Clinical features of COVID-19 in Ghana: symptomatology, illness severity and comorbid non-communicable diseases

Objective: This analysis described the clinical features of COVID-19 in the early phase of the pandemic in Ghana.Methods: Data were extracted from two national COVID-19 treatment centers in Ghana for over 11 weeks(from March to May 2020). Descriptive and inferential statistics were performed. Modified Ordered Logistic and Negative Binomial Regression analysis were applied to establish factors associated with illness severity and Non-communicable Disease (NCDs) counts respectively. All analysis was conducted at the 95% confidence level (p-value ≤ 0.05) using Stata 16.Results: Among the 275 patients, the average age was 40.7±16.4, with a preponderance of males (54.5%). The three commonest symptoms presented were cough (21.3%), headache (15.7%), and sore throat (11.7%). Only 7.6% of the patients had a history of fever. Most patients were asymptomatic (51.65). Approximately 38.9% have an underlying co-morbid NCDs, with Hypertension (32.1%), Diabetes (9.9%), and Asthma (5.2%) being the three commonest. The odds of Moderate/severe (MoS) was significantly higher for those with unknown exposures to similar illness [aOR(95%CI) = 4.27(1.12-10.2)] compared with non-exposure to similar illness. An increased unit of NCD’s count significantly increased the odds of COVID-19 MoS illness by 26%[cOR(95%CI) =1.26(1.09-1.84)] and 67% (adjusting for age) [aOR(95%CI)=1.67(1.13-2.49)].Conclusion: The presence of cardiovascular co-morbidities dictated the frequency of reported symptoms and severity of COVID-19 infection in this sample of Ghanaians. Physicians should be aware of the presence of co-morbid NCDs and prepare to manage effectively among COVID-19 patients

Sex differences in perceived risk and testing experience of HIV in an urban fishing setting in Ghana

The concept of neighborhood remains important in criminology but there is an increasing academic interest in the potential impact of the Modifiable Areal Unit Problem (MAUP) on neighborhood based studies. In the present study data over arson from the Swedish rescue services 2007-2012 have been employed to analyze MAUP in the city of Malmö, Sweden. The city has been divided into 50*50 meter pixels as micro-places (n=64540) which have been assigned a value for arson from frequency of arson within the pixel. The analysis is based on a comparison of two types of administrative geographical units alongside 40 randomly generated sets of thiessen polygon geographical units. Empty two-level hierarchical regression models with the micro-places as level 1 unit have been used to calculate Intra-Class Correlations (ICC) separately with each of the 42 different geographical units of analysis as level 2 units. The analysis is repeated with two alternative methods, kernel density and euclidian distance, to calculate a value for each micro-place. Results show that administrative geographical units of analysis in some cases just are marginally better than geographical units with random boundaries if the basic urban structure is taken into account

Prevalence of pneumonia by chest x-ray, associated demographic characteristics and health risk factors among COVID-19 patients in Ghana

Objective: The study was conducted to determine the prevalence of radiologically diagnosed pneumonia among COVID-19 patients and associated factors.Design, setting, and participants: A retrospective manual data extraction of 275 medical records of COVID-19 patients was conducted at two COVID-19 national treatment centres in Accra from March to May 2020. All patients had a chest x-ray done.Main outcome and analysis: The main outcome was the presence of pneumonia. Descriptive statistics and Chi-square test of independence were employed to determine the associations between independent variables and the presence of pneumonia. All analysis was performed using Stata 16, and a p-value ≤ 0.05 was deemed significantResults: The prevalence of pneumonia was 44%(95%CI) =38.2-50.0). Chi-square independent test indicated that pneumonia in the COVID-19 patients was associated with educational level, history of domestic and international travel, mass gathering in the past 14 days before diagnosis, and discharge plan (p-value< 0.05). Patients classified as secondary cases (61.5%) and those discharged as fully recovered from the health facility (61.2%) had a higher prevalence of pneumonia. In addition, COVID-19 patients with hypertension (32.1%) and asthma (5.2%) had a significantly higher prevalence of pneumonia.Conclusion: Overall, the prevalence of pneumonia was 44% and was associated with the demographic and personal characteristics of the patients. Early detection through contact tracing and community surveillance should be intensified to pick up more asymptomatic cases. The role of the chest x-ray for triaging patients and for clinical management of symptomatic patients remains key

Clinical features of COVID-19 in Ghana : Symptomatology, illness severity and comorbid non-communicable diseases

Objective: This analysis described the clinical features of COVID-19 in the early phase of the pandemic in Ghana. Methods: Data were extracted from two national COVID-19 treatment centers in Ghana for over 11 weeks(from March to May 2020). Descriptive and inferential statistics were performed. Modified Ordered Logistic and Negative Binomial Regression analysis were applied to establish factors associated with illness severity and Non-communicable Disease (NCDs) counts respectively. All analysis was conducted at the 95% confidence level (p-value ≤ 0.05) using Stata 16. Results: Among the 275 patients, the average age was 40.7±16.4, with a preponderance of males (54.5%). The three commonest symptoms presented were cough (21.3%), headache (15.7%), and sore throat (11.7%). Only 7.6% of the patients had a history of fever. Most patients were asymptomatic (51.65). Approximately 38.9% have an underlying co-morbid NCDs, with Hypertension (32.1%), Diabetes (9.9%), and Asthma (5.2%) being the three commonest. The odds of Moderate/severe (MoS) was significantly higher for those with unknown exposures to similar illness [aOR(95%CI) = 4.27(1.12-10.2)] compared with non-exposure to similar illness. An increased unit of NCD’s count significantly increased the odds of COVID-19 MoS illness by 26%[cOR(95%CI) =1.26(1.09-1.84)] and 67% (adjusting for age) [aOR(95%CI)=1.67(1.13-2.49)]. Conclusion: The presence of cardiovascular co-morbidities dictated the frequency of reported symptoms and severity of COVID-19 infection in this sample of Ghanaians. Physicians should be aware of the presence of co-morbid NCDs and prepare to manage effectively among COVID-19 patients