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Across Sub-Saharan Africa, an estimated 430 million people are at risk of cholera. Cholera will continue to challenge health systems in affected regions until access to safely managed water, sanitation and hygiene (WASH) services is expanded. Populations in many African countries experience concurrent humanitarian crises including natural disasters, civil conflict or war, malnutrition and food insecurity and economic crises or chronic poverty that further exacerbates the risk of both transmission and case-fatality of cholera. Efforts to control cholera across Sub-Saharan Africa have almost exclusively been reactive. Although essential, the variation in intervention strategies between epidemics and reliance on operational memory to implement emergency responses is not sufficient to guarantee success of a control programme. Controlling cholera comes with several disease-specific challenges due to its diverse transmission dynamics, the lack of specific symptoms and the insufficiency of any single intervention to sustainably control cholera. Case-area targeted interventions (CATI) are gaining traction on the premise that fast, localised response could significantly reduce transmission and control epidemics. Generation of evidence supporting the choice of interventions to include in CATI responses, and on interventions that could be systematically used by organisations for cholera preparedness and control in hotspots, is required. By integrating quantitative and qualitative methods for evaluating public health interventions, this thesis provides evidence on the effectiveness and implementation of a case-targeted WASH response to cholera in the Democratic Republic of Congo, working alongside Médecins Sans Frontières, UNICEF and the Ministry of Health, and reviews both normative guidelines for and previous experience of implementing cholera response programmes. After estimating the effect of a hygiene kit and health promotion distributed to cholera-case households, this thesis demonstrates how measuring and valuing the populations' response to and the challenges among implementation bring new insights to the effectiveness and delivery of emergency, case-targeted cholera responses.

Background: The assessment of prevalence of acute malnutrition in under-five children is widely used for the detection of nutritional emergencies, planning interventions, advocacy, and programme monitoring and evaluation. Current nutritional surveillance systems have important limitations. The aim of this thesis was to develop a new method for nutritional surveillance to assess acute malnutrition prevalence using PROBIT Methods based on Middle-Upper Arm Circumference (MUAC). Specific objectives were to: i) compare the appropriateness of MUAC versus other anthropometric measurements or indices to assess change in a population’s nutritional status; ii) Examine assumptions behind the proposed PROBIT Methods; and iii) Assess outcomes of the proposed PROBIT Methods using estimation and classification approaches. Methods: The first objective was achieved through a literature review. For the second objective, assumptions were tested on a database of 852 nutritional surveys including 668,975 children aged 6-59 months old. For the third objective, the Methods were assessed using data from 681,600 simulated surveys of eight different sizes. Results: MUAC was identified as the most appropriate anthropometric measure to detect short-term changes in the nutritional status of a population; and the main assumptions behind the proposed Methods were verified. The PROBIT methods had better precision in the estimation of acute malnutrition than the Classic Method for all sample sizes tested and a better coverage for smaller sample sizes, while having relatively little bias. The classification approach performed well with a threshold of 5% acute malnutrition. Conclusion: PROBIT Methods have a clear advantage in the assessment of acute malnutrition prevalence compared to the Classic Method. Their use would require much lower sample sizes and would enable great time- and resource-savings. There is great potential in their use in surveillance systems in order to produce timely and/or locally relevant prevalence estimates of acute malnutrition and to enable a swift and well-targeted response.