DOT: a crowdsourcing Mobile application for disease outbreak detection and surveillance in Mauritius
- PDF / 1,898,571 Bytes
- 13 Pages / 595.276 x 790.866 pts Page_size
- 13 Downloads / 260 Views
ORIGINAL PAPER
DOT: a crowdsourcing Mobile application for disease outbreak detection and surveillance in Mauritius Kavi Khedo 1 & Shakuntala Baichoo 1 & Soulakshmee Devi Nagowah 2 & Zahra Mungloo-Dilmohamud 1 & Zarine Cadersaib 2 & Sudha Cheerkoot-Jalim 3 & Leckraj Nagowah 2 & Lownish Sookha 1 Received: 28 December 2019 / Accepted: 29 June 2020 # IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Early detection of disease outbreaks is crucial and even small improvements in detection can significantly impact on a country’s public health. In this work, we investigate the use of a crowdsourcing application and a real-time disease outbreak surveillance system for five diseases; Influenza, Gastroenteritis, Upper Respiratory Tract Infection (URTI), Scabies and Conjunctivitis, that are closely monitored in Mauritius. We also analyze and correlate the collected data with past statistics. A crowdsourcing mobile application known as Disease Outbreak Tracker (DOT) was implemented and made public. A real-time disease surveillance system using the Early Aberration Reporting System algorithm (EARS) for analysis of the collected data was also implemented. The collected data were correlated to historical data for 2017. Data were successfully collected and plotted on a daily basis. The results show that a few cases of Flu and Scabies were reported in some districts. The EARS methods C1, C2 and C3 also depicted spikes above the set threshold on some days. The study covers data collected over a period of one month. Once symptoms data were collected using DOT, probabilistic methods were used to find the disease or diseases that the user was suffering from. The data were further processed to find the extent of the disease outbreak district-wise, per disease. These data were represented graphically for a rapid understanding of the situation in each district. Our findings concur with existing data for the same period for previous years showing that the crowdsourcing application can aid in the detection of disease outbreaks. Keywords Disease outbreaks . Communicable diseases . Crowdsourcing . Mobile applications
1 Introduction Despite breakthroughs in the field of medicine to prevent and cure different types of diseases, the fear of outbreaks is ever present. This is due to several factors such as the dynamic and volatile nature of viruses and bacteria or the harsh and abrupt changes in weather [1]. To be able to detect or fight these diseases, surveillance is of utmost importance [2]. Disease surveillance is the ongoing scrutiny and monitoring of clinical syndromes that have a significant impact on medical resource * Soulakshmee Devi Nagowah [email protected] 1
Department of Digital Technologies, FoICDT, University of Mauritius, Réduit, Mauritius
2
Department of Software and Information Systems, FoICDT, University of Mauritius, Réduit, Mauritius
3
Department of Information and Communication Technologies, FoICDT, University of Mauritius, Réduit, Mauritius
allocation and health policy [3]. Disea
Data Loading...
