Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context

Clinical profiles, epidemiological characteristics and treatment outcomes of COVID-19 patients in North-eastern Ethiopia: A retrospective cohort study

BACKGROUND

COVID-19 is a rapidly emerging global health threat and economic disaster. The epidemiology and outcomes of COVID-19 patients in Ethiopia are scarce. Thus, the present study aimed to assess clinical profiles, epidemiological characteristics, and treatment outcomes of patients with COVID-19 and to identify determinants of the disease outcome among COVID-19 patients in North-eastern Ethiopia.

METHODS

A retrospective observational cohort study was conducted in North-eastern Ethiopia, from May 2020 to Jan 2022 on a total of 364 SARS-COV-2 infected patients. Demographic and clinical data were abstracted from the medical records of patients. Bivariable and multivariable analyses were conducted to determine the factors associated with the mortality of COVID-19 patients and variables with a P-value < 0.05 were considered statistically significant.

RESULT

Among 364 COVID-19 patients included in this study, two-thirds (68.1%) were males with a median age of 34 years. The majority; 42.9% & 33.0% respectively cases were detected at the health facility and community level surveillance. Furthermore, 6.6% of patients had pre-existing comorbidities of which diabetes mellitus (23.1%) and hypertension (15.3%) had the highest frequency. The symptomatic rate of COVID-19 patients was 30.5%. The most common clinical presentations were cough (26.9%), fever (26.1%), and shortness of breath (15.2%). Moreover, the mortality rate of COVID-19 patients was 4.1% which was independently predicted by a history of underlining co-morbidity (AHR:6.09; 95%CI:1.299-28.56; P = 0.022) and a history of severe or critical conditions (AHR 11.8; 95%CI:4.89-28.83; P = 0.003).

CONCLUSION

Severe or critical acute COVID-19 and underlining comorbidities are associated with higher mortality. Therefore, critical follow-up and management should be given to patients with underlying diseases is required.

Magnitude and associated factors of mortality among patients admitted with COVID-19 in Addis Ababa, Ethiopia

The COVID-19 pandemic continues to grow around the world and has caused enormous mortality and morbidity. The severity and mortality of coronavirus disease are associated with various comorbidities. The infection fatality rate was reported to be inconsistent with different studies. Therefore, the aim of this study was to assess the magnitude and factors associated with mortality among patients admitted to Eka Kotebe General Hospital, Addis Ababa, Ethiopia. An institutional-based cross-sectional study was conducted at Eka Kotebe General Hospital among patients who were admitted for COVID-19 from January 15, 2021, to June 30, 2021. A total of 393 records of patients were selected by simple random sampling. Data was extracted from compiled data forms where available information was already tabulated. Data was entered and analyzed using SPSS version 25. The determinant factors associated with mortality among COVID-19 patients were identified using bivariate and multivariable logistic regression analysis. A statistical association was declared with multivariable logistic regression using a 95% confidence interval and a P-value of less than 0.05. The proportion of COVID-19 mortality among patients admitted to Eka Kotebe General Hospital was 8.1% (95% CI (5.4-10.8%)). Age >50 years [AOR = 7.91; 95% CI (2.34-25.70)], being male [AOR = 2.09; 95% CI (1.20-3.65)], having diabetes mellitus [AOR = 2.64; 95% CI (1.30-5.35)], having hypertension [AOR = 2.67; 95% CI (1.22-5.88)] and having chronic kidney disease [AOR = 12.04; 95% CI (4.03-14.22)] were determinant factors of COVID-19 mortality. The current study findings revealed that COVID-19 mortality was high among hospitalized COVID-19 patients. Furthermore, age, gender, diabetes mellitus, hypertension, and chronic kidney disease were discovered to be independent predictors of COVID-19 mortality. Therefore, older COVID-19 patients and those with established comorbidities such as hypertension, diabetes, and end-stage renal disease should receive comprehensive preventative efforts, including vaccination.

