Monitoring and evaluation of malaria vector control programmes

Public health surveillance involves ongoing systematic collection, analysis and interpretation of outcome-specific data for use in the planning, implementing, monitoring and evaluating public health practice (Brownson et al. 1999, Teutsch and Thacker 1995, Thacker et al. 2010). Disease surveillance often brings together health information and management functions within health programmes. A surveillance system encompasses data collection, processing, reporting, and use by relevant stakeholders that ultimately affects daily program practice, and implementation as well as policy (German et al. 2001, Teutsch and Thacker 1995). Such a system is often important for improving our understanding of health service delivery strengths and weaknesses, which in turn helps to optimize program effectiveness and efficiency through improved operations. The success of any surveillance system, in its broader sense, depends on a number of basic features including simplicity, flexibility, data quality, acceptability, sensitivity, positive and negative predictive value, representativeness, timeliness and stability (Thacker et al. 2010). Simple and effective health information systems are envisaged as being key to enabling disease control efforts, through appropriate allocation of resources and also by enabling inclusive decision- making and human resource management that deliver inputs where and when needed (Thacker et al. 2010). A smoothly functioning health information system that optimizes the delivery of effective interventions should be geared to address the prevailing disease burden levels and

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existing health information gaps (Breman et al. 2004, Castro et al. 2004, Guerra et al. 2008). Disease surveillance strategies are highly dependent on the type and level of disease within specified populations at risk (Thacker et al. 2010, Thurmond 2003).

Increased investments in malaria control efforts over recent years have triggered resurgence in the demand for better management of health information for resource allocation as more countries achieve substantive levels of control and several even enter the pre-elimination phase (Alonso et al. 2011c, Brabin et al. 2008, Feachem et al. 2010, Greenwood 2008b, Snow et al. 2008). The rather ambitious goals for malaria control and subsequent elimination require that significant additional resources are mobilized. Apparently for many of the countries most severely afflicted by malaria, baseline data and reliable monitoring of key impact indicators are scarce or absent. There is therefore an urgent need for developing cost-effective monitoring and evaluation systems for malaria control generally (de Savigny and Binka 2004) and vector control in particular (Fillinger et al. 2008).

Recent advances in malaria control have led to increasing reports of declining malaria mortality and morbidity and the associated malaria vector densities (Bhattarai et al. 2007, D'Acremont et al. 2010, Feachem et al. 2010, Fegan et al. 2007, O'Meara et al. 2010). As a result it is becoming increasingly difficult to measure some disease or infection indicators using the conventional tools such as cross-sectional parasite surveys which were developed for use in high transmission settings. This necessitates improved surveillance systems for malaria generally, and vector control in particular, that focus on detecting infections and characterizing transmission dynamics (Breman et al. 2001, Breman et al. 2004, de Savigny and Binka 2004, Lee et al. 2010).

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Surveillance systems are typically differentiated into two overlapping streams of activity namely monitoring and evaluation (M&E). Monitoring encompases routine tracking of the key indicators of program performance (inputs to outputs) to inform day-to-day management and optimization. In contrast, evaluation is the periodic assessment of the impact achieved by an intervention program. In other words, evaluation strives to link impact or a particular output or outcome directly to an intervention within specified period of time. While disease monitoring helps public health managers determine which areas or systems require more input, and identify process changes which might contribute to an improved response, evaluation assists them to determine the effective epidemiological impact of a specific intervention. In a well-designed surveillance system, monitoring indicators contribute greatly towards evaluation. Health systems in general and more specifically, data systems and management functions can become significant epidemiologic and infection risk determinants, because when they are effective, they promote rational decision making and resource allocation (Alilio et al. 2004, Starfield et al. 2005). Successes in a particular health information structure directly translate into improved result- based management, service delivery and epidemiological impact. The success of such disease surveillance systems depend on the adequate and timely flow of information (Buehler et al. 2004, German et al. 2001).

As malaria burden drops in response to LLIN and IRS scale up, surveillance becomes increasingly important, but also correspondingly more difficult, in order to identify persistent foci of infection for targeting additional control tools. Furthermore, these new tools, by definition, require additional monitoring indicators to enable effective delivery management. Larval control also requires quite specific ecological understanding of the major vector species

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and their distinctive interaction with the local environment on very fine spatial scales (Killeen et al. 2002b, Killeen et al. 2006c, Mukabana et al. 2006). Management burden is also exacerbated by the need for technical understanding of the principles and practice of labour-intensive larvicide application or environmental management under challenging field conditions (Killeen et al. 2002b, Killeen et al. 2006c, Mukabana et al. 2006, Townson et al. 2005). Sustainable systems for monitoring the abundance and distribution of aquatic mosquito stages are required to enable timely decisions and actions by managers responsible for such programmes. This represents a particular challenge in Africa where the most important vectors from the Anopheles gambiae can develop from egg to adult in less than a week, in habitats which can be transient and difficult to detect (Dongus et al. 2007, Fillinger et al. 2008, Gillies and DeMeillon 1968, Mutuku et al. 2009, Soper and Wilson 1943, Vanek et al. 2006). Larvicide application requires unusually intensive monitoring because success and failure occurs on remarkably fine spatial (< 1km2) and temporal scales (1 week) that match to the retreatment cycles and geographic division of responsibility to individual staff.

1.5 Opportunities for developing community-based larval source management systems in