Microclimate and Larval Habitat Density Predict Adult Aedes albopictus Abundance in Urban Areas

Evans, Michelle V.; Hintz, Carl W.; Jones, Lindsey; Shiau, Justine C.; Solano, Nicole; Drake, John M.; Murdock, Courtney C.

doi:10.4269/ajtmh.19-0220

Cited by 32 publications

(24 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, altitude and LC represented environmental variables used to determine the distribution of ecological niches for dengue. A number of studies have investigated the effects of altitude [53] [44] [54] and urban development [55] [56] on dengue incidence in various countries but not much has been done on the other LC types. Our analyses established a negative association between altitude and dengue risk.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk

et al. 2019

View full text Add to dashboard Cite

BackgroundDengue fever is the most widespread infectious disease of humans transmitted by Aedes mosquitoes. It is the leading cause of hospitalization and death in children in the Southeast Asia and western Pacific regions. We analyzed surveillance records from health centers in Vietnam collected between 2001–2012 to determine seasonal trends, develop risk maps and an incidence forecasting model.MethodsThe data were analyzed using a hierarchical spatial Bayesian model that approximates its posterior parameter distributions using the integrated Laplace approximation algorithm (INLA). Meteorological, altitude and land cover (LC) data were used as predictors. The data were grouped by province (n = 63) and month (n = 144) and divided into training (2001–2009) and validation (2010–2012) sets. Thirteen meteorological variables, 7 land cover data and altitude were considered as predictors. Only significant predictors were kept in the final multivariable model. Eleven dummy variables representing month were also fitted to account for seasonal effects. Spatial and temporal effects were accounted for using Besag-York-Mollie (BYM) and autoregressive (1) models. Their levels of significance were analyzed using deviance information criterion (DIC). The model was validated based on the Theil’s coefficient which compared predicted and observed incidence estimated using the validation data. Dengue incidence predictions for 2010–2012 were also used to generate risk maps.ResultsThe mean monthly dengue incidence during the period was 6.94 cases (SD 14.49) per 100,000 people. Analyses on the temporal trends of the disease showed regular seasonal epidemics that were interrupted every 3 years (specifically in July 2004, July 2007 and September 2010) by major fluctuations in incidence. Monthly mean minimum temperature, rainfall, area under urban settlement/build-up areas and altitude were significant in the final model. Minimum temperature and rainfall had non-linear effects and lagging them by two months provided a better fitting model compared to using unlagged variables. Forecasts for the validation period closely mirrored the observed data and accurately captured the troughs and peaks of dengue incidence trajectories. A favorable Theil’s coefficient of inequality of 0.22 was generated.ConclusionsThe study identified temperature, rainfall, altitude and area under urban settlement as being significant predictors of dengue incidence. The statistical model fitted the data well based on Theil’s coefficient of inequality, and risk maps generated from its predictions identified most of the high-risk provinces throughout the country.

show abstract

Section: Discussionmentioning

confidence: 99%

Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Mosquito data were collected using BG-Sentinel 2 traps that were deployed at the same nine sites used for microclimate monitoring. Adult mosquito samples were collected 26 times between May 2016 to December 2017 [37]. Traps were PLOS NEGLECTED TROPICAL DISEASES run continuously for 48 hours and were baited with an octenol (1-octen-3-ol) lure.…”

Section: Vectorial Capacity Modelingmentioning

confidence: 99%

“…Model predictions were cross-validated across the nine sites using the approach previously described for the microclimate models. Background information on the mosquito data and meteorological associations of mosquito abundance can be found in Evans et al [37]. The expression for temperature-dependent VC(T) assumes a constant temperature to calculate the per-generation rate of increase of a pathogen in a fully susceptible population.…”

Section: Vectorial Capacity Modelingmentioning

confidence: 99%

“…Spatial variation of vegetation, topography, and the built environment provides diverse breeding and resting habitats for mosquitoes, which in turn influence mosquito abundance and potential exposure of human and zoonotic hosts to questing mosquitoes. For container-breeding mosquitoes the abundance and quality of artificial habitats is particularly important and has been found to vary considerably across urban landscapes [37,[78][79][80]. Neighborhood-level variation in socioeconomic factors, such as housing conditions, sanitation, and accessibility of public health resources, also influence the types and abundances of artificial breeding habitats as well as human exposure to mosquitoes and the overall risk of disease transmission [26,27].…”

