1 47% of the global population has little to no access to diagnostics. 2 Diagnostics are central and fundamental to quality health care. This notion is underrecognised, leading to underfunding and inadequate resources at all levels. 3 The level of primary health care is the diagnostic so-called last mile and particularly affects poor, rural, and marginalised communities globally; appropriate access is essential for equity and social justice. 4 The COVID-19 pandemic has emphasised the crucial role of diagnostics in health care and that without access to diagnostics, delivery of universal health coverage, antimicrobial resistance mitigation, and pandemic preparedness cannot be achieved. 5 Innovations within the past 15 years in many areas (eg, in financing, technology, and workforce) can reduce the diagnostic gap, improve access, and democratise diagnostics to empower patients. 6 As an example of the potential impact, 1•1 million premature deaths in low-income and middle-income countries could be avoided annually by reducing the diagnostic gap for six priority conditions: diabetes, hypertension, HIV, and tuberculosis in the overall population, and hepatitis B virus infection and syphilis for pregnant women. 7 The economic case for such investment is strong. The median benefit-cost exceeds one for five of the six priority conditions in middle-income countries, and exceeds one for four of the six priority conditions in low-income countries, with a range of 1•4:1 to 24:1.Given the depth and breadth of the problems, sustained access to quality, affordable diagnostics will require multi-decade prioritisation, commitment, and investment.Incorporating diagnostics into universal health coverage packages will begin this process.
Background The widespread use of antibiotics plays a major role in the development and spread of antimicrobial resistance. However, important knowledge gaps still exist regarding the extent of their use in low-and middle-income countries (LMICs), particularly at the primary care level. We performed a systematic review and meta-analysis of studies conducted in primary care in LMICs to estimate the prevalence of antibiotic prescriptions as well as the proportion of such prescriptions that are inappropriate. Methods and findings We searched PubMed, Embase, Global Health, and CENTRAL for articles published between 1 January 2010 and 4 April 2019 without language restrictions. We subsequently updated our search on PubMed only to capture publications up to 11 March 2020. Studies conducted in LMICs (defined as per the World Bank criteria) reporting data on medicine use in primary care were included. Three reviewers independently screened citations by title and abstract, whereas the full-text evaluation of all selected records was performed by 2 reviewers, who also conducted data extraction and quality assessment. A modified version of a tool developed by Hoy and colleagues was utilized to evaluate the risk of bias of each included study. Meta-analyses using random-effects models were performed to identify the proportion of patients receiving antibiotics. The WHO Access, Watch, and Reserve (AWaRe) framework was used to classify prescribed antibiotics. We identified 48 studies from 27 LMICs, mostly conducted in the public sector and in urban areas, and predominantly based on medical records abstraction and/or drug prescription audits. The pooled PLOS MEDICINE
Weight loss interventions are delivered through various mediums including, increasingly, mobile phones. This systematic review and meta-analysis assesses whether interventions delivered via mobile phones reduce body weight and which intervention characteristics are associated with efficacy. The study included randomised controlled trials assessing the efficacy of weight loss interventions delivered via mobile phones. A meta-analysis to test intervention efficacy was performed, and subgroup analyses were conducted to determine whether interventions' delivery mode(s), inclusion of personal contact, duration and interaction frequency improve efficacy. Pooled body weight reduction (d = -0.23; 95% confidence interval = -0.38, -0.08) was significant. Interventions delivered via other modes in addition to the mobile phone were associated with weight reduction. Personal contact and more frequent interactions in interventions were also associated with greater weight reduction. In conclusion, the current body of evidence shows that interventions delivered via mobile phones produce a modest reduction in body weight when combined with other delivery modes. Delivering interventions with frequent and personal interactions may in particular benefit weight loss results.
The high burden of CHB in Asian countries is a major challenge for the incorporation of national programs to prevent CHB complications within health care systems.
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