A global model for predicting the arrival of imported dengue infections

TL;DR

This paper introduces a network-based model to predict the monthly number of dengue-infected air passengers arriving at airports, aiding public health efforts to prevent dengue outbreaks in non-endemic countries.

Contribution

It presents a novel network model that estimates dengue importation risk by integrating international air travel data and infection probabilities, providing new insights into dengue spread dynamics.

Findings

Identified key dengue importation routes.

Revealed country-specific reporting rates.

Enhanced understanding of dengue spread via air travel.

Abstract

With approximately half of the world's population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue's rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent future outbreaks and dengue from establishing in non-endemic countries, knowledge about the arrival time and location of infected travellers is crucial. We propose a network model that predicts the monthly number of dengue-infected air passengers arriving at any given airport. We consider international air travel volumes to construct weighted networks, representing passenger flows between airports. We further calculate the probability of passengers, who travel through the international air transport network, being infected with dengue. The probability of being infected depends on the destination, duration and timing of travel. Our findings shed light onto dengue importation routes and reveal country-specific reporting rates that have been until now largely unknown. This paper provides important new knowledge about the spreading dynamics of dengue that is highly beneficial for public health authorities to strategically allocate the often limited resources to more efficiently prevent the spread of dengue.