Chapter Three - Measuring Changes in Plasmodium falciparum Transmission: Precision, Accuracy and Costs of Metrics
Introduction
Changes in malaria transmission must be measured accurately and precisely in order to evaluate the impact and cost-effectiveness of new and existing interventions. As malaria transmission declines across much of sub-Saharan Africa, there has been renewed focus on the need to codify a set of metrics, expectations about likely changes in those metrics across the spectrum of transmission in response to control, defined end points for measuring changes in the intensity of transmission and the associated reductions in malaria burden (Cohen et al., 2010, Corran et al., 2007, Hay et al., 2008, Smith and Hay, 2009, Steketee et al., 2010), with a concurrent increase in funding directed towards improving capacity for monitoring and evaluation (Cibulskis et al., 2007, Nahlen and Low-Beer, 2007).
Malaria transmission, defined herein as the process by which a malaria parasite completes its life cycle, involves parasites being passed from a female anopheline mosquito through the skin, during a blood meal, and via the liver into human blood, and later from the blood back into the mosquito during a subsequent mosquito blood meal, leading to parasite development within a mosquito. The intensity of transmission, described by Macdonald (Macdonald, 1957, Smith et al., 2012), is a general concept describing the potential frequency of transmission, but it may also be defined as the number of times each day that a parasite infection is initiated in a human or the number of times a pathogen infection is initiated in a mosquito. Transmission intensity varies enormously within malaria-endemic areas and is determined not only by the vectorial capacity of local mosquito populations but also by other factors, including human immunity and the interventions in place (Smith et al., 2010). Transmission is intrinsically ‘noisy’ due to fluctuations in underlying mosquito populations, temperature-induced changes in mosquito interactions with the parasite, immunologic changes affecting human–parasite interactions and the spatial heterogeneity over which these occur. There is also variation in the efficiency of transmission, the number of uniquely identifiable infections caused by each infectious bite, which is affected by heterogeneous biting, multiple infections and acquired immunity (Smith et al., 2010). Spatiotemporal variability in the quantities of interest raises questions about the precision and accuracy of these metrics that must be understood to interpret these parameters properly and to measure changes over time.
Malaria control interventions slow transmission at specific points during the complex parasite life cycle, and likewise, there are several points during this cycle at which the intensity of transmission may be measured, using various metrics pertaining to the three players: mosquitoes, parasites and humans (Carter and Mendis, 2006, Hay et al., 2008). Each metric represents a quantity that is an important step in the transmission process, as illustrated in Fig. 3.1.
Metrics of malaria transmission change on different temporal scales, reflecting the dynamics of mosquito populations, parasite infections in humans, the kinetics of changing human immunity and human demographics. The metrics are causally interrelated (Fig. 3.1), but based on both a priori arguments and a posteriori examinations of patterns, some of these relationships are nonlinear when considered across the spectrum of transmission intensity (Smith et al., 2010). These nonlinearities, together with variability in transmission and measurement errors, weaken the associations between those metrics separated by a greater number of steps in the transmission cycle. The most substantiated and relevant effects on transmission are found by examining the metric that is most directly affected by an intervention, for example, the biological efficacy of a transmission-blocking vaccine is best assessed directly by measuring κ (Fig. 3.1). However, when it is not possible to measure an effect directly, the study should follow the chain of causation and examine the nearest attainable downstream metric. Generally, the end points of greatest interest are the direct outcomes of human infections: infection per se, clinical malaria, hospitalisation and death. However, the relationships between these clinical metrics and transmission are complex and are among the most difficult to measure (Ghani et al., 2009, Trape and Rogier, 1996).
The future need to approve new interventions and to evaluate existing strategies aimed at reducing transmission highlights the specific requirement for robust methods to measure a change in transmission (invariably a decrease) and the need to account for nonlinear patterns and expectations between metrics when interpreting data from intervention studies. To help guide the appropriate design of future trials seeking to evaluate transmission-reducing interventions, we first critically evaluate the precision, accuracy and costs of the metrics that have been developed to measure the transmission of falciparum malaria. To our knowledge, this is the first comprehensive review of these attributes. Second, we review the nonlinear scaling relationships between five major metrics of malaria transmission: the entomological inoculation rate (EIR), force of infection (FOI), sporozoite rate (SR), parasite rate in humans (PR) and the basic reproductive number, R0.
Section snippets
Accuracy, Precision and Costs of Malaria Metrics
The suitability of malaria transmission metrics as end points for measuring changes in transmission is determined by costs, precision, accuracy, the need for and availability of experts, the intrinsic variability of the metric across space and time and overall familiarity with the metric because of common use. In this chapter, we review 11 metrics of transmission: (1) net infectiousness of humans, (2) PR in humans, (3) EIR, (4) FOI and molecular force of infection (mFOI), (5) multiplicity of
Scaling Relationships Between Malaria Metrics
The metrics of transmission are all causally interrelated: infectious mosquitoes transmit parasites to humans causing new infections, and infectious humans transmit the parasite back to parasites that eventually appear as sporozoites in the mosquito. The potential rate at which these events occur increases with vectorial capacity or R0. The ease of measuring these metrics varies from place to place, depending in part on the value of these parameters.
In order to understand which metrics are
Discussion
The goal of measuring malaria transmission and changes in its intensity has many challenges. To critically compare the most commonly used methods for measuring malaria transmission, this chapter evaluates the (a) methods of collection (b) accuracy, (c) precision and (d) costs of collection of 11 major metrics of transmission. The chapter highlights some of the most important questions about the accuracy and precision of each metric of transmission and discusses differences in the utility of
Acknowledgements
The authors acknowledge the financial support of the PATH Malaria Vaccine Initiative. L. S. T. acknowledges funding from the Leverhulme Centre for Integrative Research on Agriculture and Health. The work of T. B. is supported by the European FP7 project REDMAL (#242079). D. L. S. acknowledges funding from NIH/NIAID (U19AI089674), the Bloomberg Family Foundation, and Research and Policy for Infectious Disease Dynamics programme of the Science and Technology Directorate, Department of Homeland
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