Background: Major psychiatric disorders are growing public health concern that attributed 14% of the global burden of diseases. The management of major psychiatric disorders is challenging mainly due to medication non-adherence. However, there is a paucity of summarized evidence on the prevalence of psychotropic medication non-adherence and associated factors. Therefore, we aimed to summarize existing primary studies’ finding to determine the pooled prevalence and factors associated with psychotropic medication non-adherence. Methods: A total of 4504 studies written in English until December 31, 2017, were searched from the main databases (n = 3125) (PubMed (MEDLINE), Embase, CINAHL, PsycINFO, and Web of Science) and other relevant sources (mainly from Google Scholar, n = 1379). Study selection, screening, and data extraction were carried out independently by two authors. Observational studies that had been conducted among adult patients (18 years and older) with major psychiatric disorders were eligible for the selection process. Critical appraisal of the included studies was carried out using the Newcastle Ottawa Scale. Systematic synthesis of the studies was carried out to summarize factors associated with psychotropic medication non-adherence. Meta-analysis was carried using Stata 14. Random effects model was used to compute the pooled prevalence, and sub-group analysis at 95% confidence interval. Results: Forty-six studies were included in the systematic review. Of these, 35 studies (schizophrenia (n = 9), depressive (n = 16), and bipolar (n = 10) disorders) were included in the meta-analysis. Overall, 49% of major psychiatric disorder patients were non-adherent to their psychotropic medication. Of these, psychotropic medication non-adherence for schizophrenia, major depressive disorders, and bipolar disorders were 56%, 50%, and 44%, respectively. Individual patient’s behaviors, lack of social support, clinical or treatment and illness-related, and health system factors influenced psychotropic medication non-adherence. Conclusion: Psychotropic medication non-adherence was high. It was influenced by various factors operating at different levels. Therefore, comprehensive intervention strategies should be designed to address factors associated with psychotropic medication non-adherence. Systematic review registration: PROSPERO CRD42017067436

Assessment of delays in seeking care and diagnosis of tuberculosis is essential to evaluate effectiveness of tuberculosis control programs, and identify programmatic impediments. Thus, this review of studies aimed to examine the extent of patient, health system, and total delays in diagnosis of pulmonary tuberculosis in low- and middle- income countries. It was done following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Electronic databases were searched to retrieve studies published from 2007 to 2015 including Pubmed central, Springer link, Hinari and Google scholar. Searching terms were pulmonary tuberculosis, health care seeking, health care seeking behavior, patient delay, diagnostic delay, health system delay, provider delay, and doctor delay. Retrieved studies were systematically reviewed and summarized using Comprehensive Meta-analysis software. Forty studies involving 18,975 patients qualified for systematic review, and 14 of them qualified for meta-analysis. The median diagnostic delay ranged from 30 to 366.5 days [IQR = 44–77.8], with a 4–199 days [IQR = 15–50] and 2–128.5 days [IQR = 12–34] due to patient and health system delays, respectively. The meta-analysis showed 42% of pulmonary tuberculosis patients delayed seeking care by a month or more; uneducated patients [pooled OR = 1.5, 95%CI = 1.1–1.9] and those who sought initial care from informal providers [pooled OR = 3, 95%CI = 2.3–3.9] had higher odds of patient delay. Delay in diagnosis is still a major challenge of tuberculosis control and prevention programs in low- and middle- income settings. Efforts to develop new strategies for better case-finding using the existing systems and improving patients’ care seeking behavior need to be intensified.

