RePEc: Research Papers in Economics, 1983

Arc, 2023

2006

In order to detect potential disease clusters where a putative source cannot be specified, classical procedures scan the geographical area with circular windows through a specified grid imposed to the map. However, the choice of the windows' shapes, sizes and centers is critical and different choices may not provide exactly the same results. The aim of our work was to use an Oblique Decision Tree model (ODT) which provides potential clusters without pre-specifying shapes, sizes or centers. For this purpose, we have developed an ODT-algorithm to find an oblique partition of the space defined by the geographic coordinates. ODT is based on the classification and regression tree (CART). As CART finds out rectangular partitions of the covariate space, ODT provides oblique partitions maximizing the interclass variance of the independent variable. Since it is a NP-Hard problem in R N , classical ODT-algorithms use evolutionary procedures or heuristics. We have developed an optimal ODT-algorithm in R 2 , based on the directions defined by each couple of point locations. This partition provided potential clusters which can be tested with Monte-Carlo inference. We applied the ODT-model to a dataset in order to identify potential high risk clusters of malaria in a village in Western Africa during the dry season. The ODT results were compared with those of the Kulldorff' s SaTScan™. The ODT procedure provided four classes of risk of infection. In the first high risk class 60%, 95% confidence interval (CI95%) [52.22-67.55], of the children was infected. Monte-Carlo inference showed that the spatial pattern issued from the ODT-model was significant (p < 0.0001). Satscan results yielded one significant cluster where the risk of disease was high with an infectious rate of 54.21%, ]. Obviously, his center was located within the first high risk ODT class. Both procedures provided similar results identifying a high risk cluster in the western part of the village where a mosquito breeding point was located. ODT-models improve the classical scanning procedures by detecting potential disease clusters independently of any specification of the shapes, sizes or centers of the clusters.

Memoirs of the American Academy in Rome 69 (2024), iv–vii

2018

Primary healthcare services are vital for determining a nation's overall health status. Improving access to and use of healthcare can lead to better health outcomes in the population. We investigated access to and utilisation of primary healthcare services in the Jere local government area of Borno State, Nigeria. Questionnaires were distributed, and interviews were conducted to collect the data. We analysed the results via descriptive statistics (frequency distribution tables). Availability sampling, a nonprobability sampling method, was used to administer 400 questionnaires to the respondents, and 292 questionnaires were returned. Most participants were young (44.50%), unmarried (87.7%), and highly literate, with 93.50% receiving tertiary education. Approximately 47.60% found healthcare inaccessible, 42.10% found it accessible, and 10.30% were undecided. A total of 51.0% used healthcare facilities, 33.2% did not, and 14.0% were undecided. A total of 38.4% visited health centers, 19.9% opted for traditional medicine, 3.4% sought treatment from religious leaders, and 34.9% used a combination of these resources. A total of 44.5% preferred modern medicine, 36.0% used herbs, 17.8% turned to prayers, and 1.7% sought blessings from elders. Therefore, the study recommends that the state and local government authorities provide a comprehensive approach encompassing infrastructural development, health education, awareness programs, staff training, and recruitment that collectively improve the primary healthcare services in the Jere local government area.