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• What are the user ratings for different vaccination apps?
Prototyped response:
The user ratings for different vaccination apps vary. Among the 29 eligible apps, the largest percentage of apps with a user star rating of 4-5 were on Android (56%), followed by iOS (46%). For Android, 44% of the apps had more than 10 million downloads. The user ratings reflect that most users were satisfied with these apps. However, users expressed dissatisfaction with privacy aspects and had mixed feelings about content, functionality, experience, and service attitude.• How does the MARS score relate to user ratings?
Prototyped response:
The MARS (Mobile Application Rating Scale) score has significant correlations with user ratings. Specifically:
– There is a significant correlation between the app rating and the subjective quality score (r=0.47; P=.006).
– There is a significant correlation between the app quality score and the subjective quality score (r=0.816; P<.001). These correlations indicate that higher MARS scores, which assess aspects like engagement, functionality, aesthetics, and information, tend to align with higher user ratings. This suggests that apps rated highly on the MARS scale are generally well-received by users. • What factors influence user satisfaction with vaccination apps? Prototyped response: User satisfaction with vaccination apps is influenced by several factors, as identified in the document: 1. Content: Users appreciate rich medical knowledge provided by the apps but are dissatisfied with issues like lost user data and difficulties in accessing vaccination records. 2. Functionality: Positive feedback is given for features like vaccination appointments and educational content. However, users are dissatisfied with forced updates, app crashes, and poor customer service features. 3. Experience: Users value the convenience of online consultations and medical appointment management. Negative experiences include unreliable registered hospitals and poor customer service. 4. Service Attitude: Users rate the professionalism and efficiency of doctors positively but express dissatisfaction with slow and perfunctory responses to queries. 5. Privacy: Users are concerned about the security of their personal information, excessive permissions required by the apps, and issues like altered vaccination records. Overall, while users find certain aspects of vaccination apps helpful, there are significant concerns regarding privacy, functionality, and customer service that need to be addressed to improve user satisfaction. • What role does privacy play in user evaluations? Prototyped response: Privacy plays a significant role in user evaluations of vaccination apps. Users express dissatisfaction with the privacy aspects of these apps due to several concerns: 1. Excessive Permissions: Users are wary of apps that require too many permissions, which raises concerns about the security of their personal information. 2. Personal Information Security: There are worries about the leakage of personal information, with some users reporting issues like receiving unexpected SMS notifications or altered vaccination records. 3. Trust and Security: Users are concerned about the reliability and security of their data, which affects their overall trust in the app. Overall, privacy concerns are a major factor in user evaluations, and addressing these issues is crucial for improving user satisfaction and trust in vaccination apps. -
What are potential follow-up studies on mobility patterns?
Potential follow-up studies on mobility patterns could include:
1. Second Wave Monitoring: Investigating mobility patterns after the relaxation of lockdown measures to assess the risk of a second wave of COVID-19 transmission.
2. Long-Term Mobility Trends: Examining how mobility patterns evolve over a longer period post-pandemic, particularly in rural and border areas.
3. Impact of Socioeconomic Factors: Studying how socioeconomic status influences mobility changes during and after government restrictions.
4. Cross-Border Movement Analysis: Conducting detailed studies on cross-border mobility to understand its role in disease transmission and the effectiveness of border control measures.
5. Occupation-Based Mobility: Exploring mobility patterns specific to different occupations, especially public health personnel, to optimize their role in disease prevention.How did government restrictions affect mobility patterns?
Government restrictions had a significant impact on mobility patterns in the rural border area of Northern Thailand:
1. Reduction in Radius of Gyration (RoG): The median RoG decreased by more than 90% during the lockdown period (Interval 4), indicating a dramatic reduction in the distance traveled by individuals.
2. Decrease in Cross-Border Movement: Cross-border trips from Thailand to Myanmar dropped significantly, with the percentage of participants taking such trips reducing from 38.8% in the pre-COVID period (Interval 1) to 9.8% after the closure of the Friendship Bridge.
3. Shift in Travel Patterns: During the lockdown, most cross-border trips were short-distance, and long trips were almost eliminated.What were the main findings on mobility after restrictions eased?
After restrictions eased (Interval 5), the study found the following main findings on mobility:
1. Quick Rebound in Mobility: Human mobility nearly returned to normal levels, with the radius of gyration (RoG) increasing to levels even higher than during Interval 2 (first publicized COVID cases).
2. Increase in Long Trips: The number of long trips outside participants’ home villages increased compared to the lockdown period (Interval 4).
3. Resumption of Cross-Border Movement: Cross-border trips to Myanmar resumed, though the number of trips remained lower than in the pre-COVID period (Interval 1). -
Thank you to you all for participation!
