biostudies-literatureUnknown6(10)Abad-Franch F<h4>Background</h4>Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data--particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment.<h4>Methodology/principal findings</h4>A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closPLoS neglected tropical diseasese1846https://www.ebi.ac.uk/biostudies/studies/S-EPMC3469468biostudies-literatureMayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment.PMC3469468Figueiredo LTLuz SLBraga WSGrimmer GHAbad-Franch Fde Paula VSfalseMayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment.<h4>Background</h4>Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data--particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment.<h4>Methodology/principal findings</h4>A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using clos2012-01-01T00:00:00Z20122025-04-19T15:52:10.803Z2019-03-27T00:58:59ZS-EPMC34694682307185210.1371/journal.pntd.0001846