Mobile health (mHealth) is a promising tool for improving healthcare access, particularly in low-resource settings. However, limited mobile accessibility and poor connectivity remain significant barriers to implementing mHealth interventions in these regions. To address these challenges and support the development and scalability of mHealth studies, we developed Pharos, a mobile GIS application designed to assess network coverage and facilitate ground-truth mapping. Pharos autonomously measures spatiotemporal variations in mobile network signal strength and enables precise mapping of critical landmarks and environmental features. We deployed Pharos in a four-county region along the shores of Lake Victoria in Western Kenya as part of a preparatory phase for a large-scale mHealth study focused on schistosomiasis control. Over six months and 10,000 km2, Pharos collected high-resolution data on network performance and landmark locations, generating a comprehensive dataset that links network availability with environmental features. These results provide essential insights for planning and implementing mHealth interventions in low-resource settings, with potential applications in infectious disease surveillance and other global health initiatives.

BACKGROUND:In the United States, young men who have sex with men (YMSM) and young transgender women (YTGW) are disproportionately affected by HIV infection. Adequate HIV knowledge is critical for protecting adolescents and young adults at risk for HIV. This study aimed to evaluate the effectiveness of the mLab App intervention in enhancing HIV knowledge among YMSM and YTGW. METHODS:This study was a secondary analysis of data collected from a randomized controlled trial (RCT) evaluating the effect of the mLab App on HIV knowledge. We calculated interactions between groups (mLab App intervention, standard of care, at-home testing) over time (6 and 12 months) following the baseline observation, indicating a difference in the outcome scores from baseline to each time across groups. RESULTS:Although the mLab App group initially had lower HIV knowledge than those in other groups, access to the App demonstrated a progressive impact on HIV knowledge over time. Despite the absence of a statistically significant effect at the 6-month follow-up, the long-term evaluation suggests improvements in HIV knowledge during the 12-month intervention follow-up. CONCLUSIONS:Our study suggests the potential of the mLab App as a valuable tool for long-term HIV education and awareness for YMSM and YTGW. Further research is needed to understand the factors influencing the short-term effect on HIV knowledge. The mLab App may be a useful intervention for improving HIV knowledge.

OBJECTIVE:To determine the efficacy of the mLab App, a mobile-delivered HIV prevention intervention to increase HIV self-testing in MSM and TGW. MATERIALS AND METHODS:This was a randomized (2:2:1) clinical trial of the efficacy the mLab App as compared to standard of care vs mailed home HIV test arm among 525 MSM and TGW aged 18-29 years to increase HIV testing. RESULTS:The mLab App arm participants demonstrated an increase from 35.1% reporting HIV testing in the prior 6 months compared to 88.5% at 6 months. In contrast, 28.8% of control participants reported an HIV test at baseline, which only increased to 65.1% at 6 months. In a generalized linear mixed model estimating this change and controlling for multiple observations of participants, this equated to control participants reporting a 61.2% smaller increase in HIV testing relative to mLab participants (P = .001) at 6 months. This difference was maintained at 12 months with control participants reporting an 82.6% smaller increase relative to mLab App participants (P < .001) from baseline to 12 months. DISCUSSION AND CONCLUSION:Findings suggest that the mLab App is well-supported, evidence-based, behavioral risk-reduction intervention for increasing HIV testing rates as compared to the standard of care, suggesting that this may be a useful behavioral risk-reduction intervention for increasing HIV testing among young MSM. TRIAL REGISTRATION:This trial was registered with Clinicaltrials.gov NCT03803683.

