Epidemiology: Open Access

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A District Level Linear Regression Analysis of Malaria Morbidity and Associated Control Interventions in Lusaka Province

Maybin Kalubula, Qigui Liu, Gui Rong Song and Xiao Feng Li

Despite being a largely preventable and treatable disease, malaria is responsible for an estimated 50% of all infant mortality and 20% of all maternal mortality in Zambia and presents severe social and economic burdens on communities living in endemic areas. A retrospective, observational study was performed in Lusaka Province from 2009 to 2013. Provincial malaria surveillance data were analyzed using a district level linear regression model to explore the association between malaria morbidity and coverage with ITNs and IRHS. The study population included all patients who suffered from malaria in relation with the provincial population annually from January 2009 to December 2013. Multiple factor association between malaria morbidity and IRHS showed the P-value = 0.851 (p > 0.05) while malaria morbidity and ITN showed the P-value = 0.004 (p < 0.05). There was insignificant or no association between malaria morbidity and IRHS in Lusaka province from 2009-2013. However, there was a relatively strong association between malaria morbidity and ITN coverage. A district level linear regression analysis showed that there was insignificant association between malaria morbidity and IRHS but there was a relatively strong association between malaria morbidity and ITN coverage.