RESUMO
BACKGROUND: The COVID-19 pandemic brought challenges requiring timely health data sharing to inform accurate decision-making at national levels. In Botswana, we adapted and integrated the Research Electronic Data Capture (REDCap) and the District Health Information System version 2 (DHIS2) platforms to support timely collection and reporting of COVID-19 cases. We focused on establishing an effective COVID-19 data flow at the national public health laboratory, being guided by the needs of health care professionals at the National Health Laboratory (NHL). This integration contributed to automated centralized reporting of COVID-19 results at the Ministry of Health (MOH). OBJECTIVE: This paper reports the experiences, challenges, and lessons learned while designing, adapting, and implementing the REDCap and DHIS2 platforms to support COVID-19 data management at the NHL in Botswana. METHODS: A participatory design approach was adopted to guide the design, customization, and implementation of the REDCap platform in support of COVID-19 data management at the NHL. Study participants included 29 NHL and 4 MOH personnel, and the study was conducted from March 2, 2020, to June 30, 2020. Participants' requirements for an ideal COVID-19 data management system were established. NVivo 11 software supported thematic analysis of the challenges and resolutions identified during this study. These were categorized according to the 4 themes of infrastructure, capacity development, platform constraints, and interoperability. RESULTS: Overall, REDCap supported the majority of perceived technical and nontechnical requirements for an ideal COVID-19 data management system at the NHL. Although some implementation challenges were identified, each had mitigation strategies such as procurement of mobile Internet routers, engagement of senior management to resolve conflicting policies, continuous REDCap training, and the development of a third-party web application to enhance REDCap's capabilities. Lessons learned informed next steps and further refinement of the REDCap platform. CONCLUSIONS: Implementation of REDCap at the NHL to streamline COVID-19 data collection and integration with the DHIS2 platform was feasible despite the urgency of implementation during the pandemic. By implementing the REDCap platform at the NHL, we demonstrated the possibility of achieving a centralized reporting system of COVID-19 cases, hence enabling timely and informed decision-making at a national level. Challenges faced presented lessons learned to inform sustainable implementation of digital health innovations in Botswana and similar resource-limited countries.
RESUMO
HIV-1 uses the coreceptors CCR5 and/or CXCR4 for cell entry. Monotropic CCR5-using variants are found early in the infection while CXCR4-using variants may appear after progression to AIDS. CXCR4 use may consist of both monotropic and dualtropic viruses. The viral phenotype is important in evaluating the response to CCR5 inhibitors, a new class of antiviral drugs. The coreceptor use of HIV-1 was investigated using population sequencing in 24 patients from Botswana, carrying HIV-1 subtype C and failing antiretroviral treatment, while 26 treatment-naive patients acted as controls. Single genome sequencing was used to discern minor HIV-1 populations in the treatment-experienced group. The Geno2Pheno method was employed to predict the coreceptor use phenotype from HIV-1 env gp120 V3 DNA sequences. The glycan-charge model adjusted for subtype C was also used for phenotype prediction. The viral phenotype of population sequences was predicted using Geno2Pheno in 24/24 treatment-experienced patients, of whom eight (33%) were predicted to harbor CXCR4-using strains as compared to 2/26 in the treatment-naive group (p=0.03). Single genome sequencing generated 4-23 clones/patient in the treatment-experienced group. Altogether, 90/295 (31%) putative CXCR4-using clones were identified. In 10/24 (42%) treated patients at least one clone was predicted to be CXCR4-using, further increasing the amount of identified treatment-experienced patients with CXCR4 use. Although subtype C is usually associated with comparatively little CXCR4 use, the frequency of CXCR4 use in treatment-experienced patients with subtype C can be higher, which may have implications for the administration of CCR5 inhibitors in this patient group.
