Prioritizing COVID-19 Contact Tracing During a Surge Using Chatbot Technology

Johnson, Brady D.; Shui, Meg Wall; Said, Kiana; Chavez, Alejandro; Sachdev, Darpun

doi:10.2105/ajph.2021.306563

Cited by 3 publications

(5 citation statements)

References 4 publications

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“…22 To prevent delayed outreach during surges, a new chatbot technology developed by CDPH was implemented to immediately reach out to people newly diagnosed with COVID-19 by text message. 23 Despite the operational challenges of contact tracing, reported data informed the local understanding of transmission networks and guided policies for schools and face masks for people who were fully vaccinated. 24 Vaccine rollout.…”

Section: Strategy 2: Prioritizing Resources In Neighborhoods Highly A...mentioning

confidence: 99%

San Francisco’s Citywide COVID-19 Response: Strategies to Reduce COVID-19 Severity and Health Disparities, March 2020 Through May 2022

et al. 2023

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San Francisco implemented one of the most intensive, comprehensive, multipronged COVID-19 pandemic responses in the United States using 4 core strategies: (1) aggressive mitigation measures to protect populations at risk for severe disease, (2) prioritization of resources in neighborhoods highly affected by COVID-19, (3) timely and adaptive data-driven policy making, and (4) leveraging of partnerships and public trust. We collected data to describe programmatic and population-level outcomes. The excess all-cause mortality rate in 2020 in San Francisco was half that seen in 2019 in California as a whole (8% vs 16%). In almost all age and race and ethnicity groups, excess mortality from COVID-19 was lower in San Francisco than in California overall, with markedly diminished excess mortality among people aged >65 years. The COVID-19 response in San Francisco highlights crucial lessons, particularly the importance of community responsiveness, joint planning, and collective action, to inform future pandemic response and advance health equity.

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Section: Strategy 2: Prioritizing Resources In Neighborhoods Highly A...mentioning

confidence: 99%

San Francisco’s Citywide COVID-19 Response: Strategies to Reduce COVID-19 Severity and Health Disparities, March 2020 Through May 2022

et al. 2023

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“…Finally, there are the chatbot types that contain only 1 article (AI Assistants), (Virtual Assistant), (Health Assistant) (Chatbot that manages information), and (Chatbot with AI, NLP, and NLC)". [25], [27], [29], [40], [46], [47], [55], [ [23], [30], [31], [33], [35], [41], [42], [44], [45], [49], [56]- [58], [ 4.5. Recent work on the processes that optimize a conversational chatbot RQ3.…”

Section: Recent Work On the Types Of Conversational Chatbots That Existmentioning

confidence: 99%

“…: Table 9 shows the processes that the chatbots optimize: according to [24], [27], [42] bots are employed in bot training processes to feed its knowledge base; on the other hand, in [23], [43]- [45], [50], [51], [56], [62], [66]. The use of conversational bots was found to be part of the teaching process [21], [22], [25], [26], [29]- [31], [40], [41], [53], [64], it was realized that healthcare processes have been altered and have incorporated the use of chatbot technology with patients and professionals. Similarly, according to, [39], [46], [61] there is a segment of users who use these bots in Processes for personal assistance for various reasons.…”

Section: Recent Work On the Types Of Conversational Chatbots That Existmentioning

confidence: 99%

“…In this analysis, the application of chatbots in incident management processes has not been identified; however, it has been mentioned that the teaching process (student-delivered course), customer service process (customer-supplier), health process (patient-doctor), processes for personal assistance (assisted-assistant) and even the training of bots (trained-trainer), are carried out by conversational bots; in the case of the Incident Management Process (user-technician), its application is highly necessary and important to increase productivity in this process. [37], [46]- [48], [53], [54], [59], [65] 3 Customer service processes 9 [23], [31], [35], [36], [39], [41], [61], [62], [66] 4 Health processes 11 [24], [25], [28], [29], [32]- [34], [43], [44], [56], [57] 5 Processes for personal assistance 3 [42], [49], […”

