An Integrated mHealth App for Dengue Reporting and Mapping, Health Communication, and Behavior Modification: Development and Assessment of Mozzify

A smartphone-based crowd-sourced real-time surveillance platform (apple snail inspector) for the invasive snails: a design and development study

BACKGROUND

The large amphibious freshwater apple snail is an important invasive species in China, but there is currently no method available for their surveillance. The development and popularization of smartphones provide a new platform for research on surveillance technologies for the early detection and effective control of invasive species.

METHODS

The ASI surveillance system was developed based on the infrastructure of the WeChat platform and Amap. The user can directly enter the game interface through the WeChat port on their mobile phone, and the system automatically obtains their location. The user can then report the location of apple snails. The administrator can audit the reported information, and all information can be exported to Microsoft Excel version 2016 for analysis. The map was generated by ArcGIS 10.2 and was used to characterize the spatial and temporal distribution of apple snails in Jiangsu Province.

RESULTS

The architecture of ASI consists of three parts: a mobile terminal, a server terminal and a desktop terminal. We published more than 10 tweets on the official WeChat account of the system to announce it to the public, and a total of 207 users in 2020 and 2021 correctly reported sightings of apple snails. We identified 550 apple snails breeding sites in 2020 and 2021, featuring ponds (81%), parks (17%) and farmland (2%). In addition, most of the locations contained snail eggs, and the reporting times mainly occurred between May and September.

CONCLUSIONS

The ASI is an effective surveillance system that can be used to identify the breeding locations of apple snails and provides the basis of prevention and control for its dispersal. Its successful development and operation provide new potential avenues for surveillance of other public health issues.

Feasibility and acceptability of a dengue self-monitoring system to reduce treatment delay in Malaysia: A single-centre pilot randomised controlled trial

Objective

Most dengue cases are managed in an outpatient setting, where patients are advised to return to the clinic daily for monitoring. Some patients can develop severe dengue at home and fail to recognise the deterioration. An application called DengueAid was designed as a self-monitoring tool for patients to reduce delay in seeking timely treatment. This study aimed to assess the feasibility of conducting a randomised controlled trial to determine the effectiveness of the DengueAid application.

Methods

Dengue patients were recruited from a public health clinic in Malaysia and randomised to either use the DengueAid application plus standard care for dengue or receive only the standard care. The outcomes evaluated were the (1) feasibility of recruitment, data collection and follow-up procedures; (2) preliminary clinical outcome measures; and (3) acceptability of DengueAid. Qualitative interviews were conducted for participants in the intervention arm to assess the acceptability of DengueAid.

Results

Thirty-seven patients were recruited with 97% (n = 36) retention rates. The recruitment rate was low (63% refusal rate, n = 62/99) with difficulty in data collection and follow-up due to the variable interval of care for dengue in an outpatient setting. DengueAid application was acceptable to the participants, but preliminary clinical outcomes and qualitative data suggested limited utility of the application. Unwell conditions of patients and limited access to healthcare are important factors impacting the application's utility.

Conclusion

The feasibility trial uncovered issues with recruitment, data collection and follow-up processes. Further research and modification to the application are needed to improve its utility and usability.

Detecting dengue fever in children using online Rasch analysis to develop algorithms for parents: An APP development and usability study

BACKGROUND

Dengue fever (DF) is a significant public health concern in Asia. However, detecting the disease using traditional dichotomous criteria (i.e., absent vs present) can be extremely difficult. Convolutional neural networks (CNNs) and artificial neural networks (ANNs), due to their use of a large number of parameters for modeling, have shown the potential to improve prediction accuracy (ACC). To date, there has been no research conducted to understand item features and responses using online Rasch analysis. To verify the hypothesis that a combination of CNN, ANN, K-nearest-neighbor algorithm (KNN), and logistic regression (LR) can improve the ACC of DF prediction for children, further research is required.

METHODS

We extracted 19 feature variables related to DF symptoms from 177 pediatric patients, of whom 69 were diagnosed with DF. Using the RaschOnline technique for Rasch analysis, we examined 11 variables for their statistical significance in predicting the risk of DF. Based on 2 sets of data, 1 for training (80%) and the other for testing (20%), we calculated the prediction ACC by comparing the areas under the receiver operating characteristic curve (AUCs) between DF + and DF- in both sets. In the training set, we compared 2 scenarios: the combined scheme and individual algorithms.

