Background: Obstetric violence is an emerging health problem in the utilization of maternal health services. In the study context, there was limited evidence on obstetric violence. Hence, the aim of this study was to assess obstetric violence and its associated factors among HIV-positive women who received birth care at public health facilities, in Addis Ababa, Ethiopia. Results: A total of 318 HIV-positive women participated in this study, yielding a 100% response rate. In this study, 79% of the HIV-positive women reported that they had been subjected to at least one form of obstetric violence during birth care. The top three reported forms of obstetric violence were as follows: 249 (78.3%) failed to provide informed consent, 227 (71.4%) did not complete medical procedures and 140 (44%) did not suffer life-threatening complications. The multivariable logistic regression analysis revealed that female birth status (AOR= 2.85; 95% CI 1.57, 5.15), fewer than three ANC visits (AOR= 2.99; 95% CI 1.39, 6.45), age >35 years old (AOR= 2.47; 95% CI 1.25, 4.90) and primary school attendance (AOR= 2.13; 95% CI 1.08, 4.17) were significantly associated with obstetric violence. This study revealed a high prevalence of obstetric violence among HIV -positive women. Hence, mitigation needs to be undertaken by taking the reported forms of obstetrics obstetric violence, and socio-demographic and obstetric variables by ensuring a systematic and strategic intervention for quality birth care utilization through the involvement of families, communities, the government and stakeholders.

There is growing evidence that the Flynn Effect, the secular rise in IQ scores that was observed across the twentieth century, has reached a plateau and has even gone into reverse in many Western countries. However, several recent studies report an ongoing Flynn Effect in developing countries, especially in those in the Arab world. Here we compare two samples from 2012 (<I>N</I> = 350) and 2021 (<I>N</I> = 1,491) of children in the Kingdom of Jordan. The children were 4, 5 and 6 years old and were randomly selected from kindergartens in the north, central and south of Jordan. They were administered the Wechsler Preschool and Primary Scale of Intelligence (WPPSI), a test which is designed for this age group. Factor analyses exhibited very similar factors loadings across samples and subtests, indicating high construct validity. Comparing effect sizes for the difference between the samples in both total and subtest scores, we find no evidence of any change in intelligence between the two samples. We explore the possible reasons for this apparent cessation of the Flynn Effect in Jordan among which may be the impact of the Covid-19 pandemic on the 2021 sample. We conclude that there is little reason to think that this would have interfered with how representative the sample was.

<i>Background</i>: This study aimed to identify the primary risk variables influencing the recurrence of cervical cancer in patients, at Tikur Anbessa Specialized Hospital. Cervical cancer deaths in Ethiopia reached 4,595, or 0.76% of total deaths. The age-adjusted death rate is 18.51 per 100,000 of the population in Ethiopia. <i>Method</i>: Among patients with cervical cancer, an institution-based retrospective follow-up research was conducted from January 2015 to March 2017 at TASH and is under follow-up. Out of a population of cervical cancer patients who were taking treatment in the hospital during that period, data on 420 patients is included in this study. Non-parametric methods, such as log-rank tests and the Kaplan-Meier method, were used to compare the rate of recurrence among the different explanatory variable categories. <i>Results</i>: After the medical cards of women were reviewed among those patients with cervical cancer, 170 (40.5%) were recurrent, and the remaining 250 (59.5%) were censored. Out of the total patients, 6.2% were at stage I, 32.6% were at stage II, 51.7% were at stage III, and 9.5% were at stage IV. The recurrence proportions of stage I, stage II, stage III, and stage IV patients were 5.88%, 27.05%, 52.35%, and 14.705%, respectively. <i>Conclusion</i>: Finally, the findings of this study implied that age, smoking cigarettes, stage of disease, initial treatment patients took, types of treatment patients took, and place were major factors related to the recurrence time of cervical cancer patients.

A passivity SEIR epidemic model with inconsistent incidence rate embedded with latency period for the imparting dynamics of epidemics is succeed and thoroughly inspected. The problem is constructed by a system of nonlinear ordinary differential equations analyzing the evaluation of susceptible, exposed, infected and removed individuals. The suggested model is established in terms of existence, positivity and boundedness of solutions. Four equilibrium points have been discussed, namely, the disease free equilibrium, endemic equilibrium with respect to strain 1, endemic equilibrium with respect to strain 2 and the terminal endemic equilibrium with respect to both strains. By constructing the suitable stability analysis function the global stability of the disease free equilibrium is proved depending on the basic reproduction number. Furthermore by using other well-known functionals the global stability results of the endemic equilibria are established depending on the strain 1 reproduction number and strain 2 reproduction number. Necessary numerical simulations are performed in order to confirm the theoretical results. Numerical comparison between the model results and clinical data was conducted. The findings of this research includes the model consistence of discordant compartments which are globally asymptotically stable aseptic equilibrium in state have an epidemiological threshold value (also known as basic reproduction rate) less than unity.