Epidemiological, clinical, therapeutic features and predictors of death among COVID-19 patients hospitalized in Parakou: a cross-sectional study in Northern Benin

BACKGROUND

COVID-19 is an emerging contagious infection with polymorphic clinical manifestations. The purpose of this study was to describe the epidemiological, clinical, therapeutic features and identify the predictors of mortality among COVID-19 hospitalized cases in Parakou.

METHODS

This was a cross-sectional, descriptive and analytic study. Systematic recruitment was used to include all patients hospitalized with COVID-19 from May 8, 2020, to December 31, 2021, whose medical records were available and usable. The variables studied were clinical and paraclinical signs, diagnostic and therapeutic means, evolution under treatment and prognostic factors. This study was approved by the Local Ethical Committee. The data were analyzed using Stata/MP 14.1 software.

RESULTS

A total of 198 cases of COVID-19 were identified, 117 of whom were men. The mean age was 51.53 ± 19.51 years. The presenting signs were fever 146 (74.11%), cough 157 (79.70%) and dyspnea 118 (53.90%). It was severe COVID-19 in 108 cases (54.55%). Therapeutically, 95 patients (47.98%) had received the combination of Lopinavir/ritonavir and Ribavirin and 95 others (47.98%) received chloroquine. Recovery was noted in 151 (76.26%) patients. Mortality rate was 18.18%. Predictors of death were high blood pressure, presence of signs of severity, high-concentration mask ventilation used, and elevated transaminases.

CONCLUSION

COVID-19 was a reality in Parakou, with a significant number of severe cases requiring hospitalization. Several factors are associated with the prognosis of the disease.

SARS-CoV-2 case detection using community event-based surveillance system-February-September 2020: lessons learned from Senegal

The COVID-19 pandemic necessitated the rapid development and implementation of effective surveillance systems to detect and respond to the outbreak in Senegal. In this documentation, we describe the design and implementation of the Community Event-Based Surveillance (CEBS) system in Senegal to strengthen the existing Integrated Disease Surveillance and Response system. The CEBS system used a hotline and toll-free number to collect and triage COVID-19-related calls from the community. Data from the CEBS system were integrated with the national system for further investigation and laboratory testing. From February to September 2020, a total of 10 760 calls were received by the CEBS system, with 10 751 calls related to COVID-19. The majority of calls came from the Dakar region, which was the epicentre of the outbreak in Senegal. Of the COVID-19 calls, 50.2% were validated and referred to health districts for further investigation, and 25% of validated calls were laboratory-confirmed cases of SARS-CoV-2. The implementation of the CEBS system allowed for timely detection and response to potential COVID-19 cases, contributing to the overall surveillance efforts in the country. Lessons learned from this experience include the importance of decentralised CEBS, population sensitisation on hotlines and toll-free usage, and the potential role of Community Health Workers in triaging alerts that needs further analysis. This experience highlights the contribution of a CEBS system in Senegal and provides insights into the design and operation of such a system. The findings can inform other countries in strengthening their surveillance systems and response strategies.

Cost Effectiveness of Strategies for Caring for Critically Ill Patients with COVID-19 in Tanzania

BACKGROUND

The resources for critical care are limited in many settings, exacerbating the significant morbidity and mortality associated with critical illness. Budget constraints can lead to choices between investing in advanced critical care (e.g. mechanical ventilators in intensive care units) or more basic critical care such as Essential Emergency and Critical Care (EECC; e.g. vital signs monitoring, oxygen therapy, and intravenous fluids).

METHODS

We investigated the cost effectiveness of providing EECC and advanced critical care in Tanzania in comparison with providing 'no critical care' or 'district hospital-level critical care' using coronavirus disease 2019 (COVID-19) as a tracer condition. We developed an open-source Markov model ( https://github.com/EECCnetwork/POETIC_CEA ) to estimate costs and disability-adjusted life-years (DALYs) averted, using a provider perspective, a 28-day time horizon, patient outcomes obtained from an elicitation method involving a seven-member expert group, a normative costing study, and published literature. We performed a univariate and probabilistic sensitivity analysis to assess the robustness of our results.