The HIV incidence rate continues to increase among youth, especially among young men who have sex with men (YMSM) and young transgender women (YTW). To date, behavioral intention has often been viewed as the likelihood of engaging in prevention behaviors and emphasized as a key antecedent for condom use, disclosure of serostatus, and PrEP use among people living with HIV. In addition, individuals with different sociodemographic factors may have varying degrees of HIV prevention intention, which is a critical knowledge needed to identify facilitators and barriers to HIV prevention intention. This is a secondary data analysis of baseline data from a randomized controlled trial (RCT) (N = 488). This study aimed to identify distinct, latent classes of HIV prevention intention among youth vulnerable to HIV acquisition and to understand the sociodemographic and contextual factors associated with each latent class. Latent class analysis was conducted to identify meaningful latent classes of youths based on HIV prevention intention. Class 1: “High condomless sex, low serosorting, low PrEP intention,” Class 2: “High condomless sex, high serosorting, low PrEP intention,” Class 3: “Moderate condom use, serosorting, low PrEP intention,” and Class 4: “Moderate condom use, high serosorting, moderate PrEP intention” were identified. Significant differences were found in age, sexual orientation, level of education, current employment status, annual household income, housing/living arrangement, and relationship status. Overall, YMSM and YTW without a recent history of HIV testing or PrEP use may have particularly low intentions for HIV prevention, and therefore may be at higher risk for HIV infection.

In recent years, infectious disease diagnosis has increasingly turned to host-centered approaches as a complement to pathogen-directed ones. The former, however, typically requires the interpretation of complex multiple biomarker datasets to arrive at an informative diagnostic outcome. This report describes a machine learning (ML)-based classification workflow that is intended as a template for researchers seeking to apply ML approaches for developing host-based infectious disease biomarker classifiers. As an example, we built a classification model that could accurately distinguish between three disease etiology classes: bacterial, viral, and normal in human sera using host protein biomarkers of known diagnostic utility. After collecting protein data from known disease samples, we trained a series of increasingly complex Auto-ML models until arriving at an optimized classifier that could differentiate viral, bacterial, and non-disease samples. Even when limited to a relatively small training set size, the model had robust diagnostic characteristics and performed well when faced with a blinded sample set. We present here a flexible approach for applying an Auto-ML-based workflow for the identification of host biomarker classifiers with diagnostic utility for infectious disease, and which can readily be adapted for multiple biomarker classes and disease states.

In the United States, young men who have sex with men (YMSM) and young transgender women (YTGW) are disproportionality affected by HIV. To overcome this public health problem, we created and tested the mLab application (app), a novel mobile health (mHealth) that offers HIV prevention information and an imaging algorithm for interpreting the at-home HIV test. This study assessed the mLab app usability for HIV testing and its relation to users’ education and health literacy. The results showed high user satisfaction and perceived usability of mLab to provide accessible HIV testing solutions for YMSM and YTGW. Findings suggest that the rigorous user-centered design of the mLab app supported a usable app independent of education and health literacy levels.

PurposeOral pre-exposure prophylaxis (PrEP) is effective in preventing HIV transmission. However, oral PrEP uptake is low, particularly among sexual and gender minority youth who are vulnerable to HIV infection. Alternative methods of PrEP delivery, such as long-acting injectable (LAI) PrEP may overcome barriers and be preferred. However, attitudes and preferences of younger sexual and gender minorities towards LAI PrEP have not been well studied. The purpose of this study is to describe preferences for initiating LAI PrEP among sexual and gender minority youth.MethodsWe analyzed data collected as part of an HIV prevention randomized trial from January 2022 to February 2023, using multiple regression to identify factors associated with a preference for LAI PrEP.ResultsThe study sample (N=265) was 50% youth of color, mean age 25 years (SD=3.4, range=18-31), and primarily identified as gay (71%) and male (91%). 42% had heard of LAI PrEP and 31% preferred LAI PrEP over other prevention methods. In multiple regression analysis, LAI PrEP preference was associated with identifying as White, previous PrEP experience, and perceived LAI PrEP efficacy.DiscussionWe conclude that gaps in awareness exist for LAI PrEP, however it may be preferred over other prevention methods especially in White youth, those with PrEP experience and higher perceptions of its efficacy. More education and outreach are needed to prevent extension of existing race/ethnicity disparities in use of oral daily PrEP to LAI PrEP.What’s NewFindings from this study suggest that awareness of LAI PrEP is low, however it may be preferred over other prevention methods especially in White youth, those with PrEP experience and higher perceptions of its efficacy.

