37 research outputs found

    Destructive arthritis in a patient with chikungunya virus infection with persistent specific IgM antibodies

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Chikungunya fever is an emerging arboviral disease characterized by an algo-eruptive syndrome, inflammatory polyarthralgias, or tenosynovitis that can last for months to years. Up to now, the pathophysiology of the chronic stage is poorly understood.</p> <p>Case presentation</p> <p>We report the first case of CHIKV infection with chronic associated rheumatism in a patient who developed progressive erosive arthritis with expression of inflammatory mediators and persistence of specific IgM antibodies over 24 months following infection.</p> <p>Conclusions</p> <p>Understanding the specific features of chikungunya virus as well as how the virus interacts with its host are essential for the prevention, treatment or cure of chikungunya disease.</p

    Post-Epidemic Chikungunya Disease on Reunion Island: Course of Rheumatic Manifestations and Associated Factors over a 15-Month Period

    Get PDF
    Although the acute manifestations of Chikungunya virus (CHIKV) illness are well-documented, few data exist about the long-term rheumatic outcomes of CHIKV-infected patients. We undertook between June and September 2006 a retrospective cohort study aimed at assessing the course of late rheumatic manifestations and investigating potential risk factors associated with the persistence of these rheumatic manifestations over 15 months. 147 participants (>16 yrs) with laboratory-confirmed CHIKV disease diagnosed between March 1 and June 30, 2005, were identified through a surveillance database and interviewed by telephone. At the 15-month-period evaluation after diagnosis, 84 of 147 participants (57%) self-reported rheumatic symptoms. Of these 84 patients, 53 (63%) reported permanent trouble while 31 (37%) had recurrent symptoms. Age ≥45 years (OR = 3.9, 95% CI 1.7–9.7), severe initial joint pain (OR = 4.8, 95% CI 1.9–12.1), and presence of underlying osteoarthritis comorbidity (OR = 2.9, 95% CI 1.1–7.4) were predictors of nonrecovery. Our findings suggest that long-term CHIKV rheumatic manifestations seem to be a frequent underlying post-epidemic condition. Three independent risk factors that may aid in early recognition of patients with the highest risk of presenting prolonged CHIKV illness were identified. Such findings may be particularly useful in the development of future prevention and care strategies for this emerging virus infection

    Impact of Chikungunya Virus Infection on Health Status and Quality of Life: A Retrospective Cohort Study

    Get PDF
    BACKGROUND:Persistent symptoms, mainly joint and muscular pain and depression, have been reported several months after Chikungunya virus (CHIKV) infection. Their frequency and their impact on quality of life have not been compared with those of an unexposed population. In the present study, we aimed to describe the frequency of prolonged clinical manifestations of CHIKV infection and to measure the impact on quality of life and health care consumption in comparison with that of an unexposed population, more than one year after infection. METHODOLOGY/PRINCIPAL FINDINGS:In a retrospective cohort study, 199 subjects who had serologically confirmed CHIKV infection (CHIK+) were compared with 199 sero-negative subjects (CHIK-) matched for age, gender and area of residence in La Réunion Island. Following an average time of 17 months from the acute phase of infection, participants were interviewed by telephone about current symptoms, medical consumption during the last 12 months and quality of life assessed by the 12-items Short-Form Health Survey (SF-12) scale. At the time of study, 112 (56%) CHIK+ persons reported they were fully recovered. CHIK+ complained more frequently than CHIK- of arthralgia (relative risk = 1.9; 95% confidence interval: 1.6-2.2), myalgia (1.9; 1.5-2.3), fatigue (2.3; 1.8-3), depression (2.5; 1.5-4.1) and hair loss (3.8; 1.9-7.6). There was no significant difference between CHIK+ and CHIK- subjects regarding medical consumption in the past year. The mean (SD) score of the SF-12 Physical Component Summary was 46.4 (10.8) in CHIK+ versus 49.1 (9.3) in CHIK- (p = 0.04). There was no significant difference between the two groups for the Mental Component Summary. CONCLUSIONS/SIGNIFICANCE:More than one year following the acute phase of infection, CHIK+ subjects reported more disabilities than those who were CHIK-. These persistent disabilities, however, have no significant influence on medical consumption, and the impact on quality of life is moderate

