Cancer is now widely recognized as a global problem that unfortunately lacks a global solution. The latest United Nations high-level meeting on noncommunicable diseases (NCDs) exemplified this conundrum.¹ Despite global commitment to reducing the risk of and disability from NCDs, including cancer, implementation of known solutions is inadequate to reach the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases^2,3 (25% reduction in premature mortality from NCDs by 2025) and the third Sustainable Development Goal (by 2030 reduce by one-third premature mortality from NCDs through prevention and treatment, and promote mental health and well-being).⁴ To reduce cancer burden, identifying the scope of the problem and mapping out implementation of solutions is best done in National Cancer Control Plans (NCCPs). However, a recent review showed that only 29% of low-income countries had a NCCP, and even if NCCPs existed, cost, financing, monitoring, and expansion of information systems was often inadequate. Many highly effective prevention and treatment strategies exist for cancer. However, they are often very specific (eg, vaccination for human papillomavirus and hepatitis B virus for prevention of cervical and liver cancer, or tyrosine kinase inhibitors for cancers with targetable mutations). Effective NCCPs therefore require detailed knowledge about the local burden of cancer and associated risk factors. We herein present results from the Global Burden of Disease (GBD) 2017 study describing cancer incidence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 195 countries from 1990 through 2017, which can inform cancer control through policy, resource allocation, and health system planning.

Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89-4·12) annually, although it grew slower in per capita terms (2·72% [2·61-2·84]) and increased by less than $1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55% [5·18-5·95]), mainly due to growth in government health spending, and in lower-middle-income countries (3·71% [3·10-4·34]), mainly from DAH. Health spending globally reached $8·0 trillion (7·8-8·1) in 2016 (comprising 8·6% [8·4-8·7] of the global economy and $10·3 trillion [10·1-10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$5252 (5184-5319) in high-income countries, $491 (461-524) in upper-middle-income countries, $81 (74-89) in lower-middle-income countries, and $40 (38-43) in low-income countries. In 2016, 0·4% (0·3-0·4) of health spending globally was in low-income countries, despite these countries comprising 10·0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ($9·5 billion, 24·3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ($644·7 million in 2018). Globally, health spending is projected to increase to $15·0 trillion (14·0-16·0) by 2050 (reaching 9·4% [7·6-11·3] of the global economy and $21·3 trillion [19·8-23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1·84% (1·68-2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0·6% (0·6-0·7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130·2 (122·9-136·9) in 2016 and is projected to remain at similar levels in 2050 (125·9 [113·7-138·1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets. Bill & Melinda Gates Foundation.

Objective: To assess the sex difference in the prevalence of COVID-19 confirmed cases. Design: Systematic review and meta-analysis. Setting: PubMed, Cochrane Library and Google Scholar were searched for related information. The authors developed a data extraction form on an Excel sheet and the following data from eligible studies were extracted: author, country, sample size, number of female patients and number of male patients. Using STATA V.14 for analysis, the authors pooled the overall prevalence of men and/or women using a random-effect meta-analysis model. The authors examined the heterogeneity in effect size using Q statistics and I ² statistics. Subgroup and sensitivity analyses were performed. Publication bias was also checked. Participants: Studies on COVID-19 confirmed cases were included. Intervention: Sex (male/female) of COVID-19 confirmed cases was considered. Primary and secondary outcome measures: The primary outcome was prevalence of COVID-19 among men and women. Results: A total of 57 studies with 221 195 participants were used in the analysis. The pooled prevalence of COVID-19 among men was found to be 55.00 (51.43–56.58, I ² =99.5%, p<0.001). Sensitivity analysis showed the findings were not dependent on a single study. Moreover, a funnel plot showed symmetrical distribution. Egger’s regression test p value was not significant, which indicates absence of publication bias in both outcomes. Conclusions: The prevalence of symptomatic COVID-19 was found to be higher in men than in women. The high prevalence of smoking and alcohol consumption contributed to the high prevalence of COVID-19 among men. Additional studies on the discrepancies in severity and mortality rate due to COVID-19 among men and women and the associated factors are recommended.