Section: Plos Neglected Tropical Diseasesmentioning

confidence: 99%

“…In most studies to date, the effects of habitat on mosquitoes have been modeled using land cover, land use, and socioeconomic indicators as indirect proxies [33][34][35]. However, recent studies combining direct monitoring of urban microclimates with field experiments [36] and observations of mosquito abundance [37] have found that variation in local temperatures account for some of the differences in mosquito abundance and life history traits across urban, suburban, and rural habitats. These results highlight the prospects for synthesizing our understanding of the thermal biology of mosquitoes with knowledge of the physical dynamics of urban climate to determine when and where microclimate conditions for disease transmission will be highest.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Land cover affects microclimate and temperature suitability for arbovirus transmission in an urban landscape

et al. 2020

Self Cite

View full text Add to dashboard Cite

The emergence of mosquito-transmitted viruses poses a global threat to human health. Combining mechanistic epidemiological models based on temperature-trait relationships with climatological data is a powerful technique for environmental risk assessment. However, a limitation of this approach is that the local microclimates experienced by mosquitoes can differ substantially from macroclimate measurements, particularly in heterogeneous urban environments. To address this scaling mismatch, we modeled spatial variation in microclimate temperatures and the thermal potential for dengue transmission by Aedes albopictus across an urban-to-rural gradient in Athens-Clarke County GA. Microclimate data were collected across gradients of tree cover and impervious surface cover. We developed statistical models to predict daily minimum and maximum microclimate temperatures using coarse-resolution gridded macroclimate data (4000 m) and high-resolution land cover data (30 m). The resulting high-resolution microclimate maps were integrated with temperaturedependent mosquito abundance and vectorial capacity models to generate monthly predictions for the summer and early fall of 2018. The highest vectorial capacities were predicted for patches of trees in urban areas with high cover of impervious surfaces. Vectorial capacity was most sensitive to tree cover during the summer and became more sensitive to impervious surfaces in the early fall. Predictions from the same models using temperature data from a local meteorological station consistently over-predicted vectorial capacity compared to the microclimate-based estimates. This work demonstrates that it is feasible to model variation in mosquito microenvironments across an urban-to-rural gradient using satellite Earth observations. Epidemiological models applied to the microclimate maps revealed localized patterns of temperature suitability for disease transmission that would not be detectable using macroclimate data. Incorporating microclimate data into disease transmission models PLOS NEGLECTED TROPICAL DISEASES

show abstract

Food web structure and microenvironment affect Chagas disease vector infection and abundance in a rural landscape

et al. 2023

View full text Add to dashboard Cite

Vector-borne pathogen transmission is shaped by multiple abiotic and biotic factors. Understanding the relative importance of these factors on vector abundance and infection is important for developing vector-borne disease control strategies. The crown of the Attalea butyracea palm provides a natural arboreal mesocosm suitable for studying how food web relations and microclimate affect Chagas disease vectors of the genus Rhodnius, which feed on vertebrate blood and interact with many vertebrate and invertebrate species, vegetation, and detritus within the palm crown. We performed a cross-sectional, observational study of A. butyracea crowns using a community ecology network approach to evaluate abiotic and biotic conditions associated with Rhodnius pallescens abundance and infection with Trypanosoma cruzi, the Chagas disease etiologic agent. We collected 1098 R. pallescens from 105 A. butyracea crowns in rural landscapes of Panama. In a palm subset (N = 49), we recorded microclimate and habitat conditions and counted vertebrate and invertebrate species in order to characterize palm crown food webs. We used food web metrics, namely Generality (average number of prey per predator) and Vulnerability (average number of predators per prey) to evaluate associations between palm community trophic structure, vector predators, vector blood meal species composition, vector abundance, and vector T. cruzi infection. Field data analyzed with generalized linear models showed that vector abundance and infection in a given palm crown were influenced by a combination of geographic location, land-use type, palm crown animal community composition, and microhabitat conditions. Vector abundance was negatively associated with increased overall palm crown community diversity. However, vector abundance was positively associated with the invertebrate predator and mammal community. R. pallescens Vulnerability score, which measures predation pressure on the vector within the palm crown, was positively associated with vector abundance. Vector infection with T. cruzi was positively associated with

show abstract

Microclimate and Larval Habitat Density Predict Adult Aedes albopictus Abundance in Urban Areas

Cited by 32 publications

References 55 publications

Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk

Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk

Land cover affects microclimate and temperature suitability for arbovirus transmission in an urban landscape

Food web structure and microenvironment affect Chagas disease vector infection and abundance in a rural landscape

Contact Info

Product

Resources

About