Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa

[Epidemiological characteristics of the Covid-19 epidemic between 2020 and 2022 in Kongo central, DRC]

Introduction

The Democratic Republic of Congo (DRC) has experienced widespread community transmission of SARS-CoV-2 and has recorded four successive waves from March 2020 to March 2022. The objective of this study is to determine the socio-demographic characteristics of Covid-19 patients during these epidemic waves in the province of Kongo central and to identify factors associated with deaths.

Material and methods

This is a cross-sectional study of Covid-19 data from the provincial surveillance system. The data consisted of epidemiological surveillance data, laboratory data (tests), hospital data and patient follow-up data. We determined the characteristics of positive cases throughout the period and implemented logistic regression of factors associated with death.

Results

During the successive waves, 9, 573 positive cases were reported in the province, 546 cases in the first wave and 6, 346 in the fourth wave. Seven positive cases out of 10 concerned people aged 25 to 64. The districts of Matadi, Moanda and Mbanza-Ngungu were the most affected. Age above 64 [OR: 7.2 CI:5.1-10.3] and wave 2 [OR: 4.4 CI:1.6-12.4] were the factors statistically associated with death.

Conclusion

As in other African settings, age, comorbidities, higher socio-professional level and living in urban areas were the major risk factors for severe forms of the disease and death. Our analysis underlines the importance of collecting and analysing several epidemiological variables down to the provincial level over time for a better continuous knowledge of the situation.

Factors associated with COVID-19 fatality among patients admitted in Mashonaland West Province, Zimbabwe 2020-2022: a secondary data analysis

Introduction

approximately 15% of COVID-19 patients develop symptoms necessitating admission. From 2020 to 2022, Mashonaland West Province had an institutional case fatality rate of 23% against a national rate of 7%. Therefore, we evaluated the COVID-19 admissions in the province to determine the factors associated with COVID-19 mortality.

Methods

we conducted an analytical cross-sectional study based on secondary data from isolation centers across the province using all 672 death audit forms and patient records. We obtained data on patient demographics, signs and symptoms, clinical management and oxygen therapy administered, among other things. Data were entered into an electronic form and imported into Epi-info 7 for analysis bivariate and multivariate conducted. Results: we found that being an older man, aOR 1.04 (1.03-1.05), who had diabetes aOR 6.0 (95% CI: 3.8-9.2) and hypertension aOR 4.5 (95% CI: 2.8-6.5) were independent risk factors. Patients put on dexamethasone aOR 2.4 (95% CI: 1.6-3.4) and heparin/clexane aOR 1.6 (95% CI: 1.1-2.2) had a higher mortality risk. However, vitamin C aOR 0.48 (95% CI: 0.31-0.71) and oxygen therapy aOR 0.14 (95% CI: 0.10-0.19) and being pregnant aOR 0.06 (95% CI: 0.02-0.14) were protective. Conclusion: mortality risk increased in older male patients with comorbidities and with those on dexamethasone and heparin therapy. Oxygen therapy and vitamin C were protective. There is a need to conduct further study of the source of these variations in risk across patients to establish the true impact of differences in individuals' mortality.

Risk factors for SARS-CoV-2 related mortality and hospitalization before vaccination: A meta-analysis

The literature remains scarce regarding the varying point estimates of risk factors for COVID-19 associated mortality and hospitalization. This meta-analysis investigates risk factors for mortality and hospitalization, estimates individual risk factor contribution, and determines drivers of published estimate variances. We conducted a systematic review and meta-analysis of COVID-19 related mortality and hospitalization risk factors using PRISMA guidelines. Random effects models estimated pooled risks and meta-regression analyses estimated the impact of geographic region and study type. Studies conducted in North America and Europe were more likely to have lower effect sizes of mortality attributed to chronic kidney disease (OR: 0.21, 95% CI: 0.09-0.52 and OR: 0.25, 95% CI: 0.10-0.63, respectively). Retrospective studies were more likely to have decreased effect sizes of mortality attributed to chronic heart failure compared to prospective studies (OR: 0.65, 95% CI: 0.44-0.95). Studies from Europe and Asia (OR: 0.42, 95% CI: 0.30-0.57 and OR: 0.49, 95% CI: 0.28-0.84, respectively) and retrospective studies (OR: 0.58, 95% CI: 0.47-0.73) reported lower hospitalization risk attributed to male sex. Significant geographic population-based variation was observed in published comorbidity related mortality risks while male sex had less of an impact on hospitalization among European and Asian populations or in retrospective studies.

