Determining health-care facility catchment areas in Uganda using data on malaria-related visits.
OBJECTIVE
To illustrate the use of a new method for defining the catchment areas of health-care facilities based on their utilization.


METHODS
The catchment areas of six health-care facilities in Uganda were determined using the cumulative case ratio: the ratio of the observed to expected utilization of a facility for a particular condition by patients from small administrative areas. The cumulative case ratio for malaria-related visits to these facilities was determined using data from the Uganda Malaria Surveillance Project. Catchment areas were also derived using various straight line and road network distances from the facility. Subsequently, the 1-year cumulative malaria case rate was calculated for each catchment area, as determined using the three methods.


RESULTS
The 1-year cumulative malaria case rate varied considerably with the method used to define the catchment areas. With the cumulative case ratio approach, the catchment area could include noncontiguous areas. With the distance approaches, the denominator increased substantially with distance, whereas the numerator increased only slightly. The largest cumulative case rate per 1000 population was for the Kamwezi facility: 234.9 (95% confidence interval, CI: 226.2-243.8) for a straight-line distance of 5 km, 193.1 (95% CI: 186.8-199.6) for the cumulative case ratio approach and 156.1 (95% CI: 150.9-161.4) for a road network distance of 5 km.


CONCLUSIONS
Use of the cumulative case ratio for malaria-related visits to determine health-care facility catchment areas was feasible. Moreover, this approach took into account patients' actual addresses, whereas using distance from the facility did not.
Surveillance Lab, Clinical and Health Informatics Research Group, McGill University, 1040 Pine Avenue West, Montreal, Quebec, Canada H3A 1A3.
Kate
K
Zinszer
Surveillance Lab, Clinical and Health Informatics Research Group, McGill University, 1040 Pine Avenue West, Montreal, Quebec, Canada H3A 1A3.
Katia
K
Charland
Uganda Malaria Surveillance Project, Kampala, Uganda .
Ruth
R
Kigozi
Department of Infectious Diseases, University of California, San Francisco, United States of America .
Grant
G
Dorsey
Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda .
Moses R
MR
Kamya
Surveillance Lab, Clinical and Health Informatics Research Group, McGill University, 1040 Pine Avenue West, Montreal, Quebec, Canada H3A 1A3.
David L
DL
Buckeridge
D002391:Catchment Area, Health / Q000706:statistics & numerical data; D003153:Community Health Services / Q000706:statistics & numerical data; D006801:Humans; D008288:Malaria / Q000453:epidemiology*; D062486:Public Health Surveillance / Q000379:methods*; D012111:Residence Characteristics; D018571:Sentinel Surveillance; D014454:Uganda / Q000453:epidemiology