Relationship between the number of pediatric patients with rotavirus and telephone triage for associated symptoms

Effectiveness of early warning systems in the detection of infectious diseases outbreaks: a systematic review

Background

Global pandemics have occurred with increasing frequency over the past decade reflecting the sub-optimum operationalization of surveillance systems handling human health data. Despite the wide array of current surveillance methods, their effectiveness varies with multiple factors. Here, we perform a systematic review of the effectiveness of alternative infectious diseases Early Warning Systems (EWSs) with a focus on the surveillance data collection methods, and taking into consideration feasibility in different settings.

Methods

We searched PubMed and Scopus databases on 21 October 2022. Articles were included if they covered the implementation of an early warning system and evaluated infectious diseases outbreaks that had potential to become pandemics. Of 1669 studies screened, 68 were included in the final sample. We performed quality assessment using an adapted CASP Checklist.

Results

Of the 68 articles included, 42 articles found EWSs successfully functioned independently as surveillance systems for pandemic-wide infectious diseases outbreaks, and 16 studies reported EWSs to have contributing surveillance features through complementary roles. Chief complaints from emergency departments’ data is an effective EWS but it requires standardized formats across hospitals. Centralized Public Health records-based EWSs facilitate information sharing; however, they rely on clinicians’ reporting of cases. Facilitated reporting by remote health settings and rapid alarm transmission are key advantages of Web-based EWSs. Pharmaceutical sales and laboratory results did not prove solo effectiveness. The EWS design combining surveillance data from both health records and staff was very successful. Also, daily surveillance data notification was the most successful and accepted enhancement strategy especially during mass gathering events. Eventually, in Low Middle Income Countries, working to improve and enhance existing systems was more critical than implementing new Syndromic Surveillance approaches.

Conclusions

Our study was able to evaluate the effectiveness of Early Warning Systems in different contexts and resource settings based on the EWSs’ method of data collection. There is consistent evidence that EWSs compiling pre-diagnosis data are more proactive to detect outbreaks. However, the fact that Syndromic Surveillance Systems (SSS) are more proactive than diagnostic disease surveillance should not be taken as an effective clue for outbreaks detection.

An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan

Background

Early surveillance to prevent the spread of influenza is a major public health concern. If there is an association of influenza epidemics with mobile app data, it may be possible to forecast influenza earlier and more easily.

Objective

We aimed to assess the relationship between seasonal influenza and the frequency of mobile app use among children in Osaka Prefecture, Japan.

Methods

This was a retrospective observational study that was performed over a three-year period from January 2017 to December 2019. Using a linear regression model, we calculated the R² value of the regression model to evaluate the relationship between the number of “fever” events selected in the mobile app and the number of influenza patients ≤14 years of age. We conducted three-fold cross-validation using data from two years as the training data set and the data of the remaining year as the test data set to evaluate the validity of the regression model. And we calculated Spearman correlation coefficients between the calculated number of influenza patients estimated using the regression model and the number of influenza patients, limited to the period from December to April when influenza is prevalent in Japan.

Results

We included 29,392 mobile app users. The R² value for the linear regression model was 0.944, and the adjusted R² value was 0.915. The mean Spearman correlation coefficient for the three regression models was 0.804. During the influenza season (December–April), the Spearman correlation coefficient between the number of influenza patients and the calculated number estimated using the linear regression model was 0.946 (P<.001).

Conclusions

In this study, the number of times that mobile apps were used was positively associated with the number of influenza patients. In particular, there was a good association of the number of influenza patients with the number of “fever” events selected in the mobile app during the influenza epidemic season.

A Mobile App for Self-Triage for Pediatric Emergency Patients in Japan: 4 Year Descriptive Epidemiological Study

BACKGROUND

When children suffer sudden illness or injury, many parents wonder whether they should go to the hospital immediately or call an ambulance. In 2015, we developed a mobile app that allows parents or guardians to determine the urgency of their child's condition or call an ambulance and that indicates available hospitals and clinics when their child is suddenly sick or injured by simple selection of the child's chief complaints and symptoms. However, the effectiveness of medical apps used by the general public has not been well evaluated.

OBJECTIVE

The purpose of this study was to clarify the use profile of this mobile app based on data usage in the app.

METHODS

This study was a descriptive epidemiological study with a 4-year study period running from January 2016 to December 2019. We included cases in which the app was used either by the children themselves or by their parents and other guardians. Cases in which the app was downloaded but never actually used were excluded from this study. Continuous variables are presented as median and IQR, and categorical variables are presented as actual number and percentages.

RESULTS

The app was used during the study period for 59,375 children whose median age was 1 year (IQR 0-3 years). The app was used for 33,874 (57.05%) infants, 16,228 (27.33%) toddlers, 8102 (13.65%) elementary school students, and 1117 (1.88%) junior high school students, with 54 (0.09%) having an unknown status. Furthermore, 31,519 (53.08%) were male and 27,329 (46.03%) were female, with sex being unknown for 527 (0.89%) children. "Sickness" was chosen for 49,101 (78.51%) patients, and "injury, poisoning, foreign, substances and others" was chosen for 13,441 (21.49%). For "sickness," "fever" was the most commonly selected option (22,773, 36.41%), followed by "cough" (4054, 6.48%), and "nausea/vomiting" (3528, 5.64%), whereas for "injury, poisoning, foreign substances and others," "head and neck injury" was the most commonly selected option (3887, 6.22%), followed by "face and extremities injury" (1493, 2.39%) and "injury and foreign substances in eyes" (1255, 2.01%).

CONCLUSIONS

This study clarified the profile of use of a self-triage app for pediatric emergency patients in Japan.

Emergency medicine in Japan: past, present, and future

Quite a few changes and challenges have arisen in society in general as technology has advanced and the aging population has increased. These can lead to the recognition of the shortcomings of a society’s traditional systems and the various changes that are needed, especially in providing emergency medical care. A super-aged society has been developing in Japan, and the emergency care system needs to change according to these new demographics and society’s needs. The focus has been shifting from critical care and trauma to medical and surgical conditions involving the elderly. Challenges in triage, ambulance diversion, and staffing are discussed in this review. Possible solutions currently underway, such as a public helpline, smartphone app system, coordination by designated hospitals, and universal coverage/government support, are discussed as future directions. Emergency medicine in Japan needs to develop in a more flexible way to meet the upcoming robust challenges of the changing demographics.