The Management of Myocardial Injury Related to SARS-CoV-2 Pneumonia

The global evolution of the SARS-CoV-2 virus is known to all. The diagnosis of SARS-CoV-2 pneumonia is expected to worsen, and mortality will be higher when combined with myocardial injury (MI). The combination of novel coronavirus infections in patients with MI can cause confusion in diagnosis and assessment, with each condition exacerbating the other, and increasing the complexity and difficulty of treatment. It would be a formidable challenge for clinical practice to deal with this situation. Therefore, this review aims to gather literature on the progress in managing MI related to SARS-CoV-2 pneumonia. This article reviews the definition, pathogenesis, clinical evaluation, management, and treatment plan for MI related to SARS-CoV-2 pneumonia based on the most recent literature, diagnosis, and treatment trial reports. Many studies have shown that early diagnosis and implementation of targeted treatment measures according to the different stages of disease can reduce the mortality rate among patients with MI related to SARS-CoV-2 pneumonia. The reviewed studies show that multiple strategies have been adopted for the management of MI related to COVID-19. Clinicians should closely monitor SARS-CoV-2 pneumonia patients with MI, as their condition can rapidly deteriorate and progress to heart failure, acute myocardial infarction, and/or cardiogenic shock. In addition, appropriate measures need to be implemented in the diagnosis and treatment to provide reasonable care to the patient.

Multiple introduced lineages and the single native lineage co-driving the four waves of the COVID-19 pandemic in West Africa

Coronavirus disease 2019 (COVID-19) has become a vast burden on public health and socioeconomics in West Africa, but the epidemic situation is unclear. Therefore, we conducted a retrospective analysis of the positive rate, death rate, and diversity of SARS-CoV-2. As of March 31, 2022, a total of 894,813 cases of COVID-19 have been recorded, with 12,028 deaths, both of which were distributed in all 16 countries. There were four waves of COVID-19 during this period. Most cases were recorded in the second wave, accounting for 34.50% of total cases. These data suggest that although West Africa seems to have experienced a low and relatively slow spread of COVID-19, the epidemic was ongoing, evolving with each COVID-19 global pandemic wave. Most cases and most deaths were both recorded in Nigeria. In contrast, the fewest cases and fewest deaths were reported, respectively, in Liberia and Sierra Leone. However, high death rates were found in countries with low incidence rates. These data suggest that the pandemic in West Africa has so far been heterogeneous, which is closely related to the infrastructure of public health and socioeconomic development (e.g., extreme poverty, GDP per capita, and human development index). At least eight SARS-CoV-2 variants were found, namely, Delta, Omicron, Eta, Alpha, Beta, Kappa, Iota, and Gamma, which showed high diversity, implicating that multiple-lineages from different origins were introduced. Moreover, the Eta variant was initially identified in Nigeria and distributed widely. These data reveal that the COVID-19 pandemic in the continent was co-driven by both multiple introduced lineages and a single native lineage. We suggest enhancing the quarantine measures upon entry at the borders and implementing a genome surveillance strategy to better understand the transmission dynamics of the COVID-19 pandemic in West Africa.

Clinical Characteristics and Treatment Outcomes of COVID-19 Patients at Eka Kotebe General Hospital, Addis Ababa, Ethiopia

Data from much of Africa are still scarce on the clinical characteristics, outcomes of treatment, and factors associated with disease severity and mortality of COVID-19. A cross-sectional study was conducted at Eka Kotebe General Hospital, Ethiopia's first COVID-19 treatment center. All consecutive symptomatic SARS CoV-2 RT-PCR positive individuals, aged 18 and older, admitted to the hospital between March 13 and September 16, 2020, were included. Of the total 463 cases, 319 (68.9%) were male. The median age was 45 years (interquartile range 32-62). The most common three symptoms were cough (69%), shortness of breath (SOB; 44%), and fatigue (37%). Hypertension was the most prevalent comorbidity, followed by diabetes mellitus. The age groups 40 to 59 and ≥ 60 were more likely to have severe disease compared with those < 40 years of age (adjusted odds ratio [aOR] = 3.45, 95% confidence interval [CI]: 1.88-6.31 and aOR = 3.46, 95% CI: 1.91-6.90, respectively). Other factors associated with disease severity included the presence of any malignancy (aOR = 4.64, 95% CI: 1.32-16.33) and SOB (aOR = 3.83, 95% CI: 2.35-6.25). The age group ≥ 60 was significantly associated with greater in-hospital mortality compared with those < 40 years. In addition, the presence of any malignancy, SOB, and vomiting were associated with higher odds of mortality. In Ethiopia, most COVID-19 patients were male and presented with cough, SOB, and fatigue. Older age, any malignancy, and SOB were associated with disease severity; these factors, in addition to vomiting, also predicted mortality.

