Epidemiological investigation support application and user evaluation based on infectious disease self-management model in the endemic era

Abstract

Objectives: Rapid epidemiological investigations are fundamental to prevent the spread of infectious diseases such as coronavirus disease 2019. An epidemiological investigation presents significant challenges for both epidemiologists and infected individuals. It requires creating an environment that enables people to independently manage infectious diseases and voluntarily participate in epidemiological investigations. Methods: We developed the KODARI application, an epidemiological investigation support system that users can voluntarily use. We developed the questionnaires based on literature reviews. We evaluated the application through an online survey from December 2 to 14, 2022. Results: The application automatically or manually collect epidemiological investigation information. The application improved data accuracy through accurate information collection. It voluntarily can transmit self-management information to epidemiologist terminals or users in real time. We collected 248 users from an online survey. Most users had high ratings and willingness to use. They have willingness to manage infectious patients was substantial. The application was evaluated as helpful for epidemiological investigations and could shorten the time required for epidemiological investigations by more than 30 min. Conclusion: The application proposes a model based on people’s voluntary participation. We demonstrated that the application could enhance epidemiological investigations and diminish the duration of existing epidemiological investigation processes.

Keywords

application coronavirus disease 2019 epidemiological investigations infectious diseases infectious disease self-management model

Introduction

In the case of a first-class infectious disease such as coronavirus disease 2019 (COVID-19), epidemiological investigations take much time and present difficulties. An epidemiological investigation is a difficult task for both epidemiologists and infected individuals. If an infectious disease is suspected, it is essential to conduct an epidemiological investigation. Individuals are expected to recall and report their contact route during the assumed infection period.¹ They should also provide their demographic and clinical characteristics to epidemiologists. While rapid epidemiological investigations are crucial, it is often challenging for subjects to remember details about their movement and infection during the disease’s incubation period. This epidemiological investigation has the disadvantage of relying only on data from infected people. Accordingly, it has limitations in terms of a lack of real-time data updates, misinformation, and manual data collection and analysis. Therefore, it is necessary to establish an environment where people can manage infectious diseases independently and actively participate in epidemiological investigations.²

Since the outbreak of COVID-19, various digital contact tracing technologies have been developed to prevent and control the spread of existing infectious diseases.^3–10 This technology verifies information regarding an infectious disease risk area and an infected individual, records the contaminated area data, tracks the location, and compares this location with the data on the infectious disease-contaminated area. When the location corresponds to an infectious disease-contaminated area, it is designed to receive the log record from a mobile terminal that sends the visitation log of the infectious disease-contaminated area. While these technologies may aid in epidemic control mechanisms,¹¹ they are limited by their inability to provide detailed accurate state information about the user. Additionally, there are difficulties in contact tracing and monitoring due to a lack of voluntary participation and misinformation.¹² Although it is possible to build extensive data sets corresponding to location, data related to state information may only be partially collected based on the selected state information. Therefore, challenges arise in constructing and generating comprehensive big data and maintaining accuracy regarding the status of infectious disease patients. Consequently, the effectiveness of these technologies is still controversial and needs more empirical studies.^13,14

Therefore, we developed an epidemiological investigative support application based on an infectious disease self-management model. This study attempted to develop voluntary data collection application for the epidemiological investigation of infectious diseases through the donation of infected patient data. We aimed to develop and evaluate application to support epidemiological investigations by local governments using big data from infectious diseases.

