Digital health technology used in emergency large-scale vaccination campaigns in low- and middle-income countries: a narrative review for improved pandemic preparedness.

INTRODUCTION: Large-scale vaccination campaigns can benefit from using digital health tools, particularly in low- and middle-income countries (LMICs). Selecting the best tool to fit into a pre-existing digital landscape can be challenging. AREAS COVERED: We conducted a narrative review in PubMed and the grey literature for data available within 5 years to provide an overview of digital health tools used in large-scale vaccination campaigns for outbreak response in LMICs. We discuss tools used along the typical steps of a vaccination process. Digital tool functionalities and technical specifications, open-source options, data privacy and security concerns, and lessons learned from the use of these tools are discussed. EXPERT OPINION: The landscape of digital health tools for large-scale vaccination processes in LMICs is growing. For efficient implementation, countries should prioritize the appropriate tool(s) depending on their needs and available resources, develop a robust framework around data privacy and security, and select sustainable features. Improving internet connectivity and digital literacy in LMICs will facilitate adoption. This review may aid LMICs still needing to prepare large-scale vaccination campaigns in the selection of supporting digital health tools. Further research on impact and cost-effectiveness is needed.

Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States.

Coronavirus disease 2019 (COVID-19) continues to affect the world, and the design of strategies to curb disease outbreaks requires close monitoring of their trajectories. We present machine learning methods that leverage internet-based digital traces to anticipate sharp increases in COVID-19 activity in U.S. counties. In a complementary direction to the efforts led by the Centers for Disease Control and Prevention (CDC), our models are designed to detect the time when an uptrend in COVID-19 activity will occur. Motivated by the need for finer spatial resolution epidemiological insights, we build upon previous efforts conceived at the state level. Our methods-tested in an out-of-sample manner, as events were unfolding, in 97 counties representative of multiple population sizes across the United States-frequently anticipated increases in COVID-19 activity 1 to 6 weeks before local outbreaks, defined when the effective reproduction number Rt becomes larger than 1 for a period of 2 weeks.

Leapfrogging with technology: introduction of a monitoring platform to support a large-scale Ebola vaccination program in Rwanda.

Continued outbreaks of Ebola virus disease, including recent outbreaks in the Democratic Republic of the Congo (DRC), highlight the need for effective vaccine programs to combat future outbreaks. Given the population flow between DRC and Rwanda, the Rwanda Ministry of Health initiated a preventive vaccination campaign supported by a vaccination monitoring platform (VMP). The campaign aimed to vaccinate approximately 200,000 people from Rwanda's Rubavu and Rusizi districts with the two-dose vaccine regimen Ad26.ZEBOV, MVA-BN-Filo. The VMP encompassed: biometric identification (iris scanning), mobile messaging, and an interactive reporting dashboard. The VMP collected data used to register and identify participants at subsequent visits. Mobile message reminders supported compliance. To 13 November 2020, the campaign was half complete with Ad26.ZEBOV administered to 116,974 participants and MVA-BN-Filo to 76,464. MVA-BN-Filo should be given to participants approximately 8 weeks after the Ad26.ZEBOV with a compliance window of -14 and +28 days. Of the 83,850 participants who were eligible per this dosing window for the subsequent MVA-BN-Filo vaccine, 91.2% (76,453/83,850) received it and 82.9% (69,505/83,850) received it within the compliance window defined for this campaign. Utilization of the VMP was instrumental to the success of the campaign, using biometric technology, dashboard reporting of near real-time data analysis and mobile phone communication technology to support vaccine administration and monitoring. A comprehensive VMP is feasible in large-scale health-care campaigns, beneficial for public health surveillance, and can allow effective response to an infectious disease outbreak.

Overcoming the challenges of iris scanning to identify minors (1-4 years) in the real-world setting.

OBJECTIVE: Biometric identification techniques for pediatric use are limited. This investigation studied iris scanning in minors aged 1-4 in two exploratory studies in Belgium (n = 197) and Sierra Leone (n = 230), and in a subsequent clinical study in Sierra Leone (n = 635). Images of participants' irises were captured using a camera, while a survey assessed the ease of use with children. RESULTS: The image capture success rate per individual was high; 86.0% of the participants had ≥ 2 successful captures. Iris scan quality and surface were similar in all age groups and in the matching population database. When including feasibility in the analysis of minors aged 3-4, sensitivity and specificity were non-inferior compared to using the biometric of a guardian. However, the quality of iris scanning in minors aged 1-4 was worse than the iris scanning reference quality in adults. A mean total usability score of 1.55 ± 0.27 was calculated; a usability threshold of 1.45 is required for routine use. Overall, this technique is feasible in minors aged 3-4, replacing the use of guardian biometrics. Additional work is ongoing to improve this technique further, striving for uniformity from the age of 1.