Feasibility and Effectiveness of Mobile App for Active Case Finding for Tuberculosis in India

  • Weijia Zhang Wellesley College, Wellesley, MA, USA
  • Mariam E. Dogar Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
  • Monika Jain TSU Quillen College of Medicine, Mountain Home, TN, USA; Collaborative to Eliminate Tuberculosis in India (CETI), Indore, India
  • Edwin Rodriges EC Digital Services, India
  • Sangeeta Pathak Collaborative to Eliminate Tuberculosis in India (CETI), Indore, India
  • Salil Bhargava Collaborative to Eliminate Tuberculosis in India (CETI), Indore, India; MGM Medical College, Indore, India
  • Amar Gupta Computer Science and Artificial Intelligence Labs (CSAIL), Institute of Medical Engineering and Science (IMES); Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
  • Manoj Jain Collaborative to Eliminate Tuberculosis in India (CETI), Indore, India; Rollins School of Public Health, Emory University, Atlanta, GA, USA
Keywords: Actice Cases Finding, Telemedicine, Tuberculosis

Abstract

Background: Tuberculosis (TB) is an infectious disease with 2.8 million cases and 480,000 deaths each year in India. The city of Indore alone with a population of 3.5 million had 7,839 identified TB cases in 2017. However, about two to three thousand additional cases remain unidentified per district officials. The unidentified cases lead to an endemic TB and hamper the efforts of organizations such as The Collaborative to Eliminate TB from India (CETI) to reduce the incidence of TB with the method of Active Case Finding (ACF).1 Previously, 1,332 mobile apps attempted to use technology to overcome the challenge of unreported TB patients in Indian slum areas due to the inaccurate, lost, or unhelpful data collected in ACF; yet the existing apps for TB prevention and treatment possessed minimal functionality. Over a period of 3 months, the CETI developed a mobile data collection app to generate a TB diagnostic survey and to collect data from patient registration form.

Methods: To study the feasibility and effectiveness of the app, a pilot survey was conducted of 163,496 homes covering a population of 828,020 in the slum areas of Indore and Bhopal.

Findings: Between the years of 2018 and 2019, 14,349 pulmonary suspected cases and 4,357 extra pulmonary suspected cases of TB were identified. Among the total of 18,706 cases identified, 7,756 patients (48.1%) had low-grade fever for over 2 weeks, 6,331 patients (39.2%) had persistent cough for more than 2 weeks, 7,693 patients (47.7%) had weight loss, and 251 patients (1.6%) had cough with blood.

Interpretation: This pilot experience shows that an app is a useful tool for TB case recording and follow-up in the field. Further training of the health workers, and more widespread availability and ease of use of mobile phones will be necessary.

Downloads

Download data is not yet available.

References

Collaboration for Elimination of TB (CETI). Collaboration to eliminate tuberculosis in India: TB free India [homepage on the Internet]. CETI; 2020 [cited 2020 Jun 26]. Available from: https://www.tbfree.org/

Ministry of Health & Family Welfare – Government of India. TB India report 2018 [Internet]. [cited 2020 Jun 26]. Available from: https://tbcindia.gov.in/showfile.php?lid=3314

CETI experience.

Active case finding: Systematic screening for active tuberculosis [Internet]. World Health Organization; 2015 [cited 2020 Jun 26]. Available from: https://www.who.int/tb/areas-of-work/laboratory/active-case-finding/en/

Iribarren SJ, Schnall R, Stone PW, Carballo-Diéguez A. Smartphone applications to support tuberculosis prevention and treatment: Review and evaluation [Internet]. JMIR mHealth and uHealth. JMIR Publications; 2016 [cited 2020 Jun 26]. Available from: https://www.ncbi.nlm.nih.gov/pubmed/27177591

Published
2020-08-07
How to Cite
Zhang, W., Dogar, M., Jain, M., Rodriges, E., Pathak, S., Bhargava, S., Gupta, A., & Jain, M. (2020). Feasibility and Effectiveness of Mobile App for Active Case Finding for Tuberculosis in India. Telehealth and Medicine Today, 5(3). https://doi.org/10.30953/tmt.v5.177
Section
Original Research