    Persisting Mixed Cryoglobulinemia in Chikungunya Infection

    Get PDF
    Chikungunya virus is present in tropical Africa and Asia and is transmitted by mosquito bites. The disease is characterized by fever, headache, severe joint pain and transient skin rash for about a week. Most patients experience persisting joint pain and/or stiffness for months to years. In routine practice, diagnosis is based upon serology. Since 2004 there has been an ongoing giant outbreak of Chikungunya fever in East Africa, the Indian Ocean Islands, India and East Asia. In parallel, more than 1,000 travelers were diagnosed with imported Chikungunya infection in most developed countries. Considering the clinical features of our patients (joint pain), we hypothesized that cryoglobulins could be involved in the pathophysiology of the disease as observed in chronic hepatitis C infection. Cryoglobulins, which are immunoglobulins that precipitate when temperature is below 37°C, can induce rheumatic and vascular disorders. From April 2005 through May 2007, we screened all patients with possible imported Chikungunya infection for cryoglobulins. They were present in over 90% of patients, and possibly responsible for the unexpected false negativity of serological assays. Cryoglobulin frequency and levels decreased with time in recovering patients

    The Chikungunya Epidemic on La Réunion Island in 2005–2006: A Cost-of-Illness Study

    Get PDF
    For a long time, studies of chikungunya virus infection have been neglected, but since its resurgence in the south-western Indian Ocean and on La Réunion Island, this disease has been paid greater amounts of attention. The economic and social impacts of chikungunya epidemics are poorly documented, including in developed countries. This study estimated the cost-of-illness associated with the 2005–2006 chikungunya epidemics on La Réunion Island, a French overseas department with an economy and health care system of a developed country. “Cost-of-illness” studies measure the amount that would have been saved in the absence of a disease. We found that the epidemic incurred substantial medical expenses estimated at €43.9 million, of which 60% were attributable to direct medical costs related, in particular, to expenditure on medical consultations (47%), hospitalization (32%) and drugs (19%). The costs related to care in ambulatory and hospitalized cases were €90 and €2000 per case, respectively. This study provides the basic inputs for conducting cost-effectiveness and cost-benefit evaluations of chikungunya prevention strategies

    Chikungunya Disease: Infection-Associated Markers from the Acute to the Chronic Phase of Arbovirus-Induced Arthralgia

    Get PDF
    At the end of 2005, an outbreak of fever associated with joint pain occurred in La Réunion. The causal agent, chikungunya virus (CHIKV), has been known for 50 years and could thus be readily identified. This arbovirus is present worldwide, particularly in India, but also in Europe, with new variants returning to Africa. In humans, it causes a disease characterized by a typical acute infection, sometimes followed by persistent arthralgia and myalgia lasting months or years. Investigations in the La Réunion cohort and studies in a macaque model of chikungunya implicated monocytes-macrophages in viral persistence. In this Review, we consider the relationship between CHIKV and the immune response and discuss predictive factors for chronic arthralgia and myalgia by providing an overview of current knowledge on chikungunya pathogenesis. Comparisons of data from animal models of the acute and chronic phases of infection, and data from clinical series, provide information about the mechanisms of CHIKV infection–associated inflammation, viral persistence in monocytes-macrophages, and their link to chronic signs

    Nucleoside/nucleotide reverse transcriptase inhibitor sparing regimen with once daily integrase inhibitor plus boosted darunavir is non-inferior to standard of care in virologically-suppressed children and adolescents living with HIV – Week 48 results of the randomised SMILE Penta-17-ANRS 152 clinical trial

    Get PDF

    Development and validation of a weather-based model for predicting infection of loquat fruit by Fusicladium eriobotryae

