RESUMO
Health facility data are a critical source of local and continuous health statistics. Countries have introduced web-based information systems that facilitate data management, analysis, use and visualisation of health facility data. Working with teams of Ministry of Health and country public health institutions analysts from 14 countries in Eastern and Southern Africa, we explored data quality using national-level and subnational-level (mostly district) data for the period 2013-2017. The focus was on endline analysis where reported health facility and other data are compiled, assessed and adjusted for data quality, primarily to inform planning and assessments of progress and performance. The analyses showed that although completeness of reporting was generally high, there were persistent data quality issues that were common across the 14 countries, especially at the subnational level. These included the presence of extreme outliers, lack of consistency of the reported data over time and between indicators (such as vaccination and antenatal care), and challenges related to projected target populations, which are used as denominators in the computation of coverage statistics. Continuous efforts to improve recording and reporting of events by health facilities, systematic examination and reporting of data quality issues, feedback and communication mechanisms between programme managers, care providers and data officers, and transparent corrections and adjustments will be critical to improve the quality of health statistics generated from health facility data.
RESUMO
BACKGROUND: One in eight sub-Saharan Africans now lives in a city with a population greater than 750,000. Decision makers require additional evidence regarding the burden of malaria in these large cities. This paper presents results from analysis of existing data from nationwide household surveys measuring malaria parasitaemia by microscopy among children six to 59 months of age in 15 countries of sub-Saharan Africa. METHODS: Geo-coordinates for each survey cluster were used to determine the distance from the cluster to the centre of each of 16 large cities with populations greater than 750,000. Geo-coordinates of each site within 25 km of the centre were entered into Google Earth to obtain a satellite image of the location and determine whether it was within the boundaries of the metropolis. In the case of two countries for which survey geo-coordinates were not available, clusters located in an additional four large cities were identified based upon their designated district. Data from all sites within city boundaries were pooled together and compared to data from all rural sites within 150 km of the city centre or in the same zone of malaria endemicity. RESULTS: Of the 20 large cities, only in Ouagadougou were more than 10% of children found to have a malaria infection. The prevalence was less than 5% for 16 of these cities. Apart from Antananarivo where both the large city and the comparison rural communities were parasite-free, the prevalence in each of the large cities was 0 to 40% of that found among children living in rural communities within 150 km of these cities or within the same zone of malaria endemicity. In 14 of the 20 large cities, all of the children living in 75% or more of the clusters were malaria parasite-free. CONCLUSIONS: Existing data from malaria indicator surveys can be used to document the substantially lower prevalence of malaria in specific large cities. These findings will help policy makers, public health programmers and clinical workers in each country to develop and promote malaria control strategies that are suited to large cities as well as to those living in smaller communities.
