Using Big Data and Experiments to Solve the Last Mile Problem in Polio Vaccination

Student Researcher: Sameem Siddiqui
Location: Pakistan

This research will use behavioral experiments in conjunction with a smartphone monitoring application to examine how to incentivize public employees to improve the effectiveness of public services, in this case polio vaccine distribution.

Pakistan is among the handful of countries that still suffers polio, and large investments being made toward eradicating it. Polio vaccinations are provided via door-to-door service delivery by government workers during monthly vaccination drives. Vaccinators are assigned to fixed geographical areas and are required to visit and vaccinate every household during each vaccination drive. However, this target conflicts with obstacles workers face in the field and leads to gaps in service delivery, even with resources spent to monitor field activity.

After building a model to predict service probability in a certain location, researchers will perform field experiments to identify the price required to obtain service at different points in space by providing geographically varied incentives. The project's goal is to minimize the cost required to reduce the gap while also improving service. 


Working with the Punjab Department of Health, researchers will identify public employees who are willing to participate in the study. The first phase consists of two parts: 1) a survey of vaccinators that asks for basic demographic information and their preferences for doing a certain percentage of their job at certain points in time for certain rates of pay; and 2) collection of monitoring data on vaccination activity through a smartphone application. 

The researchers will combine the data from the survey with the monitoring data and then tailor various treatments (bonuses given for certain performance rates and/or at a specific time) and assess whether the employees adjusted their performance based on the incentives.