University of Mbuji Mayi

This study examines the factors influencing rural household engagement in agricultural entrepreneurship in Kasai Oriental. Despite the coexistence of farming activities with a thriving artisanal diamond mining sector, the region continues to experience persistently high unemployment, poverty, and food insecurity. In front of such challenges, agricultural entrepreneurship may hold the alleviating keystone. To investigate determinants of agricultural entrepreneurship engagement, the study lies on fixed-effects logit model to control unobserved heterogeneity at the village level. Key findings indicate that self-efficacy significantly increase the likelihood to engage in agricultural entrepreneurship, while fear of failure substantially reduces it. Access to land and participation in informal credit groups also exert positive influences on decision to engage in entrepreneurial activity. Conversely, demographic factors reveal lower engagement among younger, more educated individuals, and big households, likely due to attraction of get-quick-rich artisanal mining perceived as offering high income. Additionally, land conflicts and proximity to mining sites further diminish the probability of engaging in agricultural ventures. Based on these results, policy interventions must focus on vocational training, psychological support, improved access to credit and land. Such efforts should specifically target youth and educated rural residents to enhance the attractiveness and sustainability of the agricultural sector. Thus, this study contributes to a nuanced understanding of the multifaceted drivers of rural agricultural entrepreneurship in the context of mining region and provides actionable insights for targeted strategies to foster sustainable rural economic development.

ABSTRACT Background and Aim This study aimed to investigate the epidemiological, clinical, and therapeutic aspects of osteoarticular complications in patients with sickle cell disease in Bukavu. Methods We conducted a multicenter cross‐sectional study over 5 years, focusing on 31 patients with sickle cell disease who were admitted for osteoarticular complications in Bukavu. Data were collected from medical records and analyzed with the Statistical Package for Social Science 26 (IBM, SPSS 26). Results We recorded 31 (6.07%) sickle cell patients with osteoarticular complications, with a mean age of 10.5 ± 5.6 years (extremes: 2–30 years). Pain, fever, and functional impotence were the most frequent reasons for consultation with 9 (29.03%) patients. Septic arthritis was the most common complication in 10 (32.26%), followed by osteonecrosis of the femoral head in 8 (25.81%), chronic osteomyelitis in 7 (22.58%) cases, and acute osteomyelitis in 4 (12.70%) patients. The femur was the most affected bone. Articular complications predominantly impacted larger joints, with the knee joint experiencing the highest rate of damage, occurring in 38.71% of cases. Treatment, including medical and surgical methods, was provided in 16 cases (51.6%). Complete healing without residual effects was achieved in 22 patients (70.96%). Conclusion The osteoarticular complications of sickle cell disease are frequent in the city of Bukavu, and regular monitoring and early consultation would enable early diagnosis and management.

Background Osteoarticular complications of diabetes mellitus (DM) are underrecognized but significantly impact patient outcomes. This study evaluated their prevalence, characteristics, and predictors among diabetic patients in Bukavu, Democratic Republic of Congo. Methods This retrospective multicenter study analyzed 103 diabetic patients with osteoarticular complications across four Bukavu hospitals from 2021 to 2023. Data were extracted from medical records and analyzed using descriptive statistics, chi-square tests, logistic regression, Kaplan-Meier survival analysis, and Pearson correlation in SPSS. Results Among 694 diabetic patients, 103 (14.84%) had osteoarticular complications. Gender distribution was balanced (50.5% female, sex ratio of 0.98) was observed, with a mean age of 59.98 ± 10.5 years and BMI of 27.5 ± 8.6 kg/m². Type 2 DM (80.6%), poor glycemic control (87.4%), and poor treatment compliance (68.9%) were common. Diabetic foot ulcers (36.9%) and osteoarthritis (29.1%) predominated, primarily affecting lower limbs (58.3%). Medical-surgical treatment was used in 54.4% of cases, with a 6.8% mortality rate, mostly within 36 days. Poor glycemic control increased the risk of death (OR = 3.45, 95% CI: 1.12–10.63, p = 0.031), and disease duration correlated with severity (r = 0.31, p = 0.002). As a component of Survival, Time to death was shorter with poor compliance ( p = 0.048). Conclusions Osteoarticular complications are prevalent in Bukavu’s diabetic population, associated with poor glycemic control and longer disease duration. Enhanced screening and adherence strategies are critical for prevention and improved outcomes.

Artificial Intelligence (AI) is revolutionizing various fields, including public health surveillance. In Africa, where health systems frequently encounter challenges such as limited resources, inadequate infrastructure, failed health information systems and a shortage of skilled health professionals, AI offers a transformative opportunity. This paper investigates the applications of AI in public health surveillance across the continent, presenting successful case studies and examining the benefits, opportunities, and challenges of implementing AI technologies in African healthcare settings. Our paper highlights AI's potential to enhance disease monitoring and health outcomes, and support effective public health interventions. The findings presented in the paper demonstrate that AI can significantly improve the accuracy and timeliness of disease detection and prediction, optimize resource allocation, and facilitate targeted public health strategies. Additionally, our paper identified key barriers to the widespread adoption of AI in African public health systems and proposed actionable recommendations to overcome these challenges.

Abstract Introduction: Cleft lip and/or palate (CLP) are congenital malformations which mainly affect the upper lip and/or palate and are the most common malformations of the orofacial sphere. The objective of the present study was to describe the epidemiological, clinical and therapeutic profile of cleft lip and palate patients managed in the Democratic Republic of Congo (DRC). Material and Methods a retrospective descriptive study of 1666 patients with cleft lip and palate collected in 20 provinces of the DRC and managed between January 2017 and June 2022. The variables studied were epidemiological, anatomo-clinical and therapeutic. Results The mean age of patients seeking care was 11.6 years. The male predominance was (58.6%). A family history of CLP was found in 4.3% of cases and the association of CLP with other visible congenital malformations was identified in 1.5%. Isolated cleft lips were (66.1%) and palates (2.6%) of cases. Combinations involving cleft lip, palate and alveoli were observed respectively as following in terms of frequency: cleft lip-alveolar (15.7%), cleft lip-alveolar-palatal (10.6%) and cleft lip-palate (4.9%). The left side cleft was more common. Cheiloplasty was the most common repair procedure for cleft lip (81.4%) and the isolate palatoplasty was performed for 2.6% cleft palate. Conclusion In the DRC, CLP are common, with male predominance and often treated late. Cleft lips occur more commonly than cleft palates.