, RESULTS

EECC is cost effective 94% and 99% of the time when compared with no critical care (incremental cost-effectiveness ratio [ICER] $37 [-$9 to $790] per DALY averted) and district hospital-level critical care (ICER $14 [-$200 to $263] per DALY averted), respectively, relative to the lowest identified estimate of the willingness-to-pay threshold for Tanzania ($101 per DALY averted). Advanced critical care is cost effective 27% and 40% of the time, when compared with the no critical care or district hospital-level critical care scenarios, respectively.

CONCLUSION

For settings where there is limited or no critical care delivery, implementation of EECC could be a highly cost-effective investment. It could reduce mortality and morbidity for critically ill COVID-19 patients, and its cost effectiveness falls within the range considered 'highly cost effective'. Further research is needed to explore the potential of EECC to generate even greater benefits and value for money when patients with diagnoses other than COVID-19 are accounted for.

Epidemiological factors affecting outpatient department service utilization and hospitalization in patients with diabetes: A time-series analysis from an Ethiopian hospital between 2018 and 2021

Background

The burden of diabetes-related deaths reached two million in 2019 globally. Accessibility to health care services and adherence to follow-up and therapy are key to improving outcomes for diabetic patients. We aimed to assess outpatient department (OPD) service utilization and diabetes-related hospitalizations over a period of 44 months.

Methods

A retrospective cohort study was conducted on OPD visits and hospitalizations recorded between January 1, 2018, and August 31, 2021, at the St Luke Catholic Hospital (Ethiopia). All diabetic patients were included in the analysis. A linear regression model was used for univariate analysis of OPD visits and hospitalizations and their association with potential predictors. The autoregressive integrated moving average (ARIMA) method was applied to both the time series of OPD visits and hospitalizations. Potential predictors were sociodemographic factors, COVID-19 cases, mean monthly temperature and precipitations.

Results

In the time series analysis, OPD visits increased over time (P < 0.01) while hospitalizations were stable. The time series model was ARIMA (0,1,1) for OPD visits and ARIMA (0,0,0) for hospitalizations. There were 1685 diabetes OPD patients (F = 732, 43%). Females had an average of 16% fewer OPD accesses per month (P < 0.01) and a lower number of hospitalizations per month (P = 0.03). There were 801 patients missing follow-up (48%). The time between follow-up increased with age (P < 0.01). OPD visits decreased differently by geographic area as COVID-19 cases increased (P < 0.01). There were 57 fewer forecast OPD visits per month on average using COVID-19 cases as ARIMA regressor. The odds ratio (OR) of new diagnosis at hospitalization was lower in patients with type 2 diabetes (OR = 0.26, 95% CI = 0.14-0.49, P = 0.02).

Conclusions

Despite an increase in OPD visits for diabetic patients over the study period, the number of losses at follow-up and diagnoses at hospitalization remains high. Female sex, older age, and COVID-19 were associated with impaired OPD service accessibility. Primary health care should be implemented to achieve better health coverage and improve diabetes management.

First wave COVID-19 pandemic in Senegal: Epidemiological and clinical characteristics

Background

The novel coronavirus disease 2019 (COVID-19) pandemic has spread from China to the rest of the world. Africa seems less impacted with lower number of cases and deaths than other continents. Senegal recorded its first case on March 2, 2020. We present here data collected from March 2 to October 31, 2020 in Senegal.

Methods

Socio-demographic, epidemiological, clinical and virological information were collected on suspected cases. To determine factors associated with diagnosed infection, symptomatic disease and death, multivariable binary logistic regression and log binomial models were used. Epidemiological parameters such as the reproduction number and growth rate were estimated.

