Lessons From the Implementation of Mo-Buzz, a Mobile Pandemic Surveillance System for Dengue

Abstract

BackgroundApproximately 128 countries and 3.9 billion people are at risk of dengue infection. Incidence of dengue has increased over the past decades, becoming a growing public health concern for countries with populations that are increasingly susceptible to this vector-borne disease, such as Sri Lanka. Almost 55,150 dengue cases were reported in Sri Lanka in 2016, with more than 30.40% of cases (n=16,767) originating from Colombo, which struggles with an outdated manual paper-based dengue outbreak management system. Community education and outreach about dengue are also executed using paper-based media channels such as pamphlets and brochures. Yet, Sri Lanka is one of the countries with the most affordable rates of mobile services in the world, with penetration rates higher than most developing countries.ObjectivesTo combat the issues of an exhausted dengue management system and to make use of new technology, in 2015, a mobile participatory system for dengue surveillance called Mo-Buzz was developed and launched in Colombo, Sri Lanka. This paper describes the system’s components and uptake, along with other similar disease surveillance systems.MethodsWe developed Mo-Buzz and tested its feasibility for dengue. Two versions of the app were developed. The first was for use by public health inspectors (PHIs) to digitize form filling and recording of site visit information, and track dengue outbreaks on a real-time dengue hotspot map using the global positioning system technology. The system also provides updated dengue infographics and educational materials for the PHIs to educate the general public.The second version of Mo-Buzz was created for use by the general public. This system uses dynamic mapping to help educate and inform the general public about potential outbreak regions and allow them to report dengue symptoms and post pictures of potential dengue mosquito–breeding sites, which are automatically sent to the health authorities. Targeted alerts can be sent to users depending on their geographical location.ResultsWe assessed the usage and the usability of the app and its impact on overall dengue transmission in Colombo. Initial uptake of Mo-Buzz for PHIs was low; however, after more training and incentivizing of usage, the uptake of the app in PHIs increased from less than 10% (n=3) to 76% (n=38). The general public user evaluation feedback was fruitful in providing improvements to the app, and at present, a number of solutions are being reviewed as viable options to boost user uptake.ConclusionsFrom our Mo-Buzz study, we have learned that initial acceptance of such systems can be slow but eventually positive. Mobile and social media interventions, such as Mo-Buzz, are poised to play a greater role in shaping risk perceptions and managing seasonal and sporadic outbreaks of infectious diseases in Asia and around the world.

Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats

“…“FluTracking,” which has been very successful in growing and maintaining a large volunteer network, has employed a number of tactics where they have found success; these include using friend-referral emails, inviting users to report for household members, and refraining from the use of barriers such as usernames and passwords [48]. “Mo-Buzz” incentivizes reports that were submitted by public health inspectors (PHIs), with the total number of reports submitted by an investigator contributing toward their yearly performance bonuses and pay increments [49]. “Flu Near You” has experimented with paid marketing efforts and social media campaigns with some success.…”

The Use of Mobile Phones for the Prevention and Control of Arboviral Diseases: A Scoping Review

“…However, we identi ed that providing mobile phones was probably unnecessary strategy to improve outcomes (Olso et al, Toda et al, 2017). Perceptions related to costs and mistrust that might to be related with the initial low uptake (Patil et al, 2016;Lwin et al, 2017).…”

“…mobile data plan), mobile phone features (less storage space, slow internet connection), lack of interest and ignorance regarding purpose of mobile phone intervention were associated with a proportion of users who did not use it(Patil et al, 2016). Fear and mistrust of adopting a new technology were other reasons for low usability, perceived by health staff in Mo-buzz(Lwin et al, 2017). Other external factors such as period of high staff turnover, cellular tower collapse and socio-politic events were associated with a decreased reporting (Olso et al 2017).Costs Cost calculations were done in different ways.…”

“…Most mobile applications showed a good proportion of active users out of all participants who downloaded the app (Rodrigo-Valero et al, 2018; Leal Neto et al,Patil et al, 2016), but some researchers thought more incentives, educational campaigns and constant communication between users and study personal were needed to keep them motivated (Olso et al, Lwin et al, 2017 Leal Neto et al, 2017). Some concerns related to additional expenses of mobile technology (e.g.…”

Epidemic Alert System: A Web-based Grassroots Model

“…The lessons learned from the various implementations of web-based disease surveillance systems can be seen in the article written by MO Lwin et al of how Mo-Buzz [23], a mobile pandemic surveillance system for Dengue was implemented in Colombo, Sri Lanka. The mobile application was developed to take advantage of Sri Lanka"s large mobile device using population.…”