This study provides an innovative model to harness national

This study provides an innovative model to harness national household survey data to quantify the effects of the various malaria control interventions. The model accounts for the spatial dependence in parasitaemia as a consequence of the heterogeneous distribution of malaria transmission and its drivers and also allows for the estimation of varying subnational effects of the interventions. Giardina and colleagues argue that these variations are likely to be as a result of levels of ITN/IRS coverage and the intensity of transmission where, for a unit change in intervention coverage, a greater effect is seen in moderate transmission areas than in those of high transmission. This suggestion is supported by both the theoretical and empirical literature. However, there are other factors that have not been included in this Droxinostat study that could have influenced the estimated effect of the vector control interventions on changing levels of malaria infection. Many of these are acknowledged by Giardina and colleagues and include the timing of ITN scale-up campaigns and that of surveys where a short window might not be enough to observe effect on infection rates; the age and condition of nets, which affects their effectiveness; the changing vector distribution and bionomics as a consequence of exposure to various vector control interventions; and insecticide resistance. Finally, Giardina and colleagues rightly emphasise the potential policy use of the results of their study. However, careful interpretation of these results is required. For example, where ITNs are not associated with reductions in parasitaemia, should countries stop issuing them? If the intrinsic transmission is extremely low such that, epidemiologically, ITNs have minimal impact, this might be a sensible course of action. However, where transmission is currently extremely low due to the scale-up of vector control interventions over the past few years, beginning even before the study period, or remains moderate or high, the scale up of ITNs must continue. For these decisions, a careful comparison of transmission intensity currently and in the preintervention period (circa 2000) is required.
WHO\'s Global Action Plan for tackling non-communicable diseases (NCDs) aims for 80% availability and affordability of essential medicines for NCDs in both public and private facilities, but in low-income and middle-income countries these medicines remain both poorly available (particularly in the public sector) and inordinately expensive. Access to medicines plays a vital part in achieving universal health-care coverage and many of the barriers to expanding universal health-care coverage relate to how medicines are purchased and used.
In response to the current outbreak, the international community has endorsed the clinical use of unregistered treatments for Ebola. Even with this accelerated pathway to in-human testing and use, radically novel approaches to drug development will be needed to improve the likelihood that a treatment is realised. Bypassing steps in development does not alter the probability of success, and historical patterns in drug development suggest that there is a slim probability of success with the current portfolio of potential Ebola treatments (all of which are were in preclinical development prior to the outbreak). First, preclinical research in drug development can suffer from a lack of replicability, which contributes to high development failure rates. Second, if preclinical development is successful, the likelihood of successful regulatory approval of all investigational drugs reaching phase 1 is only 10·4%. Third, these patterns and low rates are based on therapeutic areas with: (a) robust preclinical and clinical data collected (often) over decades from hundreds to thousands of research and development activities spanning the globe, and (b) socially and politically acceptable clinical development programmes spanning large populations, mainly in resource-wealthy settings with strong clinical trial infrastructure. Ebola stands in stark contrast to such therapeutic areas; thus, one could expect that the likelihood of successful regulatory approval for an Ebola treatment would be lower than these estimates.