Literature DB >> 25569303

Geographic expansion of the invasive mosquito Aedes albopictus across Panama--implications for control of dengue and Chikungunya viruses.

Matthew J Miller1, Jose R Loaiza2.   

Abstract

Entities:  

Year:  2015        PMID: 25569303      PMCID: PMC4287627          DOI: 10.1371/journal.pntd.0003383

Source DB:  PubMed          Journal:  PLoS Negl Trop Dis        ISSN: 1935-2727


× No keyword cloud information.

Background

The Asian tiger mosquito, Aedes (Stegomyia) albopictus, is an invasive species that has expanded its territory to over 40% of the earth’s terrestrial landmass in the last 30 years [1]. Ae. albopictus is an efficient vector of all serotypes of dengue, a disease that has increased in frequency over the past 30 years in the Americas [2], where it represents an annual cost of 2,100,000,000 USD per year [3]. This mosquito is also an efficient vector of the three genotypes of Chikungunya virus, a worldwide emerging pathogen that causes fever, fatigue, and joint swelling in humans. Since 2006, Chikungunya outbreaks have been increasingly recorded outside the virus’s native range in tropical Africa, perhaps because of a mutation in the virus’s envelope gene, which increases the replication and dissemination capacity of the virus in Ae. albopictus [4]. During the second quarter of 2014, Chikungunya has been detected throughout much of the Americas, with major outbreaks occurring in several Caribbean nations, and local transmission confirmed or suspected in the United States, Panama, Venezuela, Peru, and Chile, creating an imminent threat for humans throughout the Americas, who have no prior exposure to this infection [5]. The first cases of Chikungunya disease in Panama were reported in May 2014, occurring in nonresidents who most likely picked up the virus in their Caribbean countries of origin. On 23 July 2014, Panama’s health authority reported autochthonous transmission of Chikungunya virus. Coincidentally, the earliest cases involved patients located in Juan Diaz, an urban area on the eastern outskirts of Panama City, where the first specimen of invasive Ae. albopictus was collected in 2002. Ae. albopictus has expanded across much of Panama since that time, yet to date, no information exists about the degree of expansion or about the factors contributing to the geographic expansion of this important mosquito vector across Panama. Here, we map the temporal expansion of Ae. albopictus, use species distribution models to determine the ecological and nonecological factors associated with its expansion, and comment on the implications for vector and disease control programs in Panama and elsewhere in the American tropics.

Tempo and Mode of Ae. albopictus Expansion in Panama

Panama’s Ministry of Health (MINSA) maintains a nationwide surveillance program for Aedes mosquitoes (S1 Methods) and provided us with geographic coordinates and dates for confirmed samples of Ae. albopictus collected between 2002 and 2013, which were supplemented with Jose Loaiza’s surveys of mosquitoes across Panama. Mosquito occurrence data were placed into three temporal pools: 2002–2005, 2006–2009, and 2010–2013. Between 2002 and 2005, Ae. albopictus was found only in the eastern portion of Panama City (Fig. 1A). Between 2006 and 2009, mosquito density increased in Panama City and also expanded to Colón, central Panama’s Caribbean port (Fig. 1B). Between 2010 and 2013, Ae. albopictus expanded both eastward from Panama City and also into western Panama between the Costa Rican border and Santiago, Veraguas (Fig. 1C). Although Ae. albopictus appears to have expanded westward from Panama City along the Pan-American highway, the lack of confirmed samples from the Azuero Peninsula east to Panama City’s western edges raise the possibility that the 2010–2013 distribution of Ae. albopictus in western Panama was the result of a separate colonization event from Costa Rica, as the species has occurred in several locations in that country since at least 2009 [6].
Figure 1

Occurrence points for Ae. albopictus for three time periods during its recent expansion across the Republic of Panama: A) between 2002 and 2006, Ae. albopictus was found only in the eastern metropolitan area of Panama City; B) during 2006 and 2009, Ae. albopictus expanded to the Colón on the Caribbean coast; and C) between 2010 and 2013, the species was found throughout much of western Panama as well as east of Panama City.

Darker blue colors indicate political districts with higher human population densities. Ae. albopictus apparently has not yet spread to the Bocas del Toro province in northwestern Panama or the Azuero Peninsula, which includes the city of Chitré, nor to much of the lightly inhabited Darién province.