Generalizable prediction of COVID-19 mortality on worldwide patient data

Objective

Predicting Coronavirus disease 2019 (COVID-19) mortality for patients is critical for early-stage care and intervention. Existing studies mainly built models on datasets with limited geographical range or size. In this study, we developed COVID-19 mortality prediction models on worldwide, large-scale "sparse" data and on a "dense" subset of the data.

Materials and Methods

We evaluated 6 classifiers, including logistic regression (LR), support vector machine (SVM), random forest (RF), multilayer perceptron (MLP), AdaBoost (AB), and Naive Bayes (NB). We also conducted temporal analysis and calibrated our models using Isotonic Regression.

Results

The results showed that AB outperformed the other classifiers for the sparse dataset, while LR provided the highest-performing results for the dense dataset (with area under the receiver operating characteristic curve, or AUC ≈ 0.7 for the sparse dataset and AUC = 0.963 for the dense one). We also identified impactful features such as symptoms, countries, age, and the date of death/discharge. All our models are well-calibrated (P > .1).

Discussion

Our results highlight the tradeoff of using sparse training data to increase generalizability versus training on denser data, which produces higher discrimination results. We found that covariates such as patient information on symptoms, countries (where the case was reported), age, and the date of discharge from the hospital or death were the most important for mortality prediction.

Conclusion

This study is a stepping-stone towards improving healthcare quality during the COVID-19 era and potentially other pandemics. Our code is publicly available at: https://doi.org/10.5281/zenodo.6336231.

Clinical features and predictors of mortality among hospitalized patients with COVID-19 in Niger

Introduction

COVID-19 has spread across the African continent, including Niger. Yet very little is known about the phenotype of people who tested positive for COVID-19. In this humanitarian crises region, we aimed at characterizing variation in clinical features among hospitalized patients with COVID-19-like syndrome and to determine predictors associated with COVID-19 mortality among those with confirmed COVID-19.

Methods

The study was a retrospective nationwide cohort of hospitalized patients isolated for COVID-19 infection, using the health data of the National Health Information System from 19 March 2020 (onset of the pandemic) to 17 November 2020. All hospitalized patients with COVID-19-like syndrome at admission were included. A Cox-proportional regression model was built to identify predictors of in-hospital death among patients with confirmed COVID-19.

Results

Sixty-five percent (472/729) of patients hospitalized with COVID-19 like syndrome tested positive for SARS-CoV-2 among which, 70 (15%) died. Among the patients with confirmed COVID-19 infection, age was significantly associated with increased odds of reporting cough (adjusted odds ratio [aOR] 1.02; 95% confidence interval [CI] 1.01–1.03) and fever/chills (aOR 1.02; 95% CI 1.02–1.04). Comorbidity was associated with increased odds of presenting with cough (aOR 1.59; 95% CI 1.03–2.45) and shortness of breath (aOR 2.03; 95% CI 1.27–3.26) at admission. In addition, comorbidity (adjusted hazards ratio [aHR] 2.04; 95% CI 2.38–6.35), shortness of breath at baseline (aHR 2.04; 95% CI 2.38–6.35) and being 60 years or older (aHR 5.34; 95% CI 3.25–8.75) increased the risk of COVID-19 mortality two to five folds.

Conclusion

Comorbidity, shortness of breath on admission, and being aged 60 years or older are associated with a higher risk of death among patients hospitalized with COVID-19 in a humanitarian crisis setting. While robust prospective data are needed to guide evidence, our data might aid intensive care resource allocation in Niger.