Sub-Saharan Africa and south Asia contributed 81% of 5·9 million under-5 deaths and 77% of 2·6 million stillbirths worldwide in 2015. Vital registration and verbal autopsy data are mainstays for the estimation of leading causes of death, but both are non-specific and focus on a single underlying cause. We aimed to provide granular data on the contributory causes of death in stillborn fetuses and in deceased neonates and children younger than 5 years, to inform child mortality prevention efforts. The Child Health and Mortality Prevention Surveillance (CHAMPS) Network was established at sites in seven countries (Baliakandi, Bangladesh; Harar and Kersa, Ethiopia; Siaya and Kisumu, Kenya; Bamako, Mali; Manhiça, Mozambique; Bombali, Sierra Leone; and Soweto, South Africa) to collect standardised, population-based, longitudinal data on under-5 mortality and stillbirths in sub-Saharan Africa and south Asia, to improve the accuracy of determining causes of death. Here, we analysed data obtained in the first 2 years after the implementation of CHAMPS at the first five operational sites, during which surveillance and post-mortem diagnostics, including minimally invasive tissue sampling (MITS), were used. Data were abstracted from all available clinical records of deceased children, and relevant maternal health records were also extracted for stillbirths and neonatal deaths, to incorporate reported pregnancy or delivery complications. Expert panels followed standardised procedures to characterise causal chains leading to death, including underlying, intermediate (comorbid or antecedent causes), and immediate causes of death for stillbirths, neonatal deaths, and child (age 1-59 months) deaths. Between Dec 10, 2016, and Dec 31, 2018, MITS procedures were implemented at five sites in Mozambique, South Africa, Kenya, Mali, and Bangladesh. We screened 2385 death notifications for inclusion eligibility, following which 1295 families were approached for consent; consent was provided for MITS by 963 (74%) of 1295 eligible cases approached. At least one cause of death was identified in 912 (98%) of 933 cases (180 stillbirths, 449 neonatal deaths, and 304 child deaths); two or more conditions were identified in the causal chain for 585 (63%) of 933 cases. The most common underlying causes of stillbirth were perinatal asphyxia or hypoxia (130 [72%] of 180 stillbirths) and congenital infection or sepsis (27 [15%]). The most common underlying causes of neonatal death were preterm birth complications (187 [42%] of 449 neonatal deaths), perinatal asphyxia or hypoxia (98 [22%]), and neonatal sepsis (50 [11%]). The most common underlying causes of child deaths were congenital birth defects (39 [13%] of 304 deaths), lower respiratory infection (37 [12%]), and HIV (35 [12%]). In 503 (54%) of 933 cases, at least one contributory pathogen was identified. Cytomegalovirus, Escherichia coli, group B Streptococcus, and other infections contributed to 30 (17%) of 180 stillbirths. Among neonatal deaths with underlying prematurity, 60% were precipitated by other infectious causes. Of the 275 child deaths with infectious causes, the most common contributory pathogens were Klebsiella pneumoniae (86 [31%]), Streptococcus pneumoniae (54 [20%]), HIV (40 [15%]), and cytomegalovirus (34 [12%]), and multiple infections were common. Lower respiratory tract infection contributed to 174 (57%) of 304 child deaths. Cause of death determination using MITS enabled detailed characterisation of contributing conditions. Global estimates of child mortality aetiologies, which are currently based on a single syndromic cause for each death, will be strengthened by findings from CHAMPS. This approach adds specificity and provides a more complete overview of the chain of events leading to death, highlighting multiple potential interventions to prevent under-5 mortality and stillbirths. Bill & Melinda Gates Foundation.

Low Birth Weight (LBW) is one of the major risk factor for death in early life. However, little is known about predictors of LBW in sub-Saharan Africa. Therefore, the aim of this study was to measure the incidence and determinants of LBW in a rural population of Ethiopia. An observational cohort study on pregnant women was conducted from December 2009 to November 2010. During the study period 1295 live birth were registered and the weights of 956 children were measured within 24 hours after birth. Socio-demographic, economic, maternal and organizational factors were considered as a predicators of LBW, defined as birth weight below 2500g. Logistic regression was used to analyze the data, odds ratio (OR) and confidence intervals (CI) are reported. The incidence of LBW was 28.3%. It is significantly associated with poverty [OR 2.1; 95% CI: 1.42, 3.05], maternal Mid Upper Arm Circumference (MUAC) less than 23 cm [OR 1.6; 95% CI: 1.19, 2.19], not attending ANC [OR 1.6; 95% CI: 1.12, 2.28], mother’s experience of physical violence during pregnancy [OR 1.7; 95% CI: 1.12, 2.48], and longer time to walk to health facility [OR 1.6; 95% CI: 1.11, 2.40]. The incidence of LBW was high in Kersa. Babies born to women who were poor, undernourished, experienced physical violence during pregnancy and who had poor access to health services were more likely to be LBW in this part of the country. In this largely poor community where ANC coverage is low, to reduce the incidence of LBW, it is essential to improve access for maternal health care. The involvement of husbands and the community at large to seek collective action on LBW is essential.