Occurrence points for Ae. albopictus for three time periods during its recent expansion across the Republic of Panama: A) between 2002 and 2006, Ae. albopictus was found only in the eastern metropolitan area of Panama City; B) during 2006 and 2009, Ae. albopictus expanded to the Colón on the Caribbean coast; and C) between 2010 and 2013, the species was found throughout much of western Panama as well as east of Panama City.

Darker blue colors indicate political districts with higher human population densities. Ae. albopictus apparently has not yet spread to the Bocas del Toro province in northwestern Panama or the Azuero Peninsula, which includes the city of Chitré, nor to much of the lightly inhabited Darién province.

Road Networks Alone Best Explain the Geographic Expansion of Ae. albopictus across Panama

We created competing species distribution models (SDMs) via maximum entropy machine learning algorithms using the Maxent software package (version 3.3) [7] to evaluate the factors associated with Ae. albopictus expansion. SDMs predict the suitability (i.e., probability of species occurrence, range: 0–1) of map cells based on the distribution of known occurrence points and the environmental conditions of map cells. For environmental conditions, we used all 19 WorldClim climate layers [8] as well as geographic information system (GIS) layers of principal roads and population density [9], which we rasterized and scaled to 2.5 arc minutes. SDMs were created using the 2006–2009 mosquito occurrence data, and model fit was evaluated by comparing the later (2010–2013) occurrence data against the model-predicted suitability of those points. We created seven SDMs including “only climate,” “only human density,” and “only roads,” as well as all possible combinations of those three datasets. All SDMs were generated based on ten replicates using cross validation and 10,000 background points, and we set our threshold for habitat suitability at 10% of all observed occurrences. We used the 2010–2013 sample data to compare the fit of each SDM in two ways: first, we calculated the mean modeled suitability of all 2010–2013 occurrence points, and second, we calculated the percentage of those occurrence points having a predicted suitability above the 10% minimum suitability threshold. An SDM based only on the road network best predicted the 2010–2013 distribution of Ae. albopictus in Panama, compared to SDMs based on climate or human population density or even to models that included roads and other factors (Table 1; Fig. 1). The average suitability of 2010–2013 occurrences based on roads alone was 0.487, compared to average suitability of other models that ranged from 0.285–0.319. Likewise, 80% of the 2010–2013 samples occurred in areas predicted to be suitable habitats for Ae. albopictus in the roads-only model, compared to frequencies ranging from 34%–53% in other models. Interestingly, climate alone was the poorest predictor of suitability, predicting habitat suitability for only 34% of the points at which Ae. albopictus was actually sampled between 2010–2013 (Table 1). Our findings appear to be unbiased by mosquito sampling effort or by the relative intensity of sampling along versus off the principal road network (S1 Fig.).
Table 1

Performance of various geographic species distribution models to predict the expansion of Ae. albopictus in Panama.

Model Area under the ROC Curve (AUC) Average Suitability of 2010–2013 Occurrence Points 2006–2009 10% Occurrence Threshold % of 2010–2013 Occurrence Points above Threshold
Roads Only0.8810.4870.60080%
Population Density Only0.9570.3020.23953%
Roads and Population Density0.9750.3190.32949%
Climate, Roads, and Population Density0.9860.2910.36939%
Roads and Climate0.8940.3060.35336%
Climate and Population Density0.9820.2850.38335%
Climate Only0.9790.3090.43834%

Models were parameterized using occurrence points sampled between 2006 and 2009. Area under the curve (AUC) measures the efficiency of the model to discriminate occurrences from random background points; AUC ranks did not correlate with model predictive performance. Model performance was evaluated using two criteria based on 2010–2013 occurrence points: first, by averaging the predicted suitability of all 110 occurrence points, and second, by calculating the frequency of those occurrence points having a predicted suitability above the 10% model threshold.

Models were parameterized using occurrence points sampled between 2006 and 2009. Area under the curve (AUC) measures the efficiency of the model to discriminate occurrences from random background points; AUC ranks did not correlate with model predictive performance. Model performance was evaluated using two criteria based on 2010–2013 occurrence points: first, by averaging the predicted suitability of all 110 occurrence points, and second, by calculating the frequency of those occurrence points having a predicted suitability above the 10% model threshold.