Results

67,608 suspected cases were tested by the IPD laboratories (13,031 positive and 54,577 negative). All age categories were associated with SARS-CoV-2 infection, but also patients having diabetes or hypertension or other cardiovascular diseases. With diagnosed infection, patients over 65 years and those with hypertension and cardiovascular disease and diabetes were highly associated with death. Patients with co-morbidities were associated with symptomatic disease, but only the under 15 years were not associated with. Among infected, 27.67% were asymptomatic (40.9% when contacts were systematically tested; 12.11% when only symptomatic or high-risk contacts were tested). Less than 15 years-old were mostly asymptomatic (63.2%). Dakar accounted for 81.4% of confirmed cases. The estimated mean serial interval was 5.57 (± 5.14) days. The average reproduction number was estimated at 1.161 (95%CI: 1.159–1.162), the growth rate was 0.031 (95%CI: 0.028–0.034) per day.

Conclusions

Our findings indicated that factors associated with symptomatic COVID-19 and death are advanced age (over 65 years-old) and comorbidities such as diabetes and hypertension and cardiovascular disease.

COVID-19 Case Fatality Rate and Factors Contributing to Mortality in Ethiopia: A Systematic Review of Current Evidence

Background

The ongoing novel coronavirus disease 2019 (COVID-19) is triggering significant morbidity and mortality due to its contagious nature and absence of definitive management. In Ethiopia, despite a number of primary studies have been conducted to estimate the case fatality rate (CFR) of COVID-19, no review study has attempted to summarize the findings to better understand the nature of pandemics and the virulence of the disease.

Objective

To summarize the CFR of COVID-19 and factors contributing to mortality in Ethiopia.

Methods

PRISMA guideline was followed. PubMed, Science Direct, CINAHL, SCOPUS, Hinari, and Google Scholar were systematically searched using pre-specified keywords. Observational studies ie, cohort, cross-sectional, and case-control studies were included. The Newcastle-Ottawa scale adapted for observational studies was used to assess the quality of included studies. CFR was defined as the proportion of COVID-19 cases with the outcome of death within a given period. Factors contributing to COVID-19 mortality at p-value <0.05 were described narratively from the eligible articles.

Results

A total of 13 observational studies were included in this study. Consequently, this review confirmed the CFR of COVID-19 in Ethiopia ranges between 1–20%. Additionally, comorbid conditions, older age group, male sex, substance use, clinical manifestations (abnormal oxygen saturation level, atypical lymphocyte count, fever, and shortness of breath), disease severity, and history of surgery/trauma increased the likelihood of death from COVID-19 death.

Conclusion

This study shows that the range of CFR of COVID-19 in Ethiopia is almost equivalent to other countries, despite the country’s low testing capacity and case detection rate in reference to its total population. Comorbid diseases, older age group, male sex, cigarette smoking, alcohol drinking, clinical manifestations and disease severity, and history of surgery/trauma were factors contributing to COVID-19 mortality in Ethiopia. Therefore, given the alarming global situation and rapidly evolving large-scale pandemics, urgent interdisciplinary interventions should be implemented in those vulnerable groups to lessen the risk of mortality. Furthermore, the CFR of COVID-19 should be estimated from all treatment and rehabilitation centers in the country, as underestimation could be linked to a lack of preparedness and mitigation. A large set of prospective studies are also compulsory to better understand the CFR of COVID-19 in Ethiopia.

Time to Recovery from Covid-19 and Its Predictors Among Patients Admitted to Treatment Centers of Southern Nations Nationalities and Peoples Region (SNNPR), ETHIOPIA: Multi-Center Retrospective Cohort Study

Background

The world is currently facing a pandemic of Coronavirus Disease 2019 (Covid-19). It has caused significant morbidity and mortality. So far little is known about recovery time (prolonged hospital stay) from Covid-19 and its determinants in Ethiopia as well as in the study area. Therefore, the aim of this study was to determine time to recovery from Covid-19, and identify predictors of time to recovery among patients admitted to treatment centers of Southern Nations Nationalities and Peoples Region (SNNPR).