    Full text link
    A mechanistic, dynamic model was developed to predict infection of loquat fruit by conidia of Fusicladium eriobotryae, the causal agent of loquat scab. The model simulates scab infection periods and their severity through the sub-processes of spore dispersal, infection, and latency (i.e., the state variables); change from one state to the following one depends on environmental conditions and on processes described by mathematical equations. Equations were developed using published data on F. eriobotryae mycelium growth, conidial germination, infection, and conidial dispersion pattern. The model was then validated by comparing model output with three independent data sets. The model accurately predicts the occurrence and severity of infection periods as well as the progress of loquat scab incidence on fruit (with concordance correlation coefficients .0.95). Model output agreed with expert assessment of the disease severity in seven loquatgrowing seasons. Use of the model for scheduling fungicide applications in loquat orchards may help optimise scab management and reduce fungicide applications.This work was funded by Cooperativa Agricola de Callosa d'En Sarria (Alicante, Spain). Three months' stay of E. Gonzalez-Dominguez at the Universita Cattolica del Sacro Cuore (Piacenza, Italy) was supported by the Programa de Apoyo a la Investigacion y Desarrollo (PAID-00-12) de la Universidad Politecnica de Valencia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.González Domínguez, E.; Armengol Fortí, J.; Rossi, V. (2014). Development and validation of a weather-based model for predicting infection of loquat fruit by Fusicladium eriobotryae. PLoS ONE. 9(9):1-12. https://doi.org/10.1371/journal.pone.0107547S11299Sánchez-Torres, P., Hinarejos, R., & Tuset, J. J. (2009). Characterization and Pathogenicity ofFusicladium eriobotryae, the Fungal Pathogen Responsible for Loquat Scab. Plant Disease, 93(11), 1151-1157. doi:10.1094/pdis-93-11-1151Gladieux, P., Caffier, V., Devaux, M., & Le Cam, B. (2010). Host-specific differentiation among populations of Venturia inaequalis causing scab on apple, pyracantha and loquat. Fungal Genetics and Biology, 47(6), 511-521. doi:10.1016/j.fgb.2009.12.007González-Domínguez, E., Rossi, V., Armengol, J., & García-Jiménez, J. (2013). Effect of Environmental Factors on Mycelial Growth and Conidial Germination ofFusicladium eriobotryae, and the Infection of Loquat Leaves. Plant Disease, 97(10), 1331-1338. doi:10.1094/pdis-02-13-0131-reGonzález-Domínguez, E., Rossi, V., Michereff, S. J., García-Jiménez, J., & Armengol, J. (2014). Dispersal of conidia of Fusicladium eriobotryae and spatial patterns of scab in loquat orchards in Spain. European Journal of Plant Pathology, 139(4), 849-861. doi:10.1007/s10658-014-0439-0Becker, C. M. (1994). Discontinuous Wetting and Survival of Conidia ofVenturia inaequalison Apple Leaves. Phytopathology, 84(4), 372. doi:10.1094/phyto-84-372Hartman, J. R., Parisi, L., & Bautrais, P. (1999). Effect of Leaf Wetness Duration, Temperature, and Conidial Inoculum Dose on Apple Scab Infections. Plant Disease, 83(6), 531-534. doi:10.1094/pdis.1999.83.6.531Holb, I. J., Heijne, B., Withagen, J. C. M., & Jeger, M. J. (2004). Dispersal of Venturia inaequalis Ascospores and Disease Gradients from a Defined Inoculum Source. Journal of Phytopathology, 152(11-12), 639-646. doi:10.1111/j.1439-0434.2004.00910.xRossi, V., Giosue, S., & Bugiani, R. (2003). Influence of Air Temperature on the Release of Ascospores of Venturia inaequalis. Journal of Phytopathology, 151(1), 50-58. doi:10.1046/j.1439-0434.2003.00680.xStensvand, A., Gadoury, D. M., Amundsen, T., Semb, L., & Seem, R. C. (1997). Ascospore Release and Infection of Apple Leaves by Conidia and Ascospores ofVenturia inaequalisat Low Temperatures. Phytopathology, 87(10), 1046-1053. doi:10.1094/phyto.1997.87.10.1046Machardy WE (1996) Apple scab. Biology, epidemiology and management. St. Paul: APS Press. 