Modeling Population Movements under Uncertainty at the Border in Humanitarian Crises: A Situational Analysis Tool

Humanitarian agencies must be prepared to mobilize quickly in response to complex emergencies, and their effectiveness depends on their ability to identify, anticipate, and prepare for future needs. These are typically highly uncertain situations in which predictive modeling tools can be useful but challenging to build. To better understand the need for humanitarian support -- including shelter and assistance -- and strengthen contingency planning and protection efforts for displaced populations, we present a situational analysis tool to help anticipate the number of migrants and forcibly displaced persons that will cross a border in a humanitarian crisis. The tool consists of: (i) indicators of potential intent to move drawn from traditional and big data sources; (ii) predictive models for forecasting possible future movements; and (iii) a simulation of border crossings and shelter capacity requirements under different conditions. This tool has been specifically adapted to contingency planning in settings of high uncertainty, with an application to the Brazil-Venezuela border during the COVID-19 pandemic.Comment: 9 pages, 5 figure

Strategic choices of migrants and smugglers in the Central Mediterranean sea.

The sea crossing from Libya to Italy is one of the world's most dangerous and politically contentious migration routes, and yet over half a million people have attempted the crossing since 2014. Leveraging data on aggregate migration flows and individual migration incidents, we estimate how migrants and smugglers have reacted to changes in the border enforcement regime, namely the rise in interceptions by the Libyan Coast Guard starting in 2017 and the corresponding decrease in the probability of rescue to Europe. We find support for a deterrence effect in which attempted crossings along the Central Mediterranean route declined, and a diversion effect in which some migrants substituted to the Western Mediterranean route. At the same time, smugglers adapted their tactics. Using a strategic model of the smuggler's choice of boat size, we estimate how smugglers trade off between the short-run payoffs to launching overcrowded boats and the long-run costs of making less successful crossing attempts under different levels of enforcement. Taken together, these analyses shed light on how the integration of incident- and flow-level datasets can inform ongoing migration policy debates and identify potential consequences of changing enforcement regimes

The number of migrants crossing by nationality and route: North Africa.

The number of migrants crossing by nationality and route: North Africa.</p

The number of migrants crossing by nationality and route: East and Central Africa.

The following Central African countries had less than 50 monthly arrivals in all time periods (all via the Spanish route) and were omitted: the Republic of the Congo, the Central African Republic, and Chad. Data source: [63].</p

Predicted utility and distribution of boat sizes, by probability of interception.

Predicted utility and distribution of boat sizes, by probability of interception.</p

Parameter estimates for the smuggler’s utility model.

Parameter estimates for the smuggler’s utility model.</p