Despite reductions over the past 2 decades, childhood mortality remains high in low- and middle-income countries in sub-Saharan Africa and South Asia. In these settings, children often die at home, without contact with the health system, and are neither accounted for, nor attributed with a cause of death. In addition, when cause of death determinations occur, they often use nonspecific methods. Consequently, findings from models currently utilized to build national and global estimates of causes of death are associated with substantial uncertainty. Higher-quality data would enable stakeholders to effectively target interventions for the leading causes of childhood mortality, a critical component to achieving the Sustainable Development Goals by eliminating preventable perinatal and childhood deaths. The Child Health and Mortality Prevention Surveillance (CHAMPS) Network tracks the causes of under-5 mortality and stillbirths at sites in sub-Saharan Africa and South Asia through comprehensive mortality surveillance, utilizing minimally invasive tissue sampling (MITS), postmortem laboratory and pathology testing, verbal autopsy, and clinical and demographic data. CHAMPS sites have established facility- and community-based mortality notification systems, which aim to report potentially eligible deaths, defined as under-5 deaths and stillbirths within a defined catchment area, within 24–36 hours so that MITS can be conducted quickly after death. Where MITS has been conducted, a final cause of death is determined by an expert review panel. Data on cause of death will be provided to local, national, and global stakeholders to inform strategies to reduce perinatal and childhood mortality in sub-Saharan Africa and South Asia.

Background: Klebsiella pneumoniae is a gram-negative rod belonging to the order Enterobacterales and having a wide distribution in the environment, including the human colon. Recently, the bacterium is one of the known problems in the healthcare setting as it has become resistant to last-resort drugs like carbapenems. The colonized person can serve as a reservoir for his/herself and others, especially in the healthcare setting leading to nosocomial and opportunistic infections. Therefore, we aimed to quantitatively estimate the rate of prevalence and incidence of colonization with carbapenem-resistant K. pneumoniae. Methods: A literature search was conducted on PubMed/MEDLINE, Google Scholar, Science Direct, Cochrane Library, WHO Index Medicus, and university databases. The study includes all published and unpublished papers that addressed the prevalence or incidence of K. pneumoniae colonization. Data were extracted onto format in Microsoft Excel and pooled estimates with a 95% confidence interval calculated using Der-Simonian-Laird random-effects model. With the use of I² statistics and prediction intervals, the level of heterogeneity was displayed. Egger’s tests and funnel plots of standard error were used to demonstrate the publication bias. Results: A total of 35 studies were included in the review and 32 records with 37,661 patients for assessment of prevalence, while ten studies with 3643 patients for incidence of colonization. The prevalence of carbapenem-resistant K. pneumoniae colonization varies by location and ranges from 0.13 to 22%, with a pooled prevalence of 5.43%. (3.73–7.42). Whereas the incidence of colonization ranges from 2 to 73% with a pooled incidence of 22.3% (CI 12.74–31.87), both prevalence and incidence reports are majorly from developed countries. There was a variation in the distribution of carbapenem resistance genes among colonizing isolates with KPC as a prominent gene reported from many studies and NDM being reported mainly by studies from Asian countries. A univariate meta-regression analysis indicated continent, patient type, study design, and admission ward do not affect the heterogeneity (p value>0.05). Conclusion: The review revealed that colonization with K. pneumoniae is higher in a healthcare setting with variable distribution in different localities, and resistance genes for carbapenem drugs also have unstable distribution in different geographic areas.