Telecom data for efficient malaria interventions

TL;DR

This paper presents an operational telecom data-driven tool that models malaria risk flows in Zambia, enabling targeted interventions and coordination for malaria elimination and prevention of re-introduction.

Contribution

It introduces a novel real-time epidemiological modeling tool using telecom data to optimize malaria intervention strategies in Zambia.

Findings

The tool accurately maps malaria risk flows in near real-time.

It identifies priority areas for malaria eradication efforts.

It highlights regions requiring coordinated intervention.

Abstract

Telecom data is rich on mobility information and as such can be used to identify mobility patterns of people in near real time, enabling to build epidemiological models for understanding where epidemics might spread over time. Based on previous research, we have built an operational tool fed with telecom data which shows malaria risk flows in Zambia in near real time. It provides insights on which areas should eradicate malaria first in order to have a maximum impact on the overall country malaria flows, and it highlights regions that should coordinate their eradication efforts together. Such information is particularly relevant for countries like Zambia, which are getting close to malaria elimination and need to prevent its re-introduction into areas that are already malaria-free.