Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

doi:10.1038/s41564-019-0376-y

. 2019 May;4(5):854-863.

doi: 10.1038/s41564-019-0376-y. Epub 2019 Mar 4.

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Moritz U G Kraemer^#^{1

2

3}, Robert C Reiner Jr^#⁴, Oliver J Brady^#^{5

6}, Jane P Messina^#^{7

8}, Marius Gilbert^#^{9

10}, David M Pigott⁴, Dingdong Yi¹¹, Kimberly Johnson⁴, Lucas Earl⁴, Laurie B Marczak⁴, Shreya Shirude⁴, Nicole Davis Weaver⁴, Donal Bisanzio^{12

13}, T Alex Perkins¹⁴, Shengjie Lai^{15

16

17}, Xin Lu^{18

19

20}, Peter Jones²¹, Giovanini E Coelho²², Roberta G Carvalho²³, Wim Van Bortel^{24

25}, Cedric Marsboom²⁶, Guy Hendrickx²⁶, Francis Schaffner²⁷, Chester G Moore²⁸, Heinrich H Nax²⁹, Linus Bengtsson^{17

30}, Erik Wetter^{17

31}, Andrew J Tatem^{16

17}, John S Brownstein^{32

33}, David L Smith⁴, Louis Lambrechts³⁴, Simon Cauchemez³⁵, Catherine Linard^{9

36}, Nuno R Faria³⁷, Oliver G Pybus³⁷, Thomas W Scott³⁸, Qiyong Liu^{39

40

41

42}, Hongjie Yu¹⁵, G R William Wint^{37

43}, Simon I Hay^#⁴⁴, Nick Golding^#⁴⁵

Affiliations

¹ Department of Zoology, University of Oxford, Oxford, UK. moritz.kraemer@zoo.ox.ac.uk.
² Harvard Medical School, Harvard University, Boston, MA, USA. moritz.kraemer@zoo.ox.ac.uk.
³ Boston Children's Hospital, Boston, MA, USA. moritz.kraemer@zoo.ox.ac.uk.
⁴ Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
⁵ Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
⁶ Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
⁷ School of Geography and the Environment, University of Oxford, Oxford, UK.
⁸ Oxford School of Global and Area Studies, University of Oxford, Oxford, UK.
⁹ Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium.
¹⁰ Fonds National de la Recherche Scientifique, Brussels, Belgium.
¹¹ Department of Statistics, Harvard University, Cambridge, MA, USA.
¹² RTI International, Washington, DC, USA.
¹³ Epidemiology and Public Health Division, School of Medicine, University of Nottingham, Nottingham, UK.
¹⁴ Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.
¹⁵ School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
¹⁶ Department of Geography and Environment, University of Southampton, Southampton, UK.
¹⁷ Flowminder Foundation, Stockholm, Sweden.
¹⁸ School of Business, Central South University, Changsha, China.
¹⁹ College of Systems Engineering, National University of Defense Technology, Changsha, China.
²⁰ School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China.
²¹ Waen Associates Ltd, Y Waen, Islaw'r Dref, Dolgellau, Gwynedd, UK.
²² Pan American Health Organization (PAHO), Washington, DC, USA.
²³ National Dengue Control Program, Ministry of Health, Brasilia, Brazil.
²⁴ European Centre for Disease Prevention and Control, Stockholm, Sweden.
²⁵ Institute of Tropical Medicine, Antwerp, Belgium.
²⁶ Avia-GIS, Zoersel, Belgium.
²⁷ Francis Schaffner Consultancy, Riehen, Switzerland.
²⁸ Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA.
²⁹ Computational Social Science, ETH Zurich, Zurich, Switzerland.
³⁰ Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
³¹ Stockholm School of Economics, Stockholm, Sweden.
³² Harvard Medical School, Harvard University, Boston, MA, USA.
³³ Boston Children's Hospital, Boston, MA, USA.
³⁴ Insect-Virus Interactions Unit, Institut Pasteur, CNRS, UMR2000, Paris, France.
³⁵ Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, CNRS, UMR2000, Paris, France.
³⁶ Department of Geography, Universite de Namur, Namur, Belgium.
³⁷ Department of Zoology, University of Oxford, Oxford, UK.
³⁸ Department of Entomology and Nematology, University of California, Davis, Davis, CA, USA.
³⁹ State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, China.
⁴⁰ Shandong University Climate Change and Health Center, School of Public Health, Shandong University, Jinan, Shandong, China.
⁴¹ WHO Collaborating Centre for Vector Surveillance and Management, Beijing, China.
⁴² Chongqing Centre for Disease Control and Prevention, Chongqing, China.
⁴³ Environmental Research Group Oxford (ERGO), Department of Zoology, Oxford University, Oxford, UK.
⁴⁴ Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. sihay@uw.edu.
⁴⁵ School of BioSciences, University of Melbourne, Parkville, Victoria, Australia. nick.golding.research@gmail.com.

