Is the source of domestic water associated with the risk of malaria infection? Spatial variability and a mixed-effects multilevel analysis

Int J Infect Dis. 2021 Mar:104:224-231. doi: 10.1016/j.ijid.2020.12.062. Epub 2020 Dec 24.

Abstract

Background: There is a dearth of information on the relationship between domestic water source and malaria infection in malaria-endemic regions such as Tanzania. This study examined the geospatial variability and association between domestic water source and malaria prevalence in Tanzania.

Methods: We analyzed data from a sample of 6707 children, aged 6-59 months, from the 2017 Tanzania Malaria Indicator Survey. The outcome variable was the result of malaria testing (positive or negative) and the main explanatory variable was domestic water source (piped or non-piped). Random effect variables were administrative region and geographical zone. ArcGIS 10.7 was used to create geospatial distribution maps. A STATA MP 14.0 was used to fit a mixed-effects multilevel logistic regression to examine the factors associated with malaria prevalence.

Results: The prevalence of malaria and non-piped domestic water source was respectively 7.3% and 59.6%. The regions and zones with a higher prevalence of malaria also had a higher percentage of non-piped water. There was a statistically significant variation in the risk of malaria across the regions (variance = 1.27; 95% CI, 0.40-4.07) and zones (variance = 4.75; 95% CI, 1.46-15.46). The final fixed-effects model showed that non-piped domestic water was significantly associated with malaria prevalence (adjusted odds ratio (AOR) = 2.18; 95% CI, 1.64-2.89; P < 0.001).

Conclusions: A non-piped source of domestic water was independently associated with positive testing for malaria. Moreover, regions with a high percentage of non-piped domestic water had a correspondingly high prevalence of malaria.

Keywords: Domestic water; Malaria; Multilevel analysis; Non-piped; Spatial variability; Tanzania.

MeSH terms

  • Child, Preschool
  • Female
  • Humans
  • Infant
  • Logistic Models
  • Malaria / epidemiology*
  • Male
  • Multilevel Analysis
  • Odds Ratio
  • Prevalence
  • Risk Factors
  • Spatial Analysis
  • Surveys and Questionnaires
  • Tanzania / epidemiology
  • Water Supply / statistics & numerical data*
  • Water*

Substances

  • Water