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A systematic literature review and meta-analysis on the global prevalence of Naegleria spp. in water sources.

Ahmad DaryaniZahra SeifiSamira DodangehAzar NajafiSeyed Abdollah HosseiniDavood AnvariAli TaghipourMaryam NorouziMaryam Niyyati
Published in: Transboundary and emerging diseases (2020)
Naegleria species (spp.) is a free-living amoeba whose pathogenic species such as N. fowleri pose a significant health risk to young people, and the most important source of infection is water source. This study aims to perform a systematic review and meta-analysis of the data on the prevalence of Naegleria spp. in water sources in the available literature. Included articles on the prevalence of Naegleria spp. in water sources in PubMed, Google Scholar, ProQuest, ScienceDirect, EMBASE, Scopus and Web of Science were systematically searched between January 1977 and September 2019. Regarding meta-analysis, the random-effect model was employed by forest plot with 95% of confidence interval (CI). The meta-analysis considered 103 articles surveying the prevalence of Naegleria spp. in various water sources. The pooled worldwide prevalence of Naegleria spp. across 35 countries was 26.42% (95% CI = 21.52-31.63). The subgroup analysis reported that the pooled worldwide prevalence of N. fowleri is 23.27%, N. australiensis 9.12%, N. lovaniensis 7.68%, N. pagei 5.95, N. polaris 5.17%, N. gruberi 3.95%, N. clarki 3.54%, N. americana 3.19%, N. philippinensis 1.99% and N. dobsoni 1.73%. This is the first systematic review on the prevalence of Naegleria spp. in water sources. Our findings suggest a wide distribution of Naegleria spp., including potential pathogenic species such as N. fowleri, in water sources all over the world. Therefore, it is of paramount importance to provide comprehensive data and systematic analysis regarding the prevalence of Naegleria spp. in water sources. Accordingly, further studies are highly recommended to investigate the presence of pathogenic N. fowleri in other countries.
Keyphrases
  • systematic review
  • risk factors
  • drinking water
  • meta analyses
  • public health
  • risk assessment
  • big data
  • data analysis