^# Contributed equally.

PMID: 30833735
PMCID: PMC6522366
DOI: 10.1038/s41564-019-0376-y

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Moritz U G Kraemer et al. Nat Microbiol. 2019 May.

. 2019 May;4(5):854-863.

doi: 10.1038/s41564-019-0376-y. Epub 2019 Mar 4.

Authors

Affiliations

¹ Department of Zoology, University of Oxford, Oxford, UK. moritz.kraemer@zoo.ox.ac.uk.
² Harvard Medical School, Harvard University, Boston, MA, USA. moritz.kraemer@zoo.ox.ac.uk.
³ Boston Children's Hospital, Boston, MA, USA. moritz.kraemer@zoo.ox.ac.uk.
⁴ Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
⁵ Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
⁶ Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
⁷ School of Geography and the Environment, University of Oxford, Oxford, UK.
⁸ Oxford School of Global and Area Studies, University of Oxford, Oxford, UK.
⁹ Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium.
¹⁰ Fonds National de la Recherche Scientifique, Brussels, Belgium.
¹¹ Department of Statistics, Harvard University, Cambridge, MA, USA.
¹² RTI International, Washington, DC, USA.
¹³ Epidemiology and Public Health Division, School of Medicine, University of Nottingham, Nottingham, UK.
¹⁴ Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.
¹⁵ School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
¹⁶ Department of Geography and Environment, University of Southampton, Southampton, UK.
¹⁷ Flowminder Foundation, Stockholm, Sweden.
¹⁸ School of Business, Central South University, Changsha, China.
¹⁹ College of Systems Engineering, National University of Defense Technology, Changsha, China.
²⁰ School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China.
²¹ Waen Associates Ltd, Y Waen, Islaw'r Dref, Dolgellau, Gwynedd, UK.
²² Pan American Health Organization (PAHO), Washington, DC, USA.
²³ National Dengue Control Program, Ministry of Health, Brasilia, Brazil.
²⁴ European Centre for Disease Prevention and Control, Stockholm, Sweden.
²⁵ Institute of Tropical Medicine, Antwerp, Belgium.
²⁶ Avia-GIS, Zoersel, Belgium.
²⁷ Francis Schaffner Consultancy, Riehen, Switzerland.
²⁸ Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA.
²⁹ Computational Social Science, ETH Zurich, Zurich, Switzerland.
³⁰ Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
³¹ Stockholm School of Economics, Stockholm, Sweden.
³² Harvard Medical School, Harvard University, Boston, MA, USA.
³³ Boston Children's Hospital, Boston, MA, USA.
³⁴ Insect-Virus Interactions Unit, Institut Pasteur, CNRS, UMR2000, Paris, France.
³⁵ Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, CNRS, UMR2000, Paris, France.
³⁶ Department of Geography, Universite de Namur, Namur, Belgium.
³⁷ Department of Zoology, University of Oxford, Oxford, UK.
³⁸ Department of Entomology and Nematology, University of California, Davis, Davis, CA, USA.
³⁹ State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, China.
⁴⁰ Shandong University Climate Change and Health Center, School of Public Health, Shandong University, Jinan, Shandong, China.
⁴¹ WHO Collaborating Centre for Vector Surveillance and Management, Beijing, China.
⁴² Chongqing Centre for Disease Control and Prevention, Chongqing, China.
⁴³ Environmental Research Group Oxford (ERGO), Department of Zoology, Oxford University, Oxford, UK.
⁴⁴ Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. sihay@uw.edu.
⁴⁵ School of BioSciences, University of Melbourne, Parkville, Victoria, Australia. nick.golding.research@gmail.com.