Methods

Development environment

We used the Double Diamond design process to develop the application. The Double Diamond design process consists of four stages: Discovery, Define, Develop, and Deliver.¹⁵

For the Discovery and Define stages, there was a need to find out which applications were most needed and what services were needed to overcome COVID-19. We conducted a pre-online survey on the most needed applications related to COVID-19 between November 11 and December 6, 2020. From the analysis of 1148 data, we found that applications designed for epidemiological investigations are the most crucial in preventing COVID-19 (61.8%).¹⁶ Thus, we developed the KODARI application, an epidemiological investigation support system based on an infectious disease self-management model.¹⁷ The KODARI application means “KOREA with a diary.” The KODARI application is a Korean version, and there is an English version, MEDARI application¹⁷(Figure 1). In the development stage, this study developed KODARI application, utilizing various software and systems. Initially, the server’s operating system was Ubuntu version 20.04, developed by Canonical Ltd In England. Subsequently, the application operated on the PHP 8.0 Laravel framework, developed by Zend Technologies Ltd In Cupertino, California, USA. Moreover, the database server utilized MariaDB 10.51, developed by the MariaDB Foundation. Lastly, the mobile applications were implemented on iOS/Android platforms.

Figure 1.

Architecture of the KODARI app.

Application user collection items

For the Define stage, we had to select key collection items in the epidemiological investigation application. Therefore, we developed user collection items for the KODARI application (Table 1). For the information stored in the KODARI application to be used for epidemiological investigation, it was necessary to analyze the epidemiological investigation form for COVID-19 (version 6, for public health centers).¹⁸ We referred to research on existing epidemiological investigations.^19,20

Table 1.

Items of the KODARI based on the epidemiological investigation form for COVID-19(Ver. 6).

Category	Items	Items of the KODARI app
Personal information	1.1 Name	Nickname
	1.2 resident registration number	O
	1.3 sex	O
	1.4 Nationality	O
	1.5 home address	O
	1.6 phone number (guardian)	O (guardian: X)
	1.7 occupation (company name, school name)	O
Travel history to the affected area	2.1 visit to the affected area	O
	2.2 date of departure	O
	2.3 area and period of visit in the last 14 days	O
	2.4 transit of entry	X
	2.4.1 place	O
	2.5 purpose of visit	O
	2.6 companion	O
	2.7 Risk factors (Within 14 days from the date of onset)	X
	2.7 date of entry	O
Clinical symptoms	3.1 initial symptoms	O
	3.1.1 date	O
	3.1.2 place	O
	3.1.3 confirmed by	X
	3.2 current symptoms	O
	3.3 use of antipyretics	X
	3.4 Underlying disease	O
	3.5 smoking	X
	3.6 pregnancy	O
	3.7 diagnosis by medical institution	X
Other	4.1. Indicated symptoms on health questionnaire at entry	X
	4.2 verified travel history on (medical institution) DUR /Beneficiary inquiry system	X
	4.3 Received a text message about reporting 1339 after entry	X
	4.4 contact	X

The extracted items are reflected in the Input and Update units of the KODARI application. The epidemiological investigation form for public health centers (version (6) is divided into four primary sections: (1) personal information (seven items), (2) travel history to the affected area (seven items), (3) clinical symptoms (six items), and (4) other (four items). Additionally, there are four specific items that the municipal epidemiological investigation team is required to enter directly. Several items from the epidemiological investigation form are incorporated into the application; consequently, we extracted these items. The extraction of the main user collection items from the KODARI application was conducted by four researchers, including two with doctoral-level qualifications, one with a master-level qualification, and one researcher. While we aimed to integrate as many items as possible into the KODARI application, not all items could be applied.

Furthermore, this study encompassed data not captured in the initial epidemiological investigation form, incorporating additional collection items such as personal health information and vaccination history. Personal health information was meticulously selected after consulting with a physician, focusing on elements pertinent to COVID-19; this included underlying diseases, pregnancy status, history of cancer treatment, immunosuppressive conditions, confirmed infectious diseases, and side effects from vaccinations. Additionally, detailed vaccination records and exemption certificates were available. Users also had the option to manually log COVID-related assessments, including test results from medical facilities, self-diagnosed test records, and antibody testing outcomes.