Factors associated with acceptance of COVID-19 vaccine among University health sciences students in Northwest Nigeria

Students of the health sciences are the future frontliners to fight pandemics. The students' participation in COVID-19 response varies across countries and are mostly for educational purposes. Understanding the determinants of COVID-19 vaccine acceptability is necessary for a successful vaccination program. This study aimed to investigate the factors associated with COVID-19 vaccine acceptance among health sciences students in Northwest Nigeria. The study was an online self-administered cross-sectional study involving a survey among students of health sciences in some selected universities in Northwest Nigeria. The survey collected pertinent data from the students, including socio-demographic characteristics, risk perception for COVID-19, and willingness to accept the COVID-19 vaccine. Multiple logistic regression was used to determine the predictors of COVID-19 vaccine acceptance. A total of 440 responses with a median (interquartile range) age of 23 (4.0) years were included in the study. The prevalence of COVID-19 vaccine acceptance was 40.0%. Factors that independently predict acceptance of the vaccine were age of 25 years and above (adjusted odds ratio, aOR, 2.72; 95% confidence interval, CI, 1.44-5.16; p = 0.002), instructions from heads of institutions (aOR, 11.71; 95% CI, 5.91-23.20; p<0.001), trust in the government (aOR, 20.52; 95% CI, 8.18-51.51; p<0.001) and willingness to pay for the vaccine (aOR, 7.92; 95% CI, 2.63-23.85; p<0.001). The prevalence of COVID-19 vaccine acceptance among students of health sciences was low. Older age, mandate by heads of the institution, trust in the government and readiness to pay for the vaccine were associated with acceptance of the vaccine. Therefore, stakeholders should prioritize strategies that would maximize the vaccination uptake.

Fatores associados ao óbito em casos confirmados de COVID-19 no estado do Rio de Janeiro

BACKGROUND

COVID-19 can occur asymptomatically, as influenza-like illness, or as more severe forms, which characterize severe acute respiratory syndrome (SARS). Its mortality rate is higher in individuals over 80 years of age and in people with comorbidities, so these constitute the risk group for severe forms of the disease. We analyzed the factors associated with death in confirmed cases of COVID-19 in the state of Rio de Janeiro. This cross-sectional study evaluated the association between individual demographic, clinical, and epidemiological variables and the outcome (death) using data from the Unified Health System information systems.

METHODS

We used the extreme boosting gradient (XGBoost) model to analyze the data, which uses decision trees weighted by the estimation difficulty. To evaluate the relevance of each independent variable, we used the SHapley Additive exPlanations (SHAP) metric. From the probabilities generated by the XGBoost model, we transformed the data to the logarithm of odds to estimate the odds ratio for each independent variable.

RESULTS

This study showed that older individuals of black race/skin color with heart disease or diabetes who had dyspnea or fever were more likely to die.

CONCLUSIONS

The early identification of patients who may progress to a more severe form of the disease can help improve the clinical management of patients with COVID-19 and is thus essential to reduce the lethality of the disease.

COVID-19 Awareness, Adoption of COVID-19 Preventive Measures, and Effects of COVID-19 Lockdown Among Adolescent Boys and Young Men in Kampala, Uganda

There is growing evidence of the challenges with adherence to COVID-19 prevention measures and the effect of the prevention measures on the health of populations in various parts of the world but with limited documentation in sub-Saharan Africa. We assessed COVID-19 awareness, adoption of COVID-19 prevention measures, and the effects of COVID-19 lockdown on the mental health status, socio-economic disruptions and engagement in unhealthy behaviours among 2500 in- and out-of-school adolescent boys and young men (ABYM) aged 10–24 years in Kampala, Uganda. 74.8% (n = 1869) were in-school; nearly half (47.3%, n = 1182) were aged 15–19 years. Although > 80% were aware of at least two COVID-19 prevention measures, only 22.2% (n = 555) reported that they always wore a face mask while in a public place; 40.9% (n = 1023) always washed their hands with soap and running water while 17.6% (n = 440) always avoided gatherings of more than five people. COVID-19 lockdown led to: (a) increased mental health challenges (e.g. 1.2% [n = 31] contemplated committing suicide); (b) limited ability to meet basic needs (e.g. 62.0% [n = 1549] found it difficult to afford a diverse/balanced diet); (c) socio-economic disruptions (e.g. 30.3% [n = 756] experienced a reduction in income) and (d) engagement in unhealthy behaviours (e.g. 62% [n = 1554] reported a sedentary life style such as excessive watching of TV). These effects were more pronounced among older adolescent boys (15–19 years) and young men (20–24 years) and out-of-school compared to in-school ABYM. Our findings suggest a need for appropriate health promotion, mental health and socio-economic interventions targeting ABYM in Kampala, Uganda.