Google dengue trends: An indicator of epidemic behavior. The Venezuelan Case.

Abstract

Dengue Fever is a neglected increasing public health thread. Developing countries are facing surveillance system problems like delay and data loss. Lately, the access and the availability of health-related information on the internet have changed what people seek on the web. In 2004 Google developed Google Dengue Trends (GDT) based on the number of search terms related with the disease in a determined time and place. The goal of this review is to evaluate the accuracy of GDT in comparison with traditional surveillance systems in Venezuela. Weekly epidemic data from GDT, Official Reported Cases (ORC) and Expected Cases (EC) according the Ministry of Health (MH) was obtained Monthly and yearly correlation between GDT and ORC from 2004 until 2014 was obtained. Linear regressions taking the reported cases as dependent variable were calculated. The overall Pearson correlation between GDT and ORC was r=0.87 (p <0.001), while between ORC and EC according the Ministry of Health (MH) was r=0.33 (p<0.001). After clustering data in epidemic and non-epidemic weeks in comparison with GDT correlation were r=0.86 (p<0.001) and r=0.65 (p <0.001) respectively. Important interannual variation of the epidemic was observed. The model shows a high accuracy in comparison with the EC, particularly when the incidence of the disease is higher. This early warning tool can be used as an indicator for other communicable diseases in order to apply effective and timely public health measures especially in the setting of weak surveillance systems.