Background
A year after the COVID-19 pandemic started, there are still few scientific reports on COVID-19 in Africa. This study explores the clinical profiles and factors associated with COVID-19 in Cameroon.
Materials and methods
In this prospective cohort study, we followed patients admitted for suspicion of COVID-19 at Djoungolo Hospital between 01st April and 31st July 2020. Patients were categorised by age groups and disease severity: mild (symptomatic without clinical signs of pneumonia), moderate (with clinical signs of pneumonia without respiratory distress) and severe cases (clinical signs of pneumonia and respiratory distress not requiring invasive ventilation). Demographic information and clinical features were summarised. Multivariable analysis was performed to predict risk.
Findings
A total of 313 patients were admitted during the study period; 259 were confirmed cases of COVID-19 by Polymerase Chain Reaction (PCR). Among the confirmed cases, the male group aged 40 to 49 years (13.9%) was predominant. Disease severity ranged from mild (26.2%; n = 68) to moderate (59%; n = 153) to severe (14.7%; n = 38); the case fatality rate was 1% (n = 4). Dysgusia (46%; n = 119) and hyposmia/anosmia (37.8%; n = 98) were common features of COVID-19. Nearly one-third of patients had comorbidities (29%; n = 53), of which hypertension was the most common (18.9%; n = 49). Participation in mass gatherings (Odds Ratio (OR) = 2.37; P = 0.03) and dysgusia (OR = 2.09, P = 0.02) were predictive of diagnosis of COVID-19. Age groups 60 to 69 (OR = 7.41; P = 0.0001), 50 to 59 (OR = 4.09; P = 0.03), 40 to 49 (OR = 4.54; P = 0.01), male gender (OR = 2.53; P = 0.04), diabetes (OR = 4.05; P = 0.01), HIV infection (OR = 5.57; P = 0.03), lung disease (OR = 6.29; P = 0.01), dyspnoea (OR = 3.70; P = 0.008) and fatigue (OR = 3.35; P = 0.02) significantly predicted COVID-19 severity.
Conclusions
Most COVID-19 cases in this study were benign with low fatality. Age (40–70), male gender, HIV infection, lung disease, dyspnoea and fatigue are associated with severe COVID-19. Such findings may guide public health decision-making.