In repeated measures data, the observations tend to be correlated within each subject, and such data are often analyzed using Generalized Estimating Equations (GEE), which are robust to assumptions that many methods hold. The main limitation of GEE is that its method of estimation is quasi-likelihood. The recent framework of the copula is very popular for handling repeated data. The maximum likelihood-based analysis for repeated data can be obtained using Gaussian copula regression. The purpose of this study is to show the handling and analysis of the repeated data using the Gaussian copula regression approach and compare the findings with GEE. The prospective, double-blinded, randomized controlled trial data for this study was obtained from the Department of Anesthesia, Christian Medical College, and Vellore. ASA I and II patients were randomized into three groups. Hemodynamic parameters were obtained for 88 patients at thirteen-time points. The outcome of interest was mean arterial pressure. Both GEE and Gaussian copula regression were compared assuming four different correlation structures. The optimal correlation structures were selected with the Akaike Information Criterion (AIC) and Correlation Information Criterion (CIC) goodness of fit criteria according to the method of estimation of Gaussian copula regression and GEE, respectively. The correlation structures, unstructured and autoregressive, were found to be optimal for Gaussian copula regression and GEE based on AIC and CIC criteria values respectively. A comparison between the estimated values of the selected models showed no major differences. Gaussian copula regression found that intrathecal morphine has a significant reduction in MAP over time, this significance is considered important as the study uses randomized controlled trial data. Both methods have almost similar results, but Gaussian copula regression provides better results by identifying significant findings associated with the outcome using maximum likelihood estimation that GEE fails to identify using quasi-likelihood estimation.

By September 2021 the outbreak of the COVID-19 caused 228.19 million confirmed cases and 4.7 million deaths globally. Mortality measures are frequently used to estimate the severity of a pandemic. Among them is the Case Fatality Rate (CFR). Some mathematical models were developed to estimate the impact of specific factors on the disease’s mortality. These models were developed before the COVID-19 vaccines were administrated, and therefore did not consider the vaccines influence on COVID-19 fatality. Moreover, some other factors associated with COVID-19 mortality such as diabetes and cardiovascular mortality were not included in these models. This study offers a mathematical model with some potential predictors of COVID-19 CFR during the fourth pandemic wave caused by the Delta variant. To evaluate these predictors, demographic and clinical information for 10 highly populated developed countries was retrieved from a real-time available website. Demographic data included population density, percent of population above age 65, GDP per capita, and percent of smoking. Clinical data included diabetes prevalence, cardiovascular death rate, percent of fully vaccinated population, and CFR. Single linear regressions were conducted to assess the association of each potential predictor with CFR. A backward multiple linear regression was conducted to identify the most parsimonious combination of the independent variables of this study predicting CFR. The model developed in this study suggests that percent of population above age 65, and cardiovascular death rate have a positive effect on CFR, i.e., they are associated with increased COVID-19 fatality rate during the fourth wave. In addition, GDP per capita has a negative effect on CFR, i.e. – higher GDP per capita is associated with lower fatality rate during COVID-19 fourth wave. Moreover, single linear regressions show a strong negative association between percent of fully vaccinated people in each country and CFR. This model sheds light on several potential demographic and clinical factors which may predict CFR in highly populated developed countries during the emergence of the Delta variant. Vaccination in accordance with the recommendations is recommended to reduce COVID-19 mortality.

According to EDHS 2016, Low birth weight in Amhara Region was 22.2%. Studies show that low birth weight (LBW) babies are significantly at risk of death, contributing to the high neonatal and infant morbidity and mortality. The poor health outcome of low birth weight can be reduced through quality and comprehensive neonatal care. This study aimed to determine the prevalence and determinants of low birth weight among women who gave birth at health facilities in Bahir Dar city. An institution-based cross-sectional study using an incidence density sampling technique was conducted from February 01/2019 to March 30/2019 in public and private health facilities of the Bahir Dar city. The sample size was calculated using the single population proportion formula. A pre-tested questionnaire was used for data collection and data was entered into the EPI-data and transported to SPSS version 22 for analysis. The totals of 292 respondents were involved in the study. Pregnant women who did not get married [AOR=8.75, 95%CI: 3.00, 25.55], women who had a previous history of LBW [AOR=7. 81, 95%CI: 1.71, 35.69], women with less than four ANC visits [AOR=2.75, 95%: 1.14, 6.63], women whose MUAC were less than 23cm [AOR=12. 12, 95%CI (4.46, 33.02)], anemic women [AOR=9. 15, 95%CI: 2.31, 36.30] and women whose blood hemoglobin level was less than 11gm/dl [AOR=6.10, 95%CI: 2.18, 17.01] were statistically associated with low birth weight. Hence, interventions targeting on marital status, LBW histories, antenatal care visit, and maternal MUAC, anemia and hemoglobin level were recommended to reduce the prevalence of low birth weight.

