Developing an expanded vector control toolbox for malaria elimination.

Vector control using long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) accounts for most of the malaria burden reductions achieved recently in low and middle-income countries (LMICs). LLINs and IRS are highly effective, but are insufficient to eliminate malaria transmission in many settings because of operational constraints, growing resistance to available insecticides and mosquitoes that behaviourally avoid contact with these interventions. However, a number of substantive opportunities now exist for rapidly developing and implementing more diverse, effective and sustainable malaria vector control strategies for LMICs.

The central role of national programme management for the achievement of malaria elimination: a cross case-study analysis of nine malaria programmes.

Background: A malaria eradication goal has been proposed, at the same time as a new global strategy and implementation framework. Countries are considering the strategies and tools that will enable progress towards malaria goals. The eliminating malaria case-study series reports were reviewed to identify successful programme management components using a cross-case study analytic approach.

Strategies and approaches to vector control in nine malaria-eliminating countries: a cross-case study analysis.

Background: There has been progress towards malaria elimination in the last decade. In response, WHO launched the Global Technical Strategy (GTS), in which vector surveillance and control play important roles. Country experiences in the Eliminating Malaria Case Study Series were reviewed to identify success factors on the road to elimination using a cross-case study analytic approach.

The independent effect of living in malaria hotspots on future malaria infection: an observational study from Misungwi, Tanzania.

Background: As malaria transmission declines, continued improvements of prevention and control interventions will increasingly rely on accurate knowledge of risk factors and an ability to define high-risk areas and populations at risk for focal targeting of interventions. This paper explores the independent association between living in a hotspot and prospective risk of malaria infection.

Methods: Malaria infection status defined by nPCR and AMA-1 status in year 1 were used to define geographic hotspots using two geospatial statistical methods (SaTScan and Kernel density smoothing).

Fine-scale malaria risk mapping from routine aggregated case data.

Background: Mapping malaria risk is an integral component of efficient resource allocation. Routine health facility data are convenient to collect, but without information on the locations at which transmission occurred, their utility for predicting variation in risk at a sub-catchment level is presently unclear.

Methods: Using routinely collected health facility level case data in Swaziland between 2011-2013, and fine scale environmental and ecological variables, this study explores the use of a hierarchical Bayesian modelling framework for downscaling risk maps from health facility catchment level to a fine scale (1 km x 1 km).

Hot spot or not: a comparison of spatial statistical methods to predict prospective malaria infections.

Background: Within affected communities, Plasmodium falciparum infections may be skewed in distribution such that single or small clusters of households consistently harbour a disproportionate number of infected individuals throughout the year. Identifying these hotspots of malaria transmission would permit targeting of interventions and a more rapid reduction in malaria burden across the whole community. This study set out to compare different statistical methods of hotspot detection (SaTScan, kernel smoothing, weighted local prevalence) using different indicators (PCR positivity, AMA-1 and MSP-1 antibodies) for prediction of infection the following year.

A reiterative method for calculating the early bactericidal activity of antituberculosis drugs.

Studies of early bactericidal activity (EBA) are important in the rapid evaluation of new antituberculosis drugs. Historically, these have concentrated on the log fall in the viable count in sputum during the first 48 hours of therapy. In this paper, we provide a mathematical model that suggests that the viable count in sputum follows an exponential decay curve with the equation V = S + Me(-kt) (where V is the viable count, M the population of bacteria susceptible to the test drug, S the population susceptible only to sterilizing agents, t the day of sputum collection as related to start of therapy, k the rate constant for the bacteria killed each day, and e the Napierian constant).