The Role of Telehealth in Disaster Management: Lessons for the Philippines

According to the WorldRiskIndex 2016, the Philippines is the third country most at risk of disasters in the world. Typhoon Haiyan, the strongest on local record, caused widespread destruction to life and property. Current disaster management strategies in the country do not include telehealth as a formal tool in disaster mitigation, response, or recovery. This study reviewed research incorporating telehealth in disaster management from multiple low and lower middle income countries like the Philippines to address this gap by identifying lessons the country might be able to adopt. Studies show that most initiatives centre on evaluating telehealth’s effectiveness during the response phase. Unsurprisingly, mobile technology and satellite communications predominated, and most projects were launched using donor funding. Use of telehealth in disaster management in the Philippines could begin by recognising and including telehealth in formal government protocols. The government could leverage the National Telehealth Service Program of the University of the Philippines National Telehealth Center. Documentation and systematic research on telehealth’s expected positive contributions to disaster preparedness and response should also be initiated

General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review

BackgroundA conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services during the COVID-19 pandemic. However, the multitude of conversational agents explicitly designed during the COVID-19 pandemic calls for characterization and analysis using rigorous technological frameworks and extensive systematic reviews. ObjectiveThis study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework. MethodsWe conducted a systematic review of the general characteristics and design taxonomy of COVID-19 chatbots, with 56 studies included in the final analysis. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to select papers published between March 2020 and April 2022 from various databases and search engines. ResultsResults showed that most studies on COVID-19 chatbot design and development worldwide are implemented in Asia and Europe. Most chatbots are also accessible on websites, internet messaging apps, and Android devices. The COVID-19 chatbots are further classified according to their temporal profiles, appearance, intelligence, interaction, and context for system design trends. From the temporal profile perspective, almost half of the COVID-19 chatbots interact with users for several weeks for >1 time and can remember information from previous user interactions. From the appearance perspective, most COVID-19 chatbots assume the expert role, are task oriented, and have no visual or avatar representation. From the intelligence perspective, almost half of the COVID-19 chatbots are artificially intelligent and can respond to textual inputs and a set of rules. In addition, more than half of these chatbots operate on a structured flow and do not portray any socioemotional behavior. Most chatbots can also process external data and broadcast resources. Regarding their interaction with users, most COVID-19 chatbots are adaptive, can communicate through text, can react to user input, are not gamified, and do not require additional human support. From the context perspective, all COVID-19 chatbots are goal oriented, although most fall under the health care application domain and are designed to provide information to the user. ConclusionsThe conceptualization, development, implementation, and use of COVID-19 chatbots emerged to mitigate the effects of a global pandemic in societies worldwide. This study summarized the current system design trends of COVID-19 chatbots based on 5 design perspectives, which may help developers conveniently choose a future-proof chatbot archetype that will meet the needs of the public in the face of growing demand for a better pandemic response