Methods and Materials

A facility-based retrospective cohort study was conducted among Covid-19 patients admitted to care centers of SNNPR from May 30, 2020 to October 15, 2021. A sample of 845 patients was included in the study. Summarization of the data was done using mean (standard deviation) and median (inter quartile range). Kaplan–Meier Survival Curve was used to estimate recovery time from Covid-19 and the independent effects of covariates on recovery time was analyzed using multivariable Cox-proportional hazard model.

Results

The incidence density of recovery was 8.24 per 100 person-days (95% CI: 7.67, 8.85). The overall median recovery time was 10 days (IQR: 8–16 days). Critical stage of Covid-19 (aHR = 0.19, 95% CI: 0.12, 0.29), severe stage of Covid-19 (aHR = 0.40, 95% CI: 0.29, 0.56), mechanical ventilation (aHR = 0.20, 95% CI: 0.073, 0.56) and treatment center (aHR = 0.68, 95% CI: 0.51, 0.90) were significant predictors of recovery rate among Covid-19 patients.

Conclusion

The median time to recovery from Covid-19 was relatively short. The incidence density of recovery was 8.24 per 100 person-days. The hazard of recovery was lower for patients at higher levels of Covid-19 severity and for patients in need of mechanical ventilation. Early identification of severity levels of the patients is required at the time of admission. Special attention, critical follow–up and management is warranted for patients at higher levels of Covid-19 severity.

Factors Associated for COVID19 Severity Among Patients Treated at Selgalu Treatment Center Assosa in Ethiopia: A Case-Control Study

Background

Most people infected with the SARS-CoV-2 virus experienced mild to moderate respiratory illness and recovered without requiring special treatment. However, some became seriously ill with conditions that require medical attention and intensive care unit (ICU) admission. Severity varies among individuals; this may be due to age differences and the presence of underlying disease conditions.

Objective

To identify factors associated with disease severity among COVID19 patients treated at Selgalu treatment center from November 1, 2020, to April 30, 2021.

Methods

A case–control study was implemented among patients admitted to Selgalu COVID19 treatment center in October 2021. A 210 (70 severe disease and 140 non-severe diseases), cases (disease severity), and controls (non-severe disease). Data entered to Epi data 4.6, exported to SPSS 25. A Chi-square test with a p-value of <0.05 was used as a statistically significant difference between characteristics of disease severity and non-severity of disease. Multivariable binary logistic regression was used to determine variables associated with disease severity based on an adjusted odds ratio with 95% CI and p-value < 0.05.

Results

210 (70 cases and 140 controls) selected charts in this study. Patients age category between 40–59 [AOR: 5.30 (2.27–12.34)], aged 60 or older [AOR: 3.85 (1.39–10.64)], patients with fever [AOR: 3.98 (1.59–9.96)], fatigue [AOR: 3.14 (1.50–6.54)], and hypertensive patients [AOR: 3.68 (1.53–8.82)] were significantly predictors for COVID19 disease severity after adjusting for other variables.

Conclusion

From this study, we conclude that being age 60 or older and 40–59 age groups, having symptoms of fever, fatigue, and underlying comorbid illness hypertension. Were identified a significant predictor of severe COVID-19 disease; despite our limitation of study data highlights the important factors associated with disease severity with covid19 admitted to Selgalu treatment center.

COVID-19 disease severity and associated factors among Ethiopian patients: A study of the millennium COVID-19 care center

Background

The COVID-19 pandemic started a little later in Ethiopia than the rest of the world and most of the initial cases were reported to have a milder disease course and a favorable outcome. This changed as the disease spread into the population and the more vulnerable began to develop severe disease. Understanding the risk factors for severe disease in Ethiopia was needed to provide optimal health care services in a resource limited setting.