RESULTS

Our findings indicate that visual displays of DF data are easily interpreted using Rasch analysis; the k-nearest neighbors algorithm has a lower AUC (<0.50); LR has a relatively higher AUC (0.70); all 3 algorithms have an almost equal AUC (=0.68), which is smaller than the individual algorithms of Naive Bayes, LR in raw data, and Naive Bayes in normalized data; and we developed an app to assist parents in detecting DF in children during the dengue season.

CONCLUSION

The development of an LR-based APP for the detection of DF in children has been completed. To help patients, family members, and clinicians differentiate DF from other febrile illnesses at an early stage, an 11-item model is proposed for developing the APP.

Has Zika Been Forgotten? Findings From Nationwide Survey on Knowledge, Attitudes, and Mosquito Preventive Practices in Malaysia

OBJECTIVE

The aim of this study is to assess knowledge and attitudes toward Zika virus disease (ZVD) as well as mosquito prevention practices in Malaysia at a nationwide level.

METHODS

Computer-assisted telephone interviews (CATI) were conducted between June 2019 and February 2020.

RESULTS

There are gaps in knowledge about the symptoms, mode of transmission, and risk of microcephaly. The mean for the Zika-related knowledge score was 5.9 (SD ± 4.4) out of a possible score of 14. The majority perceived little or no risk of getting ZVD (75.0%) and 75.5% were a little or not at all worried about ZVD. A high proportion reported the use of insect sprays or mosquito coils to prevent mosquito bites; however, a relatively lower proportion of people reported fixing mosquito netting on doors and windows, and using mosquito bed nets. The mean for the mosquito prevention practices score was 11.9 (SD ± 4.7) out of a possible score of 27. Important factors influencing mosquito prevention practices include household income, environment factors, risk perception, and Zika-related knowledge.

CONCLUSION

Zika prevention measures should be targeted in priority toward residents in lower socioeconomic neighborhoods. Campaigns should focus on messages highlighting the high risk of getting dengue.

An Innovative App (ExoDont) for Postoperative Care of Patients After Tooth Extraction: Prototype Development and Testing Study

BACKGROUND

The postoperative period is crucial for the initiation of healing and prevention of complications after any surgical procedure. Due to factors such as poor compliance, comprehension, and retention of instructions, and other unaccounted factors, the objectives of postoperative care are not always achieved. Therefore, an Android-based mobile health app (ExoDont) was developed to ensure a smooth postoperative period for patients after a dental extraction. The ExoDont app delivers reminders for postoperative instructions and drug intake at defined intervals, thus fostering self-reliance among patients in taking their prescribed dose of medication.

OBJECTIVE

The aim of this study is to design, develop, and validate ExoDont, an innovative app for improved adherence to postoperative instructions after tooth extraction.

METHODS

A postoperative treatment protocol was developed by a team of oral and maxillofacial surgeons and general dentists, following which the clinical and technological requirements of the app were determined along with the software engineers, graphic designers, and applications architect in the team. ExoDont was developed to provide timely reminders for medication and postoperative care. The app was field tested and validated using the User Version of the Mobile Application Rating Scale.

RESULTS

The ExoDont software design was divided into a 3-level architecture comprising a user interface application, logical layer, and database layer. The software architecture consists of an Android-based ExoDont app for patients and a web version of the admin panel. The testing and validation of the ExoDont app revealed that Perceived Impact received the highest mean score of all rated components (mean 4.6, SD 0.5), while Engagement received the lowest mean score (mean 3.5, SD 0.8).

CONCLUSIONS

The testing and validation of the app support its usability and functionality, as well as its impact on users. The ExoDont app has been designed, keeping the welfare of patients in view, in a user-friendly manner that will help patients adhere to the prescribed drug regimen and ensure easy and efficient dissemination of postoperative instructions. It could play an instrumental role in fostering compliance among patients and significantly decrease the complication rate following dental extractions.