KODARI application evaluation

We employed a set of 11 questions to assess the application (Appendix table 1): three questions were concerning the willingness to utilize the healthcare application related to infectious diseases; two questions were about the willingness to record movement; two questions evaluated satisfaction with the KODARI application; one question addressed the burden associated with using the KODARI application; one question gauged the intention to use the KODARI application; and two questions explored the value of the KODARI application.^16,21–24

The survey period was from December 02 to December 14, 2022. Participation was only possible if informed consent was obtained prior to the survey. Furthermore, only users who donated data to the KODARI application participated in the online survey. Voucher coupons were provided to those who responded.

Inclusion/exclusion criteria

Before the Deliver stage, we conducted an online survey to evaluate satisfaction with the KODARI application. The inclusion criteria are those who have used KODARI application for more than 2 weeks after installing it. The target was Koreans in their 20s and 40s who own an Android smartphone. The target was a user who donated data in the app. Exclusion criteria are those who have only installed the application but have not used it for more than 2 weeks. The exclusion criteria are those who did not donate app data. Additionally, adults over 50 years of age were excluded.

Ethics statement

The study procedures were carried out in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Dankook University (2021-12-009). All participants provided written informed consent prior to enrolment in the study. Participants’ data were anonymized to ensure confidentiality.

Results

KODARI application

The KODARI application collects three types of information: user route information and related daily events, infectious disease-related information, and health-related information (Figure 1). The KODARI application has four units: input, update, big data, and transmission.

Input and update unit

The input and update unit features a self-tracing diary and infectious disease management functions (Figure 2). The units gather user status information based on the GPS-derived user location. Furthermore, users can update their daily information regarding changes in infectious disease status.

Figure 2.

Four units of the KODARI app.

Initially, users may automatically or manually log their immigration records and movements they deem necessary to remember. Subsequently, users can manage their activity patterns, save companions, and note the characteristics of specific locations. On the detailed registration page for each place, it is possible to enter information such as mask-wearing requirements, visit characteristics, companion details, the presence of group facilities, facilities with infection risks, and the number of companions.

Moreover, users can store and manage personal health information and vaccination histories by registering vaccination details and exemption certificates. Personal health information includes underlying diseases, pregnancy status, cancer treatment history, immunosuppressed status, confirmed infectious disease status, and vaccine side effects. Additionally, users can manually document COVID-related inspections, such as medical institution test records, self-diagnosis test results, and antibody test findings.

Bigdata unit

Users can modify their records at any time and delete them freely at any time if they do not want to save them. Therefore, it is possible to reduce concerns about the accumulation of records for storing and managing records related to infectious diseases. In-application records were automatically deleted after four or more weeks. Through donations, users can contribute to constructing big data on infectious diseases.

The application has a function to approve donations from constructed epidemiological data, and donations have been developed to be withdrawn at any time. When a user cancels a data donation, the user's data is not visible and cannot be used even on the admin page.

Transmission unit

Users can send their activities' records in an Excel file by email or text message at any time. The recipient of the data was the user or epidemiological investigator. Users can export records up to 4 weeks before the date of transmission. The KODARI application was developed to store and transmit user information for up to 4 weeks. It can be sent by, for instance, email, KakaoTalk as a messenger service, and text messages. KakaoTalk refers to a global free mobile messaging service provided by Korea’s Kakao Co., Ltd. Users can also copy and send the links. This finding is useful for epidemiological investigation.

User’s evaluation of the KODARI application

Characteristics of respondents are presented in Table 2. A total of 248 individuals participated in the evaluation of the KODARI application, with 127 males (51.7%) and 121 females (48.8%). Among these, 76 individuals in their 20s represented 30.6% of participants, while 89 individuals in their 30s constituted 35.9%. Additionally, 83 participants in their 40s comprised 33.5% of the total. With respect to marital status, 130 respondents (52.4%) were unmarried, and 116 (46.8%) were married, indicating a marginal difference between these groups. Regarding education, 171 respondents (69.0%) had attained a college degree or higher. In terms of occupations, 80.7% of respondents reported being professionals, managers, office workers, housewives, or students.

Table 2.

Respondent characteristics.

