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Abstract Background Digital health is being used as an accelerator to improve the traditional healthcare system, aiding countries in achieving their sustainable development goals. Burkina Faso aims to harmonize its digital health interventions to guide its digital health strategy for the coming years. The current assessment represents upstream work to steer the development of this strategic plan. Methods This was a quantitative, descriptive study conducted between September 2022 and April 2023. It involved a two-part survey: a self-administered questionnaire distributed to healthcare information managers in facilities, and direct interviews conducted with software developers. This was complemented by a documentary review of the country’s strategic and standards documents on digital transformation. Results Burkina Faso possesses a relatively comprehensive collection of governance documents pertaining to digital transformation. The study identified a total of 35 digital health interventions. Analysis showed that 89% of funding originated from technical and financial partners as well as the private sector. While the use of open-source technologies for the development of the applications, software, or platforms used to implement these digital health interventions is well established (77%), there remains a deficiency in the integration of data from different platforms. Furthermore, the classification of digital health interventions revealed an uneven distribution between the different elements across domains: the health system, the classification of digital health interventions (DHI), and the subsystems of the National Health Information System (NHIS). Most digital health intervention projects are still in the pilot phase (66%), with isolated electronic patient record initiatives remaining incomplete. Within the public sector, these records typically take the form of electronic registers or isolated specialty records in a hospital. Within the private sector, tool implementation varies based on expressed needs. Challenges persist in adhering to interoperability norms and standards during tool design, with minimal utilization of the data generated by the implemented tools. Conclusion This study provides an insightful overview of the digital health environment in Burkina Faso and highlights significant challenges regarding intervention strategies. The findings serve as a foundational resource for developing the digital health strategic plan. By addressing the identified shortcomings, this plan will provide a framework for guiding future digital health initiatives effectively.

The aim of this study was to analyze the spatio-temporal distribution and determinants of the 2017 dengue epidemic in Burkina Faso. A principal component analysis of meteorological and environmental factors was performed to reduce dimensions and avoid collinearities. An initial generalized additive model assessed the impact of the components derived from this analysis on dengue incidence. Dengue incidence increased mainly with relative humidity, precipitation, normalized difference vegetation index and minimum temperature with an 8-week lag. A Kulldoff Satscan scan was used to identify high-risk dengue clusters, and a second generalized additive model assessed the risk of a health area being at high risk according to land-use factors. The spatio-temporal distribution of dengue fever was heterogeneous and strongly correlated with meteorological factors. The rural communes of Sabaa and Koubri were the areas most at risk. This study provides useful information for planning targeted dengue control strategies in Burkina Faso.

BackgroundTo limit the spread of COVID-19 due to imported cases, Burkina Faso has set up quarantine measures for arriving passengers. We aimed to determine the incidence and predictors of imported cases of COVID-19 in Burkina Faso.MethodsA prospective cohort study was performed using data from passengers arriving at the airport from April 9 to August 31, 2020. The data was extracted from the District Health Information Software 2 (DHIS2) platform. Cox regression was used to identify predictors of imported cases of COVID-19.ResultsAmong 6,332 travelers who arrived in the study period, 173 imported cases (2.7%) were recorded. The incidence rate was 1.9 cases per 1,000 traveler-days (95%CI: 1.6–2.2 per 1,000). Passengers arriving in April (Adjusted hazard ratio [aHR] = 3.56; 95%CI: 1.62–7.81) and May (aHR = 1.92; 95% CI: 1.18–3.12) were more at risk of being tested positive compared to those arriving in August, as well as, passengers presenting with one symptom (aHR = 3.71; 95% CI: 1.63–8.43) and at least two symptoms (aHR = 10.82; 95% CI: 5.24–22,30) compared to asymptomatic travelers.ConclusionsThe incidence of imported cases was relatively low in Burkina Faso between April and August 2020. The period of travel and the presence of symptoms at arrival predicted the risk of being tested positive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This is essential in the context of the high circulation of virus variants worldwide and the low local capacity to perform genotyping tests to strengthen the surveillance and screening capacities at the points of entry into the country.

Abstract Background Early data on COVID-19 (based primarily on PCR testing) indicated a low burden in Sub-Saharan Africa. To better understand this, this study aimed to estimate the incidence rate and identify predictors of SARS-CoV-2 seroconversion in the two largest cities of Burkina Faso. This study is part of the EmulCOVID-19 project (ANRS-COV13). Methods Our study utilized the WHO Unity protocol for cohort sero-epidemiological studies of COVID-19 in general population. We conducted random sampling stratified by age group and sex. Individuals aged 10 years and older in the cities of Ouagadougou and Bobo-Dioulasso, Burkina Faso were included and surveyed at 4 time points, each 21 days apart, from March 3 to May 15, 2021. WANTAI SARS-CoV-2 Ab ELISA serological tests were used to detect total antibodies (IgM, IgG) in serum. Predictors were investigated using Cox proportional hazards regression. Results We analyzed the data from 1399 participants (1051 in Ouagadougou, 348 in Bobo-Dioulasso) who were SARS-CoV-2 seronegative at baseline and had at least one follow-up visit. The incidence rate of SARS-CoV-2 seroconversion was 14.3 cases [95%CI 13.3–15.4] per 100 person-weeks. The incidence rate was almost three times higher in Ouagadougou than in Bobo-Dioulasso (Incidence rate ratio: IRR = 2.7 [2.2–3.2], p