Using digital tools and antigen rapid testing to support household-level SARS-CoV-2 detection by community health workers in Rwanda: an operational pilot study.

OBJECTIVE: To evaluate the use of antigen-based rapid diagnostic tests (Ag-RDTs) alongside a digital tool to deliver household-level COVID-19 testing by community health workers (CHWs), in line with Rwanda's ambition to decentralise COVID-19 testing. DESIGN: This was an operational pilot study to evaluate the impact and operational characteristics of using the digital e-ASCov tool combined with Ag-RDTs to support COVID-19 symptom screening and rapid testing by CHWs across eight districts in Rwanda. A total of 800 CHWs selected from both rural and urban areas were trained in delivering Ag-RDTs for COVID-19 testing and using the e-ASCOV application for data capture on a smartphone. Laboratory technicians repeated a subset of Ag-RDTs to assess the concordance of results obtained by CHWs. The study also assessed CHWs' experience of the intervention using a mixed-methods approach. SETTING: Eight rural, urban and semiurban districts in Rwanda. PARTICIPANTS: A total of 19 544 individuals were enrolled and screened for signs and symptoms of COVID-19. INTERVENTIONS: Community-based screening for COVID-19 by CHWs using the digital tool e-ASCov combined with rapid testing using Ag-RDTs. MAIN OUTCOME MEASURES: Number of participants screened and tested; concordance of Ag-RDT results between CHWs and laboratory technicians; feasibility of study procedures by CHWs and CHWs perceptions of the digital tool and Ag-RDT testing. RESULTS: From February to May 2022, CHWs screened 19 544 participants, of whom 4575 (23.4%) had COVID-19-related symptoms or a history of exposure to the infection. Among them, 86 (1.9%) were positive on Ag-RDTs. Concordance of Ag-RDT results between CHWs and laboratory technicians was 100%. Of the 800 trained CHWs, 746 (93.3%) were independently able to conduct household-based COVID-19 screening, perform the Ag-RDTs and send data to the central server. Most CHWs (>80%) found Ag-RDTs and e-ASCOV easy to use. CONCLUSIONS: This study demonstrated the feasibility of deploying a digital tool and Ag-RDTs for household-level SARS-CoV-2 detection in Rwanda. The findings support a broader roll-out of digitally supported rapid testing by CHWs to broaden access to testing for priority diseases.

Improving COVID-19 contact tracing and testing of exposed individuals in Cameroon using digital health technology: a cluster randomised trial.

Background: Contact tracing was described as a key strategy to contribute to controlling the spread of severe acute respiratory syndrome of Coronavirus 2 (SARS-CoV-2) but implementing it can be a challenge. Digitalisation of contact tracing is among the proposed solutions being explored in sub-Saharan African settings. We assessed the effectiveness of a digital tool to expand SARS-CoV-2 testing in exposed individuals in Cameroon. Methods: We conducted a cluster-randomised (1:1) trial in eight health districts, including 22 facilities and SARS-CoV-2 testing units, randomly assigned to a digital (intervention) or standard (control) contact tracing approach. The intervention consisted of a contact tracing module added to the digital platform "Mamal PRO" used for monitoring and coordination of Coronavirus Disease 2019 pandemic response in Cameroon. The primary outcome was the proportion of contacts declared by SAR-CoV-2 index patients who were successfully traced and tested for SARS-CoV-2 evaluated with a Poisson regression model with cluster adjustment. This study is registered with ClinicalTrials.gov (NCT05684887). Findings: Between October 18, 2022, and March 31, 2023, we enrolled 164 index patients in the intervention arm and 149 in the control arm, who identified 854 and 849 contacts, respectively. In the intervention arm, 93.8% (801/854) of identified contacts were successfully reached by the tracing unit versus 54.5% (463/849) in the control arm. The intervention significantly increased the likelihood of successfully tracing contacts (adjusted relative risks (RR) 1.72 [95% CI: 1.00-2.95], p = 0.049). The median (interquartile range, IQR) time to successfully tracing contacts was 0 days [IQR: 0, 1] in the intervention and 1 day [IQR: 0, 2] in the control arm. In the intervention arm, 21.3% (182/854) of identified contacts received SARS-CoV-2 testing compared to 14.5% (123/849) in the control arm (adjusted RR 1.47 [95% CI: 0.44-4.90], p = 0.530). Interpretation: Digitalising the contact tracing process improved exposure notification and facilitated the tracing of a greater number of contacts of individuals infected with SARS-CoV-2 in resource-limited settings. Funding: The study was funded by FIND, United Kingdom (FCDO 40105983), Switzerland (81066910), Netherlands (SDD 4000004160), Canada (DFATD 7429348), The Kingdom of Saudi Arabia (FIND-ACT-A DX PARTNERSHIP 20.08.2020), The Rockefeller Foundation (2020 HTH 059), Germany (BMZ Covid-19 Diagnostic and Surveillance Response 27.07.2021), Australia (DFAT 76442), Kuwait (M239/2020), The Government of Portugal and Partners (ANF, BCP, CGF, APIFARMA) and The BlackRock Foundation (Grant Agreement as of April 20, 2022).

Uptake and effectiveness of a mobile application for real-time reporting and quality assurance of decentralized SARS-CoV-2 testing in Uganda.

