Indigenously developed digital handheld Android-based Geographic Information System (GIS)-tagged tablets (TABs) in malaria elimination programme in Mangaluru city, Karnataka, India

Abstract

Abstract Background Under-reporting, delayed diagnosis, incomplete treatment and inadequate vector management are few among many factors responsible for uninterrupted transmission of malaria in India. Information technology (IT) and mobile apps can be utilized effectively to overcome these hurdles. Indigenously developed digital handheld geographic information system (GIS)-tagged Android-based tablets (TABs) has been designed especially for implementation of digitization protocol. This has changed the effectiveness of malaria surveillance and intervention strategies in a malaria endemic area of Mangaluru city, Karnataka, India. Methods A software was developed and implemented for control measures to create a digital database of each malaria case. Secondary data analyses were carried out to determine and compare differences in malariometric indices between pre- and post-digitization years. With the introduction of this software active surveillance, information education and communication (IEC), and anti-vector measures were made ‘incidence-centric’. This means that the entire control measures were carried out in the houses where the malaria cases (index cases) were reported and also in surrounding houses. Results Annual blood examination rate (ABER) increased from 13.82 to 32.8%. Prompt reporting of new cases had improved (36% within 24 h and 80% within 72 h). Complete treatment and parasite clearance time were documented in 98% of cases. In the second post-digitization year untraceable cases reduced from 11.3 to 2.7%; contact blood smears collection also increased significantly (p < 0.001); Slide Positivity Rate (SPR) decreased from 15.5 to 10.48%; malaria cases reduced by 30%. Conclusions IT is very useful in translation of digitized surveillance to core interventions thereby effectively reduce incidence of malaria. This technology can be used effectively to translate smart surveillance to core interventions following the ‘1-3-7-14’ strategy.