Variables	Frequency (percent)
Gender
Male	127 (51.2)
Female	121 (48.8)
Age
20-29 years old	76 (30.6)
30∼39 years old	89 (35.9)
40∼49 years old	83 (33.5)
Marital status
Married	130 (52.4)
Unmarried	116 (46.8)
Others (including separation, bereavement, etc.)	2 (0.8)
Final education level
High school graduate or less	20 (8.1)
College student	57 (23.0)
College graduates or higher	171 (69.0)
Job
Professionals/managers/office workers	144 (58.1)
Housewives/students	56 (22.6)
Self-employed/freelance	17 (6.9)
Service/sales/production	17 (6.9)
Unemployed/other	14 (5.6)
Total	248 (100.0)

Willingness to use healthcare applications related to infectious diseases

First, we inquired whether participants would be willing to protect themselves from infectious diseases by using a healthcare application related to infectious diseases, if given the opportunity (Table 3). To this question, 194 of the 248 respondents (78.2%) answered affirmatively. Secondly, 126 of the 248 respondents (50.8%) expressed a positive response to the query, “I want to be monitored through an infectious disease management application.” For this question, 89 respondents (35.9%) expressed a neutral opinion, termed “normal,” which represented a significant proportion. Lastly, 175 respondents (58.9%) indicated a positive desire to manage infectious diseases independently using an infectious disease-related application. For this question, 58 respondents (23.4%) held a neutral stance, described as “normal.”

Table 3.

Results of the KODARI app evaluation.

Variable	Scale		Frequency (percent)
Willingness to use the healthcare app related to infectious diseases	I want to be willing to protect themselves from infectious diseases by using an infectious disease-related healthcare app if given the opportunity	Strongly disagree	1 (0.4)
		Disagree	4 (1.6)
		Neutral	49 (19.8)
		Agree	151 (60.9)
		Strongly agree	43 (17.3)
	I want to be monitored through an infectious disease management app	Strongly disagree	1 (0.4)
		Disagree	32 (12.9)
		Neutral	89 (35.9)
		Agree	101 (40.7)
		Strongly agree	25 (10.1)
	I want to manage infectious diseases by myself using an infectious disease-related app	Strongly disagree	1 (0.4)
		Disagree	14 (5.6)
		Neutral	58 (23.4)
		Agree	133 (53.6)
		Strongly agree	42 (16.9)
Willingness to record movement	Are you willing to record the movements for a certain period of time for future epidemiological investigations when suspicious symptoms appear?	Strongly disagree	7 (2.8)
		Disagree	12 (4.8)
		Neutral	45 (18.1)
		Agree	120 (48.4)
		Strongly agree	64 (25.8)
	For epidemiological investigation, do you agree to provide the public health authorities with suspicious symptoms?	Strongly disagree	4 (1.6)
		Disagree	10 (4.0)
		Neutral	39 (15.7)
		Agree	123 (49.6)
		Strongly agree	72 (29.0)
The KODARI app satisfaction	I am satisfied with the quality of the KODARI app	Strongly disagree	6(2.4)
		Disagree	30(12.1)
		Neutral	88(35.5)
		Agree	99(39.9)
		Strongly agree	25(10.1)
	I am satisfied with the main features of the KODARI app	Strongly disagree	5(2.0)
		Disagree	14(5.6)
		Neutral	79(31.9)
		Agree	119(48.0)
		Strongly agree	31(12.5)
Burden of using the KODARI app	Are you burdened with using the KODARI app for some period of time?	Strongly disagree	15(6.0)
		Disagree	81(32.7)
		Neutral	78(31.5)
		Agree	69(27.8)
		Strongly agree	5(2.0)
Intention to use the KODARI app	If it was 2021 when COVID-19 was severe, would you use the KODARI app?	Strongly disagree	4(1.6)
		Disagree	15(6.0)
		Neutral	43(17.3)
		Agree	112(45.2)
		Strongly agree	74(29.8)
Total			248(100.0)

Willingness to record movement

The results of the two questions about the willingness to record movement are as follows (Table 3). First, 184 out of 248 respondents (74.2%) responded positively to the question, “Are you willing to record your movements for a certain period of time for future epidemiological investigations when suspicious symptoms appear?” Second, 195 (83.9%) of the total 248 respondents responded positively to the question, “Do you agree to provide the public health authorities with suspicious symptoms for epidemiological investigation?”

