Predicting Malaria Risk and Utilization of Health Care Services among the Population in Uganda
Background: Incidence rate is the most commonly used direct measure of disease occurrences in the population at risk. Predicting malaria risk and utilization of health care services among the population is important in explaining the dynamics of the disease.
Objective: The objective of this study was to predict malaria risk and utilization of health care services among the population in Uganda. Methods: We used a retrospective longitudinal study design that involved a secondary analysis of data from Ministry of Health (MoH) and Uganda Bureau of statistics (UBOS).The predicting model was derived taking limiting distribution of the partial derivative with respect to time of the malaria predicting model at the health facilities.
Results: Our findings revealed that some of the infected individuals are infectious within the first 2 months but the infectiousness decreases with increasing time implying the individuals become susceptible again. The monthly model predicted new cases of malaria were more than the observed new cases of malaria. This implies that not all cases are routinely diagnosed and not all infected individuals in the population are seeking treatment for malaria at the health facilities. The observed new cases of malaria at the government facilities account for about 39% of the malaria risk in the population. Furthermore 61% of the new cases of malaria either sought treatment from non-government facilities or never sought treatment at all.
Conclusions: The proposed model can be used to predict both the intensity and expected number of new cases of malaria at health facility and population level in the next month. The model can further be used to assess the monthly intensity of malaria; evaluate the effectiveness of the interventions in reducing the risk in the general population, and to provide timely statistics for better monitoring and design of targeted interventions that will reduce malaria incidence in Uganda. Therefore the observed stagnation in malaria incidence in the country could be attributable to the failure to monitor the 61% of the incidence that do not seek treatment from government health facilities.