Longer intervals between consecutive births decrease the number of children a woman can have. This results in beneficial effects on population size and on the health status of mothers and children. The general objective of this study was to model the birth intervals of adult women age 15-49 years old in Ethiopia and to identify the variable that affects the length of birth intervals of women. The study utilizes the data extracted from the 2011 Ethiopian Demographic and Health Survey (EDHS). In this study cox proportional hazards and shared gamma frailty models were adopted for the analysis to identify important demographic and socioeconomic factors that may affect the length of birth intervals and to analyze correlated birth intervals respectively. The result of the two models revealed that mother’s age, place of residence, mother education level, wealth index, mother age at first birth, childbirth order, survival status of the previous child, breast feeding status, and contraceptive use were found to have significant effect on the length of birth interval for Ethiopian women. The analysis with the frailty model shows that child birth order may not be an important covariate for analyzing birth intervals, especially when mother’s age at first birth is already in the model. Moreover, shared gamma frailty model have resulted in a minimum AIC as compared to cox proportional hazard model without frailty term in the model, suggesting that shared gamma frailty model is the most powerful one in predicting the birth intervals of women among regional states of Ethiopia. Hence, the setting of correlated observations, the cox frailty models are recommended for providing statistically valid estimates of the effects of proximate determinants after adjusting for the background variables and unobserved random effects.

A Study on the prevalence of <i>Plasmodium falciparum</i> infection among pregnant women visiting community hospitals in Aguata LGA of Anambra State, Nigeria was carried out between October, 2014 and March 2015. Six hundred and five (605) pregnant women from 5 communities, who attended antenatal clinic during the research period, were involved in the study. Venous blood samples were collected and <i>Plasmodium</i> infection determined using microscopy of Giemsa stained thick and thin blood films. Of the 605 pregnant women sampled, 263 (43.5%) were infected. The prevalence by community was highest (67.4%) in Uga and least (29.9%) in Achina (P<0.05). Prevalence by age was highest (46.9%) in the age group (21–25) years and least (39.5%) in the age group (31-35) years (P>0.05). Highest prevalence (43.7%) was recorded among women that attained secondary school while women that attained tertiary education recorded the least (42.5%) prevalence (P>0.05). Farmers had the highest (81.8%) prevalence and the least (40.5%) was among traders (P<0.05). The highest prevalence (52.0%) was recorded among those in their second trimester and lowest (33.7%) among those in their third trimester (P<0.05). Women who started ANC in their third trimester had highest prevalence (56.5%) whereas those that started ANC in second trimester had least (37.6%) prevalence (P<0.05). With the high prevalence of <i>Plasmodium</i> infection in the study area, there is need for continual community enlightenment programs to reduce the burden of <i>Plasmodium</i> infection especially during pregnancy.

<i>Introductions</i>: Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. According to updated global burden of cholera estimate 2019 in Ethiopia 68,805,272 populations are at risk of cholera with incidence rate of 4 per 1000 population and case fatality of 3.8% estimated annual number of cases 275,221. <i>Methods</i>: The main objective of this study is to identify the significant risk factors of dehydration status of cholera outbreak in Oromia regional state of Ethiopia. Ordinal logistic regression was used to model the data by incorporating the assumption behind this novel model. <i>Results</i>: The results of the study indicated that of the total 965 cholera patients, most of them 560 (58%) were severely dehydrated by cholera. The overall goodness of model (p-valu=0.07) shows that the model fits the data well. Besides, the proportional odds assumption also revealed that the slop coefficients in the model are the same across dehydration status (p-value=0.094). For those have history of travel, the odds of severely dehydrated versus the combined some dehydrated and no dehydrated was exp (1.133804)=3.11 times higher than those have no history of travel (p-value<0.01). All the other factors like history of contact with other patients, other sick patients in the family, Intravenous and Antibiotics drugs are statistically significant with 5% level of significance to determine the status of dehydration. <i>Conclusions</i>: The ordinal logistic regression was fitted the data well and most of the included factors were significant for the dehydration status of cholera outbreak.