545.James, J. R. (1982). Environmental Factors Influencing Pseudothecial Development and Ascospore Maturation ofVenturia inaequalis. Phytopathology, 72(8), 1073. doi:10.1094/phyto-72-1073Li, B., Zhao, H., Li, B., & Xu, X.-M. (2003). Effects of temperature, relative humidity and duration of wetness period on germination and infection by conidia of the pear scab pathogen (Venturia nashicola). Plant Pathology, 52(5), 546-552. doi:10.1046/j.1365-3059.2003.00887.xLi, B.-H., Xu, X.-M., Li, J.-T., & Li, B.-D. (2005). Effects of temperature and continuous and interrupted wetness on the infection of pear leaves by conidia of Venturia nashicola. Plant Pathology, 54(3), 357-363. doi:10.1111/j.1365-3059.2005.01207.xUMEMOTO, S. (1990). Dispersion of ascospores and conidia of causal fungus of Japanese pear scab, Venturia nashicola. Japanese Journal of Phytopathology, 56(4), 468-473. doi:10.3186/jjphytopath.56.468Rossi, V., Salinari, F., Pattori, E., Giosuè,, S., & Bugiani, R. (2009). Predicting the Dynamics of Ascospore Maturation ofVenturia pirinaBased on Environmental Factors. Phytopathology, 99(4), 453-461. doi:10.1094/phyto-99-4-0453Spotts, R. A. (1991). Effect of Temperature and Wetness on Infection of Pear byVenturia pirinaand the Relationship Between Preharvest Inoculation and Storage Scab. Plant Disease, 75(12), 1204. doi:10.1094/pd-75-1204Spotts, R. A. (1994). Factors Affecting Maturation and Release of Ascospores ofVenturia pirinain Oregon. Phytopathology, 84(3), 260. doi:10.1094/phyto-84-260Villalta, O., Washington, W. S., Rimmington, G. M., & Taylor, P. A. (2000). Australasian Plant Pathology, 29(4), 255. doi:10.1071/ap00048Villalta, O. N., Washington, W. S., Rimmington, G. M., & Taylor, P. A. (2000). Effects of temperature and leaf wetness duration on infection of pear leaves by Venturia pirina. Australian Journal of Agricultural Research, 51(1), 97. doi:10.1071/ar99068Lan, Z., & Scherm, H. (2003). Moisture Sources in Relation to Conidial Dissemination and Infection byCladosporium carpophilumWithin Peach Canopies. Phytopathology, 93(12), 1581-1586. doi:10.1094/phyto.2003.93.12.1581Lawrence, Jr., E. G. (1982). Environmental Effects on the Development and Dissemination ofCladosporium carpophilumon Peach. Phytopathology, 72(7), 773. doi:10.1094/phyto-72-773Gottwald, T. R. (1985). Influence of Temperature, Leaf Wetness Period, Leaf Age, and Spore Concentration on Infection of Pecan Leaves by Conidia ofCladosporium caryigenum. Phytopathology, 75(2), 190. doi:10.1094/phyto-75-190Latham, A. J. (1982). Effects of Some Weather Factors andFusicladium effusumConidium Dispersal on Pecan Scab Occurrence. Phytopathology, 72(10), 1339. doi:10.1094/phyto-72-1339MARZO, L., FRISULLO, S., LOPS, F., & ROSSI, V. (1993). Possible dissemination of Spilocaea oleagina conidia by insects (Ectopsocus briggsi). EPPO Bulletin, 23(3), 389-391. doi:10.1111/j.1365-2338.1993.tb01341.xLOPS, F., FRISULLO, S., & ROSSI, V. (1993). Studies on the spread of the olive scab pathogen, Spilocaea oleagina. EPPO Bulletin, 23(3), 385-387. doi:10.1111/j.1365-2338.1993.tb01340.xObanor, F. O., Walter, M., Jones, E. E., & Jaspers, M. V. (2007). Effect of temperature, relative humidity, leaf wetness and leaf age on Spilocaea oleagina conidium germination on olive leaves. European Journal of Plant Pathology, 120(3), 211-222. doi:10.1007/s10658-007-9209-6Obanor, F. O., Walter, M., Jones, E. E., & Jaspers, M. V. (2010). Effects of temperature, inoculum concentration, leaf age, and continuous and interrupted wetness on infection of olive plants by Spilocaea oleagina. Plant Pathology, 60(2), 190-199. doi:10.1111/j.1365-3059.2010.02370.xViruega, J. R., Moral, J., Roca, L. F., Navarro, N., & Trapero, A. (2013). Spilocaea oleaginain Olive Groves of Southern Spain: Survival, Inoculum Production, and Dispersal. Plant Disease, 97(12), 1549-1556. doi:10.1094/pdis-12-12-1206-reViruega, J. R., Roca, L. F., Moral, J., & Trapero, A. (2011). Factors Affecting Infection and Disease Development on Olive Leaves Inoculated withFusicladium oleagineum. Plant Disease, 95(9), 1139-1146. doi:10.1094/pdis-02-11-0126Eikemo, H., Gadoury, D. M., Spotts, R. A., Villalta, O., Creemers, P., Seem, R. C., & Stensvand, A. (2011). Evaluation of Six Models to Estimate Ascospore Maturation in Venturia pyrina. Plant Disease, 95(3), 279-284. doi:10.1094/pdis-02-10-0125Li, B.