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Defining micro-epidemiology for malaria elimination: systematic review and meta-analysis.

Bannister-Tyrrell, Melanie; Verdonck, Kristien; Hausmann-Muela, Susanna; Gryseels, Charlotte; Muela Ribera, Joan; Peeters Grietens, Koen.
Malar J; 16(1): 164, 2017 04 20.
Artigo em Inglês | MEDLINE | Abr 2017 | ID: mdl-28427389
Resumo: BACKGROUND: Malaria risk can vary markedly between households in the same village, or between villages, but the determinants of this "micro-epidemiological" variation in malaria risk remain poorly understood. This study aimed to identify factors that explain fine-scale variation in malaria risk across settings and improve definitions and methods for malaria micro-epidemiology. METHODS: A systematic review of studies that examined risk factors for variation in malaria infection between individuals, households, clusters, hotspots, or villages in any malaria-endemic setting was conducted. Four databases were searched for studies published up until 6th October 2015. Crude and adjusted effect estimates for risk factors for malaria infection were combined in random effects meta-analyses. Bias was assessed using the Newcastle-Ottawa Quality Assessment Scale. RESULTS: From 743 retrieved records, 51 studies were selected, representing populations comprising over 160,000 individuals in 21 countries, in high- and low-endemicity settings. Sixty-five risk factors were identified and meta-analyses were conducted for 11 risk factors. Most studies focused on environmental factors, especially increasing distance from a breeding site (OR 0.89, 95% CI 0.86-0.92, 10 studies). Individual bed net use was protective (OR 0.63, 95% CI 0.52-0.77, 12 studies), but not household bed net ownership. Increasing household size (OR 1.08, 95% CI 1.01-1.15, 4 studies) and household crowding (OR 1.79, 95% CI 1.48-2.16, 4 studies) were associated with malaria infection. Health seeking behaviour, medical history and genetic traits were less frequently studied. Only six studies examined whether individual-level risk factors explained differences in malaria risk at village or hotspot level, and five studies reported different risk factors at different levels of analysis. The risk of bias varied from low to high in individual studies. Insufficient reporting and comparability of measurements limited the number of meta-analyses conducted. CONCLUSIONS: Several variables associated with individual-level malaria infection were identified, but there was limited evidence that these factors explain variation in malaria risk at village or hotspot level. Social, population and other factors may confound estimates of environmental risk factors, yet these variables are not included in many studies. A structured framework of malaria risk factors is proposed to improve study design and quality of evidence in future micro-epidemiological studies.