Abstract
BackgroundAccurate and timely malaria data are crucial to monitor the progress towards and attainment of elimination. Lusaka, the capital city of Zambia, has reported very low malaria prevalence in Malaria Indicator Surveys. Issues of low malaria testing rates, high numbers of unconfirmed malaria cases and over consumption of anti-malarials were common at clinics within Lusaka, however. The Government of Zambia (GRZ) and its partners sought to address these issues through an enhanced surveillance and feedback programme at clinic level.MethodsThe enhanced malaria surveillance programme began in 2011 to verify trends in reported malaria, as well as to implement a data feedback loop to improve data uptake, use, and quality. A process of monthly data collection and provision of feedback was implemented within all GRZ health clinics in Lusaka District. During clinic visits, clinic registers were accessed to record the number of reported malaria cases, malaria test positivity rate, malaria testing rate, and proportion of total suspected malaria that was confirmed with a diagnostic test.Results and discussionFollowing the enhanced surveillance programme, the odds of receiving a diagnostic test for a suspected malaria case increased (OR = 1.54, 95 % CI = 0.96–2.49) followed by an upward monthly trend (OR = 1.05, 95 % CI = 1.01–1.09). The odds of a reported malaria case being diagnostically confirmed also increased monthly (1.09, 95 % CI 1.04–1.15). After an initial 140 % increase (95 % CI = 91–183 %), costs fell by 11 % each month (95 % CI = 5.7–10.9 %). Although the mean testing rate increased from 18.9 to 64.4 % over the time period, the proportion of reported malaria unconfirmed by diagnostic remained high at 76 %.ConclusionsEnhanced surveillance and implementation of a data feedback loop have substantially increased malaria testing rates and decreased the number of unconfirmed malaria cases and courses of ACT consumed in Lusaka District within just two years. Continued support of enhanced surveillance in Lusaka as well as national scale-up of the system is recommended to reinforce good case management and to ensure timely, reliable data are available to guide targeting of limited malaria prevention and control resources in Zambia.
Highlights
Accurate and timely malaria data are crucial to monitor the progress towards and attainment of elimination
Enhanced surveillance and implementation of a data feedback loop have substantially increased malaria testing rates and decreased the number of unconfirmed malaria cases and courses of artemisinin combination therapy (ACT) consumed in Lusaka District within just two years
This paper examines trends in malaria indicators before and after the enhanced surveillance programme, and assesses the benefits these investments had on reducing the levels of reported malaria in the district
Summary
Accurate and timely malaria data are crucial to monitor the progress towards and attainment of elimination. Issues of low malaria testing rates, high numbers of unconfirmed malaria cases and over consumption of anti-malarials were common at clinics within Lusaka, . Despite the need for improved information, routine malaria surveillance throughout sub-Saharan Africa is known to have many challenges including underrepresentation of the true burden of malaria circulating in communities [1,2,3], as well as lacking quality and timely data reporting. As malaria control programmes pursue malaria elimination, timely, reliable data becomes crucial to respond to potential resurgence and to target foci of malaria transmission with appropriate interventions [4, 5]. National malaria control programme data are often from population-based surveys conducted at intervals of two years or more, rather than relying upon surveillance data from continuously operating health information systems [8, 9]. Scaling up and integrating the reporting of diagnostic confirmations of malaria cases has the potential to significantly reduce malaria reporting and unnecessary anti-malarial treatment administration, especially in areas with variable malaria transmission patterns [10]
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