-H., Yang, J.-R., Dong, X.-L., Li, B.-D., & Xu, X.-M. (2007). A dynamic model forecasting infection of pear leaves by conidia of Venturia nashicola and its evaluation in unsprayed orchards. European Journal of Plant Pathology, 118(3), 227-238. doi:10.1007/s10658-007-9138-4Rossi, V., Giosuè, S., & Bugiani, R. (2007). A-scab (Apple-scab), a simulation model for estimating risk of Venturia inaequalis primary infections. EPPO Bulletin, 37(2), 300-308. doi:10.1111/j.1365-2338.2007.01125.xXU, X.-M., BUTT, D. J., & SANTEN, G. (1995). A dynamic model simulating infection of apple leaves by Venturia inaequalis. Plant Pathology, 44(5), 865-876. doi:10.1111/j.1365-3059.1995.tb02746.xRoubal, C., Regis, S., & Nicot, P. C. (2012). Field models for the prediction of leaf infection and latent period ofFusicladium oleagineumon olive based on rain, temperature and relative humidity. Plant Pathology, 62(3), 657-666. doi:10.1111/j.1365-3059.2012.02666.xPayne, A. F., & Smith, D. L. (2012). Development and Evaluation of Two Pecan Scab Prediction Models. Plant Disease, 96(9), 1358-1364. doi:10.1094/pdis-03-11-0202-reTrapman M, Jansonius PJ (2008) Disease management in organic apple orchards is more than applying the right product at the correct time. Ecofruit-13th International Conference on Cultivation Technique and Phytopathological Problems in Organic Fruit-Growing: Proceedings to the Conference from 18th February to 20th February 2008 at Weinsberg/Germany. 16–22.HOLB, I. J., JONG, P. F., & HEIJNE, B. (2003). Efficacy and phytotoxicity of lime sulphur in organic apple production. Annals of Applied Biology, 142(2), 225-233. doi:10.1111/j.1744-7348.2003.tb00245.xGent, D. H., Mahaffee, W. F., McRoberts, N., & Pfender, W. F. (2013). The Use and Role of Predictive Systems in Disease Management. Annual Review of Phytopathology, 51(1), 267-289. doi:10.1146/annurev-phyto-082712-102356Alavanja, M. C. R., Hoppin, J. A., & Kamel, F. (2004). Health Effects of Chronic Pesticide Exposure: Cancer and Neurotoxicity. Annual Review of Public Health, 25(1), 155-197. doi:10.1146/annurev.publhealth.25.101802.123020Brent KJ, Hollomon DW (2007) Fungicide resistance in crop pathogens: How can it be managed? FRAC Monog 2. Fungicide Resistance Action Committee.Shtienberg, D. (2013). Will Decision-Support Systems Be Widely Used for the Management of Plant Diseases? Annual Review of Phytopathology, 51(1), 1-16. doi:10.1146/annurev-phyto-082712-102244Leffelaar P (1993) On Systems Analysis and Simulation of Ecological Processes. Kluwer. London.Rossi V, Giosuè S, Caffi T (2010) Modelling plant diseases for decision making in crop protection. In: Oerke E-C, Gerhards R, Menz G, Sikora RA, editors. Precision Crop Protection-the Challenge and Use of Heterogeneity.Hui, C. (2006). Carrying capacity, population equilibrium, and environment’s maximal load. Ecological Modelling, 192(1-2), 317-320. doi:10.1016/j.ecolmodel.2005.07.001Townsend C, Begon M, Harper J (2008) Essentials of ecology. John Wiley and Sons. New York. 510.Zadoks J, Schein R (1979) Epidemiology and plant disease management. Oxford University Press, New York. 427.Bennett, J. C., Diggle, A., Evans, F., & Renton, M. (2013). Assessing eradication strategies for rain-splashed and wind-dispersed crop diseases. Pest Management Science, 69(8), 955-963. doi:10.1002/ps.3459Ghanbarnia, K., Dilantha Fernando, W. G., & Crow, G. (2009). Developing Rainfall- and Temperature-Based Models to Describe Infection of Canola Under Field