Global versus Local Scales of Ae. albopictus Expansion

In general, our results agree with the global pattern of rapid expansion for Ae. albopictus, which is mainly attributed to human-aided dispersal [1]. Earlier studies have accurately predicted the global expansion of Ae. albopictus using climate-based SDMs [10,11]. Our results should not be seen as in conflict with those findings; rather, they demonstrate the dynamics of Aedes invasions on differing scales of time and space. At global scales, all of Panama is within the climate threshold for Ae. albopictus [10,11]; therefore, the immediate geographic spread across Panama is likely to be determined by factors other than ecology. Likewise, international expansion of Ae. albopictus has occurred principally via oceanic container vessels and/or international air traffic [1], yet our results confirm the primacy of road networks for determining patterns of Aedes expansion and distributional limits at local scales [12,13].

Interactions with Ae. aegypti and Implications for Dengue and Chikungunya Control

Panama’s current urban mosquito control programs focus primarily on Ae. aegypti, yet both this species and Ae. albopictus are vectors of Chikungunya and dengue viruses [4,5]. Some evidence from outside the Americas suggests that reducing Ae. aegypti populations may be less effective at reducing Chikungunya and dengue outbreaks in Panama if simultaneous efforts to reduce the population of Ae. albopictus are not undertaken [14,15]. At the same time, these efforts might facilitate the ecological replacement of Ae. aegypti by Ae. albopictus, which could have both favorable and unfavorable consequences that are difficult to predict a priori. For example, there is evidence that Ae. aegypti is a more efficient vector of dengue virus than Ae. albopictus [16], which may be the result of a greater preference for human bite targets among Ae. aegypti than among Ae. albopictus [17]. Additionally, the particular strain of Chikungunya virus currently circulating in the Americas lacks the mutation allowing for selectively enhanced transmission efficiency in Ae. albopictus [5]. On the other hand, current vector control programs include the indoor application of insecticide in urban areas of Panama, taking advantage of the fact that Ae. aegypti tends to rest inside dwellings rather than in vegetation outside homes [18], while the latter is the preferred resting habitat of Ae. albopictus [17]. However, Ae. albopictus may be ecologically more plastic than Ae. aegypti [17], and it is likely only a matter of time until the mutations favoring Chikungunya transmission in Ae. albopictus migrate to the Americas. Our model presents implications for the control of dengue and Chikungunya disease. The road-only model predicts future expansion of Ae. albopictus into northwestern and eastern Panama as well as in the Azuero Peninsula, which includes Chitré, Panama’s third largest urban area (Fig. 2). This presents an immediate opportunity for Panama’s Ministry of Health to control the expansion of Ae. albopictus. Evidence from Europe suggests that passive transport of larvae occurs in items in which open water accumulates, such as used tires, while adults can be passively transported inside the cabin of cars and trucks [19]. Specifically, we recommend the fumigation of vehicles at transportation checkpoints (see suggested checkpoints in Fig. 2), which could stop the movement of adults and immature stages of Ae. albopictus across Panama.
Figure 2

Geographic model predicting future range expansion of Ae. albopictus in Panama.

This model is based on the best-performing-species distribution model (highway network model). Blue pixels represent locations predicted to be likely areas of Ae. albopictus expansion, whereas gray pixels represent areas that had a model suitability that was below the minimum threshold and therefore were unlikely to harbor mosquitoes. Orange points represent species occurrences sampled between 2010 and 2013. A series of surveillance and fumigation chokepoints at strategic locations on the highway network (e.g., points A, B, C, and D) could limit the continued expansion of Ae. albopictus as a first step to reduce the epidemiological risk posed by this invasive vector.

Geographic model predicting future range expansion of Ae. albopictus in Panama.

This model is based on the best-performing-species distribution model (highway network model). Blue pixels represent locations predicted to be likely areas of Ae. albopictus expansion, whereas gray pixels represent areas that had a model suitability that was below the minimum threshold and therefore were unlikely to harbor mosquitoes. Orange points represent species occurrences sampled between 2010 and 2013. A series of surveillance and fumigation chokepoints at strategic locations on the highway network (e.g., points A, B, C, and D) could limit the continued expansion of Ae. albopictus as a first step to reduce the epidemiological risk posed by this invasive vector. Finally, our results present a cautionary tale in the face of proposals to release genetically modified Ae. aegypti (GM programs); trial GM program releases began in Panama in May 2014. Given that Ae. aegypti has similar demographic and dispersal patterns as Ae. albopictus [13], Ae. aegypti populations may quickly rebound via recolonization after cessation of GM programs. Thus, GM strategies might have only short-term effects on vector population size and may commit Panama to a repeated and costly program for long-term arbovirus control [20]. Additionally such programs could increase the chance that Ae. albopictus displaces Ae. aegypti, making the GM program less relevant. We encourage health authorities in Panama and elsewhere in tropical America to fully consider the ecology of Ae. albopictus alongside Ae. aegypti when developing dengue and Chikungunya disease control programs.