The POC-CCA test is subject to variations in reading interpretations depending on the intensity of its results, and trace test reading have implications for determining prevalence. The aim of this study was to assess whether the readings obtained from the POC-CCA tests, conducted using a semi-quantitative scale (the G-score classification for test determination), exhibited concurrence with the direct visual interpretation (positive, negative, or trace) performed by two distinct analysts, using photographs from previously performed POC-CCA test carried out in the municipality of Maruim, in the state of Sergipe-Brazil, a region of high endemicity. The devices used to read the photographs were smartphones, so as to simulate field usage, and a desktop, a tool with higher image quality that would help the researchers in the evaluation and establishment of the final result at a later. In direct visual interpretation of the POC-CCA photographs, the most discordant results occurred in the identification of the trace response (T). The Kappa index established for the direct visual interpretation between the two analysts, in which T is considered as positive, in the desktop was κ=0.826 and in the smartphone, κ=0.950. When we use the G-score as a reading standardization technique and classify the results according to the manufacturer, with trace being evaluated as positive, the highest level of agreement was obtained. Some disagreement remains between the direct visual interpretation and the G-score when performed on the desktop, with more individuals being classified as negative in the direct visual interpretation, by both analysts. However, this result was not statistically significant. The use of the G-score scale proved to be an excellent tool for standardizing the readings and classifying the results according to the semi-quantitative scale showed greater concordance of results both among analysts and among the different devices used to view the photographs.

OBJECTIVES/GOALS: The aim of this study was to design and implement the Pharos application to map the cellular network support structure around Lake Victoria in Western Kenya. Additionally, the Pharos app was used to collect images of disease-relevant vector and plant life surrounding the study sites to train a computer vision algorithm to map disease-relevant areas. METHODS/STUDY POPULATION: Pharos was provided to a 4-person team of healthcare workers. The app was pre-loaded on both iOS and Android devices to be used during the course of normal field activity. Pharos ambiently collects network data and the team was asked to capture images of landmarks relevant to their work in schistosomiasis control. The field team traveled to 4 counties of differing schistosomiasis risk surrounding Kisumu, Kenya in autumn 2022 and will return to these areas in early spring 2023. Cell signal indicators (upload and download speed) were collected and asynchronously uploaded to a database for further analysis. Additionally, all landmark images (cell network towers, landmarks (e.g. schools, churches, public centers), plant life, vectors, and water bodies) were recorded and tagged with GPS coordinates and time stamps. RESULTS/ANTICIPATED RESULTS: Iterative development powered by small, informal, user-centered focus group discussions with the field team led to several key adaptations to the Pharos software. On the first deployment, 1,297 unique upload and download events were recorded across 3 Kenyan cell providers and 1 American provider. 1,197 data points were collected in Kenya using both Android and iOS devices using several versions of the Pharos application. 154 unique landmarks were photographed, but a distinct difference in landmark recording was observed between devices, prompting a transition to iOS-only data collection. Of the landmarks recorded, the majority (120, 77.9%) were landmarks or cell network towers, while 22.1% were water bodies, plant life, or schistosomiasis vectors. DISCUSSION/SIGNIFICANCE: For the first time, high-detail maps of cellular signal and critical schistosomiasis-related landmarks were generated. Future work on this project is focused on training computer vision algorithms using the captured images of environmental and ecological factors to isolate possible areas of human disease transmission.

Lateral flow assays (LFAs) have been used extensively for diagnosis of various diseases and conditions because they are inexpensive, rapid, robust, and easy to use. Incorporating LFAs into undergraduate chemistry courses could enrich the curricula by providing the students with a real-world application of analytical chemistry concepts, particularly why point of care diagnostics can give false positives and false negatives. We developed an LFA module for a class of 25 undergraduate analytical chemistry students that used a hybrid (part face-to-face (F2F) and part remote) learning format. The laboratory consisted of two sessions, the first of which was conducted F2F and the second of which was conducted remotely via conferencing software. In the laboratory session, the students ran LFAs that were designed in house and that detected a well-established malaria biomarker. The students subsequently captured photos and quantified the LFA signal using a mobile-friendly web application that allows for quantification of LFA test and control lines using a smartphone camera. During the second remote session, the students constructed receiver operating characteristic curves, and this activity was used to foster a broader discussion among the students about diagnostic specificity and sensitivity. Following the conclusion of the module, we had the students complete an anonymous survey where students reported they felt an increase in comprehension regarding the topics of LFAs and diagnostic specificity versus sensitivity. We have included all data and protocols to perform this lab and believe this module is well-suited as an in-person, hybrid, or remote-only lab or even as a lecture content supplement.