Objective

The study assessed COVID-19 patients admitted to Millennium COVID-19 Care Center in Ethiopia for characteristics associated with COVID-19 disease severity.

Methods

A cross-sectional study was conducted from June to August 2020 among 686 randomly selected patients. Chi-square test was used to detect the presence of a statistically significant difference in the characteristics of the patients based on disease severity (Mild vs Moderate vs Severe). A multinomial logistic regression model was used to identify factors associated with COVID-19 disease severity where Adjusted Odds ratio (AOR), 95% CIs for AOR and P-values were used for significance testing.

Results

Having moderate as compared with mild disease was significantly associated with having hypertension (AOR = 2.30, 95%CI = 1.27,4.18), diabetes mellitus (AOR = 2.61, 95%CI = 1.31,5.19for diabetes mellitus), fever (AOR = 6.12, 95%CI = 2.94,12.72) and headache (AOR = 2.69, 95%CI = 1.39,5.22). Similarly, having severe disease as compared with mild disease was associated with age group (AOR = 4.43, 95%CI = 2.49,7.85 for 40–59 years and AOR = 18.07, 95%CI = 9.29,35.14for ≥ 60 years), sex (AOR = 1.84, 95%CI = 1.12,3.03), hypertension (AOR = 1.97, 95%CI = 1.08,3.59), diabetes mellitus (AOR = 3.93, 95%CI = 1.96,7.85), fever (AOR = 13.22, 95%CI = 6.11, 28.60) and headache (AOR = 4.82, 95%CI = 2.32, 9.98). In addition, risk factors of severe disease as compared with moderate disease were found to be significantly associated with age group (AOR = 4.87, 95%CI = 2.85, 8.32 for 40–59 years and AOR = 18.91, 95%CI = 9.84,36.331 for ≥ 60 years), fever (AOR = 2.16, 95%CI = 1.29,3.63) and headache (AOR = 1.79, 95%CI = 1.03, 3.11).

Conclusions

Significant factors associated with severe COVID-19 in Ethiopia are being older than 60 years old, male, a diagnosis of hypertension, diabetes mellitus, and the presence of fever and headache. This is consistent with severity indicators identified by WHO and suggests the initial finding of milder disease in Ethiopia may have been because the first people to get COVID-19 in the country were the relatively younger with fewer health problems.

Willingness to Receive COVID-19 Vaccination Among Adult Diabetes Patients in Woldia Comprehensive Specialized Hospital, North Ethiopia; A Cross-Sectional Study

BACKGROUND

According to recently published data, individuals infected with COVID-19 having concomitant diabetes may experience disease worsening or even death. The purpose of this study was to determine diabetes patients' willingness to get the COVID-19 vaccine as well as its magnitude and determinants.

METHODS

Three hundred eighty six diabetes patients who visited Woldia Comprehensive Specialized Hospital during February and March 2022 participated in this institution-based cross-sectional study. Descriptive statistics were used to demonstrate frequencies and percentages, while logistic regression was used to identify the relevant determinants of vaccination readiness. Age, gender, income, place of residence, COVID-19 exposure, length of diabetes, awareness of and attitudes toward the COVID-19 immunization were all evaluated as associated factors.

RESULTS

Out of 386 study participants, 268 (69.43%) were male and 146 (37.82) completed their secondary schooling. From 386 study participants 82.6% (95% CI; 78.5-86.3%) were willing to get vaccinated. The uptake of the COVID-19 vaccination among diabetes patients was independently influenced by sex (Adjusted Odd Ratio [AOR] = 6.84 (2.98, 15.68)), exposure to the illness (AOR 8.98 (3.22, 25.04)), attitude (AOR = 2.63 (1.2, 5.77)), and length of the disease (AOR = 0.62 (0.51, 0.76)).

CONCLUSION

Most of the study participants were willing to get the COVID-19 immunization. The relevant agency should make the immunization available in order to enhance disease control and reduce infection-related complications with special consideration of diabetes patients.