A map of 2010–2013 Ae. albopictus occurrences (yellow points) compared to Ministry of Health (MINSA) occurrence points for Ae. aegypti (gray points).

MINSA surveys exhaustively across Panama for mosquitoes of medical importance, recording positive species occurrences, but they do not tabulate negative samples. In order to estimate sampling intensity and the proportion of sampling effort along the principle road network (gray lines), we plotted Ae. aegypti data that were provided to us by MINSA for the years 2007–2010. These points serve as a proxy for MINSA sampling effort. Comparing these points to the 2010–2013 Ae. albopictus occurrences and the road network demonstrates that MINSA intensively sampled for mosquitoes in areas such as Bocas del Toro and the eastern Azuero Peninsula where Ae. albopictus was not recorded and also routinely sampled in areas such as much of eastern Panama where no roads occur. (PDF) Click here for additional data file. Sampling strategies for adult and immature stages of Aedes mosquitoes and other medically important mosquito species in Panama. (DOCX) Click here for additional data file.
  14 in total

1.  The epidemiology of dengue in the americas over the last three decades: a worrisome reality.

Authors:  José Luis San Martín; Olivia Brathwaite; Betzana Zambrano; José Orlando Solórzano; Alain Bouckenooghe; Gustavo H Dayan; María G Guzmán
Journal:  Am J Trop Med Hyg       Date:  2010-01       Impact factor: 2.345

2.  Behavior of resting Aedes aegypti (Culicidae: Diptera) and its relation to ultra-low volume adulticide efficacy in Panama City, Panama.

Authors:  M J Perich; G Davila; A Turner; A Garcia; M Nelson
Journal:  J Med Entomol       Date:  2000-07       Impact factor: 2.278

3.  Global traffic and disease vector dispersal.

Authors:  Andrew J Tatem; Simon I Hay; David J Rogers
Journal:  Proc Natl Acad Sci U S A       Date:  2006-04-10       Impact factor: 11.205

Review 4.  Aedes albopictus in the United States: ten-year presence and public health implications.

Authors:  C G Moore; C J Mitchell
Journal:  Emerg Infect Dis       Date:  1997 Jul-Sep       Impact factor: 6.883

5.  Spread of the tiger: global risk of invasion by the mosquito Aedes albopictus.

Authors:  Mark Q Benedict; Rebecca S Levine; William A Hawley; L Philip Lounibos
Journal:  Vector Borne Zoonotic Dis       Date:  2007       Impact factor: 2.133

6.  Comparative role of Aedes albopictus and Aedes aegypti in the emergence of Dengue and Chikungunya in central Africa.

Authors:  Christophe Paupy; Benjamin Ollomo; Basile Kamgang; Sara Moutailler; Dominique Rousset; Maurice Demanou; Jean-Pierre Hervé; Eric Leroy; Frédéric Simard
Journal:  Vector Borne Zoonotic Dis       Date:  2010-04       Impact factor: 2.133

7.  Biogeography of the two major arbovirus mosquito vectors, Aedes aegypti and Aedes albopictus (Diptera, Culicidae), in Madagascar.

Authors:  Fara Nantenaina Raharimalala; Lala Harivelo Ravaomanarivo; Pierre Ravelonandro; Lala Sahondra Rafarasoa; Karima Zouache; Van Tran-Van; Laurence Mousson; Anna-Bella Failloux; Eléonore Hellard; Claire Valiente Moro; Bakoly Olga Ralisoa; Patrick Mavingui
Journal:  Parasit Vectors       Date:  2012-03-20       Impact factor: 3.876

8.  Economic impact of dengue illness in the Americas.

Authors:  Donald S Shepard; Laurent Coudeville; Yara A Halasa; Betzana Zambrano; Gustavo H Dayan
Journal:  Am J Trop Med Hyg       Date:  2011-02       Impact factor: 2.345

9.  Scientific standards and the regulation of genetically modified insects.

Authors:  R Guy Reeves; Jai A Denton; Fiammetta Santucci; Jarosław Bryk; Floyd A Reed
Journal:  PLoS Negl Trop Dis       Date:  2012-01-31

10.  Arrival of chikungunya virus in the new world: prospects for spread and impact on public health.

Authors:  Scott C Weaver
Journal:  PLoS Negl Trop Dis       Date:  2014-06-26
View more
  19 in total

1.  Genetic Diversity among Four Populations of Aedes aegypti (Diptera: Culicidae) from Honduras as Revealed by Mitochondrial DNA Cytochrome Oxidase I.