^# Contributed equally.

PMID: 30833735
PMCID: PMC6522366
DOI: 10.1038/s41564-019-0376-y

Erratum in

Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.
Kraemer MUG, Reiner RC Jr, Brady OJ, Messina JP, Gilbert M, Pigott DM, Yi D, Johnson K, Earl L, Marczak LB, Shirude S, Weaver ND, Bisanzio D, Perkins TA, Lai S, Lu X, Jones P, Coelho GE, Carvalho RG, Van Bortel W, Marsboom C, Hendrickx G, Schaffner F, Moore CG, Nax HH, Bengtsson L, Wetter E, Tatem AJ, Brownstein JS, Smith DL, Lambrechts L, Cauchemez S, Linard C, Faria NR, Pybus OG, Scott TW, Liu Q, Yu H, Wint GRW, Hay SI, Golding N. Kraemer MUG, et al. Nat Microbiol. 2019 May;4(5):900. doi: 10.1038/s41564-019-0429-2. Nat Microbiol. 2019. PMID: 30903094 Free PMC article.
Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.
Kraemer MUG, Reiner RC Jr, Brady OJ, Messina JP, Gilbert M, Pigott DM, Yi D, Johnson K, Earl L, Marczak LB, Shirude S, Weaver ND, Bisanzio D, Perkins TA, Lai S, Lu X, Jones P, Coelho GE, Carvalho RG, Van Bortel W, Marsboom C, Hendrickx G, Schaffner F, Moore CG, Nax HH, Bengtsson L, Wetter E, Tatem AJ, Brownstein JS, Smith DL, Lambrechts L, Cauchemez S, Linard C, Faria NR, Pybus OG, Scott TW, Liu Q, Yu H, Wint GRW, Hay SI, Golding N. Kraemer MUG, et al. Nat Microbiol. 2019 May;4(5):901. doi: 10.1038/s41564-019-0440-7. Nat Microbiol. 2019. PMID: 30962571 Free PMC article.

Abstract

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

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Conflict of interest statement

The authors declare no competing interests.

Figures

**Fig. 1. Reconstruction of *Ae. albopictus* and *Ae. aegypti* spread.**
a–c, Spread of *Ae. albopictus* (a) and *Ae.* *aegypti* (b) in the United States, and spread of *Ae. albopictus* in Europe (c). Estimates of speed of spread in km per year are based on thin spline regression on mosquito observations since their earliest detection in each continent. Red indicates fast dispersal whereas yellow and white indicate slower spread velocity measured in km per year (see legend below b). Areas highlighted in grey have no reported mosquito presence. d–f, Summaries of the speed of dispersal of *Ae. albopictus* (d) and *Ae. aegypti* (e) spread in the United States and of *Ae. albopictus* spread in Europe (f) starting from their date of first detection until 2017. The red line indicates the average velocity per year across all districts using the thin spline regression model.

**Fig. 2. Predicted future spread of *Ae. aegypti* and *Ae. albopictus* in the United States.**
Spread was estimated using human-mobility metrics and ecological determinants fitted to past occurrence data. a, Forecasted change in the distribution of *Ae. aegypti* between 2020 and 2050 using the medium climatic scenario RCP 6.0 at the US county-level ranging from −0.25 (blue) to 0.25 (red). Red indicates expansion and dark blue contraction of the *Aedes* range distribution between 2020 and 2050. b, The predicted habitat suitability for the presence of *Ae. aegypti* in 2050. Pixels with no predicted suitability are in grey. c,d, The corresponding results of a and b for *Ae. albopictus*.

**Fig. 3. Predicted future spread of *Ae. albopictus* in Europe.**
a, The expansion (red) and contraction (blue) of *Ae. albopictus* between 2020 and 2050 under the medium climate scenario RCP 6.0, with emissions peaking in 2080. b, The predicted distribution of *Ae. albopictus* and predicted habitat suitability for the presence of *Ae. albopictus* in 2050. Pixels with no predicted suitability are in grey.