Seems every response are right and here are my prototyped responses to those questions.• What factors influenced participant engagement in the study?
Prototyped response:
Several factors influenced participant engagement in the study:
1. Ease of Use: The web-based notification platform was found to be easier to use compared to the mobile app, which likely contributed to higher engagement among web-based users.
2. Technological Literacy: Participants aged 30-39 years had the highest response rate in the mobile app group, possibly due to higher technological literacy and comfort with mobile apps. Conversely, older adults (>65 years) had the lowest response rate, potentially due to less comfort with mobile apps or difficulty reading smaller fonts.
3. Complexity of Registration: Mobile app users were required to download the app and register their account, which added complexity and likely served as a barrier to engagement.
4. Reminder Emails: The implementation of additional reminder emails improved survey completion rates in the mobile app arm, indicating that reminders played a significant role in participant engagement.
5. Usability Survey: The usability survey was provided as a separate email link after the safety survey, which may have been missed by users, affecting the assessment of user experience and engagement.
Overall, the web-based notification platform’s simplicity and ease of access were key factors that influenced higher participant engagement compared to the mobile app.• What barriers did mobile app users face?
Prototyped response:
Mobile app users faced several barriers:
1. Complexity of Registration: Users had to download the app and register their account, which added an extra step and complexity, likely deterring participation.
2. Technological Literacy: Older adults (>65 years) had lower response rates, possibly due to less comfort with mobile apps or difficulty reading smaller fonts.
3. Usability Issues: The mobile app may not have been optimally designed for usability across all target demographics, making it challenging to navigate.
4. Low Registration Numbers: Many participants did not register for the app, indicating that the registration process itself was a significant barrier.
5. Preference for Email Links: A large majority of mobile app users who completed the survey chose to use the direct link provided in reminder emails rather than registering for the app.
These barriers contributed to lower engagement and completion rates among mobile app users compared to web-based notification platform users.• How did the web-based platform compare to the mobile app?
Prototyped response:
The web-based platform compared favorably to the mobile app in several ways:
1. Completion Rates: The web-based notification platform had a higher survey completion rate (64%) compared to the mobile app (45%).
2. Ease of Use: Web-based platform users reported high ease-of-use ratings, with 99% agreeing or strongly agreeing that the platform was easy to use.
3. User Experience: 88.8% of web-based platform users felt that the system made reporting adverse events following immunization (AEFIs) easier.
4. Perceived Usefulness: A significant majority (91.4%) of web-based platform users agreed or strongly agreed that the system could make it easier for public health professionals to detect vaccine safety issues.
5. Response Time: The mean response time for the day 8 survey was slightly shorter for web-based platform users (10.1 days) compared to mobile app users (10.7 days).
Overall, the web-based platform was more effective and user-friendly, leading to higher engagement and satisfaction among participants compared to the mobile app. -
1. What were the significant benefits reported by the studies?
Prototyped response:
The systematic review found that out of the 28 studies evaluating 25 apps, 4 studies reported significant benefits in improving vaccination uptake. These studies showed increases in vaccination rates after the implementation of the app:
EPI app: Reported a 17% increase in vaccination rates (P=.03).
Carrot Rewards app: Reported a 5% increase in vaccination rates (P<.001). Mother and Child Care Module-EPI module: Reported a 9.7% increase in vaccination rates (P<.001). mTika app: Reported a 17.9% increase in rural areas and a 16.4% increase in urban areas (P<.001 for both). Additionally, 4 studies indicated significant improvements in vaccination knowledge or learning (P≤.05), and 4 studies reported significant improvements in vaccination decision making (P≤.05). These findings suggest that while some apps showed significant benefits in specific areas, overall evidence supporting the effectiveness of childhood vaccination apps remains limited. 2. How did apps affect vaccination uptake rates?
Prototyped response:
The systematic review found that 9 studies assessed the impact of apps on vaccination uptake rates. Among these, 4 studies reported significant improvements:
EPI app: Reported a 17% increase in vaccination rates (P=.03).
Carrot Rewards app: Reported a 5% increase in vaccination rates (P<.001). Mother and Child Care Module-EPI module: Reported a 9.7% increase in vaccination rates (P<.001). mTika app: Reported a 17.9% increase in rural areas and a 16.4% increase in urban areas (P<.001 for both). Additionally, the mTika app study identified a significant difference-in-difference estimate between the intervention and control groups, showing a 21.6% rural and 23.2% urban difference (P<.05). Conversely, 2 studies reported no significant benefit, and 3 studies did not indicate a significance level regarding an increase in vaccination rates. Overall, while some apps demonstrated significant benefits in improving vaccination uptake, the evidence remains limited and further research is needed to confirm these findings in larger, more robust studies. 3. How did the apps influence vaccination decision making?
