Assessing and correcting neighborhood socioeconomic spatial sampling biases in citizen science mosquito data collection.
Aedes albopictus
Citizen science
Mosquito-borne diseases
Social inequality
Vector control
Vector surveillance
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
28 Sep 2024
28 Sep 2024
Historique:
received:
08
03
2024
accepted:
17
09
2024
medline:
29
9
2024
pubmed:
29
9
2024
entrez:
28
9
2024
Statut:
epublish
Résumé
Climatic, ecological, and socioeconomic factors are facilitating the spread of mosquito-borne diseases, heightening the importance of vector surveillance and control. Citizen science is proving to be an effective tool to track mosquito populations, but methods are needed to detect and account for small scale sampling biases in citizen science surveillance. In this article we combine two types of traditional mosquito surveillance records with data from the Mosquito Alert citizen science system to explore the ways in which the socioeconomic characteristics of urban neighborhoods result in sampling biases in citizen scientists' mosquito reports, while also shaping the spatial distribution of mosquito populations themselves. We use Barcelona, Spain, as an example, and focus on Aedes albopictus, an invasive vector species of concern worldwide. Our results suggest citizen scientists' sampling effort is focused more in Barcelona's lower and middle income census tracts than in its higher income ones, whereas Ae. albopictus populations are concentrated in the city's upper-middle income tracts. High resolution estimates of the spatial distribution of Ae. albopictus risk can be improved by controlling for citizen scientists' sampling effort, making it possible to provide better insights for efficiently targeting control efforts. Our methodology can be replicated in other cities faced with vector mosquitoes to improve public health responses to mosquito-borne diseases, which impose massive burdens on communities worldwide.
Identifiants
pubmed: 39341898
doi: 10.1038/s41598-024-73416-6
pii: 10.1038/s41598-024-73416-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
22462Subventions
Organisme : 'la Caixa' Foundation
ID : HR19-00336
Organisme : 'la Caixa' Foundation
ID : HR19-00336
Organisme : H2020 European Research Council
ID : 853271
Organisme : H2020 European Research Council
ID : 853271
Informations de copyright
© 2024. The Author(s).
Références
Adams, B. & Kapan, D. D. Man bites mosquito: understanding the contribution of human movement to vector-borne disease dynamics. PloS one4(8), e6763 (2009).
doi: 10.1371/journal.pone.0006763
pubmed: 19707544
pmcid: 2727792
Allison, P. D. Discrete-time methods for the analysis of event histories. Sociological methodology13, 61–98 (1982).
doi: 10.2307/270718
Balakrishnan, V. S. WHO launches global initiative for arboviral diseases. The Lancet Microbe3(6), e407 (2022).
doi: 10.1016/S2666-5247(22)00130-6
pubmed: 35659901
pmcid: 9159734
Barbet-Massin, M. et al. Selecting pseudo-absences for species distribution models: How, where and how many?: How to use pseudo-absences in niche modelling?. Methods in Ecology and Evolution3(2), 327–338. https://doi.org/10.1111/j.2041-210X.2011.00172.x (2012).
doi: 10.1111/j.2041-210X.2011.00172.x
Bartumeus, F., Oltra, A. & Palmer, J. R. Citizen science: a gateway for innovation in disease-carrying mosquito management?. Trends in Parasitology34(9), 727–729 (2018).
doi: 10.1016/j.pt.2018.04.010
pubmed: 29793805
Bazin, M. & Williams, C. R. Mosquito traps for urban surveillance: collection efficacy and potential for use by citizen scientists. Journal of Vector Ecology43(1), 98–103 (2018).
doi: 10.1111/jvec.12288
pubmed: 29757507
Bocanegra, C. et al. Imported cases of chikungunya in barcelona in relation to the current american outbreak. Journal of travel medicine23(3), tav033 (2016).
doi: 10.1093/jtm/tav033
pubmed: 26984354
Borrell, C. et al. Veinticinco años de informes de salud en Barcelona: una apuesta por la transparencia y un instrumento para la acción. Revista Española de Salud Pública85(5), 449–458. https://doi.org/10.1590/S1135-57272011000500004 (2011).
doi: 10.1590/S1135-57272011000500004
pubmed: 22212832
Botts, E. A., Erasmus, B. F. & Alexander, G. J. Geographic sampling bias in the south african frog atlas project: implications for conservation planning. Biodiversity and Conservation20, 119–139 (2011).
