Design of a Streptococcus suis Meningitis Epidemiological Surveillance Application to Improve Zoonotic Disease Prevention and Control in Bali Province, Indonesia - Putu Putri Agustini; I Made Subrata; I Gusti Ngurah Agung Surya Pratama; I Dewa Agung Ayu Ari Shinta Dewi; Ngakan Putu Anom Harjana; Sang Gede Purnama; Romy Muhammad Dary Mufa (Masters Program in Public Health, 2025)
Background: Streptococcus suis meningitis is an inflammation of the human central nervous system caused by the Streptococcus suis bacterium. The Health Department of Bali Province, Indonesia, reported a total of 7 cases of Streptococcus suis meningitis in Bali Province from January to April 2023, with 2 fatalities. The government has conducted an epidemiological investigation. However, the recording of epidemiological investigation data is still done manually, resulting in inaccurate and untimely data. This study aimed to develop a digital surveillance application for investigating Streptococcus suis meningitis based on Figma and Kobo Toolbox. Subjects and Method: This was a design-based study using the Design Science Research Method (DSRM), conducted across all nine districts and cities in Bali Province. The target users were public health surveillance officers. A total of 130 respondents participated in the user acceptance evaluation. The application prototype was developed using Figma, and data collection forms were designed via Kobo Toolbox. The study evaluated application acceptance using the Technology Acceptance Model (TAM), which includes the following dependent variables: timeliness, information completeness, information accuracy, accessibility, usefulness, and ease of use. Data were analyzed descriptively. Results: The results showed high user acceptance of the application, with mean percentages as follows: timeliness (85.8%), information completeness (86.8%), information accuracy (84.6%), accessibility (86.2%), usefulness (84.7%), and ease of use (81.9%). Conclusion: The digital application for epidemiological surveillance of Streptococcus suis meningitis demonstrated good acceptance among users. Its implementation could improve the accuracy and efficiency of data collection, potentially enhancing the response time and decision-making in zoonotic disease control.