Assessment of Burden of Malaria in Gwanda District, Zimbabwe, Using the Disability Adjusted Life Years

Abstract

Malaria is one of the highest contributors to morbidity and mortality in Zimbabwe. However, there is paucity of knowledge regarding disability adjusted life years (DALYs) as a measure of burden of malaria in affected communities. The DALYs metric was used to assess the burden of malaria in Gwanda District with the aim of contributing to a better understanding of the impact of disease on affected communities. Data was collected from health facility malaria registers and the District Health Information System (DHIS) to estimate DALYs at household and district levels respectively. The household DALYs included 130 malaria cases from 2013 to 2015 while the DALYs for the district included 719 confirmed malaria cases from 2011 to 2015. Households lost a total of 153.89 DALYs with the majority of the disease burden (65.55%) occurring in the most economically productive age group (15–45 years) with a mean loss of 1.18 DALYs per malaria case. At district level, 251.09 DALYs were lost due to malaria and the calculated average district DALY rate for 2011–2015 was 36.29 DALYs/100,000 persons per year. It is important to estimate malaria burden to assist policy makers in making informed decisions when channelling resources for control and prevention of the disease.

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“…Many of the studies utilized the highly disaggregated nature of the data by using either facility or district level data, with the exception of two studies which modelled national trends [ 33 , 116 ]. Studies commonly applied strategies to account for temporal autocorrelation and the correlation between geographical units, including generalized linear models [ 58 ], multi-level analysis [ 77 , 78 ], and ordinary least-squares regression with adjustment for seasonality and lag [ 34 , 37 , 117 ]. Among studies that modelled multiple facilities or administrative regions, random effects were commonly applied to account for heterogeneity.…”

Using Routine Health Information Data for Research in Low- and Middle-Income Countries: A Systematic Review

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