Article ; Online: Ecological predictors of mosquito population and arbovirus transmission synchrony estimates.
2023 Volume 60, Issue 3, Page(s) 564–574
Abstract: Quantifying synchrony in species population fluctuations and determining its driving factors can inform multiple aspects of ecological and epidemiological research and policy decisions. We examined seasonal mosquito and arbovirus surveillance data ... ...
Abstract | Quantifying synchrony in species population fluctuations and determining its driving factors can inform multiple aspects of ecological and epidemiological research and policy decisions. We examined seasonal mosquito and arbovirus surveillance data collected in Connecticut, United States from 2001 to 2020 to quantify spatial relationships in 19 mosquito species and 7 arboviruses timeseries accounting for environmental factors such as climate and land cover characteristics. We determined that mosquito collections, on average, were significantly correlated up to 10 km though highly variable among the examined species. Few arboviruses displayed any synchrony and significant maximum correlated distances never exceeded 5 km. After accounting for distance, mixed effects models showed that mosquito or arbovirus identity explained more variance in synchrony estimates than climate or land cover factors. Correlated mosquito collections up to 10-20 km suggest that mosquito control operations for nuisance and disease vectors alike must expand treatment zones to regional scales for operations to have population-level impacts. Species identity matters as well, and some mosquito species will require much larger treatment zones than others. The much shorter correlated detection distances for arboviruses reinforce the notion that focal-level processes drive vector-borne pathogen transmission dynamics and risk of spillover into human populations. |
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MeSH term(s) | Animals ; Humans ; Arboviruses ; Arbovirus Infections ; Climate ; Mosquito Control ; Connecticut ; Mosquito Vectors ; Culicidae |
Language | English |
Publishing date | 2023-03-15 |
Publishing country | England |
Document type | Journal Article ; Research Support, U.S. Gov't, P.H.S. ; Research Support, Non-U.S. Gov't |
ZDB-ID | 410635-0 |
ISSN | 1938-2928 ; 0022-2585 |
ISSN (online) | 1938-2928 |
ISSN | 0022-2585 |
DOI | 10.1093/jme/tjad024 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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