Background: Pneumonia is defined as an acute inflammation of the Lungs’ parenchymal structure. It is a major public health problem and the leading cause of morbidity and mortality in under-five children especially in developing countries. In 2015, it was estimated that about 102 million cases of pneumonia occurred in under-five children, of which 0.7 million were end up with death. Different primary studies in Eastern Africa showed the burden of pneumonia. However, inconsistency among those studies was seen and no review has been conducted to report the amalgamated magnitude and associated factors. Therefore, this review aimed to estimate the national prevalence and associated factors of pneumonia in Eastern Africa Methods: Using PRISMA guideline, we systematically reviewed and meta-analyzed studies that examined the prevalence and associated factors of pneumonia from PubMed, Cochrane library, and Google Scholar. Heterogeneity across the studies was evaluated using the Q and the I² test. A weighted inverse variance random-effects model was applied to estimate the national prevalence and the effect size of associated factors. The subgroup analysis was conducted by country, study design, and year of publication. A funnel plot and Egger’s regression test were used to see publication bias. Sensitivity analysis was also done to identify the impact of studies. Result: A total of 34 studies with 87, 984 participants were used for analysis. The pooled prevalence of pneumonia in East Africa was 34% (95% CI; 23.80–44.21). Use of wood as fuel source (AOR = 1.53; 95% CI:1.30–1.77; I² = 0.0%;P = 0.465), cook food in living room (AOR = 1.47;95% CI:1.16–1.79; I² = 0.0%;P = 0.58), caring of a child on mother during cooking (AOR = 3.26; 95% CI:1.80–4.72; I² = 22.5%;P = 0.26), Being unvaccinated (AOR = 2.41; 95% CI:2.00–2.81; I² = 51.4%;P = 0.055), Child history of Acute Respiratory Tract Infection (ARTI) (AOR = 2.62; 95% CI:1.68–3.56; I² = 11.7%;P = 0.337) were identified factors of pneumonia. Conclusion: The prevalence of pneumonia in Eastern Africa remains high. This review will help policy-makers and program officers to design pneumonia preventive interventions.

Background: Neonatal hypothermia is a global health problem and a major factor for neonatal morbidity and mortality, especially in low and middle-income countries. Therefore, this systematic review and meta-analysis aimed to assess the prevalence of neonatal hypothermia and its associated factors in Eastern Africa. Methods: We used the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines to search electronic databases (PubMed, Cochrane Library and Google Scholar; date of last search: 15 October 2019) for studies reporting the prevalence and associated factors of neonatal hypothermia. The data was extracted in the excel sheet considering prevalence, and categories of associated factors reported. A weighted inverse variance random-effects model was used to estimate the magnitude and the effect size of factors associated with hypothermia. The subgroup analysis was done by country, year of publication, and study design. Results: A total of 12 potential studies with 20,911 participants were used for the analysis. The pooled prevalence of neonatal hypothermia in East Africa was found to be 57.2% (95%CI; 39.5–75.0). Delay in initiation of breastfeeding (adjusted Odds Ratio(aOR) = 2.83; 95% CI: 1.40–4.26), having neonatal health problem (aOR = 2.68; 95% CI: 1.21–4.15), being low birth weight (aOR =2.16; 95%CI: 1.03–3.29), being preterm(aOR = 4.01; 95%CI: 3.02–5.00), and nighttime delivery (aOR = 4.01; 95% CI:3.02–5.00) were identified associated factors which significantly raises the risk of neonatal hypothermia. Conclusions: The prevalence of neonatal hypothermia in Eastern Africa remains high. Delay in initiation of breastfeeding, having a neonatal health problem, being low birth weight, preterm, and nighttime delivery were identified associated factors that significantly raises the risk of neonatal hypothermia.

Background: Overweight and obesity are emerging public health problems in Ethiopia. However, primary study findings on the prevalence of overweight and obesity in Ethiopia are inconsistent. Therefore, this study aimed to estimate the pooled prevalence of overweight and obesity among adults in Ethiopia.Methods: Studies that looked at overweight and obesity among adults were searched from four international databases. The search involved articles published from 1 January 2010 to 10 March 2020. The Cochran’s Q χ² and the I² test statistics were used to check heterogeneity among the studies. The funnel plot and Egger’s regression tests were also used to assess the presence of publication bias. Subgroup analysis was performed by residence, study setting, sample size and year of study. Sensitivity analysis was also done to assess the effect of a single study on the pooled estimates. Data analysis was done using STATA V.14 software program.Results: A total of 16 studies with 19 527 study participants were included in this systematic review and meta-analysis. The estimated pooled prevalence of overweight among adults in Ethiopia was 20.4%, and after adjustment for publication bias with the trim-and-fill analysis, the estimated prevalence rate was changed to 19%. Besides, the estimated pooled prevalence of obesity was 5.4%. The prevalence of overweight was higher, 22.6% in studies published since 2015, 22.4% in studies conducted only in urban settings and 24.4% in studies with small sample size (≤384 participants). Similarly, the prevalence of obesity was 6.9% in studies published since 2015, 6.2% in studies conducted only in urban settings, 6.4% in institution-based settings and 9.6% in studies with small sample size.Conclusion: The prevalence of overweight and obesity is high in Ethiopia compared with previous studies. This needs large scale awareness creation campaigns and situation-based and context-specific prevention strategies.