Lateral flow assays (LFAs) are immunochromatographic point-of-care devices that have greatly impacted disease diagnosis through their rapid, inexpensive, and easy-to-use form factor. While LFAs have been successful as field-deployable tools, they have a relatively poor limit of detection when compared to more complex methods. Moreover, most design and manufacturing optimization is achieved through time- and resource-intensive brute-force optimization. Despite increased interests in LFA manufacturing, more quantitative tools are needed to study current manufacturing protocols and therefore, optimize and streamline development of these devices further. In this work, we focus on a critical LFA component, colloidal gold conjugated to a detection antibody, one of the most commonly used reporter elements. This study utilizes inductively coupled plasma optical emission spectroscopy (ICP-OES) in conjunction with a lateral flow reader to quantitatively analyze colloidal gold distributions at the read-out test and control lines, as well as residual gold on the conjugate pad and other flow through regions. Our goals are to develop a more rigorous understanding of current LFA designs as well as a quantitative understanding of shortcomings of operational characteristics for future improvement. To our knowledge, this is the first time that ICP-OES has been used to study the initial distribution of colloidal gold on an unused LFA and its redistribution after a test is performed. Using three different brands of commercially available malaria LFAs, gold content was measured within each section of an LFA at varying parasite test concentrations. As expected, the total mass of gold remained unchanged after LFA use; however, the total mass of initial gold and its redistribution varied among manufacturers. Importantly, there are also some inherent inefficiencies that exist in these commercial LFA designs; for example, only 30% of the total gold deposited onto Brand A LFAs binds to the test and control lines, sections of the test that contain interpretable signal. Using information gathered with this method, future devices could be more purposefully engineered to focus on improved binding efficiency, resulting in reduced costs, improved limit of detection, and diminished test-to-test and manufacturer-to-manufacturer variability.

Abstract Background The number of youth living with HIV in the United States (US) continues to rise, and racial, ethnic, and sexual minority youth including young men who have sex with men (YMSM) and young transgender women (YTGW) bear a disproportionate burden of the HIV epidemic. Due to social and healthcare system factors, many YMSM and YTGW do not seek HIV testing services and are therefore less likely to be aware that they are infected. Mobile health technology (mHealth) has the ability to increase uptake of HIV testing among these populations. Thus, the mLab App—which combines HIV prevention information with a mobile phone imaging feature for interpreting at-home HIV test results—was developed to improve testing rates and linkage to care among Black, Latino, and other YMSM and YTGW living in New York City and Chicago and their surrounding areas. Methods This study is a three-arm randomized controlled trial among YMSM and YTGW aged 18–29 years. Participants are randomized to either the mLab App intervention including HIV home test kits and standard of preventive care, standard of preventive care only, or HIV home test kits and standard of preventive care only. Discussion mHealth technology used for HIV prevention is capable of delivering interventions in real-time, which creates an opportunity to remotely reach users across the country to strengthen their HIV care continuum engagement and treatment outcomes. Specifically during the COVID-19 pandemic, mHealth technology combined with at-home testing may prove to be essential in increasing HIV testing rates, especially among populations at high-risk or without regular access to HIV testing. Trial registration This trial was registered with Clinicaltrials.gov ( NCT03803683 ) on January 14, 2019.