Fig. 4. Predicted global geographical distribution of *Ae. aegypti* and *Ae. albopictus.*
a–d, The distribution of *Ae. aegypti* (a) and *Ae. albopictus* (b) in 2050 under the medium climatic scenario RCP 6.0 and uncertainty for *Ae. aegypti* (c) and *Ae. albopictus* (d). Predicted habitat suitability of Ae. *aegypti* quantile cut-off points were 0.24, 0.66, 0.88. Relative uncertainty was computed as the ratio of the 95% uncertainty intervals and predicted *Ae. aegypti* suitability for each pixel. Cut-off points for uncertainty were 0.08, 0.18, 0.31. The lowest quantile of predicted suitability is shown in white and the highest in dark pink. The lowest quantile for uncertainty is white and the highest is blue. The colours overlap such that areas in purple have both high predicted suitability of *Ae. aegypti* and high relative uncertainty. Pixels with high predicted suitability are shown in red whereas pixels with no predicted suitability are in grey. Predicted habitat suitability of Ae. *albopictus* quantile cut-off points were 0.13, 0.41, 0.70. Cut-off points for uncertainty for *Ae. albopictus* were 0.16, 0.36, 0.53. e,f, The global population predicted to live in areas suitable for *Ae. aegypti* (e) and *Ae. albopictus* (f) under the conservative (RCP 4.5), medium (RCP 6.0) and worst-case scenario (RCP 8.5) using the binary cut-off values of suitability of 0.46 and 0.51 for both species, respectively.

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References

1. Nsoesie EO, et al. Global distribution and environmental suitability for chikungunya virus, 1952 to 2015. Eurosurveillance. 2015;21:30234. doi: 10.2807/1560-7917.ES.2016.21.20.30234. - DOI - PMC - PubMed
1. Messina JP, et al. Mapping global environmental suitability for Zika virus. eLife. 2016;5:e15272. doi: 10.7554/eLife.15272. - DOI - PMC - PubMed
1. Bhatt S, et al. The global distribution and burden of dengue. Nature. 2013;496:504–507. doi: 10.1038/nature12060. - DOI - PMC - PubMed
1. Kraemer MUG, et al. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. eLife. 2015;4:e08347. doi: 10.7554/eLife.08347. - DOI - PMC - PubMed
1. Lessler J, et al. Assessing the global threat from Zika virus. Science. 2016;353:aaf8160. doi: 10.1126/science.aaf8160. - DOI - PMC - PubMed

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[1] Nsoesie EO, et al. Global distribution and environmental suitability for chikungunya virus, 1952 to 2015. Eurosurveillance. 2015;21:30234. doi: 10.2807/1560-7917.ES.2016.21.20.30234. - DOI - PMC - PubMed

[2] Nsoesie EO, et al. Global distribution and environmental suitability for chikungunya virus, 1952 to 2015. Eurosurveillance. 2015;21:30234. doi: 10.2807/1560-7917.ES.2016.21.20.30234. - DOI - PMC - PubMed

[3] Messina JP, et al. Mapping global environmental suitability for Zika virus. eLife. 2016;5:e15272. doi: 10.7554/eLife.15272. - DOI - PMC - PubMed

[4] Messina JP, et al. Mapping global environmental suitability for Zika virus. eLife. 2016;5:e15272. doi: 10.7554/eLife.15272. - DOI - PMC - PubMed

[5] Bhatt S, et al. The global distribution and burden of dengue. Nature. 2013;496:504–507. doi: 10.1038/nature12060. - DOI - PMC - PubMed

[6] Bhatt S, et al. The global distribution and burden of dengue. Nature. 2013;496:504–507. doi: 10.1038/nature12060. - DOI - PMC - PubMed

[7] Kraemer MUG, et al. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. eLife. 2015;4:e08347. doi: 10.7554/eLife.08347. - DOI - PMC - PubMed

[8] Kraemer MUG, et al. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. eLife. 2015;4:e08347. doi: 10.7554/eLife.08347. - DOI - PMC - PubMed

[9] Lessler J, et al. Assessing the global threat from Zika virus. Science. 2016;353:aaf8160. doi: 10.1126/science.aaf8160. - DOI - PMC - PubMed

[10] Lessler J, et al. Assessing the global threat from Zika virus. Science. 2016;353:aaf8160. doi: 10.1126/science.aaf8160. - DOI - PMC - PubMed

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Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Affiliations

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

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Erratum in

Abstract

Conflict of interest statement

Figures

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Erratum in

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Conflict of interest statement

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