Background: Effective management of the COVID-19 pandemic required rapid expansion of diagnosis. The introduction of antigen tests presented an opportunity to decentralize testing, but raised challenges with ensuring accurate and timely reporting of testing data, which is essential to guide the response. Digital solutions can help address this challenge and provide more efficient means of monitoring and quality assurance. Methods: Uganda's existing laboratory investigation form was digitized in the form of an Android-based application, eLIF, which was developed by the Central Public Health Laboratory and implemented in 11 high-volume facilities between December 2021 and May 2022. The app enabled healthcare workers to report testing data via mobile phone or tablet. Uptake of the tool was monitored through a dashboard that enabled real-time visibility into data being transmitted from sites, as well as qualitative insights from site visits and online questionnaires. Results and discussion: A total of 15,351 tests were conducted at the 11 health facilities during the study period. Of these, 65% were reported through eLIF, while 12% were reported through preexisting Excel-based tools. However, 23% of tests were only captured in paper registers and not transmitted to the national database, illustrating the need for increased uptake of digital tools to ensure real-time data reporting. While data captured through eLIF were transmitted to the national database within 0-3 days (min, max), data transmitted through Excel were transmitted in within 0-37 days (min, max), and data for paper-based reporting took up to 3 months. The majority of healthcare workers interviewed in an endpoint questionnaire responded that eLIF improved timeliness of patient management, and reduced reporting time. However, some functions of the app were not successfully implemented, such as providing random selections of samples for external quality assurance and enabling seamless linkage of these data. Challenges arose from broader operational complexities, such as staff workload, frequent task-shifting and unexpected changes to facility workflows, which limited adherence to the envisioned study procedures. Ongoing improvements are needed to adjust to these realities, to strengthen the technology and support to healthcare workers using it, to optimize the impact of this digital intervention.

Utilization of digital tools to enhance COVID-19 and tuberculosis testing and linkage to care: A cross-sectional evaluation study among Bodaboda motorbike riders in the Nairobi Metropolis, Kenya.

Kenya has registered over 300,000 cases of COVID-19 and is a high-burden tuberculosis country. Tuberculosis diagnosis was significantly disrupted by the pandemic. Access to timely diagnosis, which is key to effective management of tuberculosis and COVID-19, can be expanded and made more efficient through integrated screening. Decentralized testing at community level further increases access, especially for underserved populations, and requires robust systems for data and process management. This study delivered integrated COVID-19 and tuberculosis testing to commercial motorbike (Bodaboda) riders, a population at increased risk of both diseases with limited access to services, in four counties: Nairobi, Kiambu, Machakos and Kajiado. Testing sheds were established where riders congregate, with demand creation carried out by the Bodaboda association. Integrated symptom screening for tuberculosis and COVID-19 was conducted through a digital questionnaire which automatically flagged participants who should be tested for either, or both, diseases. Rapid antigen-detecting tests (Ag-RDTs) for COVID-19 were conducted onsite, while sputum samples were collected and transported to laboratories for tuberculosis diagnosis. End-to-end patient data were captured using digital tools. 5663 participants enrolled in the study, 4946 of whom were tested for COVID-19. Ag-RDT positivity rate was 1% but fluctuated widely across counties in line with broader regional trends. Among a subset tested by PCR, positivity was greater in individuals flagged as high risk by the digital tool (8% compared with 4% overall). Of 355 participants tested for tuberculosis, 7 were positive, with the resulting prevalence rate higher than the national average. Over 40% of riders had elevated blood pressure or abnormal sugar levels. The digital tool successfully captured complete end-to-end data for 95% of all participants. This study revealed high rates of undetected disease among Bodaboda riders and demonstrated that integrated diagnosis can be delivered effectively in communities, with the support of digital tools, to maximize access.

Adoption and uptake of the lateral flow urine LAM test in countries with high tuberculosis and HIV/AIDS burden: current landscape and barriers.

Background: Since 2015, the World Health Organization (WHO) has recommended a commercially available lateral-flow urine LAM test (Alere-LAM) to assist in the diagnosis of tuberculosis (TB) in severely ill people living with HIV (PLHIV). The test can rapidly detect TB in severely ill PLHIV and can identify PLHIV most at-risk of death, leading to mortality reductions. However, its uptake in countries with high burdens of TB and HIV has been slow. To assess the current use landscape and identify barriers to the adoption of Alere-LAM, we conducted a questionnaire-based study in 31 high TB and HIV/AIDS burden countries. Methods: Between November 2018 and December 2019, we collected responses to a semi-structured questionnaire that had been emailed to staff and affiliates of National TB Programs or HIV/AIDS Programs, Ministries of Health, and TB or HIV institutes of 31 high TB/HIV burden countries. Questions concerned country policies, adoption, and current use of Alere-LAM testing, as well as testing algorithms and barriers preventing Alere-LAM uptake. Results: We received questionnaire responses from 24 out of 31 (77%) high TB/HIV burden countries. Of these 24 countries, 11 (46%) had adopted Alere-LAM policies, with only five (21%) countries currently using Alere-LAM testing. Testing algorithms were generally aligned with WHO recommendations. Fifteen countries (63%) said they were planning to implement Alere-LAM testing in the near future. The most commonly cited constraint to adoption and implementation was budget limitations. Additional barriers to Alere-LAM implementation included lack of country-specific data and piloting, administrative hurdles such as regulatory agency approval, lack of coordination between National TB and HIV programs, and small perceived patient population. Conclusion: Responses to our questionnaire demonstrate the persistent gap between country-level policy and real-world use of Alere-LAM, as well as specific barriers that must be addressed to scale-up testing in PLHIV.