Background There are a variety of approaches being used for malaria surveillance. While active and reactive case detection have been successful in localized areas of low transmission, concerns over scalability and sustainability keep the approaches from being widely accepted. Mobile health interventions are poised to address these shortcomings by automating and standardizing portions of the surveillance process. In this study, common challenges associated with current data aggregation methods have been quantified, and a web-based mobile phone application is presented to reduce the burden of reporting rapid diagnostic test (RDT) results in low-resource settings. Methods De-identified completed RDTs were collected at 14 rural health clinics as part of a malaria epidemiology study at Macha Research Trust, Macha, Zambia. Tests were imaged using the mHAT web application. Signal intensity was measured and a binary result was provided. App performance was validated by: (1) comparative limits of detection, investigated against currently used laboratory lateral flow assay readers; and, (2) receiver operating characteristic analysis comparing the application against visual inspection of RDTs by an expert. Secondary investigations included analysis of time-to-aggregation and data consistency within the existing surveillance structures established by Macha Research Trust. Results When compared to visual analysis, the mHAT app performed with 91.9% sensitivity (CI 78.7, 97.2) and specificity was 91.4% (CI 77.6, 97.0) regardless of device operating system. Additionally, an analysis of surveillance data from January 2017 through mid-February 2019 showed that while the majority of the data packets from satellite clinics contained correct data, 36% of data points required correction by verification teams. Between November 2018 and mid-February 2019, it was also found that 44.8% of data was received after the expected submission date, although most (65.1%) reports were received within 2 days. Conclusions Overall, the mHAT mobile app was observed to be sensitive and specific when compared to both currently available benchtop lateral flow readers and visual inspection. The additional benefit of automating and standardizing LFA data collection and aggregation poses a vital improvement for low-resource health facilities and could increase the accuracy and speed of data reporting in surveillance campaigns.

Background The COVID-19 pandemic has drastically changed life in the United States, as the country has recorded over 23 million cases and 383,000 deaths to date. In the leadup to widespread vaccine deployment, testing and surveillance are critical for detecting and stopping possible routes of transmission. Contact tracing has become an important surveillance measure to control COVID-19 in the United States, and mobile health interventions have found increased prominence in this space. Objective The aim of this study was to investigate the use and usability of MyCOVIDKey, a mobile-based web app to assist COVID-19 contact tracing efforts, during the 6-week pilot period. Methods A 6-week study was conducted on the Vanderbilt University campus in Nashville, Tennessee. The study participants, consisting primarily of graduate students, postdoctoral researchers, and faculty in the Chemistry Department at Vanderbilt University, were asked to use the MyCOVIDKey web app during the course of the study period. Paradata were collected as users engaged with the MyCOVIDKey web app. At the end of the study, all participants were asked to report on their user experience in a survey, and the results were analyzed in the context of the user paradata. Results During the pilot period, 45 users enrolled in MyCOVIDKey. An analysis of their enrollment suggests that initial recruiting efforts were effective; however, participant recruitment and engagement efforts at the midpoint of the study were less effective. App use paralleled the number of users, indicating that incentives were useful for recruiting new users to sign up but did not result in users attempting to artificially inflate their use as a result of prize offers. Times to completion of key tasks were low, indicating that the main features of the app could be used quickly. Of the 45 users, 30 provided feedback through a postpilot survey, with 26 (58%) completing it in its entirety. The MyCOVIDKey app as a whole was rated 70.0 on the System Usability Scale, indicating that it performed above the accepted threshold for usability. When the key-in and self-assessment features were examined on their own, it was found that they individually crossed the same thresholds for acceptable usability but that the key-in feature had a higher margin for improvement. Conclusions The MyCOVIDKey app was found overall to be a useful tool for COVID-19 contact tracing in a university setting. Most users suggested simple-to-implement improvements, such as replacing the web app framework with a native app format or changing the placement of the scanner within the app workflow. After these updates, this tool could be readily deployed and easily adapted to other settings across the country. The need for digital contact tracing tools is becoming increasingly apparent, particularly as COVID-19 case numbers continue to increase while more businesses begin to reopen.

Improving access to HIV testing among youth at high risk is essential for reaching those who are most at risk for HIV and least likely to access health care services. This study evaluates the usability of mLab, an app with image-processing feature that analyzes photos of OraQuick HIV self-tests and provides real-time, personalized feedback. mLab includes HIV prevention information, testing reminders, and instructions. It was developed through iterative feedback with a youth advisory board (N = 8). The final design underwent heuristic (N = 5) and end-user testing (N = 20). Experts rated mLab following Nielsen's heuristic checklist. End-users used the Health Information Technology Usability Evaluation Scale. While there were some usability problems, overall study participants found mLab useful and user-friendly. This study provides important insights into using a mobile app with imaging for interpreting HIV test results with the goal of improving HIV testing and prevention in populations at high risk.