Authors:  Denis Escobar; Bryan Ortiz; Oscar Urrutia; Gustavo Fontecha
Journal:  Pathogens       Date:  2022-05-26

2.  Aedes aegypti NeSt1 Protein Enhances Zika Virus Pathogenesis by Activating Neutrophils.

Authors:  Andrew K Hastings; Ryuta Uraki; Hallie Gaitsch; Khushwant Dhaliwal; Sydney Stanley; Hannah Sproch; Eric Williamson; Tyler MacNeil; Alejandro Marin-Lopez; Jesse Hwang; Yuchen Wang; Jonathan R Grover; Erol Fikrig
Journal:  J Virol       Date:  2019-06-14       Impact factor: 5.103

3.  Potential geographic distribution of the tiger mosquito Aedes albopictus (Skuse, 1894) (Diptera: Culicidae) in current and future conditions for Colombia.

Authors:  Emmanuel Echeverry-Cárdenas; Carolina López-Castañeda; Juan D Carvajal-Castro; Oscar Alexander Aguirre-Obando
Journal:  PLoS Negl Trop Dis       Date:  2021-05-11

4.  Forecasting Chikungunya spread in the Americas via data-driven empirical approaches.

Authors:  Luis E Escobar; Huijie Qiao; A Townsend Peterson
Journal:  Parasit Vectors       Date:  2016-02-29       Impact factor: 3.876

Review 5.  Chikungunya Virus Infection: An Update on Joint Manifestations and Management.

Authors:  Maria Krutikov; Jessica Manson
Journal:  Rambam Maimonides Med J       Date:  2016-10-31

6.  Tiger on the prowl: Invasion history and spatio-temporal genetic structure of the Asian tiger mosquito Aedes albopictus (Skuse 1894) in the Indo-Pacific.

Authors:  Andrew J Maynard; Luke Ambrose; Robert D Cooper; Weng K Chow; Joseph B Davis; Mutizwa O Muzari; Andrew F van den Hurk; Sonja Hall-Mendelin; Jeomhee M Hasty; Thomas R Burkot; Michael J Bangs; Lisa J Reimer; Charles Butafa; Neil F Lobo; Din Syafruddin; Yan Naung Maung Maung; Rohani Ahmad; Nigel W Beebe
Journal:  PLoS Negl Trop Dis       Date:  2017-04-14

7.  Short-term suppression of Aedes aegypti using genetic control does not facilitate Aedes albopictus.

Authors:  Kevin Gorman; Josué Young; Lleysa Pineda; Ricardo Márquez; Nestor Sosa; Damaris Bernal; Rolando Torres; Yamilitzel Soto; Renaud Lacroix; Neil Naish; Paul Kaiser; Karla Tepedino; Gwilym Philips; Cecilia Kosmann; Lorenzo Cáceres
Journal:  Pest Manag Sci       Date:  2015-10-16       Impact factor: 4.845

8.  Unusual pattern of chikungunya virus epidemic in the Americas, the Panamanian experience.

Authors:  Jean-Paul Carrera; Yamilka Díaz; Bernardino Denis; Itza Barahona de Mosca; Dennys Rodriguez; Israel Cedeño; Dimelza Arauz; Publio González; Lizbeth Cerezo; Lourdes Moreno; Lourdes García; Lisseth E Sáenz; María Aneth Atencio; Eddy Rojas-Fermin; Fernando Vizcaino; Nicolas Perez; Brechla Moreno; Sandra López-Vergès; Anayansi Valderrama; Blas Armién
Journal:  PLoS Negl Trop Dis       Date:  2017-02-21

Review 9.  Complex Roles of Neutrophils during Arboviral Infections.

Authors:  Abenaya Muralidharan; St Patrick Reid
Journal:  Cells       Date:  2021-05-26       Impact factor: 6.600

10.  Perspectives on modelling the distribution of ticks for large areas: so far so good?

Authors:  Agustín Estrada-Peña; Neil Alexander; G R William Wint
Journal:  Parasit Vectors       Date:  2016-03-31       Impact factor: 3.876

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.