This study investigated whether passively collected routine
health facility data can be used for mapping spatial heterogeneities
in malaria transmission at the level of local government housing
cluster administrative units in Dar es Salaam, Tanzania. From June
2012 to January 2013, residential locations of patients tested for
malaria at a public health facility were traced based on their local
leaders’ names and geo-referencing the point locations of these
leaders’ houses. Geographic information systems (GIS) were used
to visualise the spatial distribution of malaria infection rates.
Spatial scan statistics was deployed to detect spatial clustering of
high infection rates. Among 2407 patients tested for malaria,
46.6% (1121) could be traced to their 411 different residential
housing clusters. One small spatially aggregated cluster of neighbourhoods
with high prevalence was identified. While the home
residence housing cluster leader was unambiguously identified for73.8% (240/325) of malaria-positive patients, only 42.3%
(881/2082) of those with negative test results were successfully
traced. It was concluded that recording simple points of reference
during routine health facility visits can be used for mapping malaria
infection burden on very fine geographic scales, potentially
offering a feasible approach to rational geographic targeting of
malaria control interventions. However, in order to tap the full
potential of this approach, it would be necessary to optimise
patient tracing success and eliminate biases by blinding personnel
to test results.