KODARI application satisfaction

The results of the two questions concerning satisfaction with the KODARI application are presented in Table 3. In response to the question, “I am satisfied with the quality of the KODARI application,” 50% of participants indicated agreement or strong agreement. Concerning the main features’ satisfaction of the KODARI application, 60.5% of respondents indicated agreement or strong agreement.

Burden of using the KODARI and intention to use the KODARI application

When queried about feeling burdened by using the KODARI application over a certain period, 38.7% of participants reported feeling not at all or minimally burdened (Table 3). Moreover, 31.5% described their burden as normal, suggesting that the overall burden of use was manageable. We also inquired whether participants would be willing to use the KODARI application in 2021, during the peak of COVID-19. Of the total respondents, 186 (75%) provided positive feedback, agreeing or strongly agreeing.

Value of the KODARI application

Participants were asked to identify the potential contributions of the KODARI application to mitigating infectious diseases (Table 4, Figure 3). The most frequent response was its contribution to epidemiological investigations, noted by 140 participants (56.5%). The application was also found to aid in the management of infectious diseases (88, 35.5%), alleviate anxiety related to infectious diseases (15, 6%), and reduce the number of seriously ill patients by managing underlying diseases (5, 2%).

Table 4.

Value of the KODARI app evaluation.

Variable	Scale		Frequency (percent)
What the app contributes	What can potentially be contributed to mitigating infectious diseases by using the KODARI application?	Contribute to epidemiological investigation	140(56.5)
		Contribution to infectious disease management (control)	88(35.5)
		Contribution to relieving anxiety about infectious diseases	15(6)
		Reduction of seriously ill patients through management of underlying diseases	5(2)
Effect of reducing epidemiological investigation time	Compared to existing epidemiological investigations, how much do you think the KODARI app will reduce the epidemiological investigation time?	No effect	7(2.8)
		Less than 30 min	74(29.8)
		More than 30 min to less than an hour	95(38.3)
		More than 1 h but less than 2 h	35(14.1)
		2 h or more	37(14.9)
Total			248(100.0)

Figure 3.

Value of the KODARI app.

We inquired about the perceived reduction in time in epidemiological investigations when using the KODARI app compared to traditional methods (Table 4, Figure 3). A total of 38.3% of respondents believed that the investigation time could be reduced from 30 min to less than an hour. Additionally, 29.8% thought that using the app could decrease the time spent on an epidemiological investigation by less than 30 min. Only 2.8% felt there would be no reduction in investigation time.

Discussion

We developed an application to support the epidemiological investigations of governments in the endemic era: the KODARI application. The KODARI application has several advantages.

First, the KODARI application has the advantage of solving personal information issues and automatically collecting epidemiological investigation information. GPS-based route self-management is possible. As in Singapore, a confirmed case of COVID-19 must be interviewed by an epidemiologist.¹ Epidemiological investigation subjects should provide epidemiological investigators with information on demographic characteristics, clinical symptoms, and activities from 14 days before the onset of COVID-19 symptoms to isolation. Epidemiologists also perform contact tracing to identify close contacts and other contacts that interact with confirmed cases. During an epidemiological investigation, it is difficult to remember one’s movements and specific details. Thus, the KODARI application automatically collects movements based on GPS. However, it is also possible to collect movement only using the application. In addition, the user can store location and state information they want to remember. The stored information could be deleted at any time. Considering concerns about personal information exposure, it can be deleted at any time, and the deleted information cannot be recovered. The stored data were automatically deleted after 4 weeks. Even in the case of digital contact tracing, perceived security, privacy, and technology trust have been reported as major factors affecting user satisfaction.²⁵ Privacy concerns are predictors of resistance to digital contact tracing applications.^16,26–29 Therefore, we made it possible for users to use the application to delete and edit their movement records as freely as possible so as not to worry about privacy and security.

