Determine the factors affecting the time to recovery of children with bacterial meningitis at Jigjiga university referral hospital in the Somali Regional State of Ethiopia: using the parametric shared frailty and AFT models.

BACKGROUND: Neisseria meningitides, Streptococcus pneumonia, and hemophilic influenza type B are frequently linked to bacterial meningitis (BM) in children. It's an infectious sickness that kills and severely mobilizes children. For a variety of reasons, bacterial meningitis remains a global public health concern; most cases and deaths are found in Sub-Saharan Africa, particularly in Ethiopia. Even though vaccination has made BM more preventable, children worldwide are still severely harmed by this serious illness. Age, sex, and co-morbidity are among the risk variables for BM that have been found. Therefore, the main objective of this study was to identify the variables influencing the time to recovery for children with bacterial meningitis at Jigjiga University referral hospital in the Somali regional state of Ethiopia. METHOD: A retrospective cohort of 535 children with bacterial meningitis who received antibiotic treatment was the subject of this study. Parametric Shared Frailty ty and the AFT model were employed with log likelihood, BIC, and AIC methods of model selection. The frailty models all employed the patients' kebele as a clustering factor. RESULTS: The number of cases of BM declined in young children during the duration of the 2 year, 11 month study period, but not in the elderly. Streptococcus pneumonia (50%), hemophilic influenza (30.5%), and Neisseria meningitides (15%) were the most frequent causes of BM. The time to recovery of patients from bacteria was significantly influenced by the covariates male patients (ϕ = 0.927; 95% CI (0.866, 0.984); p-value = 0.014), patients without a vaccination history (ϕ = 0.898; 95% CI (0.834, 0.965); P value = 0.0037), and patients who were not breastfeeding (ϕ = 0.616; 95% CI (0.404, 0.039); P-value = 0.024). The recovery times for male, non-breastfed children with bacterial patients are 7.9 and 48.4% shorter, respectively. In contrast to children with comorbidity, the recovery time for children without comorbidity increased by 8.7%. CONCLUSION: Age group, sex, vaccination status, co-morbidity, breastfeeding, and medication regimen were the main determinant factors for the time to recovery of patients with bacterial meningitis. Patients with co-morbidities require the doctor at Jigjiga University Referral Hospital to pay close attention to them.

An Analysis of Various Factors Underlying Covid-19 Prevention Practice and Strategy in Jigjiga Town, Northeast Ethiopia.

Background: COVID-19, a severe respiratory illness, is caused by the SARS-CoV-2 virus. The pandemic has devastated public health, economies, and social structures worldwide. In Ethiopia, the government and health authorities have implemented various COVID-19 prevention strategies to contain the spread of the virus. This study aims to investigates the factors influencing the implementation and effectiveness of COVID-19 prevention strategies in Jigjiga Town, Ethiopia. Methods: A community-based cross-sectional study was conducted from April 2022 to December 2022, involving 593 participants in Jigjiga town. Multi-stage sampling techniques were used, and data was collected using a structured questionnaire covering demographic characteristics, socioeconomic status, attitude, knowledge, prevention practices, misconceptions, and COVID-19 prevention strategies. A multivariate model was developed to control for confounding, using variables suitable for multivariate logistic regression analysis with p-values less than 0.25. A variable is considered significant in multivariable logistic regression analysis if its p-value is less than 0.05. Results: The study found that only 12.2% of participants used COVID-19 prevention strategies. Those with a bachelor's degree or higher had a strong association with prevention strategies (AOR: 20.08, 95% CI: 2.13-188.85). Participants informed about COVID-19 prevention were 6.886 times more likely to use strategies (95% CI: 2.975-15.938). People who received the COVID-19 vaccine were 1.14 times more likely to engage in reasonable preventive measures compared to those who did not get vaccinated. Conclusion: The study reveals low COVID-19 prevention practices among participants, with only 12.2% utilizing preventive strategies. The covariate, the kinds of information received on COVID-19 prevention mechanisms, participants with a favorable attitude toward COVID-19, educational level, mask-wearing, social distancing, vaccination, hand hygiene, public health communication, and household income were significantly associated with COVID-19 prevention strategies. The COVID-19 vaccination promotes preventive practices, reduces infection risk, protects against severe illness, and decreases community spread.

Application of parametric survival analysis to women patients with breast cancer at Jimma University Medical Center.

Public health systems in both industrialized and undeveloped countries continue to struggle with the worldwide problem of breast cancer. In sub-Saharan African countries, notably Ethiopia, it is the form of cancer that strikes women the most commonly. Despite the extreme difficulties, the causes of mortality in Ethiopia have not yet been identified. In addition, little study has been done in this area. Therefore, the major objective of this analysis was to pinpoint the factors that were most responsible for the decreased life expectancy of breast cancer patients at the University of Jimma Medical Center. 552 women who had been treated for breast cancer at Jimma University Medical Center between October 2018 and December 2022 were included in this study, which used a retrospective cohort study design and five-year follow-up data. The most frequent and widely used test for comparing the probability of survival curves between several categorical independent variables was the log-rank test. Next, semi-parametric methods for multivariable analysis using the Cox proportional hazards model were used. Furthermore, a parametric strategy that includes fully parametric survival models better achieves the goal of the analysis. Among covariate, age of patient (ϕ = 254.06; 95% CI (3.95, 7.13), P-value = 0.000), patient live in urban (ϕ = 0.84; 95% CI (-0.35,-0.00), P-value = 0.047), preexisting comorbidity (ϕ = 2.46; 95% CI (0.39, 1.41), P-value = 0.001), overweight women cancer patient (ϕ = 0.05; 95% CI(-4.41,-1.57), P-value = 0.000, positive Axillary Node status cancer patient (ϕ = 0.04; 95% CI(-4.45,-1.88), P-value = 0.000), both surgery and chemotropic baseline treatment patient (ϕ = 0.53; 95% CI(-1.12,-0.16), P-value = 0.009) significantly affected the survival of women breast cancer. Age of breast cancer patient, patient education level, place of residence, marital status, pre-existing comorbidity, axillary node status, estrogen receptor, tumor size, body mass index at diagnosis, stage of cancer, and baseline treatment were found to have a significant effect on time to survive for women with breast cancer at the University of Jimma Medical Center, Oromia region, Ethiopia. However, the covariate histologic grade, number of positive lymph nodes involved, and type of hormone used were insignificant to the survival of breast cancer patients.