Prototyped response:The systematic review found that the apps had a positive impact on vaccination decision making in several studies. Specifically:
Fadda et al. : Exposure to the knowledge intervention significantly improved the intent to vaccinate (P=.03) and confidence in the participants’ vaccination decision (P=.006) versus control.
Baldwin et al. : Reported significant improvements in the intent to vaccinate children and positive attitudes toward vaccination after interaction with the app.
Gockley et al.: Found significant improvements in vaccination beliefs and intent to vaccinate compared with a control group.
Kaewkungwal et al. : Indicated significant improvements in confidence in vaccination decision making after using the app.
Overall, 7 out of 8 studies reporting on vaccination decision making indicated a positive impact of the apps on vaccination beliefs and intent to vaccinate. However, 3 studies also noted the potential for apps to discourage vaccination among users who were initially undecided or had previously intended to vaccinate their children. This highlights the importance of understanding how vaccination information is interpreted by users and its potential dichotomous effects. 4. How do user perceptions of vaccination apps vary?
Prototyped response:
User perceptions of vaccination apps were generally positive across the studies included in the systematic review. Specifically:
Positive Experiences: All 10 studies reporting quantitative results indicated positive user experiences. Participants considered the apps helpful, trustworthy, and reported satisfaction, confidence, and likelihood to recommend the app (average score of >70%, or >70% of participants agreeing with relevant statements).
Qualitative Feedback: The study on the mTika app revealed that mothers and vaccination service providers found the app helpful, user-friendly, time-efficient, and beneficial in reducing the workload of service providers.
Specific Features: Users appreciated features such as vaccination tracking, appointment reminders, and access to vaccination information. For example, the ImmunizeCA app’s tracking function was accessed in 47.6% of all app sessions, indicating its popularity.
Overall, user perceptions of vaccination apps were positive, with high usability and acceptability scores, suggesting that these apps are well-received and considered beneficial by their users. -
Pneumococcal disease modeling
The model divides the total population(N) into six sub-classes according to their disease status. susceptible S(t), vaccinated V(t), infected I(t), and recovery R(t).
The total population size: N = V+S+I+R
SVIR model
Here is the link for table; https://1drv.ms/w/s!AjwS_uCrdS0jg_sI48FLeMyEWx3YLw?e=BPw4sA -
Topic: A 13-valent pneumococcal vaccine (Prevnar 13®) implementation in Thai elderly
Invasive pneumococcal disease in elderly is preventable by vaccine in high income countries. However, this vaccine is not provided by Thai national immunization program according to high cost.Rationale: Previous studies on economic evaluation of pneumococcal vaccine in Thailand based on static rather than infectious modeling approach.
Research question: Is it worth to implement a 13-valent pneumococcal vaccine in Thai societal perspectives based on infectious modelling approach?
References:
– Kulpeng W, Leelahavarong P, Rattanavipapong W, et al. Cost-utility analysis of 10- and 13-valent pneumococcal conjugate vaccines: protection at what price in the Thai context? Vaccine. 2013;31(26):2839-47.
– Dilokthornsakul P, Kengkla K, Saokaew S, et al. An updated cost-effectiveness analysis of pneumococcal conjugate vaccine among children in Thailand. Vaccine. 2019;37(32):4551-60.
– Ounsirithupsakul T, Dilokthornsakul P, Kongpakwattana K, Ademi Z, Liew D, Chaiyakunapruk N. Estimating the Productivity Burden of Pediatric Pneumococcal Disease in Thailand. Appl Health Econ Health Policy. 2020;18(4):579-87. -
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I love your idea about scrub typhus. Most of patients are empirically treated with doxycycline which leads to under diagnosis. Most of patients dramatically clinical improve after 2-3 days of medication. The key of your system is how to make definite diagnosis of scrub typhus. The limitation of IFA is positive after 1-2 weeks of clinical onset. Therefore, your system might delay to detect the outbreak. In addition, most rapid test to detect scrub typhus is not valid. Eventually, we need early definite case detection to make your system achievement.
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This is very interesting system because hypertension is classified as silent killer. Your system would help a lot of Thais who do not recognize their health status. I recommend that your system may initially apply for outpatient clinic internal medicine. All population are adult, mostly age more than 18 years. Since hypertension in children or pregnancy need distinct treatment. Also, syndromic surveillance can be integrated to yours. A few of patients visit hospital when they have symptoms such as headache, stroke or heart failure. Lastly, active surveillance might be better when we can early detect patients finding in their village or home.
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Your presentation is Great!, comprehensive, informative and complete. Additionally, for legal consideration, I consider about data permission. We need to ask inform and consent with their parents. Case definition, I assume that “probable case” is not consist of laboratory result. If the test show positive with clinical suspicious, it could be definite case.
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