Deconstructing the differences: a comparison of GBD 2010 and CHERG's approach to estimating the mortality burden of diarrhea, pneumonia, and their etiologies.

BACKGROUND: Pneumonia and diarrhea are leading causes of death for children under five (U5). It is challenging to estimate the total number of deaths and cause-specific mortality fractions. Two major efforts, one led by the Institute for Health Metrics and Evaluation (IHME) and the other led by the World Health Organization (WHO)/Child Health Epidemiology Reference Group (CHERG) created estimates for the burden of disease due to these two syndromes, yet their estimates differed greatly for 2010. METHODS: This paper discusses three main drivers of the differences: data sources, data processing, and covariates used for modelling. The paper discusses differences in the model assumptions for etiology-specific estimates and presents recommendations for improving future models. RESULTS: IHME's Global Burden of Disease (GBD) 2010 study estimated 6.8 million U5 deaths compared to 7.6 million U5 deaths from CHERG. The proportional differences between the pneumonia and diarrhea burden estimates from the two groups are much larger; GBD 2010 estimated 0.847 million and CHERG estimated 1.396 million due to pneumonia. Compared to CHERG, GBD 2010 used broader inclusion criteria for verbal autopsy and vital registration data. GBD 2010 and CHERG used different data processing procedures and therefore attributed the causes of neonatal death differently. The major difference in pneumonia etiologies modeling approach was the inclusion of observational study data; GBD 2010 included observational studies. CHERG relied on vaccine efficacy studies. DISCUSSION: Greater transparency in modeling methods and more timely access to data sources are needed. In October 2013, the Bill & Melinda Gates Foundation (BMGF) hosted an expert meeting to examine possible approaches for better estimation. The group recommended examining the impact of data by systematically excluding sources in their models. GBD 2.0 will use a counterfactual approach for estimating mortality from pathogens due to specific etiologies to overcome bias of the methods used in GBD 2010 going forward.

Technologies for detecting falsified and substandard drugs in low and middle-income countries.

Falsified and substandard drugs are a global health problem, particularly in low- and middle-income countries (LMIC) that have weak pharmacovigilance and drug regulatory systems. Poor quality medicines have important health consequences, including the potential for treatment failure, development of antimicrobial resistance, and serious adverse drug reactions, increasing healthcare costs and undermining the public's confidence in healthcare systems. This article presents a review of the methods employed for the analysis of pharmaceutical formulations. Technologies for detecting substandard and falsified drugs were identified primarily through literature reviews. Key-informant interviews with experts augmented our methods when warranted. In order to aid comparisons, technologies were assigned a suitability score for use in LMIC ranging from 0-8. Scores measured the need for electricity, need for sample preparation, need for reagents, portability, level of training required, and speed of analysis. Technologies with higher scores were deemed the most feasible in LMICs. We categorized technologies that cost $10,000 USD or less as low cost, $10,000-100,000 USD as medium cost and those greater than $100,000 USD as high cost technologies (all prices are 2013 USD). This search strategy yielded information on 42 unique technologies. Five technologies were deemed both low cost and had feasibility scores between 6-8, and an additional four technologies had medium cost and high feasibility. Twelve technologies were deemed portable and therefore could be used in the field. Many technologies can aid in the detection of substandard and falsified drugs that vary from the simplest of checklists for packaging to the most complex mass spectrometry analyses. Although there is no single technology that can serve all the requirements of detecting falsified and substandard drugs, there is an opportunity to bifurcate the technologies into specific niches to address specific sections within the workflow process of detecting products.

Host-directed therapeutics for tuberculosis: can we harness the host?

Treatment of tuberculosis (TB) remains challenging, with lengthy treatment durations and complex drug regimens that are toxic and difficult to administer. Similar to the vast majority of antibiotics, drugs for Mycobacterium tuberculosis are directed against microbial targets. Although more effective drugs that target the bacterium may lead to faster cure of patients, it is possible that a biological limit will be reached that can be overcome only by adopting a fundamentally new treatment approach. TB regimens might be improved by including agents that target host pathways. Recent work on host-pathogen interactions, host immunity, and host-directed interventions suggests that supplementing anti-TB therapy with host modulators may lead to shorter treatment times, a reduction in lung damage caused by the disease, and a lower risk of relapse or reinfection. We undertook this review to identify molecular pathways of the host that may be amenable to modulation by small molecules for the treatment of TB. Although several approaches to augmenting standard TB treatment have been proposed, only a few have been explored in detail or advanced to preclinical and clinical studies. Our review focuses on molecular targets and inhibitory small molecules that function within the macrophage or other myeloid cells, on host inflammatory pathways, or at the level of TB-induced lung pathology.

Rare HLA drive additional HIV evolution compared to more frequent alleles.

HIV-1 can evolve HLA-specific escape variants in response to HLA-mediated cellular immunity. HLA alleles that are common in the host population may increase the frequency of such escape variants at the population level. When loss of viral fitness is caused by immune escape variation, these variants may revert upon infection of a new host who does not have the corresponding HLA allele. Furthermore, additional escape variants may appear in response to the nonconcordant HLA alleles. Because individuals with rare HLA alleles are less likely to be infected by a partner with concordant HLA alleles, viral populations infecting hosts with rare HLA alleles may undergo a greater amount of evolution than those infecting hosts with common alleles due to the loss of preexisting escape variants followed by new immune escape. This hypothesis was evaluated using maximum likelihood phylogenetic trees of each gene from 272 full-length HIV-1 sequences. Recent viral evolution, as measured by the external branch length, was found to be inversely associated with HLA frequency in nef (p < 0.02), env (p < 0.03), and pol (p < or = 0.05), suggesting that rare HLA alleles provide a disproportionate force driving viral evolution compared to common alleles, likely due to the loss of preexisting escape variants during early stages postinfection.