Date of Award

Spring 1-1-2013

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Balaji Rajagopalan

Second Advisor

Thomas Hopson

Third Advisor

Edith Zagona

Abstract

Meningococcal meningitis (meningitis) is endemic to West Africa, with the disease being fatal in 50% of the cases if left untreated. This region relies upon the international community for assistance in prevention and treatment. The International Coordinating Group for Vaccine Provision (ICG) oversees the monitoring of meningitis

cases and the allocation of vaccine to limit case spread. Given the limited supply of vaccine, determining its deployment is contingent upon a number of factors including predictions of future cases. An inverse relationship exists between relative humidity and the incidence of meningitis cases providing a method of prediction based on understanding of climate variability. This research focused on first examining the interseasonal variability of relative humidity to develop predictive models based on climate features and then extend those models to forecast meningitis case counts.

The annual latitudinal migration of the Intertropical Convergence Zone (ITCZ) drives the monsoon onset and retreat, however ancillary factors such as sea-surface temperatures can have a large influence on monsoon timing and strength. This onset and

retreat of the monsoon plays an important role in the occurrence of meningococcal meningitis in the region. The first part of the thesis involves a systematic analysis of relative humidity during the onset, peak and retreat periods of the monsoon over Western

Africa. A K-means cluster analysis was performed to identify spatially coherent regions of relative humidity variability during the three periods. The cluster average of the relative humidity provides a robust representative index of the strength and timing of the

WAM. Correlating the cluster anomalies with large-scale dynamical and thermodynamical features indicate that the anomalies are most strongly connected to the land-ocean temperature gradient and the corresponding circulation, tropical Atlantic sea surface temperatures (SSTs), and to a somewhat lesser extent SSTs over the tropical

Pacific. These connections to large-scale climate features were also found to be persistent over intraseasonal time scales, and thus best linear predictive models were developed to enable skillful forecasts of relative humidity during the two periods at 15-75 day lead times.

The second part of the research involved analyzing the meningitis incidence within four countries of West Africa (Benin, Chad, Nigeria, and Togo) and their links to meteorological variables. The predictive models of relative humidity during the onset and withdrawal season of the monsoon, which also coincides with the withdrawal and onset

of meningitis season, respectively, were used to model the occurrences of meningitis cases. Skill scores were found to determine the effectiveness of these models in forecasting meningitis case counts. These two components of the research make important contributions towards understanding the processes that govern meningitis occurrences and provide the tools for improving the efficiency of mitigation strategies.

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