Remote monitoring of health has the potential to reduce the burden to patients of face-to-face appointments and make healthcare more efficient. Apps are available for patients to self-monitor vision at home, for example, to detect reactivation of age-related macular degeneration (AMD). Describing the challenges when implementing apps for self-monitoring of vision at home was an objective of the MONARCH study to evaluate two vision-monitoring apps on an iPod Touch (Multibit and MyVisionTrack).

Diagnostic Test Accuracy study.

Six UK hospitals.

The study provides an example of the real-world implementation of such apps across health sectors in an older population. Challenges described include the following: (1) frequency and reason for incoming calls made to a helpline and outgoing calls made to participants; (2) frequency and duration of events responsible for the tests being unavailable; and (3) other technical and logistical challenges.

Patients (n=297) in the study were familiar with technology; 252/296 (85%) had internet at home and 197/296 (67%) had used a smartphone. Nevertheless, 141 (46%) called the study helpline, more often than anticipated. Of 435 reasons for calling, all but 42 (10%) related to testing with the apps or hardware, which contributed to reduced adherence. The team made at least one call to 133 patients (44%) to investigate why data had not been transmitted. Multibit and MyVisionTrack apps were unavailable for 15 and 30 of 1318 testing days for reasons which were the responsibility of the app providers. Researchers also experienced technical challenges with a multiple device management system. Logistical challenges included regulations for transporting lithium-ion batteries and malfunctioning chargers.

Implementation of similar technologies should incorporate a well-resourced helpline and build in additional training time for participants and troubleshooting time for staff. There should also be robust evidence that chosen technologies are fit for the intended purpose.

ISRCTN79058224.

Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus that causes encephalitis and other morbidity in Southeast Asia. Since February 2022, geographically dispersed JEV human, animal and vector detections occurred on the Australian mainland for the first time. This study will determine the prevalence of JEV-specific antibodies in human blood with a focus on populations at high risk of JEV exposure and determine risk factors associated with JEV seropositivity by location, age, occupation and other factors.

Samples are collected using two approaches: from routine blood donors (4153 samples), and active collections targeting high-risk populations (convenience sampling). Consent-based sampling for the latter includes a participant questionnaire on demographic, vaccination and exposure data. Samples are tested for JEV-specific total antibody using a defined epitope-blocking ELISA, and total antibody to Australian endemic flaviviruses Murray Valley encephalitis and Kunjin viruses.

Two analytic approaches will occur: descriptive estimates of seroprevalence and multivariable logistic regression using Bayesian hierarchical models. Descriptive analyses will include unadjusted analysis of raw data with exclusions for JEV-endemic country of birth, travel to JEV-endemic countries, prior JEV-vaccination, and sex-standardised and age-standardised analyses. Multivariable logistic regression will determine which risk factors are associated with JEV seropositivity likely due to recent transmission within Australia and the relative contribution of each factor when accounting for effects within the model.

National Mutual Acceptance ethical approval was obtained from the Sydney Children’s Hospitals Network Human Research Ethics Committee (HREC). Local approvals were sought in each jurisdiction. Ethical approval was also obtained from the Australian Red Cross Lifeblood HREC.

Findings will be communicated to participants and their communities, and human and animal health stakeholders and policy-makers iteratively and after final analyses. Understanding human infection rates will inform procurement and targeted allocation of limited JEV vaccine, and public health strategies and communication campaigns, to at-risk populations.