BACKGROUND:The COVID-19 pandemic has forced drastic changes to daily life, from the implementation of stay-at-home orders to mandating facial coverings and limiting in-person gatherings. While the relaxation of these control measures has varied geographically, it is widely agreed that contact tracing efforts will play a major role in the successful reopening of businesses and schools. As the volume of positive cases has increased in the United States, it has become clear that there is room for digital health interventions to assist in contact tracing.OBJECTIVE:The goal of this study was to evaluate the use of a mobile-friendly app designed to supplement manual COVID-19 contact tracing efforts on a university campus. Here, we present the results of a development and validation study centered around the use of the MyCOVIDKey app on the Vanderbilt University campus during the summer of 2020.METHODS:We performed a 6-week pilot study in the Stevenson Center Science and Engineering Complex on Vanderbilt University's campus in Nashville, TN. Graduate students, postdoctoral fellows, faculty, and staff >18 years who worked in Stevenson Center and had access to a mobile phone were eligible to register for a MyCOVIDKey account. All users were encouraged to complete regular self-assessments of COVID-19 risk and to key in to sites by scanning a location-specific barcode.RESULTS:Between June 17, 2020, and July 29, 2020, 45 unique participants created MyCOVIDKey accounts. These users performed 227 self-assessments and 1410 key-ins. Self-assessments were performed by 89% (n=40) of users, 71% (n=32) of users keyed in, and 48 unique locations (of 71 possible locations) were visited. Overall, 89% (202/227) of assessments were determined to be low risk (ie, asymptomatic with no known exposures), and these assessments yielded a CLEAR status. The remaining self-assessments received a status of NOT CLEAR, indicating either risk of exposure or symptoms suggestive of COVID-19 (7.5% [n=17] and 3.5% [n=8] of self-assessments indicated moderate and high risk, respectively). These 25 instances came from 8 unique users, and in 19 of these instances, the at-risk user keyed in to a location on campus.CONCLUSIONS:Digital contact tracing tools may be useful in assisting organizations to identify persons at risk of COVID-19 through contact tracing, or in locating places that may need to be cleaned or disinfected after being visited by an index case. Incentives to continue the use of such tools can improve uptake, and their continued usage increases utility to both organizational and public health efforts. Parameters of digital tools, including MyCOVIDKey, should ideally be optimized to supplement existing contact tracing efforts. These tools represent a critical addition to manual contact tracing efforts during reopening and sustained regular activity.

Background Mobile health (mHealth) interventions have the potential to transform the global health care landscape. The processing power of mobile devices continues to increase, and growth of mobile phone use has been observed worldwide. Uncertainty remains among key stakeholders and decision makers as to whether global health interventions can successfully tap into this trend. However, when correctly implemented, mHealth can reduce geographic, financial, and social barriers to quality health care. Objective The aim of this study was to design and test Beacon, a mobile phone–based tool for evaluating mHealth readiness in global health interventions. Here, we present the results of an application validation study designed to understand the mobile network landscape in and around Macha, Zambia, in 2019. Methods Beacon was developed as an automated mobile phone app that continually collects spatiotemporal data and measures indicators of network performance. Beacon was used in and around Macha, Zambia, in 2019. Results were collected, even in the absence of network connectivity, and asynchronously uploaded to a database for further analysis. Results Beacon was used to evaluate three mobile phone networks around Macha. Carriers A and B completed 6820/7034 (97.0%) and 6701/7034 (95.3%) downloads and 1349/1608 (83.9%) and 1431/1608 (89.0%) uploads, respectively, while Carrier C completed only 62/1373 (4.5%) file downloads and 0/1373 (0.0%) file uploads. File downloads generally occurred within 4 to 12 seconds, and their maximum download speeds occurred between 2 AM and 5 AM. A decrease in network performance, demonstrated by increases in upload and download durations, was observed beginning at 5 PM and continued throughout the evening. Conclusions Beacon was able to compare the performance of different cellular networks, show times of day when cellular networks experience heavy loads and slow down, and identify geographic “dead zones” with limited or no cellular service. Beacon is a ready-to-use tool that could be used by organizations that are considering implementing mHealth interventions in low- and middle-income countries but are questioning the feasibility of the interventions, including infrastructure and cost. It could also be used by organizations that are looking to optimize the delivery of an existing mHealth intervention with improved logistics management.