doi: 10.1007/s10531-010-9950-6
Bürkner, P. C. brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software80(1), 1–28. https://doi.org/10.18637/jss.v080.i01 (2017).
doi: 10.18637/jss.v080.i01
Bürkner, P. C. Advanced Bayesian multilevel modeling with the R package brms. The R Journal10(1), 395–411. https://doi.org/10.32614/RJ-2018-017 (2018).
doi: 10.32614/RJ-2018-017
Carney, R. M. et al. Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes. Insects13(8), 675 (2022).
doi: 10.3390/insects13080675
pubmed: 36005301
pmcid: 9409379
Chakraborty, L. et al. Exploring spatial heterogeneity and environmental injustices in exposure to flood hazards using geographically weighted regression. Environmental Research210, 112982. https://doi.org/10.1016/j.envres.2022.112982 (2022).
doi: 10.1016/j.envres.2022.112982
pubmed: 35218710
Chan, M. & Johansson, M. A. The incubation periods of dengue viruses. PLOS ONE7(11), 1–7. https://doi.org/10.1371/journal.pone.0050972 (2012).
doi: 10.1371/journal.pone.0050972
Collantes, F., Delacour, S., Alarcón-Elbal, P.M., et al. Review of ten-years presence of Aedes albopictus in spain 2004-2014: known distribution and public health concerns. Parasites and Vectors8. https://doi.org/10.1186/s13071-015-1262-y (2015).
Colón-González, F. J. et al. Projecting the risk of mosquito-borne diseases in a warmer and more populated world: a multi-model, multi-scenario intercomparison modelling study. The Lancet Planetary Health5(7), e404–e414 (2021).
doi: 10.1016/S2542-5196(21)00132-7
pubmed: 34245711
pmcid: 8280459
Cunha, H. S. et al. Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control. PLOS ONE16(12), e0258681. https://doi.org/10.1371/journal.pone.0258681 (2021).
doi: 10.1371/journal.pone.0258681
pubmed: 34882711
pmcid: 8659416
van Daalen, K. R. et al. The 2022 Europe report of the Lancet Countdown on health and climate change: towards a climate resilient future. The Lancet Public Health7(11), e942–e965 (2022).
doi: 10.1016/S2468-2667(22)00197-9
pubmed: 36306805
pmcid: 9597587
Dekramanjian, B. et al. Demographic and motivational differences between participants in analog and digital citizen science projects for monitoring mosquitoes. Scientific Reports13(1), 12384 (2023).
doi: 10.1038/s41598-023-38656-y
pubmed: 37524770
pmcid: 10390545
Delatte, H. et al. Blood-feeding behavior of Aedes albopictus, a vector of chikungunya on la réunion. Vector-Borne and Zoonotic Diseases10(3), 249–258 (2010).
doi: 10.1089/vbz.2009.0026
pubmed: 19589060
Dennis, R. & Thomas, C. Bias in butterfly distribution maps: the influence of hot spots and recorder’s home range. Journal of Insect Conservation4, 73–77 (2000).
doi: 10.1023/A:1009690919835
Dickinson, J. L., Zuckerberg, B. & Bonter, D. N. Citizen Science as an Ecological Research Tool: Challenges and Benefits. Annual Review of Ecology, Evolution, and Systematics41(1), 149–172. https://doi.org/10.1146/annurev-ecolsys-102209-144636 (2010).
doi: 10.1146/annurev-ecolsys-102209-144636
Diez Roux, A. V. & Mair, C. Neighborhoods and health: Neighborhoods and health. Annals of the New York Academy of Sciences1186(1), 125–145. https://doi.org/10.1111/j.1749-6632.2009.05333.x (2010).
doi: 10.1111/j.1749-6632.2009.05333.x
pubmed: 20201871
Dunnington, D. ggspatial: Spatial Data Framework for ggplot2. https://CRAN.R-project.org/package=ggspatial , r package version 1.1.9 (2023).
Efron, B. Logistic regression, survival analysis, and the kaplan-meier curve. Journal of the American statistical Association83(402), 414–425 (1988).
doi: 10.1080/01621459.1988.10478612
Egizi, A., Fefferman, N. H. & Fonseca, D. M. Evidence that implicit assumptions of ‘no evolution’ of disease vectors in changing environments can be violated on a rapid timescale. Philosophical Transactions of the Royal Society B: Biological Sciences370(1665), 20140136. https://doi.org/10.1098/rstb.2014.0136 (2015).
doi: 10.1098/rstb.2014.0136
Elith, J. & Leathwick, J. R. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics40(1), 677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159 (2009).
doi: 10.1146/annurev.ecolsys.110308.120159
Eritja, R. et al. Direct evidence of adult Aedes albopictus dispersal by car. Scientific Reports7(1), 14399 (2017).
doi: 10.1038/s41598-017-12652-5
pubmed: 29070818
pmcid: 5656642
Eritja, R. et al. At the tip of an iceberg: citizen science and active surveillance collaborating to broaden the known distribution of Aedes japonicus in spain. Parasites & Vectors14(1), 1–12 (2021).
doi: 10.1186/s13071-021-04874-4
Ferraguti, M. et al. Spatial distribution and temporal dynamics of invasive and native mosquitoes in a large mediterranean city. Science of the Total Environment896, 165322 (2023).
doi: 10.1016/j.scitotenv.2023.165322
pubmed: 37414178
Gabry, J. & Češnovar, R. cmdstanr: R Interface to ’CmdStan’. URL: Https://mc-stan.org/cmdstanr/, https://discourse.mc-stan.org (2022).
Geldmann, J. et al. What determines spatial bias in citizen science? Exploring four recording schemes with different proficiency requirements. Diversity and Distributions22(11), 1139–1149. https://doi.org/10.1111/ddi.12477 (2016).
doi: 10.1111/ddi.12477
Galster, George & Sharkey, Patrick. Spatial Foundations of Inequality: A Conceptual Model and Empirical Overview. RSF: The Russell Sage Foundation Journal of the Social Sciences3(2), 1. https://doi.org/10.7758/rsf.2017.3.2.01 (2017).
doi: 10.7758/rsf.2017.3.2.01
Gossner, C. M., Ducheyne, E. & Schaffner, F. Increased risk for autochthonous vector-borne infections transmitted by Aedes albopictus in continental Europe. Eurosurveillance23(24), 1800268. https://doi.org/10.2807/1560-7917.ES.2018.23.24.1800268 (2018). https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2018.23.24.1800268 .
Gutiérrez-López, R. et al. Vector Competence of Aedes Caspius and Ae. Albopictus Mosquitoes for Zika Virus, Spain. Emerging Infectious Diseases25(2), 346–348. https://doi.org/10.3201/eid2502.171123 (2019).
doi: 10.3201/eid2502.171123
pubmed: 30666939
pmcid: 6346449
Haklay, M. Citizen science and volunteered geographic information: Overview and typology of participation. Crowdsourcing geographic knowledge: Volunteered geographic information (VGI) in theory and practice pp 105–122 (2012).
Haklay, M.M., Dörler, D., Heigl, F., et al. What is citizen science? the challenges of definition. The science of citizen science13 (2021).
Halasa, Y. A. et al. Quantifying the impact of mosquitoes on quality of life and enjoyment of yard and porch activities in new jersey. PLOS ONE9(3), 1–9. https://doi.org/10.1371/journal.pone.0089221 (2014).
doi: 10.1371/journal.pone.0089221
Hall, D. B. Zero-inflated poisson and binomial regression with random effects: a case study. Biometrics56(4), 1030–1039 (2000).
doi: 10.1111/j.0006-341X.2000.01030.x
pubmed: 11129458
Harvey, D. The right to the city. International Journal of Urban and Regional Research27(4), 939–941. https://doi.org/10.1111/j.0309-1317.2003.00492.x (2003). https://onlinelibrary.wiley.com/doi/abs/10.1111/j.0309-1317.2003.00492.x , _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.0309-1317.2003.00492.x .
Heigl, F. et al. Toward an international definition of citizen science. Proceedings of the National Academy of Sciences116(17), 8089–8092 (2019).
doi: 10.1073/pnas.1903393116
Hobbs, S. J. & White, P. C. L. Motivations and barriers in relation to community participation in biodiversity recording. Journal for Nature Conservation20(6), 364–373. https://doi.org/10.1016/j.jnc.2012.08.002 (2012).
doi: 10.1016/j.jnc.2012.08.002
INE. Atlas de Distributión de Renta de los Hogares (ADRH). Metodología. Tech. rep., Instituto Nacional de Estadística, https://www.ine.es/metodologia/metodologia_adrh.pdf (2022a).
INE. Cartografía digitalizada de secciones censales. https://ine.es/ss/Satellite?c=Page&cid=1259952026632&p=1259952026632&pagename=ProductosYServicios%2FPYSLayout (2022b).
Institut Cartogràfic i Geològic de Catalunya. Vegetable cover of the city of Barcelona, based on the NVDI index, seen from the sky. https://opendata-ajuntament.barcelona.cat/data/en/dataset/cobertura-vegetal-ndvi/resource/0003c7ee-9b66-43f6-b9cc-ff9314c208e4 (2019).
Johnston, A. et al. Estimating species distributions from spatially biased citizen science data. Ecological Modelling422, 108927. https://doi.org/10.1016/j.ecolmodel.2019.108927 (2020).
doi: 10.1016/j.ecolmodel.2019.108927
Južnič-Zonta, Ž., Sanpera-Calbet, I., Eritja, R., et al. Mosquito alert: leveraging citizen science to create a gbif mosquito occurrence dataset. Gigabyte 2022 (2022).
Kröckel, U. et al. New tools for surveillance of adult yellow fever mosquitoes: comparison of trap catches with human landing rates in an urban environment. Journal of the American Mosquito Control Association22(2), 229–238 (2006).
doi: 10.2987/8756-971X(2006)22[229:NTFSOA]2.0.CO;2
pubmed: 17019768
LaDeau, S. L. et al. The ecological foundations of transmission potential and vector-borne disease in urban landscapes. Functional Ecology29(7), 889–901. https://doi.org/10.1111/1365-2435.12487 (2015).
doi: 10.1111/1365-2435.12487
pubmed: 26549921
pmcid: 4631442
Lambert, D. Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics34(1), 1–14 (1992).
doi: 10.2307/1269547
Li, Y. et al. Comparative evaluation of the efficiency of the bg-sentinel trap, cdc light trap and mosquito-oviposition trap for the surveillance of vector mosquitoes. Parasites & vectors9(1), 1–8 (2016).
doi: 10.1186/s13071-016-1724-x
Lillepold, K., Rocklöv, J., Liu-Helmersson, J., et al. More arboviral disease outbreaks in continental Europe due to the warming climate? Journal of Travel Medicine26(5), taz017. https://doi.org/10.1093/jtm/taz017 (2019). https://doi.org/10.1093/jtm/taz017 , https://academic.oup.com/jtm/article-pdf/26/5/taz017/28926801/taz017.pdf .
Londoño-Cañola, C., Serral, G., Díez, J., et al. Retail food environment around schools in barcelona by neighborhood socioeconomic status: Implications for local food policy. International Journal of Environmental Research and Public Health20(1) (2023). https://doi.org/10.3390/ijerph20010649 . https://www.mdpi.com/1660-4601/20/1/649 .
Lucati, F. et al. Multiple invasions, wolbachia and human-aided transport drive the genetic variability of Aedes albopictus in the iberian peninsula. Scientific Reports12(1), 20682 (2022).
doi: 10.1038/s41598-022-24963-3
pubmed: 36450768
pmcid: 9712423
Lührsen, D. S. et al. Adult Aedes albopictus in winter: implications for mosquito surveillance in southern Europe. The Lancet Planetary Health7(9), e729–e731 (2023).
doi: 10.1016/S2542-5196(23)00170-5
pubmed: 37673540
Marí-Dell’Olmo, M. et al. Climate change and health in urban areas with a mediterranean climate: a conceptual framework with a social and climate justice approach. International Journal of Environmental Research and Public Health19(19), 12764 (2022).
doi: 10.3390/ijerph191912764
pubmed: 36232063
pmcid: 9566374
Marini, F. et al. Estimating spatio-temporal dynamics of Aedes albopictus dispersal to guide control interventions in case of exotic arboviruses in temperate regions. Scientific Reports9(1), 10281 (2019).
doi: 10.1038/s41598-019-46466-4
pubmed: 31311945
pmcid: 6635400
Medley, K. A., Westby, K. M. & Jenkins, D. G. Rapid local adaptation to northern winters in the invasive Asian tiger mosquito Aedes albopictus: A moving target. Journal of Applied Ecology56(11), 2518–2527. https://doi.org/10.1111/1365-2664.13480 (2019).
doi: 10.1111/1365-2664.13480
Millet, J. P. et al. Imported zika virus in a European city: how to prevent local transmission?. Frontiers in microbiology8, 1319 (2017).
doi: 10.3389/fmicb.2017.01319
pubmed: 28769893
pmcid: 5513902
Ministerio de Sanidad. Plan Nacional de Prevención, Vigilancia y Control de las enfermedades transmitidas por vectores. Tech. rep., Ministerio de Sanidad, https://www.sanidad.gob.es/profesionales/saludPublica/ccayes/activPreparacionRespuesta/doc/PLAN_DE_VECTORES.pdf (2023).
Montalvo, T., Valsecchi, A., Peracho, V., et al. Vigilancia y control de mosquitos en barcelona: Informe 2021. Tech. rep., Agència de Salut Pública de Barcelona (2021).
Mordecai, E. A. et al. Climate change could shift disease burden from malaria to arboviruses in africa. The Lancet Planetary Health4(9), e416–e423 (2020).
doi: 10.1016/S2542-5196(20)30178-9
pubmed: 32918887
pmcid: 7490804
Morris, M. et al. Bayesian hierarchical spatial models: Implementing the Besag York Mollié model in stan. Spatial and Spatio-temporal Epidemiology31, 100301. https://doi.org/10.1016/j.sste.2019.100301 (2019).
doi: 10.1016/j.sste.2019.100301
pubmed: 31677766
pmcid: 6830524
Alert, Mosquito. Sampling effort data.[SPACE] https://doi.org/10.5281/zenodo.10674718 (2024).
Murphy, A. K. et al. Climate variability and Aedes vector indices in the southern Philippines: An empirical analysis. PLOS Neglected Tropical Diseases16(6), e0010478. https://doi.org/10.1371/journal.pntd.0010478 (2022).
doi: 10.1371/journal.pntd.0010478
pubmed: 35700164
pmcid: 9197058
Nov, O., Arazy, O. & Anderson, D. Dusting for science: Motivation and participation of digital citizen science volunteers. In iConference ’11., New York, NY., https://doi.org/10.1145/1940761.1940771 (2011).
Oltra, A., Palmer, J.R. & Bartumeus, F. Atrapaeltigre. com: enlisting citizen-scientists in the war on tiger mosquitoes. In European Handbook of Crowdsourced Geographic Information. Ubiquity Press (2016).
Padilla-Pozo, A. & Palmer, J.R. Open Code for “Assessing and Correcting Neighborhood Socioeconomic Spatial Sampling Biases in Citizen Science Mosquito Data Collection”. https://doi.org/10.5281/zenodo.10796342 (2024).
Padilla-Pozo, A., Bartumeus, F., Montalvo, T., et al. Untangling neighborhoods effects in citizen science vector-mosquito surveillance: Mosquito Alert Barcelona Reports Data - All Adult Mosquitoes and Mosquito Bites 2014-23. https://doi.org/10.5281/zenodo.10684357 (2024).
Palmer, J. R. B. et al. Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes. Nature Communications8(1), 916. https://doi.org/10.1038/s41467-017-00914-9 (2017).
doi: 10.1038/s41467-017-00914-9
pubmed: 29066710
pmcid: 5655677
Pandya, R. E. A framework for engaging diverse communities in citizen science in the US. Frontiers in Ecology and the Environment10(6), 314–317. https://doi.org/10.1890/120007 (2012).
doi: 10.1890/120007
R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (2023).
Rocklöv, J. & Dubrow, R. Climate change: an enduring challenge for vector-borne disease prevention and control. Nature immunology21(5), 479–483 (2020).
doi: 10.1038/s41590-020-0648-y
pubmed: 32313242
pmcid: 7223823
Rocklöv, J. et al. Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond. The Lancet Regional Health-Europe32, 100701 (2023).
doi: 10.1016/j.lanepe.2023.100701
pubmed: 37583927
pmcid: 10424206
Rubies, A.E. & Alert, M. Mosquitoalert/data: v1.051.2024. https://doi.org/10.5281/zenodo.10681774 (2024).
Scavo, N. A. et al. Lower socioeconomic status neighborhoods in Puerto Rico have more diverse mosquito communities and higher Aedes Aegypti abundance. Journal of Urban Ecology7(1), juab009. https://doi.org/10.1093/jue/juab009 (2021).
doi: 10.1093/jue/juab009
Schaffner, F., Medlock, J. M. & Bortel, W. V. Public health significance of invasive mosquitoes in Europe. Clinical Microbiology and Infection19(8), 685–692. https://doi.org/10.1111/1469-0691.12189 (2013). https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61413-0/fulltext , publisher: Elsevier.
Semenza, J. C., Rocklöv, J. & Ebi, K. L. Climate change and cascading risks from infectious disease. Infectious Diseases and Therapy11(4), 1371–1390 (2022).
doi: 10.1007/s40121-022-00647-3
pubmed: 35585385
pmcid: 9334478
Tajudeen, Y. A. et al. Tackling the global health threat of arboviruses: An appraisal of the three holistic approaches to health. Health Promotion Perspectives11(4), 371–381. https://doi.org/10.34172/hpp.2021.48 (2021).
doi: 10.34172/hpp.2021.48
pubmed: 35079581
pmcid: 8767080
Talbot, B. et al. Determinants of Aedes mosquito density as an indicator of arbovirus transmission risk in three sites affected by co-circulation of globally spreading arboviruses in Colombia. Ecuador and Argentina. Parasites & Vectors14(1), 482. https://doi.org/10.1186/s13071-021-04984-z (2021).
doi: 10.1186/s13071-021-04984-z
Tang, B., Clark, J. S. & Gelfand, A. E. Modeling spatially biased citizen science effort through the eBird database. Environmental and Ecological Statistics28(3), 609–630. https://doi.org/10.1007/s10651-021-00508-1 (2021).
doi: 10.1007/s10651-021-00508-1
Tennekes, M. tmap: Thematic maps in R. Journal of Statistical Software84(6), 1–39. https://doi.org/10.18637/jss.v084.i06 (2018).
doi: 10.18637/jss.v084.i06
Tesla, B. et al. Temperature drives Zika virus transmission: Evidence from empirical and mathematical models. Proceedings Biological Sciences285(1884), 20180795. https://doi.org/10.1098/rspb.2018.0795 (2018).
doi: 10.1098/rspb.2018.0795
pubmed: 30111605
pmcid: 6111177
Vehtari, A., Gelman, A. & Gabry, J. Practical bayesian model evaluation using leave-one-out cross-validation and waic. Statistics and computing27, 1413–1432 (2017).
doi: 10.1007/s11222-016-9696-4
Venter, Z. S. et al. Environmental justice in a very green city: Spatial inequality in exposure to urban nature, air pollution and heat in Oslo. Norway. Science of The Total Environment858, 160193. https://doi.org/10.1016/j.scitotenv.2022.160193 (2023).
doi: 10.1016/j.scitotenv.2022.160193
pubmed: 36384175
Wang, Y. et al. The effect of urbanization and climate change on the mosquito population in the pearl river delta region of china. International journal of biometeorology64, 501–512 (2020).
doi: 10.1007/s00484-019-01837-4
pubmed: 31811391
Whiteman, A. et al. Aedes Mosquito Infestation in Socioeconomically Contrasting Neighborhoods of Panama City. EcoHealth16(2), 210–221. https://doi.org/10.1007/s10393-019-01417-3 (2019).
doi: 10.1007/s10393-019-01417-3
pubmed: 31114946
Whiteman, A. et al. Do socioeconomic factors drive aedes mosquito vectors and their arboviral diseases? A systematic review of dengue, chikungunya, yellow fever, and Zika Virus. One Health11, 100188. https://doi.org/10.1016/j.onehlt.2020.100188 (2020) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772681/ .
doi: 10.1016/j.onehlt.2020.100188
pubmed: 33392378
pmcid: 7772681
Whiteman, A. et al. Do socioeconomic factors drive Aedes mosquito vectors and their arboviral diseases? A systematic review of dengue, chikungunya, yellow fever, and Zika Virus. One Health11, 100188. https://doi.org/10.1016/j.onehlt.2020.100188 (2020).
doi: 10.1016/j.onehlt.2020.100188
pubmed: 33392378
pmcid: 7772681
WHO. A global brief on vector-borne diseases. Tech. rep., World Health Organization, DOI: WHO/DCO/WHD/2014.1. http://apps.who.int/iris/bitstream/10665/111008/1/WHO_DCO_WHD_2014.1_eng.pdf (2014).
WHO. Global Vector Control response 2017 -2030: An integrated approach for the control of vector borne diseases. http://www.who.int/vector-control/burden_vector-borne_diseases.pdf (2017).
WHO. Launch of the WHO Global Arbovirus Initiative. Tech. rep., WHO (2022).
Wick, H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, https://ggplot2.tidyverse.org (2016).
Wodtke, G. T. et al. Concentrated poverty, ambient air pollution, and child cognitive development. Science Advances8(48), eadd0285. https://doi.org/10.1126/sciadv.add0285 (2022).
doi: 10.1126/sciadv.add0285
pubmed: 36449613
pmcid: 9710878
Zwijnenburg, J., Bournot, S., Grahn, D., et al. Distribution of household income, consumption and saving in line with national accounts: Methodology and results from the 2020 collection round. Tech. rep., OECD (2021).