Potential Development of Digital Environmental Surveillance System in Dengue Control: A Qualitative Study

Background: The development of digital environmental technology can be conducted to implement reports, surveillance, and manage dengue control. Therefore, this study aims to determine the barriers to the use of paper-based and the potential development of digital environmental technology in dengue control.   Methods In-depth qualitative interviews were conducted using 14 key informants and four focus group discussions (FGD) from May-August 2021 in Denpasar City, Bali. The interviews were consistent with the flow of the epidemiological and entomological surveillance system, the obstacles to the dengue control program, the potential for the application of digital technology, and the challenges in the application of digital surveillance technology. Furthermore, open-ended questions and content analysis by qualitative study procedures were adopted. The results were transcribed verbatim and triangulation of sources was conducted for data validation.   Results The reporting system that used paper-based was not optimally implemented due to repetition of reporting, speed of information, data bias, performance measurement as well as case surveillance and reporting system constraints. An integrated digital environmental surveillance system (SILIRA) was also developed for dengue control. In the current Covid-19 pandemic, the need for digital applications is high due to the policy of not accepting guests and keeping a distance. Epidemiological surveillance for case data collection, entomological surveillance for larva density, case reporting, and educational videos are the required data in the application.   Conclusion The development of an integrated application for an environmental monitoring system can be created for the continuous reporting of case information and larval density for dengue hemorrhagic fever control. Keywords: digital, surveillance, environment, dengue  

Sociodemographic Characteristics and Interests of FeverApp Users

The FeverApp Registry is a model registry focusing on pediatric fever using a mobile app to collect data and present recommendations. The recorded interactions can clarify the relationship between user documentation and user information. This initial evaluation regarding features of participants and usage intensity of educational video, information library, and documentation of fever events covers the runtime of FeverApp for the first 14 months. Of the 1592 users, the educational opening video was viewed by 41.5%, the Info Library was viewed by 37.5%, and fever events were documented by 55.5%. In the current sample, the role of a mother (p < 0.0090), having a higher level of education (p = 0.0013), or being registered at an earlier date appear to be cues to take note of the training video, Info Library, and to document. The FeverApp was used slightly less by people with a lower level of education or who had a migration background, but at the current stage of recruitment no conclusion can be made. The user analyses presented here are plausible and should be verified with further dissemination of the registry. Ecological momentary assessment is used more than the information option, in line with the task of a registry. Data collection via app seems feasible.

Early Detection of Dengue Fever Outbreaks Using a Surveillance App (Mozzify): Cross-sectional Mixed Methods Usability Study

Background

While early detection and effective control of epidemics depend on appropriate surveillance methods, the Philippines bases its dengue fever surveillance system on a passive surveillance method (notifications from barangay/village health centers, municipal or city health offices, hospitals, and clinics). There is no available mHealth (mobile health) app for dengue fever that includes all the appropriate surveillance methods in early detection of disease outbreaks in the country.

Objective

This study aimed to evaluate the usability of the Mozzify app in terms of objective quality (engagement, functionality, aesthetics, information) and app subjective and app-specific qualities and compare total app mean score ratings by sociodemographic profile and self and family dengue fever history to see what factors are associated with high app mean score rating among school-based young adult samples and health care professionals. Individual interviews and focus group discussions were also conducted among participants to develop themes from their comments and suggestions to help structure further improvement and future development of the app.

Methods

User experience sessions were conducted among participants, and the Mobile Application Rating Scale (MARS) professional and user versions (uMARS) were administered followed by individual interviews and focus group discussions. Descriptive statistical analysis of the MARS and uMARS score ratings was performed. The total app mean score ratings by sociodemographic and dengue fever history using nonparametric mean difference analyses were also conducted. Thematic synthesis was used to develop themes from the comments and suggestions raised in individual interviews and focus group discussions.

Results

Mozzify obtained an overall >4 (out of 5) mean score ratings in the MARS and uMARS app objective quality (4.45), subjective (4.17), and specific (4.55) scales among 948 participants (79 health care professionals and 869 school-based samples). Mean difference analyses revealed that total app mean score ratings were not significantly different across ages and gender among health care professionals and across age, income categories, and self and family dengue fever history but not gender (P<.001) among the school-based samples. Thematic syntheses revealed 7 major themes: multilanguage options and including other diseases; Android version availability; improvements on the app’s content, design, and engagement; inclusion of users from low-income and rural areas; Wi-Fi connection and app size concerns; data credibility and issues regarding user security and privacy.

Conclusions

With its acceptable performance as perceived by health care professionals and school-based young adults, Mozzify has the potential to be used as a strategic health intervention system for early detection of disease outbreaks in the Philippines. It can be used by health care professionals of any age and gender and by school-based samples of any age, socioeconomic status, and dengue fever history. The study also highlights the feasibility of school-based young adults to use health-related apps for disease prevention.