Second, the KODARI application has advantages such as improved data accuracy through accurate information collection, improved contact tracing capabilities, and the ability to provide timely and targeted interventions. When an infectious disease is confirmed, it is possible to manage daily symptoms and write a symptom diary. It is also possible to manage the self-symptoms one wants to remember daily. This could provide clues to revive memories of the symptoms necessary for epidemiological investigations. The [My Data] menu in the KODARI application facilitates the self-management of infectious diseases by enabling users to record and store their vaccination and examination histories, as well as daily health records. This feature is particularly valuable when it is essential to document various infectious-disease-related information. Previous studies have demonstrated that self-reported symptom tracking is effective in predicting potential COVID-19 infections.³⁰ Self-reported symptoms, such as loss of sense of smell and taste, are included in the screening criteria. Moreover, following an infectious disease episode like COVID-19, individuals are keen to manage their condition promptly. This functionality proves beneficial during an endemic period.

In South Korea, the Epidemic Investigation Support System (EISS) is employed to track epidemics. This system features capabilities for mapping the movement data of confirmed cases and forecasting regions at risk of infection.³¹ The EISS mitigates the spread of infectious diseases by monitoring confirmed cases, leveraging data from public transportation, mobile network base stations, healthcare facility visits, and international travel records. Nonetheless, it faces challenges in gathering and utilizing detailed individual symptom data and self-reported infectious disease information. Consequently, the KODARI application’s key benefit is enabling individuals to self-manage infectious diseases during endemic periods, exemplifying the characteristics of an ideal digital tracking application.^2,32,33

Third, the data were used to build big epidemiological data through donations. It is possible to build big data based on the status of patients with infectious diseases. Infectious disease-related data collected by users are useful in epidemiological studies of infectious diseases.³⁴ In South Korea, many efforts are being made to induce users to donate data in COVID-19-related applications, such as SHINE (Study of Health Information for Next Epidemic).³⁵ Government-driven COVID-19-related big data exist, but user-driven data are also essential. This is because user-centric data include specific records and specifics of the time in which it was collected. Even in the COVID-19-related application evaluation framework, user control and self-determination are crucial from epidemiological and legal perspectives.¹¹

Fourth, it can transmit self-management information data to epidemiologist terminals or users in real time. Users can export records for up to 4 weeks prior to the transmission date. When an infected individual partakes in an epidemiological investigation, the investigator collects data on the individual’s movements and peculiarities during a specific period. However, it is challenging for individuals to recall all details pertinent to the estimated infection period. Users can now access and utilize the data stored in the KODARI application. An environment that facilitates independent management of infectious diseases and active participation in epidemiological investigations can be established. COVID-related applications serve various purposes, including monitoring the epidemic, tracing and tracking movements, and assessing exposure risks.¹¹ However, no service allows users to utilize recorded user information for epidemiological investigations. This can be said to be the most significant feature of the KODARI application.

Fifth, following experiences with COVID-19, analyses indicated that people are now more inclined to protect themselves from infectious diseases and utilize related applications. Moreover, there was a high level of self-management willingness regarding infectious diseases. Participants also consented to record their movements for epidemiological purposes. Furthermore, there were positive evaluations of the KODARI application, accompanied by a strong willingness to use it. The burden associated with using the KODARI application was also found to be relatively low. For COVID-19-related applications, such as contact tracing apps, to be effective, they must be adopted and utilized by the public.³⁶ However, prior studies have highlighted low adoption rates among the population.^36–38 If a COVID-19-related application encourages voluntary participation, it is likely that users will actively engage with it, even if it involves collecting location data. Looking ahead, there is potential for expanding the KODARI application to manage other infectious diseases.

