ready-formed, into a new incarnation where the only thing that’s ever happened is the current earthquake, flood, famine etc. Countries have histories. Events happen, societies form, agencies and other countries, if needed, help them to develop and become resilient. And all this activity creates data.
One of the first things that a response agency does, as it goes into a crisis, is create a profile of that country. How many people are there? What’s it society like? What are its existing needs? Which crises have happened before (and how did people respond to them)? Which NGOs are already active there? Where is everything (towns, hospitals, clean water sources etc)?
I’ve been studying the crisis indicators from 3 organisations (UNOCHA, WWHGD, ACAPS), and the development indicators from many more (UNSTATS, UNDP, WHO, World Bank etc). And the big questions that I’ve been asking are: what do responders going into a crisis need, where can we find that information, and how can we make that faster and easier to do.
IMHO, ACAPS has one of the best indicator lists available. Which is handy because I’m about to co-lead a Standby Task Force deployment to help make obtaining and organizing their indicator data faster and easier. The numbers that they’re looking for are:
| Country size in square kilometres |
| Average population growth rate |
| Climate |
| Corruption Perceptions Index |
| Country size in comparison to the world |
| Distribution of poverty (areas, vulnerable groups) |
| GDP |
| Gross national income per capita |
| Human Development Index |
| Labour force per occupation |
| Land cover, elevation, soils and geology |
| Literacy rate |
| Malnutrition prevalence, height for age (Percentage of children under 5) |
| Maternal Mortality rate as deaths per 100,000 live births |
| Mobile cellular subscriptions (per 100 people) |
| Natural Disasters Risk Index |
| Percentage of population living below poverty line – urban |
| Percentage of population living below poverty line – rural |
| Percentage of the population – rural |
| Percentage of the population – urban |
| Population density (people per square km) |
| Poverty rate |
| Seasonal migration patterns, by region and reasons |
| Socio cultural characteristics of the population – ethnic group, language, religion etc |
| under-5 Mortality Rate as deaths per 1,000 people |
| Unemployment (Percentage of total labour force) |
| Vulnerability and Crisis Index |
An SBTF team is spending the next week looking for these indicators for a specific country (DR Congo) so we can learn about how difficult that is, alternative sources of information, indicator provenance etc. whilst other teams look for demographics, crisis timelines, existing surveys and ways to generalize and automate parts of this process. I’s going to be quite an exciting week.
References: