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Gutierrez B, da Silva Candido D, Bajaj S, Rodriguez Maldonado AP, Ayala FG, Rodriguez MDLLT, Rodriguez AA, Arámbula CW, González ER, Martínez IL, Díaz-Quiñónez JA, Pichardo MV, Hill SC, Thézé J, Faria NR, Pybus OG, Preciado-Llanes L, Reyes-Sandoval A, Kraemer MUG, Escalera-Zamudio M. Convergent trends and spatiotemporal patterns of Aedes-borne arboviruses in Mexico and Central America. PLoS Negl Trop Dis 2023; 17:e0011169. [PMID: 37672514 PMCID: PMC10506721 DOI: 10.1371/journal.pntd.0011169] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 09/18/2023] [Accepted: 08/21/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Aedes-borne arboviruses cause both seasonal epidemics and emerging outbreaks with a significant impact on global health. These viruses share mosquito vector species, often infecting the same host population within overlapping geographic regions. Thus, comparative analyses of the virus evolutionary and epidemiological dynamics across spatial and temporal scales could reveal convergent trends. METHODOLOGY/PRINCIPAL FINDINGS Focusing on Mexico as a case study, we generated novel chikungunya and dengue (CHIKV, DENV-1 and DENV-2) virus genomes from an epidemiological surveillance-derived historical sample collection, and analysed them together with longitudinally-collected genome and epidemiological data from the Americas. Aedes-borne arboviruses endemically circulating within the country were found to be introduced multiple times from lineages predominantly sampled from the Caribbean and Central America. For CHIKV, at least thirteen introductions were inferred over a year, with six of these leading to persistent transmission chains. For both DENV-1 and DENV-2, at least seven introductions were inferred over a decade. CONCLUSIONS/SIGNIFICANCE Our results suggest that CHIKV, DENV-1 and DENV-2 in Mexico share evolutionary and epidemiological trajectories. The southwest region of the country was determined to be the most likely location for viral introductions from abroad, with a subsequent spread into the Pacific coast towards the north of Mexico. Virus diffusion patterns observed across the country are likely driven by multiple factors, including mobility linked to human migration from Central towards North America. Considering Mexico's geographic positioning displaying a high human mobility across borders, our results prompt the need to better understand the role of anthropogenic factors in the transmission dynamics of Aedes-borne arboviruses, particularly linked to land-based human migration.
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Affiliation(s)
- Bernardo Gutierrez
- Department of Biology, University of Oxford, Oxford, United Kingdom
- Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Darlan da Silva Candido
- Department of Biology, University of Oxford, Oxford, United Kingdom
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Sumali Bajaj
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | | | - Fabiola Garces Ayala
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - María de la Luz Torre Rodriguez
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - Adnan Araiza Rodriguez
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - Claudia Wong Arámbula
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - Ernesto Ramírez González
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - Irma López Martínez
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - José Alberto Díaz-Quiñónez
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
- Instituto de Ciencias de la Salud, Universidad Autónoma del Estado de Hidalgo, Pachuca de Soto, Mexico
| | - Mauricio Vázquez Pichardo
- Instituto de Diagnóstico y Referencia Epidemiológicos (InDRE) "Dr. Manuel Martínez Báez", Secretaría de Salud, Mexico City, México
| | - Sarah C Hill
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, United Kingdom
| | - Julien Thézé
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Genès-Champanelle, France
| | - Nuno R Faria
- Department of Biology, University of Oxford, Oxford, United Kingdom
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, United Kingdom
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, United Kingdom
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, United Kingdom
| | - Lorena Preciado-Llanes
- Nuffield Department of Medicine/Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Arturo Reyes-Sandoval
- Nuffield Department of Medicine/Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Instituto Politécnico Nacional (IPN), Av. Luis Enrique Erro s/n., Unidad Adolfo López Mateos, Mexico City, Mexico
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2
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Ryan SJ, Lippi CA, Caplan T, Diaz A, Dunbar W, Grover S, Johnson S, Knowles R, Lowe R, Mateen BA, Thomson MC, Stewart-Ibarra AM. The current landscape of software tools for the climate-sensitive infectious disease modelling community. Lancet Planet Health 2023; 7:e527-e536. [PMID: 37286249 DOI: 10.1016/s2542-5196(23)00056-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 03/15/2023] [Accepted: 03/16/2023] [Indexed: 06/09/2023]
Abstract
Climate-sensitive infectious disease modelling is crucial for public health planning and is underpinned by a complex network of software tools. We identified only 37 tools that incorporated both climate inputs and epidemiological information to produce an output of disease risk in one package, were transparently described and validated, were named (for future searching and versioning), and were accessible (ie, the code was published during the past 10 years or was available on a repository, web platform, or other user interface). We noted disproportionate representation of developers based at North American and European institutions. Most tools (n=30 [81%]) focused on vector-borne diseases, and more than half (n=16 [53%]) of these tools focused on malaria. Few tools (n=4 [11%]) focused on food-borne, respiratory, or water-borne diseases. The under-representation of tools for estimating outbreaks of directly transmitted diseases represents a major knowledge gap. Just over half (n=20 [54%]) of the tools assessed were described as operationalised, with many freely available online.
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Affiliation(s)
- Sadie J Ryan
- Quantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
| | - Catherine A Lippi
- Quantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | | | - Avriel Diaz
- Department of Earth and Environmental Sciences, Columbia University, New York, NY, USA
| | - Willy Dunbar
- National Collaborating Centre for Healthy Public Policy, Montreal, QC, Canada
| | | | | | | | - Rachel Lowe
- Barcelona Supercomputing Center, Barcelona, Spain; Catalan Institution for Research and Advanced Studies, Barcelona, Spain; Centre on Climate Change & Planetary Health and Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
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3
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Hartinger SM, Yglesias-González M, Blanco-Villafuerte L, Palmeiro-Silva YK, Lescano AG, Stewart-Ibarra A, Rojas-Rueda D, Melo O, Takahashi B, Buss D, Callaghan M, Chesini F, Flores EC, Gil Posse C, Gouveia N, Jankin S, Miranda-Chacon Z, Mohajeri N, Helo J, Ortiz L, Pantoja C, Salas MF, Santiago R, Sergeeva M, Souza de Camargo T, Valdés-Velásquez A, Walawender M, Romanello M. The 2022 South America report of The Lancet Countdown on health and climate change: trust the science. Now that we know, we must act. LANCET REGIONAL HEALTH. AMERICAS 2023; 20:100470. [PMID: 37125022 PMCID: PMC10122119 DOI: 10.1016/j.lana.2023.100470] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/13/2023] [Accepted: 02/28/2023] [Indexed: 05/02/2023]
Affiliation(s)
- Stella M. Hartinger
- Centro Latino Americano de Excelencia en Cambio Climático y Salud, Universidad Peruana Cayetano Heredia, Lima, Peru
- Corresponding author. Av. Honorio Delgado 430, San Martín de Porres, 15102, Lima, Peru.
| | - Marisol Yglesias-González
- Centro Latino Americano de Excelencia en Cambio Climático y Salud, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Luciana Blanco-Villafuerte
- Centro Latino Americano de Excelencia en Cambio Climático y Salud, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Yasna K. Palmeiro-Silva
- Pontificia Universidad Católica de Chile, Santiago, Chile
- University College London, London, UK
| | - Andres G. Lescano
- Centro Latino Americano de Excelencia en Cambio Climático y Salud, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | | | - Oscar Melo
- Centro Interdisciplinario de Cambio Global, Pontificia Universidad Católica de Chile, Santiago, Chile
| | | | - Daniel Buss
- Pan American Health Organization, Washington, DC, USA
| | - Max Callaghan
- Mercator Research Institute on Global Commons and Climate Change, Berlin, Germany
| | | | - Elaine C. Flores
- Centro Latino Americano de Excelencia en Cambio Climático y Salud, Universidad Peruana Cayetano Heredia, Lima, Peru
- Centre on Climate Change and Planetary Health, LSHTM, London, UK
| | | | | | | | | | | | | | | | - Chrissie Pantoja
- Duke University, Durham, NC, USA
- Universidad del Pacífico, Lima, Peru
| | | | - Raquel Santiago
- Universidade de São Paulo, São Paulo, Brazil
- Universidade Federal de Goiás, Goiás, Brazil
| | | | | | - Armando Valdés-Velásquez
- Centro Latino Americano de Excelencia en Cambio Climático y Salud, Universidad Peruana Cayetano Heredia, Lima, Peru
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Browne AS, Rickless D, Hranac CR, Beron A, Hillman B, de Wilde L, Short H, Harrison C, Prosper A, Joseph EJ, Guendel I, Ekpo LL, Roth J, Grossman M, Ellis BR, Ellis EM. Spatial, Sociodemographic, and Weather Analysis of the Zika Virus Outbreak: U.S. Virgin Islands, January 2016-January 2018. Vector Borne Zoonotic Dis 2022; 22:600-605. [PMID: 36399688 DOI: 10.1089/vbz.2021.0098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: The first Zika virus outbreak in U.S. Virgin Islands identified 1031 confirmed noncongenital Zika disease (n = 967) and infection (n = 64) cases during January 2016-January 2018; most cases (89%) occurred during July-December 2016. Methods and Results: The epidemic followed a continued point-source outbreak pattern. Evaluation of sociodemographic risk factors revealed that estates with higher unemployment, more houses connected to the public water system, and more newly built houses were significantly less likely to have Zika virus disease and infection cases. Increased temperature was associated with higher case counts, which suggests a seasonal association of this outbreak. Conclusion: Vector surveillance and control measures are needed to prevent future outbreaks.
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Affiliation(s)
- A Springer Browne
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - David Rickless
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Carter Reed Hranac
- Colorado Department of Public Health and Environment, Denver, Colorado, USA
| | - Andrew Beron
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Breanna Hillman
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Leah de Wilde
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Harris Short
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Cosme Harrison
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Andra Prosper
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - E Joy Joseph
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Irene Guendel
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Lisa L Ekpo
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Joseph Roth
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Marissa Grossman
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brett R Ellis
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
| | - Esther M Ellis
- US Virgin Islands Department of Health, Christiansted, Virgin Islands, USA
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Glidden CK, Field LC, Bachhuber S, Hennessey SM, Cates R, Cohen L, Crockett E, Degnin M, Feezell MK, Fulton‐Bennett HK, Pires D, Poirson BN, Randell ZH, White E, Gravem SA. Strategies for managing marine disease. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2022; 32:e2643. [PMID: 35470930 PMCID: PMC9786832 DOI: 10.1002/eap.2643] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 02/24/2022] [Indexed: 06/14/2023]
Abstract
The incidence of emerging infectious diseases (EIDs) has increased in wildlife populations in recent years and is expected to continue to increase with global environmental change. Marine diseases are relatively understudied compared with terrestrial diseases but warrant parallel attention as they can disrupt ecosystems, cause economic loss, and threaten human livelihoods. Although there are many existing tools to combat the direct and indirect consequences of EIDs, these management strategies are often insufficient or ineffective in marine habitats compared with their terrestrial counterparts, often due to fundamental differences between marine and terrestrial systems. Here, we first illustrate how the marine environment and marine organism life histories present challenges and opportunities for wildlife disease management. We then assess the application of common disease management strategies to marine versus terrestrial systems to identify those that may be most effective for marine disease outbreak prevention, response, and recovery. Finally, we recommend multiple actions that will enable more successful management of marine wildlife disease emergencies in the future. These include prioritizing marine disease research and understanding its links to climate change, improving marine ecosystem health, forming better monitoring and response networks, developing marine veterinary medicine programs, and enacting policy that addresses marine and other wildlife diseases. Overall, we encourage a more proactive rather than reactive approach to marine wildlife disease management and emphasize that multidisciplinary collaborations are crucial to managing marine wildlife health.
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Affiliation(s)
- Caroline K. Glidden
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
- Present address:
Department of BiologyStanford UniversityStanfordCaliforniaUSA
| | - Laurel C. Field
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
| | - Silke Bachhuber
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
| | | | - Robyn Cates
- College of Veterinary MedicineOregon State UniversityCorvallisOregonUSA
| | - Lesley Cohen
- College of Veterinary MedicineOregon State UniversityCorvallisOregonUSA
| | - Elin Crockett
- College of Veterinary MedicineOregon State UniversityCorvallisOregonUSA
| | - Michelle Degnin
- College of Veterinary MedicineOregon State UniversityCorvallisOregonUSA
| | - Maya K. Feezell
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
| | | | - Devyn Pires
- College of Veterinary MedicineOregon State UniversityCorvallisOregonUSA
| | | | - Zachary H. Randell
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
| | - Erick White
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
| | - Sarah A. Gravem
- Department of Integrative BiologyOregon State UniversityCorvallisOregonUSA
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6
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Cascante-Vega J, Cordovez JM, Santos-Vega M. Estimating and forecasting the burden and spread of Colombia's SARS-CoV2 first wave. Sci Rep 2022; 12:13568. [PMID: 35945249 PMCID: PMC9427755 DOI: 10.1038/s41598-022-15514-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 06/24/2022] [Indexed: 12/03/2022] Open
Abstract
Following the rapid dissemination of COVID-19 cases in Colombia in 2020, large-scale non-pharmaceutical interventions (NPIs) were implemented as national emergencies in most of the country’s municipalities, starting with a lockdown on March 20th, 2020. Recently, approaches that combine movement data (measured as the number of commuters between units), metapopulation models to describe disease dynamics subdividing the population into Susceptible-Exposed-Asymptomatic-Infected-Recovered-Diseased and statistical inference algorithms have been pointed as a practical approach to both nowcast and forecast the number of cases and deaths. We used an iterated filtering (IF) framework to estimate the model transmission parameters using the reported data across 281 municipalities from March to late October in locations with more than 50 reported deaths and cases in Colombia. Since the model is high dimensional (6 state variables in every municipality), inference on those parameters is highly non-trivial, so we used an Ensemble-Adjustment-Kalman-Filter (EAKF) to estimate time variable system states and parameters. Our results show the model’s ability to capture the characteristics of the outbreak in the country and provide estimates of the epidemiological parameters in time at the national level. Importantly, these estimates could become the base for planning future interventions as well as evaluating the impact of NPIs on the effective reproduction number (\documentclass[12pt]{minimal}
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\begin{document}$$\mathscr {R}_{eff}$$\end{document}Reff) and the critical epidemiological parameters, such as the contact rate or the reporting rate. However, our forecast presents some inconsistency as it overestimates the deaths for some locations as Medellín. Nevertheless, our approach demonstrates that real-time, publicly available ensemble forecasts can provide short-term predictions of reported COVID-19 deaths in Colombia. Therefore, this model can be used as a forecasting tool to evaluate disease dynamics and aid policymakers in infectious outbreak management and control.
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Affiliation(s)
- Jaime Cascante-Vega
- Universidad de los Andes, Grupo de Biología y Matemática Computacional (BIOMAC), Bogotá D.C., 111711, Colombia.,Facultad de Medicina, Universidad de los Andes, Bogotá D.C., Colombia
| | - Juan Manuel Cordovez
- Universidad de los Andes, Grupo de Biología y Matemática Computacional (BIOMAC), Bogotá D.C., 111711, Colombia
| | - Mauricio Santos-Vega
- Universidad de los Andes, Grupo de Biología y Matemática Computacional (BIOMAC), Bogotá D.C., 111711, Colombia. .,Facultad de Medicina, Universidad de los Andes, Bogotá D.C., Colombia.
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7
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Moreira RP, de Oliveira FBB, de Araujo TL, Morais HCC, Cavalcante TF, Gomez MBS, Felício JF, de Oliveira Ferreira G. Health Interventions for Preventing Climate-Sensitive Diseases: Scoping Review. J Urban Health 2022; 99:519-532. [PMID: 35467327 PMCID: PMC9187784 DOI: 10.1007/s11524-022-00631-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/18/2022] [Indexed: 10/18/2022]
Abstract
Climate variations cause public health problems, but the literature is still scarce on studies involving health interventions against climate-sensitive diseases. The objective of this review was to identify health interventions for the prevention of such diseases. We conducted a scoping review using the JBI Methodology. Six large research databases were searched (PubMed, Scopus, Web of Science, Lilacs, Embase, and Cochrane). The following inclusion criterion was used: studies addressing health interventions to prevent climate-sensitive diseases or consequences of climate on people's health. The exclusion criteria consisted of thesis, dissertations, conference proceedings, studies with unclear information/methodology, and studies not addressing climate-related health interventions. No language or date restrictions were applied. Of 733 studies identified and screened by title and abstract, 55 studies underwent full-text screening, yielding 13 studies for review. The health interventions identified were classified into three levels of management. The macro level included the use of epidemiological models, renewable energy, and policies sensitive to climate change. The meso level comprised interventions such as the creation of environmental suitability maps, urban greening, chemoprophylaxis, water security plans, and sanitation projects, among other measures. Some interventions are at the intersection, such as educational campaigns and the modification of artificial larvae sites. Finally, the micro level contained interventions such as the inspection of window screens and the use of light-colored clothing and repellents. The health interventions at the macro, meso, and micro levels and the intersection may serve as a basis for public managers to implement appropriate interventions against climate-sensitive diseases.
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Affiliation(s)
- Rafaella Pessoa Moreira
- Health Sciences Institute, University for International Integration of the Afro-Brazilian Lusophony, s/n José Franco de Oliveira St., Redenção, CE 62790-970, Brazil.
| | - Francisco Breno Barbosa de Oliveira
- Health Sciences Institute, University for International Integration of the Afro-Brazilian Lusophony, s/n José Franco de Oliveira St., Redenção, CE 62790-970, Brazil
| | - Thelma Leite de Araujo
- Nursing Departament, Federal University of Ceará, 1115 Alexandre Baraúna St., Fortaleza, CE 60430-160, Brazil
| | - Huana Carolina Candido Morais
- Health Sciences Institute, University for International Integration of the Afro-Brazilian Lusophony, s/n José Franco de Oliveira St., Redenção, CE 62790-970, Brazil
| | - Tahissa Frota Cavalcante
- Health Sciences Institute, University for International Integration of the Afro-Brazilian Lusophony, s/n José Franco de Oliveira St., Redenção, CE 62790-970, Brazil
| | - Maria Begoña Sanchez Gomez
- School of Nursing, University of La Laguna, Candelaria NS University Hospital, Canary Islands Health Service, 38010, Santa Cruz de Tenerife, Spain
| | - Janiel Ferreira Felício
- Health Sciences Institute, University for International Integration of the Afro-Brazilian Lusophony, s/n José Franco de Oliveira St., Redenção, CE 62790-970, Brazil
| | - Glauciano de Oliveira Ferreira
- Health Sciences Institute, University for International Integration of the Afro-Brazilian Lusophony, s/n José Franco de Oliveira St., Redenção, CE 62790-970, Brazil
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8
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Simon LM, Rangel TF. Are Temperature Suitability and Socioeconomic Factors Reliable Predictors of Dengue Transmission in Brazil? FRONTIERS IN TROPICAL DISEASES 2021. [DOI: 10.3389/fitd.2021.758393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Dengue is an ongoing problem, especially in tropical countries. Like many other vector-borne diseases, the spread of dengue is driven by a myriad of climate and socioeconomic factors. Within developing countries, heterogeneities on socioeconomic factors are expected to create variable conditions for dengue transmission. However, the relative role of socioeconomic characteristics and their association with climate in determining dengue prevalence are poorly understood. Here we assembled essential socioeconomic factors over 5570 municipalities across Brazil and assessed their effect on dengue prevalence jointly with a previously predicted temperature suitability for transmission. Using a simultaneous autoregressive approach (SAR), we showed that the variability in the prevalence of dengue cases across Brazil is primarily explained by the combined effect of climate and socioeconomic factors. At some dengue seasons, the effect of temperature on transmission potential showed to be a more significant proxy of dengue cases. Still, socioeconomic factors explained the later increase in dengue prevalence over Brazil. In a heterogeneous country such as Brazil, recognizing the transmission drivers by vectors is a fundamental issue in effectively predicting and combating tropical diseases like dengue. Ultimately, it indicates that not considering socioeconomic factors in disease transmission predictions might compromise efficient surveillance strategies. Our study shows that sanitation, urbanization, and GDP are regional indicators that should be considered along with temperature suitability on dengue transmission, setting effective directions to mosquito-borne disease control.
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9
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Nissan H, Ukawuba I, Thomson M. Climate-proofing a malaria eradication strategy. Malar J 2021; 20:190. [PMID: 33865383 PMCID: PMC8053291 DOI: 10.1186/s12936-021-03718-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 03/30/2021] [Indexed: 11/10/2022] Open
Abstract
Two recent initiatives, the World Health Organization (WHO) Strategic Advisory Group on Malaria Eradication and the Lancet Commission on Malaria Eradication, have assessed the feasibility of achieving global malaria eradication and proposed strategies to achieve it. Both reports rely on a climate-driven model of malaria transmission to conclude that long-term trends in climate will assist eradication efforts overall and, consequently, neither prioritize strategies to manage the effects of climate variability and change on malaria programming. This review discusses the pathways via which climate affects malaria and reviews the suitability of climate-driven models of malaria transmission to inform long-term strategies such as an eradication programme. Climate can influence malaria directly, through transmission dynamics, or indirectly, through myriad pathways including the many socioeconomic factors that underpin malaria risk. These indirect effects are largely unpredictable and so are not included in climate-driven disease models. Such models have been effective at predicting transmission from weeks to months ahead. However, due to several well-documented limitations, climate projections cannot accurately predict the medium- or long-term effects of climate change on malaria, especially on local scales. Long-term climate trends are shifting disease patterns, but climate shocks (extreme weather and climate events) and variability from sub-seasonal to decadal timeframes have a much greater influence than trends and are also more easily integrated into control programmes. In light of these conclusions, a pragmatic approach is proposed to assessing and managing the effects of climate variability and change on long-term malaria risk and on programmes to control, eliminate and ultimately eradicate the disease. A range of practical measures are proposed to climate-proof a malaria eradication strategy, which can be implemented today and will ensure that climate variability and change do not derail progress towards eradication.
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Affiliation(s)
- Hannah Nissan
- Grantham Research Institute for Climate Change and the Environment, London School of Economics and Political Science, London, UK.
- International Research Institute for Climate and Society, Columbia University, Palisades, NY, USA.
| | - Israel Ukawuba
- Mailman School for Public Health, Columbia University, New York, NY, USA
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DiSera L, Sjödin H, Rocklöv J, Tozan Y, Súdre B, Zeller H, Muñoz ÁG. The Mosquito, the Virus, the Climate: An Unforeseen Réunion in 2018. GEOHEALTH 2020; 4:e2020GH000253. [PMID: 32864539 PMCID: PMC7443513 DOI: 10.1029/2020gh000253] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 06/29/2020] [Accepted: 07/03/2020] [Indexed: 05/07/2023]
Abstract
The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and led to the dengue outbreak in early 2018. A stage-structured model was run using observed temperature and rainfall data to simulate the life cycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias-corrected subseasonal forecasts to determine if the event could have been forecast up to 4 weeks in advance. With unseasonably warm temperatures remaining above 25°C, along with large tropical-cyclone-related rainfall events accumulating 10-15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although subseasonal forecasts of rainfall for the December-January period in Réunion are skillful up to 4 weeks in advance, the outbreak could only have been forecast 2 weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state-of-the-art subseasonal climate forecasts to produce actionable subseasonal dengue predictions. To the best of the authors' knowledge, this is the first time subseasonal forecasts have been used this way.
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Affiliation(s)
- Laurel DiSera
- International Research Institute for Climate and Society, The Earth InstituteColumbia UniversityNew YorkNYUSA
| | - Henrik Sjödin
- Section of Sustainable Health, Department of Public Health and Clinical MedicineUmeå UniversityUmeåSweden
| | - Joacim Rocklöv
- Section of Sustainable Health, Department of Public Health and Clinical MedicineUmeå UniversityUmeåSweden
| | - Yesim Tozan
- School of Global Public HealthNew York UniversityNew YorkNYUSA
| | - Bertrand Súdre
- European Centre for Disease Prevention and ControlStockholmSweden
| | - Herve Zeller
- European Centre for Disease Prevention and ControlStockholmSweden
| | - Ángel G. Muñoz
- International Research Institute for Climate and Society, The Earth InstituteColumbia UniversityNew YorkNYUSA
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