Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment.
BACKGROUND: 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 hy...
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ftdoajarticles:oai:doaj.org/article:5bd0c5abff534b058e2f9f7793baff89 2023-05-15T15:15:48+02:00 Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. Fernando Abad-Franch Gustavo H Grimmer Vanessa S de Paula Luiz T M Figueiredo Wornei S M Braga Sérgio L B Luz 2012-01-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0001846 https://doaj.org/article/5bd0c5abff534b058e2f9f7793baff89 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC3469468?pdf=render https://doaj.org/toc/1935-2735 1935-2735 doi:10.1371/journal.pntd.0001846 https://doaj.org/article/5bd0c5abff534b058e2f9f7793baff89 PLoS Neglected Tropical Diseases, Vol 6, Iss 10, p e1846 (2012) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2012 ftdoajarticles https://doi.org/10.1371/journal.pntd.0001846 2022-12-31T06:09:16Z BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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 closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (β ± SE) on which to base inference. Residence area (β(Village) = 2.93 ± 0.41; β(Upland) = -0.56 ± 0.33, β(Riverbanks) = -2.37 ± 0.55) and bednet use (β = -0.95 ± 0.28) were the most important factors, followed by crop-plot ownership (β = 0.39 ± 0.22) and regular use of a closed toilet/latrine (β = 0.19 ± 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. CONCLUSIONS/SIGNIFICANCE: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLoS Neglected Tropical Diseases 6 10 e1846 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Fernando Abad-Franch Gustavo H Grimmer Vanessa S de Paula Luiz T M Figueiredo Wornei S M Braga Sérgio L B Luz Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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 closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (β ± SE) on which to base inference. Residence area (β(Village) = 2.93 ± 0.41; β(Upland) = -0.56 ± 0.33, β(Riverbanks) = -2.37 ± 0.55) and bednet use (β = -0.95 ± 0.28) were the most important factors, followed by crop-plot ownership (β = 0.39 ± 0.22) and regular use of a closed toilet/latrine (β = 0.19 ± 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. CONCLUSIONS/SIGNIFICANCE: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a ... |
format |
Article in Journal/Newspaper |
author |
Fernando Abad-Franch Gustavo H Grimmer Vanessa S de Paula Luiz T M Figueiredo Wornei S M Braga Sérgio L B Luz |
author_facet |
Fernando Abad-Franch Gustavo H Grimmer Vanessa S de Paula Luiz T M Figueiredo Wornei S M Braga Sérgio L B Luz |
author_sort |
Fernando Abad-Franch |
title |
Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
title_short |
Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
title_full |
Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
title_fullStr |
Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
title_full_unstemmed |
Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
title_sort |
mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2012 |
url |
https://doi.org/10.1371/journal.pntd.0001846 https://doaj.org/article/5bd0c5abff534b058e2f9f7793baff89 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 6, Iss 10, p e1846 (2012) |
op_relation |
http://europepmc.org/articles/PMC3469468?pdf=render https://doaj.org/toc/1935-2735 1935-2735 doi:10.1371/journal.pntd.0001846 https://doaj.org/article/5bd0c5abff534b058e2f9f7793baff89 |
op_doi |
https://doi.org/10.1371/journal.pntd.0001846 |
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PLoS Neglected Tropical Diseases |
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6 |
container_issue |
10 |
container_start_page |
e1846 |
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1766346138913341440 |