Sixth, this study demonstrated that the KODARI application can enhance epidemiological investigations and diminish the duration of existing epidemiological investigation processes. A majority of respondents (56.5%) assessed the KODARI application as beneficial for epidemiological investigations. This benefit distinguishes it from other existing contact tracing applications. Moreover, it was observed that using the KODARI application could reduce the epidemiological investigation time by more than 30 min compared to the conventional epidemiological investigation duration (97.2%). Merely 2.8% of participants indicated that there would be no reduction in investigation time.

Limitations and future research

Despite these advantages, this study had several limitations. First, we developed the KODARI application, which enables users to transmit epidemiologically relevant information to epidemiologists. Thus, it is necessary to develop a dedicated application for epidemiologists in the future. Second, a survey study on the effectiveness of the KODARI application is essential for epidemiological investigations. Therefore, focusing on individuals who have undergone such investigations is crucial. Third, we developed a Korean version of the KODARI application. It is imperative to create versions in various languages for national use. Fourth, we developed the application by extracting data items from an epidemiological investigation form for COVID-19 (Version 6, for public health centers) 17. As of December 2022, the 13th edition of the Response Guidelines was published. The epidemiological investigation form for COVID-19 evolves based on the COVID-19 response level, which cannot all be reflected. We aimed to include as many items as possible in the application, but some were not implemented. We plan to incorporate all items in future upgrades of the application. Fifth, the KODARI application anonymizes user data, ensuring there are no security issues. However, the implementation of security technologies, such as blockchain, is necessary. Sixth, we surveyed the KODARI application users and ultimately used data from 248 users for analysis. According to existing literature, when there are less than 12 variables, the number of samples is suggested to be 200. This study used 11 variables to assess the application. We determined that 248 data sets were appropriate for this study. Future studies need to calculate and justification of the sample size to choose for the study.

Conclusions

The KODARI application stands out as it introduces a service model predicated on voluntary participation. In the context of COVID-19-related applications, most were orchestrated by governments and centrally managed. Moreover, concerns about personal information exposure have made users hesitant to engage with these applications. Although COVID-19-related applications are acknowledged as providing theoretical evidence for new public health interventions, the global adoption of digital contact-tracing applications remains limited. Therefore, it is necessary to allow users to manage infectious disease-related information or track it on their own. Infectious diseases that threaten people’s lives worldwide are expected to continue to appear in the future. Therefore, the world requires a non-centralized and autonomous service that can protect itself when an infectious disease is confirmed, such as the KODARI application. Ultimately, collecting and utilizing epidemiological survey data through voluntary participation have the potential to improve the efficiency and effectiveness of disease surveillance and control efforts.

Finally, the KODARI application is valuable as a technology that supports epidemiological investigations based on collected big data. The KODARI application would be useful in cooperation with epidemiological investigations of infectious diseases in future pandemics.

Supplemental Material

Supplemental Material - Epidemiological investigation support application and user evaluation based on infectious disease self-management model in the endemic era

Supplemental Material for Epidemiological investigation support application and user evaluation based on infectious disease self-management model in the endemic era by Jihwan Park and Mi Jung Rho in Health Informatics Journal.

Footnotes

Author contributions

Conceptualization: Jihwan Park and Mi Jung Rho. Data curation: Mi Jung Rho. Formal analysis: Mi Jung Rho. Funding acquisition: Mi Jung Rho. Methodology: Jihwan Park and Mi Jung Rho. Project administration: Mi Jung Rho. Writing – original draft: Jihwan Park and Mi Jung Rho. Review & editing: Jihwan Park and Mi Jung Rho. App planning& app development: Jihwan Park and Mi Jung Rho.

Declaration of conflicting interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: The corresponding author and the first author are a married couple. They participated in this project at the time of the study. There are no competing financial interests.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1I1A1A01072400). In addition, this research also was supported by Australia-Korea Joint Call for Joint Research Projects through the NRF (NRF-2021K1A3A1A17102523).

Ethical statement

ORCID iDs

Jihwan Park

Mi Jung Rho

Supplemental Material

Supplemental material for this article is available online.

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