Conditions Caused by Pycnidiospores of Leptosphaeria maculans. Phytopathology, 99(7), 879-886. doi:10.1094/phyto-99-7-0879Gilligan, C. A., & van den Bosch, F. (2008). Epidemiological Models for Invasion and Persistence of Pathogens. Annual Review of Phytopathology, 46(1), 385-418. doi:10.1146/annurev.phyto.45.062806.094357Buck, A. L. (1981). New Equations for Computing Vapor Pressure and Enhancement Factor. Journal of Applied Meteorology, 20(12), 1527-1532. doi:10.1175/1520-0450(1981)0202.0.co;2Madden L V, Hughes G, van den Bosch F (2007) The study of plant disease epidemics. APS press. St. Paul. 421.González-Domínguez E, Rodríguez-Reina J, García-Jiménez J, Armengol J (2014) Evaluation of fungicides to control loquat scab caused by Fusicladium eriobotryae. Plant Heal Prog Accepted.De Wolf, E. D., & Isard, S. A. (2007). Disease Cycle Approach to Plant Disease Prediction. Annual Review of Phytopathology, 45(1), 203-220. doi:10.1146/annurev.phyto.44.070505.143329Krause, R. A., & Massie, L. B. (1975). Predictive Systems: Modern Approaches to Disease Control. Annual Review of Phytopathology, 13(1), 31-47. doi:10.1146/annurev.py.13.090175.000335Fourie, P., Schutte, T., Serfontein, S., & Swart, F. (2013). Modeling the Effect of Temperature and Wetness on Guignardia Pseudothecium Maturation and Ascospore Release in Citrus Orchards. Phytopathology, 103(3), 281-292. doi:10.1094/phyto-07-11-0194Gadoury, D. M. (1982). A Model to Estimate the Maturity of Ascospores ofVenturia inaequalis. Phytopathology, 72(7), 901. doi:10.1094/phyto-72-901Holtslag, Q. A., Remphrey, W. R., Fernando, W. G. D., St-Pierre, R. G., & Ash, G. H. B. (2004). The development of a dynamic diseaseforecasting model to controlEntomosporium mespilionAmelanchier alnifolia. Canadian Journal of Plant Pathology, 26(3), 304-313. doi:10.1080/07060660409507148Legler SEE, Caffi T, Rossi V (2013) A Model for the development of Erysiphe necator chasmothecia in vineyards. Plant Pathol. DOI:10.1111/ppa.12145.Luo, Y., & Michailides, T. J. (2001). Risk Analysis for Latent Infection of Prune by Monilinia fructicola in California. Phytopathology, 91(12), 1197-1208. doi:10.1094/phyto.2001.91.12.1197Gadoury, D. M. (1986). Forecasting Ascospore Dose of Venturia inaequalis in Commercial Apple Orchards. Phytopathology, 76(1), 112. doi:10.1094/phyto-76-112Gent, D. H., De Wolf, E., & Pethybridge, S. J. (2011). Perceptions of Risk, Risk Aversion, and Barriers to Adoption of Decision Support Systems and Integrated Pest Management: An Introduction. Phytopathology, 101(6), 640-643. doi:10.1094/phyto-04-10-0124Schut, M., Rodenburg, J., Klerkx, L., van Ast, A., & Bastiaans, L. (2014). Systems approaches to innovation in crop protection. A systematic literature review. Crop Protection, 56, 98-108. doi:10.1016/j.cropro.2013.11.017Mills W, Laplante A (1954) Diseases and insect in the orchard. Cornell Ext Bull 711.GVA (2013) Octubre-Noviembre 2013. Butlletí d’avisos 13.MacHardy, W. E. (1989). A Revision of Mills’s Criteria for Predicting Apple Scab Infection Periods. Phytopathology, 79(3), 304. doi:10.1094/phyto-79-30

    Chikungunya Virus Pathogenesis and Immunity

    No full text
    International audienceChikungunya virus (CHIKV) is an arbovirus associated with acute and chronic arthralgia that re-emerged in the Indian Ocean islands in 2005–2006 and is currently responsible for the ongoing outbreaks in the Caribbean islands and the Americas. We describe here the acute and chronic clinical manifestations of CHIKV in patients that define the disease. We also review the various animal models that have been developed to study CHIKV infection and pathology and further strengthened the understanding of the cellular and molecular mechanisms of CHIKV infection and immunity. A complete understanding of the immunopathogenesis of CHIKV infection will help develop the needed preventive and therapeutic approaches to combat this arbovirosis
    corecore