Section: Recent Work On the Types Of Conversational Chatbots That Existmentioning

confidence: 99%

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Productivity of incident management with conversational bots-a review

Iparraguirre-Villanueva,

Obregon-Palomino,

Pujay-Iglesias

et al. 2023

IJ-AI

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<p>The use of conversational agents (bots) in information systems managed by company’s increases productivity in the development of activities focused on processes such as customer service, healthcare, and presentation. The present work is a systematic literature review that collects articles from 2019 to 2022 in the databases Scopus, Springer, Willey, Indexes-Csic, Taylor & Francis, Pubmed, and Ebsco Host. PRISMA methodology was used to systematize 47 relevant articles. As a result of the analysis, 2/19 very important benefits were obtained, which are: helping to obtain information and facilitating customer service; as for the types of conversational bots, a total of 9 types were found, of which conversational agents and chatbots with artificial intelligence (AI) are the most common; in the case of processes, 3/5 processes that optimize conversational bots were found, where the most prominent are: teaching process, health processes, and customer service processes. An architecture model for conversational bots in incident management is also proposed.</p>

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“…For example, one study conducted in San Francisco (California, United States) during the COVID-19 pandemic evaluated the use of a chatbot to inform (relatively low-risk) cases about CT-guidelines and -measures, assess their ability to isolate, and elicit at-risk contacts. This study found that, with help from the chatbot, PHS were able to reduce the proportion of cases assigned to a telephone interview by 31.5%, allowing PHPs to direct more resources towards relatively vulnerable communities [ 7 ]. Another study conducted in the United States investigated the perspectives of individuals who recently tested for COVID-19 on using website services for (anonymous) contact notification.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Dutch public health professionals’ intention to use digital contact tracing support tools: A cross-sectional online questionnaire study

Helms,

Stein,

Hamdiui

et al. 2024

PLOS Digit Health

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Contact tracing (CT) can be a resource intensive task for public health services. To alleviate their workload and potentially accelerate the CT-process, public health professionals (PHPs) may transfer some tasks in the identification, notification, and monitoring of contacts to cases and their contacts themselves, using ‘digital contact tracing support tools’ (DCTS-tools). In this study, we aimed to identify determinants of PHPs’ intention to use DCTS-tools. Between February and April 2022, we performed a cross-sectional online questionnaire study among PHPs involved in CT for COVID-19 in the Netherlands. We built three random forest models to identify determinants of PHPs’ intention to use DCTS-tools for the identification, notification, and monitoring of contacts, respectively. The online questionnaire was completed by 641 PHPs. Most respondents had a positive intention towards using DCTS-tools for the identification (64.5%), notification (58%), and monitoring (55.2%) of contacts. Random forest models were able to correctly predict the intention of 81%, 80%, and 81% of respondents to use DCTS-tools for the identification, notification, and monitoring of contacts, respectively. Top-determinants of having a positive intention are the anticipated effect of DCTS-tools on the feasibility and efficiency of CT (speed, workload, difficulty), the degree to which PHPs anticipated that cases and contacts may find it pleasant and may be willing to participate in CT using DCTS-tools, and the degree to which PHPs anticipated that cases and contacts are sufficiently supported in CT when using DCTS-tools. Most PHPs have a positive intention to involve cases and their contacts in the identification, notification, and monitoring stages of the CT-process through DCTS-tools. The identified top-determinants should be prioritized in the (future) development and implementation of DCTS-tools in public health practice. Citizens’ perspectives on the use of DCTS-tools should be investigated in future research.

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Prioritizing COVID-19 Contact Tracing During a Surge Using Chatbot Technology

Cited by 3 publications

References 4 publications

San Francisco’s Citywide COVID-19 Response: Strategies to Reduce COVID-19 Severity and Health Disparities, March 2020 Through May 2022

San Francisco’s Citywide COVID-19 Response: Strategies to Reduce COVID-19 Severity and Health Disparities, March 2020 Through May 2022

Productivity of incident management with conversational bots-a review

Determinants of Dutch public health professionals’ intention to use digital contact tracing support tools: A cross-sectional online questionnaire study

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